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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>With each set of indexes, you can multiplex up to 24.</span></p>
<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
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<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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<p><br /><br /></p>
<p></p>
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<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'name' => 'D-Plex Single Indexes for Illumina - Set A',
'description' => '<p style="text-align: left;"><span>D-Plex Single Indexes Module - Set A includes PCR primers with <span>24</span><span><span> barcodes (i7 index)</span> for library multiplexing</span> with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. </span></p>
<p style="text-align: left;"><span>These single indexes (SI) were designed and validated to fit the D-Plex technology for Illumina sequencing. Addition of a unique molecular identifier (UMI) sequence enables the accurate bioinformatic identification and removal of PCR duplicates from amplified libraries.</span></p>
<p><span>Two sets are available separately: </span></p>
<ul>
<li><span>C05030010 - </span>D-Plex Single Indexes for Illumina - Set A</li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-single-indexes-set-b" title="D-Plex 24 Single Indexes for Illumina - Set #B">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
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<p><span>Read more about the </span><a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a><span>.</span><span> </span></p>',
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<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
<p>Benefits of the MicroChIP DiaPure columns:</p>
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<p>Successful ChIP-seq results generated on 50,000 of K562 cells using True MicroChIP technology. ChIP has been performed accordingly to True MicroChIP protocol (Diagenode, Cat. No. C01010130), including DNA purification using the MicroChIP DiaPure columns. For the library preparation the MicroPlex Library Preparation Kit (Diagenode, Cat. No. C05010001) has been used. The below figure shows the peaks from ChIP-seq experiments using the following Diagenode antibodies: H3K4me1 (C15410194), H3K9/14ac (C15410200), H3K27ac (C15410196) and H3K36me3 (C15410192).</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'name' => '次世代シーケンシング',
'description' => '<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2 style="font-size: 22px;">DNA断片化、ライブラリー調製、自動化：NGSのワンストップショップ</h2>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-12 medium-12 large-12 columns">
<h4>1. 断片化装置を選択してください：150 bp〜75 kbの範囲でDNAを断片化します。</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-pico-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/bioruptor_pico.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/megaruptor2-1-unit"><img src="https://www.diagenode.com/img/product/shearing_technologies/B06010001_megaruptor2.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-one-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/br-one-profil.png" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns">5μlまで断片化：150 bp〜2 kb<br />NGS DNAライブラリー調製およびFFPE核酸抽出に最適で、</td>
<td class="small-4 medium-4 large-4 columns">2 kb〜75 kbの範囲をできます。<br />メイトペアライブラリー調製および長いフラグメントDNAシーケンシングに最適で、この軽量デスクトップデバイスで</td>
<td class="small-4 medium-4 large-4 columns">20または50μlの断片化が可能です。</td>
</tr>
</tbody>
</table>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-8 medium-8 large-8 columns">
<h4>2. 最適化されたライブラリー調整キットを選択してください。</h4>
</th>
<th class="small-4 medium-4 large-4 columns">
<h4>3. ライブラリー前処理自動化を選択して、比類のないデータ再現性を実感</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><img src="https://www.diagenode.com/img/product/kits/microPlex_library_preparation.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/ideal-library-preparation-kit-x24-incl-index-primer-set-1-24-rxns"><img src="https://www.diagenode.com/img/product/kits/box_kit.jpg" style="display: block; margin-left: auto; margin-right: auto;" height="173" width="250" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/sx-8g-ip-star-compact-automated-system-1-unit"><img src="https://www.diagenode.com/img/product/automation/B03000002%20_ipstar_compact.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">50pgの低入力：MicroPlex Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">5ng以上：iDeal Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">Achieve great NGS data easily</td>
</tr>
</tbody>
</table>
</div>
</div>
<blockquote>
<div class="row">
<div class="small-12 medium-12 large-12 columns"><span class="label" style="margin-bottom: 16px; margin-left: -22px; font-size: 15px;">DiagenodeがNGS研究にぴったりなプロバイダーである理由</span>
<p>Diagenodeは15年以上もエピジェネティクス研究に専念、専門としています。 ChIP研究クロマチン用のユニークな断片化システムの開発から始まり、 専門知識を活かし、5μlのせん断体積まで可能で、NGS DNAライブラリーの調製に最適な最先端DNA断片化装置の開発にたどり着きました。 我々は以来、ChIP-seq、Methyl-seq、NGSライブラリー調製用キットを研究開発し、業界をリードする免疫沈降研究と同様に、ライブラリー調製を自動化および完結させる独自の自動化システムを開発にも成功しました。</p>
<ul>
<li>信頼されるせん断装置</li>
<li>様々なインプットからのライブラリ作成キット</li>
<li>独自の自動化デバイス</li>
</ul>
</div>
</div>
</blockquote>
<div class="row">
<div class="small-12 columns">
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#panel1a">次世代シーケンシングへの理解とその専門知識</a>
<div id="panel1a" class="content">
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><strong>次世代シーケンシング (NGS)</strong> ）は、著しいスケールとハイスループットでシーケンシングを行い、1日に数十億もの塩基生成を可能にします。 NGSのハイスループットは迅速でありながら正確で、再現性のあるデータセットを実現し、さらにシーケンシング費用を削減します。 NGSは、ゲノムシーケンシング、ゲノム再シーケンシング、デノボシーケンシング、トランスクリプトームシーケンシング、その他にDNA-タンパク質相互作用の検出やエピゲノムなどを示します。 指数関数的に増加するシーケンシングデータの需要は、計算分析の障害や解釈、データストレージなどの課題を解決します。</p>
<p>アプリケーションおよび出発物質に応じて、数百万から数十億の鋳型DNA分子を大規模に並行してシーケンシングすることが可能です。その為に、異なる化学物質を使用するいくつかの市販のNGSプラットフォームを利用することができます。 NGSプラットフォームの種類によっては、事前準備とライブラリー作成が必要です。</p>
<p>NGSにとっても、特にデータ処理と分析に関した大きな課題はあります。第3世代技術はゲノミクス研究にさらに革命を起こすであろうと大きく期待されています。</p>
</div>
</div>
<div class="row">
<div class="small-6 medium-6 large-6 columns">
<p><strong>NGS アプリケーション</strong></p>
<ul>
<li>全ゲノム配列決定</li>
<li>デノボシーケンシング</li>
<li>標的配列</li>
<li>Exomeシーケンシング</li>
<li>トランスクリプトーム配列決定</li>
<li>ゲノム配列決定</li>
<li>ミトコンドリア配列決定</li>
<li>DNA-タンパク質相互作用（ChIP-seq</li>
<li>バリアント検出</li>
<li>ゲノム仕上げ</li>
</ul>
</div>
<div class="small-6 medium-6 large-6 columns">
<p><strong>研究分野におけるNGS:</strong></p>
<ul>
<li>腫瘍学</li>
<li>リプロダクティブ・ヘルス</li>
<li>法医学ゲノミクス</li>
<li>アグリゲノミックス</li>
<li>複雑な病気</li>
<li>微生物ゲノミクス</li>
<li>食品・環境ゲノミクス</li>
<li>創薬ゲノミクス - パーソナライズド・メディカル</li>
</ul>
</div>
<div class="small-12 medium-12 large-12 columns">
<p><strong>NGSの用語</strong></p>
<dl>
<dt>リード（読み取り）</dt>
<dd>この装置から得られた連続した単一のストレッチ</dd>
<dt>断片リード</dt>
<dd>フラグメントライブラリからの読み込み。 シーケンシングプラットフォームに応じて、読み取りは通常約100〜300bp。</dd>
<dt>断片ペアエンドリード</dt>
<dd>断片ライブラリーからDNA断片の各末端2つの読み取り。</dd>
<dt>メイトペアリード</dt>
<dd>大きなDNA断片（通常は予め定義されたサイズ範囲）の各末端から2つの読み取り。</dd>
<dt>カバレッジ（例）</dt>
<dd>30×適用範囲とは、参照ゲノム中の各塩基対が平均30回の読み取りを示す。</dd>
</dl>
</div>
</div>
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2>NGSプラットフォーム</h2>
<h3><a href="http://www.illumina.com" target="_blank">イルミナ</a></h3>
<p>イルミナは、クローン的に増幅された鋳型DNA（クラスター）上に位置する、蛍光標識された可逆的鎖ターミネーターヌクレオチドを用いた配列別合成技術を使用。 DNAクラスターは、ガラスフローセルの表面上に固定化され、 ワークフローは、4つのヌクレオチド（それぞれ異なる蛍光色素で標識された）の組み込み、4色イメージング、色素や末端基の切断、取り込み、イメージングなどを繰り返します。フローセルは大規模な並列配列決定を受ける。 この方法により、単一蛍光標識されたヌクレオチドの制御添加によるモノヌクレオチドのエラーを回避する可能性があります。 読み取りの長さは、通常約100〜150 bpです。</p>
<h3><a href="http://www.lifetechnologies.com" target="_blank">イオン トレント</a></h3>
<p>イオントレントは、半導体技術チップを用いて、合成中にヌクレオチドを取り込む際に放出されたプロトンを検出します。 これは、イオン球粒子と呼ばれるビーズの表面にエマルションPCR（emPCR）を使用し、リンクされた特定のアダプターを用いてDNA断片を増幅します。 各ビーズは1種類のDNA断片で覆われていて、異なるDNA断片を有するビーズは次いで、チップの陽子感知ウェル内に配置されます。 チップには一度に4つのヌクレオチドのうちの1つが浸水し、このプロセスは異なるヌクレオチドで15秒ごとに繰り返されます。 配列決定の間に4つの塩基の各々が1つずつ導入されます、組み込みの場合はプロトンが放出され、電圧信号が取り込みに比例して検出されます。.</p>
<h3><a href="http://www.pacificbiosciences.com" target="_blank">パシフィック バイオサイエンス</a></h3>
<p>パシフィックバイオサイエンスでは、20kbを超える塩基対の読み取りも、単一分子リアルタイム（SMRT）シーケンシングによる構造および細胞タイプの変化を観察することができます。 このプラットフォームでは、超長鎖二本鎖DNA（dsDNA）断片が、Megaruptor（登録商標）のようなDiagenode装置を用いたランダムシアリングまたは目的の標的領域の増幅によって生成されます。 SMRTbellライブラリーは、ユニバーサルヘアピンアダプターをDNA断片の各末端に連結することによって生成します。 サイズ選択条件による洗浄ステップの後、配列決定プライマーをSMRTbellテンプレートにアニーリングし、鋳型DNAに結合したDNAポリメラーゼを含む配列決定を、蛍光標識ヌクレオチドの存在下で開始。 各塩基が取り込まれると、異なる蛍光のパルスをリアルタイムで検出します。</p>
<h3><a href="https://nanoporetech.com" target="_blank">オックスフォード ナノポア</a></h3>
<p>Oxford Nanoporeは、単一のDNA分子配列決定に基づく技術を開発します。その技術により生物学的分子、すなわちDNAが一群の電気抵抗性高分子膜として位置するナノスケールの孔（ナノ細孔）またはその近くを通過し、イオン電流が変化します。 この変化に関する情報は、例えば4つのヌクレオチド（AまたはG r CまたはT）ならびに修飾されたヌクレオチドすべてを区別することによって分子情報に訳されます。 シーケンシングミニオンデバイスのフローセルは、数百個のナノポアチャネルのセンサアレイを含みます。 DNAサンプルは、Diagenode社のMegaruptor（登録商標）を用いてランダムシアリングによって生成され得る超長鎖DNAフラグメントが必要です。</p>
<h3><a href="http://www.lifetechnologies.com/be/en/home/life-science/sequencing/next-generation-sequencing/solid-next-generation-sequencing.html" target="_blank">SOLiD</a></h3>
<p>SOLiDは、ユニークな化学作用により、何千という個々のDNA分子の同時配列決定を可能にします。 それは、アダプター対ライブラリーのフラグメントが適切で、せん断されたゲノムDNAへのアダプターのライゲーションによるライブラリー作製から始まります。 次のステップでは、エマルジョンPCR（emPCR）を実施して、ビーズの表面上の個々の鋳型DNA分子をクローン的に増幅。 emPCRでは、個々の鋳型DNAをPCR試薬と混合し、水中油型エマルジョン内の疎水性シェルで囲まれた水性液滴内のプライマーコートビーズを、配列決定のためにロードするスライドガラスの表面にランダムに付着。 この技術は、シークエンシングプライマーへのライゲーションで競合する4つの蛍光標識されたジ塩基プローブのセットを使用します。</p>
<h3><a href="http://454.com/products/technology.asp" target="_blank">454</a></h3>
<p>454は、大規模並列パイロシーケンシングを利用しています。 始めに全ゲノムDNAまたは標的遺伝子断片の300〜800bp断片のライブラリー調製します。 次に、DNAフラグメントへのアダプターの付着および単一のDNA鎖の分離。 その後アダプターに連結されたDNAフラグメントをエマルジョンベースのクローン増幅（emPCR）で処理し、DNAライブラリーフラグメントをミクロンサイズのビーズ上に配置します。 各DNA結合ビーズを光ファイバーチップ上のウェルに入れ、器具に挿入します。 4つのDNAヌクレオチドは、配列決定操作中に固定された順序で連続して加えられ、並行して配列決定されます。</p>
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<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3´ end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode’s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching”</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg. </span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>® - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing. <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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'description' => '<div class="row"><div class="small-12 medium-4 large-4 columns"><div class="panel"><h3><em>lncRNAs in cancer</em></h3><p class="text-left">Gastrointestinal cancer: Gastrointestinal cancers occur as a result of dysregulated signaling pathways and cellular processes, such as the cell cycle or apoptosis. LncRNAs can regulate proliferation of gastrointestinal cancer through interacting with RNA targets, localization to chromatin, or binding to proteins. Read more about Long non-coding RNAs: crucial regulators of gastrointestinal cancer cell proliferation</p><h3><em>microRNAs in cancer</em></h3><p class="text-left">miR-155 has been found overexpressed in many cancer types including hematopoietic cancers, breast, lung and colon cancer<br /><br /> <a href="https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf">https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf</a></p></div></div><div class="small-12 medium-8 large-8 columns"><center><img src="https://www.diagenode.com/img/cancer/long-non-coding-rna.jpg" width="550" height="345" /></center><p></p><p>Various non-coding RNAs (ncRNAs) have been found to function as key regulators for transcription, chromatin remodelling, and post-transcriptional modification, thus making them relevant in oncogenesis, both as tumor suppressors and as drivers. For example, a number of microRNAs (miRNAs), one of the more well-studied types of ncRNAs, have been identified as potential cancer biomarkers and clinical targets. Other ncRNAs, such as long noncoding RNAs are involved in cancer regulation and proliferation. Understanding the role of ncRNAs will be critical for cancer research and therapeutic development.</p></div></div>',
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<p><img src="https://www.diagenode.com/img/areas/toxicology.jpg" /></p>
</div>
<h2>Epigenetics in environmental toxicology</h2>
<p>The fact that environmental factors induce DNA mutations that may lead to disease is well-established and will have tremendous benefits when incorporated into various environmental safety and health assessments. Environmental factors such as dietary intake, drugs, stress, or exposure to toxins, can cause epigenetic changes by possibly altering how transcription factors bind to DNA or changing the structure of the histones that DNA wraps around. These structural changes can affect gene activity or gene expression. A number of environmental factors have been investigated for their effect on epigenetic changes including phthalates, toxic metals, smoking, air pollution, jet fuel, environmental stress, and a high fat diet. Effects on epigenetic mechanisms, DNA methylation patterns, histone modifications, miRNA expression have been documented as a result. The table below (Marczylo et al, 2016 and Society of Toxicology, 2018) summarizes a few of the studies that have been done for putative environmentally-induced epigenetic toxicity in humans or rat/mouse.</p>
<p class="extra-spaced">In the future, incorporating epigenetic evaluation into toxicity tests can increase the safety of both food and environmental substances.</p>
<table class="extra-spaced">
<tbody>
<tr>
<th style="text-align: center;">Toxin/exposure</th>
<th style="text-align: center;">Species/stage of exposure/effect</th>
<th style="text-align: center;">Phenotype</th>
<th style="text-align: center;">Epigenetic change</th>
<th style="text-align: center;">Reference(s)</th>
</tr>
<tr>
<td>Air pollution</td>
<td style="text-align: center;">Human/childhood/childhood</td>
<td style="text-align: center;">Asthma</td>
<td style="text-align: center;">Epigenetic mechanisms</td>
<td style="text-align: left;">Somineni et al. (2016)</td>
</tr>
<tr style="text-align: center;">
<td style="text-align: left;">BPA</td>
<td>Human/in utero/childhood</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">DNA methylation</td>
<td style="text-align: left;">Kundakovic (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Formaldehyde</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Alzheimer’s</td>
<td style="text-align: center;">Epigenetic mechanisms and DNA methylation</td>
<td>Tong et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Methylmercury</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">Histone modifications and DNA methylation</td>
<td>Onishchenko (2008)</td>
</tr>
<tr style="text-align: center;">
<td>Arsenic</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Skin disorder</td>
<td style="text-align: center;">DNA methylation</td>
<td>Paul et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Nickel</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">NSCLC survival</td>
<td style="text-align: center;">miRNA</td>
<td>Chiou et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Polycyclic aromatic hydrocarbons</td>
<td style="text-align: center;">Human/adult/adult</td>
<td style="text-align: center;">Chromosome aberrations - PBL</td>
<td style="text-align: center;">DNA methylation</td>
<td>Yang et al. (2012)</td>
</tr>
<tr style="text-align: center;">
<td>Various phthalates</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Decreased testosterone/gonadal</td>
<td style="text-align: center;">DNA methylation and histone modifications</td>
<td>Kilcoyne et al. (2014) Martinez-Arguelles et al. (2009), Papoutsis et al. (2015), Takeda et al. (2012), Yoshioka et al. (2011)</td>
</tr>
<tr style="text-align: center;">
<td>Smoking</td>
<td style="text-align: center;">Human/Lifetime/adult</td>
<td style="text-align: center;">COPD and tumor</td>
<td style="text-align: center;">Epigenetic mechanisms, DNA methylation, miRNA</td>
<td>Lin (2010), Ostrow (2013) Shenker (2013), Xie et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Alcohol</td>
<td style="text-align: center;">Rodent/lifetime and in utero</td>
<td style="text-align: center;">Nuerological, cardiac, behavior, stem cell</td>
<td style="text-align: center;">Histone modification and miRNA</td>
<td>Ignacio et al. (2014), Middleton et al. (2012), Leu et al. (2014), Pascual et al. (2011), Peng et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>High fat diet</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Diet preference</td>
<td style="text-align: center;">DNA methylation and miRNAs</td>
<td>Baselga-Escudero (2015), Carlin et al. (2013), Vucetic et al. (2010)</td>
</tr>
<tr>
<td style="text-align: left;">Under-nourishment</td>
<td style="text-align: center;">Rodent/adult/adult</td>
<td style="text-align: center;">Hepatic</td>
<td style="text-align: center;">miRNAs</td>
<td>Tryndyak et al. (2016)</td>
</tr>
</tbody>
</table>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<h3>Diagenode products for your epigenomics research in Toxicology</h3>
<div class="row">
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #099f92; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/chromatin-function">Chromatin analysis</a></h3>
<center><a href="https://www.diagenode.com/en/categories/chromatin-function"><img src="https://www.diagenode.com/img/cancer/chromatin-icon.png" /></a></center>
<p class="text-left">Understand the effects on chromatin and histone modifcations</p>
</div>
<ul>
<li>New to ChIP? <a href="https://www.diagenode.com/en/pages/portal/chip">Learn more</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-shearing">Chromatin shearing optimization</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-immunoprecipitation">Chromatin Immunoprecipitation</a></li>
<li>Validated <a href="https://www.diagenode.com/en/categories/antibodies">Antibodies</a></li>
<li><a href="https://www.diagenode.com/en/categories/library-preparation">Library preparation</a></li>
</ul>
</div>
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #30415c; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
<center><a href="https://www.diagenode.com/en/categories/dna-methylation"><img src="https://www.diagenode.com/img/cancer/dna-icon.png" /></a></center>
<p class="text-left">Analyze DNA methylation and the effects of environmental toxins</p>
</div>
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<p class="text-left">Discover noncoding RNAs and miRNAs in the regulation of gene expression</p>
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<li><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">RNA-seq using CATS</a> (Capture and Amplification by Tailing and Switching)</li>
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<h2>Epigenetics and Cancer</h2>
<p>Epigenetic processes control the normal development and maintenance of gene expression in a number of organisms. However, disruption of epigenetic mechanisms may alter gene function, potentially leading to cellular transformations that lead to tumorigenesis. Cancer is a multistep process from a succession of processes that alter the growth of normal cells. In cancer, epigenetic reprogramming occurs at multiple levels including nuclear organization and nucleosome positioning, DNA methylation, modification of histones, alteration of epigenetic regulators such as transcription factor binding, and non-coding RNA, such as microRNA.</p>
<p>Epigenetic modifications are reversible and potential treatments could be geared to alter irregular transcription factor binding, DNA methylation or histone acetylation. Accurate study with a versatile number of tools is essential for the study of epigenetics including sound sample preparation and analysis methodologies for DNA methylation such as with immunoprecipitation or bisulfite sequencing, chromatin analysis with chromatin immunoprecipitation (ChIP) combined with qPCR or sequencing, and RNA modification study. As researchers elucidate the mechanisms and specific modifications associated with cancer, it may be possible to target abnormal modifications in cells with minimal damage to normal cells, making the prospect of epigenetic therapy increasingly promising.</p>
<h3>Diagenode products for your epigenomics research in Cancer</h3>
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<p class="text-left">Understand the role of chromatin in cancer regulation</p>
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<p class="text-left">Analyze DNA methylation and the effects on oncogenesis and tumor suppression</p>
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<li><a href="https://www.diagenode.com/en/categories/bisulfite-conversion">Bisulfite sequencing</a></li>
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<li><a href="https://www.diagenode.com/en/categories/dna-methylation-profiling-services">DNA methylation services</a></li>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in cancer</p>
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<h2>Epigenetics in Neuroscience</h2>
<p>Neuroscience and epigenetics are at an exciting crossroads. Current research has shown that epigenetic mechanisms play a critical role in both behavior and the development and function of the nervous system. Histone modifications, changes in DNA methylation, and non-coding RNAs regulate various stages of neurogenesis and brain development while aberrant epigenetic regulation has been implicated in a number of neurological and brain disorders (Yao et, al. Nature Reviews Neuroscience, 2016).</p>
<p>Neuroscientists seek to uncover how epigenetic marks and transcriptional changes regulate gene expression to influence changes in areas such as behavior and the development of neural pathways and brain structures. Understanding how epigenetics affects nervous system function requires an integrative approach incorporating multiple levels of analysis. For example, research has uncovered the role of transcription factors, non-coding RNAs, and other molecules that mediate learning and memory. In addition, chromatin modifications and non-coding RNAs have been shown to influence epigenetic mechanisms in neurogenesis.</p>
<p>Understanding the molecular components and environmental conditions that affect epigenetic change will eventually provide the basis to develop therapies to treat neurological and psychiatric conditions. As neuroscientists learn how changes in chromatin architecture affect transcriptional regulation and gene expression, the link between the epigenome and the various areas in neuroscience will become clearer.</p>
<h3><span class="diacol">Neuroscience and epigenetics intersect in a number of areas: </span></h3>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#memory"> <i class="fa fa-square-o"></i> Epigenetics in memory, memory disorders, and learning</a>
<div id="memory" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms underlying learning and the inheritance of learned behaviors</strong></p>
<p>In this review, researchers outline epigenetic mechanisms by which gene expression is regulated in animals and humans. Using fear learning as a framework, they show how such mechanisms underlie learning and stress responsiveness. Finally, they discuss how epigenetic mechanisms might inform us about the transgenerational inheritance of behavioral traits that are being increasingly reported. Trends in Neuroscience, 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
<blockquote><br />
<p><strong>Epigenetic regulation of memory formation and maintenance</strong></p>
<p>In the last decade, epigenetic markers like DNA methylation and post-translational modifications of histone tails have emerged as important regulators of the memory process. Their ability to regulate gene transcription dynamically in response to neuronal activation supports the consolidation of long-term memory.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2779706/" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#schizophrenia"> <i class="fa fa-square-o"></i> Schizophrenia</a>
<div id="schizophrenia" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in schizophrenia</strong></p>
<p>In this review, the authors present an overview of schizophrenia and discuss the role of nature versus nurture in its pathology, where ‘nature’ is considered to be inherited or genetic vulnerability to schizophrenia, and ‘nurture’ is proposed to exert its effects through epigenetic mechanisms. Second, they define DNA methylation and discuss the evidence for its role in schizophrenia. Third, they define posttranslational histone modifications and discuss their place in schizophrenia. This research is likely to lead to the development of epigenetic therapy, which holds the promise of alleviating cognitive deficits associated with schizophrenia. Biochimica and Biophysica Acta, 2009.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#addiction"> <i class="fa fa-square-o"></i> Addiction disorder</a>
<div id="addiction" class="content">
<blockquote><br />
<p><strong>Epigenetics of addiction: Epigenetic study untangles addiction and relapse in the brain</strong></p>
<p>New research uncovers an epigenetic reason why drug users who attempt to quit are prone to relapse despite negative consequences to their health and livelihood. The findings help to explain how casual drug use can produce long-lasting brain changes that increase vulnerability to relapse in individuals suffering from substance use disorders. Science Daily, September 2017.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.sciencedaily.com/releases/2017/09/170927123612.htm" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#neurogenesis"> <i class="fa fa-square-o"></i> Neurogenesis</a>
<div id="neurogenesis" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in neurogenesis</strong></p>
<p>Epigenetic mechanisms — including DNA and histone modifications, as well as regulation by non-coding RNAs — have pivotal roles in different stages of neurogenesis. The authors also briefly cover the emerging field of epitranscriptomics, which involves modifications of mRNAs and long non-coding RNAs.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-017-0365-z">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#depression"> <i class="fa fa-square-o"></i> Depression</a>
<div id="depression" class="content">
<blockquote><br />
<p><strong>Epigenetics of depression</strong></p>
<p>Major depressive disorder (MDD) is a leading cause of disability worldwide and is associated with poor psychological, medical, and socioeconomic outcomes. This review presents the evidence supporting a role for epigenetic effects in MDD and in treatment response. Prog Mol Biol Transl Sci. 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25410543">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#other"> <i class="fa fa-square-o"></i> Other disorders such as Rett’s, Autism, Parkinson’s, Huntington’s </a>
<div id="other" class="content">
<blockquote>
<p><strong>Parkinson’s disease</strong></p>
<p>DNA methylation in Parkinson's disease</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/27120258">Read more</a></p>
</blockquote>
<blockquote>
<p><strong>Rett’s Syndrome</strong></p>
<p>Epigenetic regulation of memory by acetylation and methylation of chromatin: implications in neurological disorders, aging, and addiction</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/24777294">Read more</a></p>
</blockquote>
</div>
</li>
</ul>
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<h3>Diagenode products for your epigenomics research in Neuroscience</h3>
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<p class="text-left">Understand the role of chromatin in neuroscience</p>
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<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
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<p class="text-left">Analyze DNA methylation and the effects on neurogenesis, brain development, and more</p>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression</p>
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<div class="extra-spaced">
<h2>Epigenetic Regulation in Plants</h2>
<p>Plants utilize a number of gene regulation mechanisms to ensure proper development, function, growth, and survival under different environmental conditions. Plants depend on changes in gene expression to respond to environmental stimuli, in which the full repertoire of histone modifications, DNA methylation, and small ncRNAs play an important role in epigenetic regulation.</p>
<p>Studying the epigenetics of model plants such as Arabidopsis thaliana have allowed researchers to understand pathways that maintain chromatin modifications as well as the mapping of modifications such as DNA methylation on a genome-wide scale. Small RNAs have also been implicated in playing a role in the distribution of chromatin modifications, and RNA may also play a role in the complex epigenetic interactions that occur between homologous sequences (Moazed et al, 2009). In the future, by understanding epigenetic control, researchers can uncover the research necessary to improve plant growth, yields, and transformation efficiency especially in the face of climate change and other environmental factors.</p>
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<h3 style="font-weight: 100; margin-top: 0;">Chromatin</h3>
<p>Chromatin consists of nucleosomes formed by a complex of histone proteins and DNA, which allows the packaging of DNA into the nucleus. The less condensed euchromatin represents transcriptionally active regions, while heterochromatin is usually inactive (Vaillant and Paszkowski, 2007). Chromatin state is known to be influenced by both DNA methylation and histone modifications which in turn impact gene expression and the structure of chromosomes. In a recent study, the role of chromatin modifications during plant reproduction elucidated 3-dimensional chromosome reorganization mediated by histones and DNA methylation (Dukowic-Schulze et al. 2017). In addition, gibberellins have been shown in increasing the level of histone acetylation, which affects regions of chromatin involved in maize seed germination (Zheng et al. 2017). Another study reports a novel function of a tomato histone deacetylase gene in the regulation of fruit ripening (Guo et al. 2017).</p>
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<p>In addition, multigene families encode transcription factors, with members found throughout the genome or clustered on the same chromosome. Numerous DNA binding proteins that interact with plant promoters have been identified -- some are similar to well-characterized transcription factors in animals or yeast, while others are unique to plants. For example, diverse members of the subfamily X of the plant-specific ethylene response factor (ERF) transcription factors coordinate stress signaling with wound repair activation. Tissue repair is also enhanced through a protein complex of ERF and GRAS TFs (Heyman et. al,.2018). A compilation of known plant transcription factors can be found in the plant transcription factor database at http://plntfdb.bio.uni-potsdam.de/v3.0/.</p>
</div>
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<h3 style="font-weight: 100; margin-top: 0;">RNA</h3>
<p>Recent research shows that a number of classes of small RNAs are key epigenetic regulators. In many cases, small RNAs have been implicated in DNA methylation and chromatin modification (Meyer, 2015). In addition, the role of small RNAs has been implicated in plant stress tolerance (Kumar et al., 2017). López-Galiano et al also provided insight into a coordinated function of a miRNA gene and histone modifications in regulating the expression of a WRKY transcription factor in response to stress.</p>
<p>RNA interference (RNAi) is another epigenetic mechanism that leads to small RNA generation, which mediates gene silencing at the post-transcriptional level. RNAi technology has immense potential for plant disease resistance.</p>
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<h3 style="font-weight: 100; margin-top: 0;">DNA methylation</h3>
<p>Plants, unlike animals, have three sites that can be methylated G, CHG (H can be A, C, T), and CHH (Law and Jacobsen, 2010). DNA methylation has attracted particular interest. In Arabidopsis, one-third of methylated genes occur in transcribed regions, and 5% of genes are methylated in promoter regions, suggesting that many of these are epigenetically regulated. (Zhang et al., 2006).</p>
<p>There are thousands of differentially methylated regions (DMRs) that influence phenotype by influencing gene expression. The analysis of epigenetic recombinant inbred line (epiRIL) plants from Arabidopsis points to the evidence of the influence of DMRs. An epiRIL results from crossing two genetically identical plants with differing DNA methylation levels (with one parent as a homozygous mutant for an essential DNA methylation maintenance gene). The offspring of these plants have similar genomes that vary only in methylation levels. Many traits have been studied using epiRILs -- flowering time, plant height, and response to abiotic stress, some of which have now been mapped to DMRs (Zhang et al. 2018)</p>
<p>Regulation by DNA methylation has been shown to be important in many aspects of plant development and response such as vernalization, hybrid vigor, and self-incompatibility (Itabashi et al. 2017). For example, vernalization treatments have shown reduced DNA methylation and subsequent initiation of flowering (Burn et al., 1993). Stress can also influence DNA methylation in plants as a response to environmental stimuli. (Steward et al., 2002; Song et al., 2012). A high degree of DNA methylation has also suggested the role in the improvement of plant fitness under different environmental conditions (Saéz-Laguna et al., 2014). In addition, methylation can affect normal fruit and hypomethylation predicts homeotic transformation and loss of fruit yield (Ong-Abdullah et al., 2015)</p>
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<p>DNA demethylation has also been implied in various aspects of plant development including pollen tube formation, embryogenesis, fruit ripening, stomatal development, and nodule formation ( Li et al. 2017). Demethylation of rice genomic DNA caused an altered pattern of gene expression, inducing dwarf plants (Sano et al., 1990).</p>
<p>Epigenetic modifications contribute to the stability and survival of the plants and their ability to adapt in different environmental conditions.</p>
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<h3>Diagenode products for your epigenomics research in plants</h3>
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<p class="text-left">DNA methylation and demethylation and the effects on plant response and function</p>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression in plants</p>
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<h3>References</h3>
<p><small> Burn, J. et al (1993). DNA methylation, vernalization, and the initiation of flowering. Proc. Natl. Acad. Sci. U.S.A. 90, 287–291. doi: 10.1006/scdb.1996.0055 </small></p>
<p><small> Dukowic-Schulze S, Liu C, Chen C (2017) Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2222-0</small></p>
<p><small> Guo J et al (2017) A histone deacetylase gene, SlHDA3, acts as a negative regulator of fruit ripening and carotenoid accumulation. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2211-3</small></p>
<p><small> Heyman J, et.al (2018) Journal of Cell Science Emerging role of the plant ERF transcription factors in coordinating wound defense responses and repair doi: 10.1242/jcs.208215</small></p>
<p><small> Itabashi E, Osabe K, Fujimoto R, Kakizaki T (2017) Epigenetic regulation of agronomical traits in Brassicaceae. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2223-z</small></p>
<p><small> Kumar V et al (2017) Plant small RNAs: the essential epigenetic regulators of gene expression for salt-stress responses and tolerance. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2210-4</small></p>
<p><small> Law, J. A., and Jacobsen, S. E. (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11, 204–220. doi: 10.1038/nrg2719</small></p>
<p><small> Meyer, P. (2015). Epigenetic variation and environmental change. J. Exp. Bot. 66, 3541–3548. doi: 10.1093/jxb/eru502</small></p>
<p><small> Moazed, D. (2009) Small RNAs in transcriptional gene silencing and genome defence. Nature. doi: 10.1038/nature07756</small></p>
<p><small> Ong-Abdullah et al. (2015). Loss of Karma transposon methylation underlies the mantled somaclonal variant of oil palm. Nature 525, 533–537. doi: 10.1038/nature15365</small></p>
<p><small> Saéz-Laguna et al. (2014). Epigenetic variability in the genetically uniform forest tree species. PLoS One 9:e103145. doi: 10.1371/journal.pone.0103145</small></p>
<p><small> Sano, H. et al. (1990). A single treatment of rice seedlings with 5-azacytidine induces heritable dwarfism and undermethylation of genomic DNA. Mol. Gen. Genet. 220, 441–447. doi: 10.1007/BF00391751</small></p>
<p><small> Song, J et al (2012). Vernalization – A cold-induced epigenetic switch. J. Cell Sci. 125, 3723–3731. doi: 10.1242/jcs.084764</small></p>
<p><small> Steward, N et al. (2002). Periodic DNA methylation in maize nucleosomes and demethylation by environmental stress. J. Biol. Chem. 277, 37741–37746. doi: 10.1074/jbc.M204050200</small></p>
<p><small> Vaillant, I., and Paszkowski, J. (2007). Role of histone and DNA methylation in gene regulation. Curr. Opin. Plant Biol. 10, 528–533. doi: 10.1016/j.pbi.2007.06.008</small></p>
<p><small> Zhang, et al. (2006). Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201. doi: 10.1016/j.cell.2006.08.003</small></p>
<p><small> Zhang et al. 2018 Understanding the evolutionary potential of epigenetic variation: a comparison of heritable phenotypic variation in epiRILs, RILs, and natural ecotypes of Arabidopsis thaliana. Heredity 121, 257–265 (2018) doi:10.1038/s41437-018-0095-9</small></p>
<p><small> Zheng X et al (2017) Histone acetylation is involved in GA-mediated 45S rDNA decondensation in maize aleurone layers. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2207-z</small></p>
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
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'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'description' => '<p style="text-align: left;"><span>D-Plex Single Indexes Module - Set A includes PCR primers with <span>24</span><span><span> barcodes (i7 index)</span> for library multiplexing</span> with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. </span></p>
<p style="text-align: left;"><span>These single indexes (SI) were designed and validated to fit the D-Plex technology for Illumina sequencing. Addition of a unique molecular identifier (UMI) sequence enables the accurate bioinformatic identification and removal of PCR duplicates from amplified libraries.</span></p>
<p><span>Two sets are available separately: </span></p>
<ul>
<li><span>C05030010 - </span>D-Plex Single Indexes for Illumina - Set A</li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-single-indexes-set-b" title="D-Plex 24 Single Indexes for Illumina - Set #B">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
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<p><span>Each set can be used for library multiplexing up to 24. <span>Set A and Set B can be used simultaneously for library multiplexing up to 48.</span></span></p>
<p><span>Read more about the </span><a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a><span>.</span><span> </span></p>',
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<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
<p>Benefits of the MicroChIP DiaPure columns:</p>
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<p>Successful ChIP-seq results generated on 50,000 of K562 cells using True MicroChIP technology. ChIP has been performed accordingly to True MicroChIP protocol (Diagenode, Cat. No. C01010130), including DNA purification using the MicroChIP DiaPure columns. For the library preparation the MicroPlex Library Preparation Kit (Diagenode, Cat. No. C05010001) has been used. The below figure shows the peaks from ChIP-seq experiments using the following Diagenode antibodies: H3K4me1 (C15410194), H3K9/14ac (C15410200), H3K27ac (C15410196) and H3K36me3 (C15410192).</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'description' => '<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2 style="font-size: 22px;">DNA断片化、ライブラリー調製、自動化：NGSのワンストップショップ</h2>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-12 medium-12 large-12 columns">
<h4>1. 断片化装置を選択してください：150 bp〜75 kbの範囲でDNAを断片化します。</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-pico-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/bioruptor_pico.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/megaruptor2-1-unit"><img src="https://www.diagenode.com/img/product/shearing_technologies/B06010001_megaruptor2.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-one-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/br-one-profil.png" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns">5μlまで断片化：150 bp〜2 kb<br />NGS DNAライブラリー調製およびFFPE核酸抽出に最適で、</td>
<td class="small-4 medium-4 large-4 columns">2 kb〜75 kbの範囲をできます。<br />メイトペアライブラリー調製および長いフラグメントDNAシーケンシングに最適で、この軽量デスクトップデバイスで</td>
<td class="small-4 medium-4 large-4 columns">20または50μlの断片化が可能です。</td>
</tr>
</tbody>
</table>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-8 medium-8 large-8 columns">
<h4>2. 最適化されたライブラリー調整キットを選択してください。</h4>
</th>
<th class="small-4 medium-4 large-4 columns">
<h4>3. ライブラリー前処理自動化を選択して、比類のないデータ再現性を実感</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><img src="https://www.diagenode.com/img/product/kits/microPlex_library_preparation.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/ideal-library-preparation-kit-x24-incl-index-primer-set-1-24-rxns"><img src="https://www.diagenode.com/img/product/kits/box_kit.jpg" style="display: block; margin-left: auto; margin-right: auto;" height="173" width="250" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/sx-8g-ip-star-compact-automated-system-1-unit"><img src="https://www.diagenode.com/img/product/automation/B03000002%20_ipstar_compact.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">50pgの低入力：MicroPlex Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">5ng以上：iDeal Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">Achieve great NGS data easily</td>
</tr>
</tbody>
</table>
</div>
</div>
<blockquote>
<div class="row">
<div class="small-12 medium-12 large-12 columns"><span class="label" style="margin-bottom: 16px; margin-left: -22px; font-size: 15px;">DiagenodeがNGS研究にぴったりなプロバイダーである理由</span>
<p>Diagenodeは15年以上もエピジェネティクス研究に専念、専門としています。 ChIP研究クロマチン用のユニークな断片化システムの開発から始まり、 専門知識を活かし、5μlのせん断体積まで可能で、NGS DNAライブラリーの調製に最適な最先端DNA断片化装置の開発にたどり着きました。 我々は以来、ChIP-seq、Methyl-seq、NGSライブラリー調製用キットを研究開発し、業界をリードする免疫沈降研究と同様に、ライブラリー調製を自動化および完結させる独自の自動化システムを開発にも成功しました。</p>
<ul>
<li>信頼されるせん断装置</li>
<li>様々なインプットからのライブラリ作成キット</li>
<li>独自の自動化デバイス</li>
</ul>
</div>
</div>
</blockquote>
<div class="row">
<div class="small-12 columns">
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#panel1a">次世代シーケンシングへの理解とその専門知識</a>
<div id="panel1a" class="content">
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><strong>次世代シーケンシング (NGS)</strong> ）は、著しいスケールとハイスループットでシーケンシングを行い、1日に数十億もの塩基生成を可能にします。 NGSのハイスループットは迅速でありながら正確で、再現性のあるデータセットを実現し、さらにシーケンシング費用を削減します。 NGSは、ゲノムシーケンシング、ゲノム再シーケンシング、デノボシーケンシング、トランスクリプトームシーケンシング、その他にDNA-タンパク質相互作用の検出やエピゲノムなどを示します。 指数関数的に増加するシーケンシングデータの需要は、計算分析の障害や解釈、データストレージなどの課題を解決します。</p>
<p>アプリケーションおよび出発物質に応じて、数百万から数十億の鋳型DNA分子を大規模に並行してシーケンシングすることが可能です。その為に、異なる化学物質を使用するいくつかの市販のNGSプラットフォームを利用することができます。 NGSプラットフォームの種類によっては、事前準備とライブラリー作成が必要です。</p>
<p>NGSにとっても、特にデータ処理と分析に関した大きな課題はあります。第3世代技術はゲノミクス研究にさらに革命を起こすであろうと大きく期待されています。</p>
</div>
</div>
<div class="row">
<div class="small-6 medium-6 large-6 columns">
<p><strong>NGS アプリケーション</strong></p>
<ul>
<li>全ゲノム配列決定</li>
<li>デノボシーケンシング</li>
<li>標的配列</li>
<li>Exomeシーケンシング</li>
<li>トランスクリプトーム配列決定</li>
<li>ゲノム配列決定</li>
<li>ミトコンドリア配列決定</li>
<li>DNA-タンパク質相互作用（ChIP-seq</li>
<li>バリアント検出</li>
<li>ゲノム仕上げ</li>
</ul>
</div>
<div class="small-6 medium-6 large-6 columns">
<p><strong>研究分野におけるNGS:</strong></p>
<ul>
<li>腫瘍学</li>
<li>リプロダクティブ・ヘルス</li>
<li>法医学ゲノミクス</li>
<li>アグリゲノミックス</li>
<li>複雑な病気</li>
<li>微生物ゲノミクス</li>
<li>食品・環境ゲノミクス</li>
<li>創薬ゲノミクス - パーソナライズド・メディカル</li>
</ul>
</div>
<div class="small-12 medium-12 large-12 columns">
<p><strong>NGSの用語</strong></p>
<dl>
<dt>リード（読み取り）</dt>
<dd>この装置から得られた連続した単一のストレッチ</dd>
<dt>断片リード</dt>
<dd>フラグメントライブラリからの読み込み。 シーケンシングプラットフォームに応じて、読み取りは通常約100〜300bp。</dd>
<dt>断片ペアエンドリード</dt>
<dd>断片ライブラリーからDNA断片の各末端2つの読み取り。</dd>
<dt>メイトペアリード</dt>
<dd>大きなDNA断片（通常は予め定義されたサイズ範囲）の各末端から2つの読み取り。</dd>
<dt>カバレッジ（例）</dt>
<dd>30×適用範囲とは、参照ゲノム中の各塩基対が平均30回の読み取りを示す。</dd>
</dl>
</div>
</div>
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2>NGSプラットフォーム</h2>
<h3><a href="http://www.illumina.com" target="_blank">イルミナ</a></h3>
<p>イルミナは、クローン的に増幅された鋳型DNA（クラスター）上に位置する、蛍光標識された可逆的鎖ターミネーターヌクレオチドを用いた配列別合成技術を使用。 DNAクラスターは、ガラスフローセルの表面上に固定化され、 ワークフローは、4つのヌクレオチド（それぞれ異なる蛍光色素で標識された）の組み込み、4色イメージング、色素や末端基の切断、取り込み、イメージングなどを繰り返します。フローセルは大規模な並列配列決定を受ける。 この方法により、単一蛍光標識されたヌクレオチドの制御添加によるモノヌクレオチドのエラーを回避する可能性があります。 読み取りの長さは、通常約100〜150 bpです。</p>
<h3><a href="http://www.lifetechnologies.com" target="_blank">イオン トレント</a></h3>
<p>イオントレントは、半導体技術チップを用いて、合成中にヌクレオチドを取り込む際に放出されたプロトンを検出します。 これは、イオン球粒子と呼ばれるビーズの表面にエマルションPCR（emPCR）を使用し、リンクされた特定のアダプターを用いてDNA断片を増幅します。 各ビーズは1種類のDNA断片で覆われていて、異なるDNA断片を有するビーズは次いで、チップの陽子感知ウェル内に配置されます。 チップには一度に4つのヌクレオチドのうちの1つが浸水し、このプロセスは異なるヌクレオチドで15秒ごとに繰り返されます。 配列決定の間に4つの塩基の各々が1つずつ導入されます、組み込みの場合はプロトンが放出され、電圧信号が取り込みに比例して検出されます。.</p>
<h3><a href="http://www.pacificbiosciences.com" target="_blank">パシフィック バイオサイエンス</a></h3>
<p>パシフィックバイオサイエンスでは、20kbを超える塩基対の読み取りも、単一分子リアルタイム（SMRT）シーケンシングによる構造および細胞タイプの変化を観察することができます。 このプラットフォームでは、超長鎖二本鎖DNA（dsDNA）断片が、Megaruptor（登録商標）のようなDiagenode装置を用いたランダムシアリングまたは目的の標的領域の増幅によって生成されます。 SMRTbellライブラリーは、ユニバーサルヘアピンアダプターをDNA断片の各末端に連結することによって生成します。 サイズ選択条件による洗浄ステップの後、配列決定プライマーをSMRTbellテンプレートにアニーリングし、鋳型DNAに結合したDNAポリメラーゼを含む配列決定を、蛍光標識ヌクレオチドの存在下で開始。 各塩基が取り込まれると、異なる蛍光のパルスをリアルタイムで検出します。</p>
<h3><a href="https://nanoporetech.com" target="_blank">オックスフォード ナノポア</a></h3>
<p>Oxford Nanoporeは、単一のDNA分子配列決定に基づく技術を開発します。その技術により生物学的分子、すなわちDNAが一群の電気抵抗性高分子膜として位置するナノスケールの孔（ナノ細孔）またはその近くを通過し、イオン電流が変化します。 この変化に関する情報は、例えば4つのヌクレオチド（AまたはG r CまたはT）ならびに修飾されたヌクレオチドすべてを区別することによって分子情報に訳されます。 シーケンシングミニオンデバイスのフローセルは、数百個のナノポアチャネルのセンサアレイを含みます。 DNAサンプルは、Diagenode社のMegaruptor（登録商標）を用いてランダムシアリングによって生成され得る超長鎖DNAフラグメントが必要です。</p>
<h3><a href="http://www.lifetechnologies.com/be/en/home/life-science/sequencing/next-generation-sequencing/solid-next-generation-sequencing.html" target="_blank">SOLiD</a></h3>
<p>SOLiDは、ユニークな化学作用により、何千という個々のDNA分子の同時配列決定を可能にします。 それは、アダプター対ライブラリーのフラグメントが適切で、せん断されたゲノムDNAへのアダプターのライゲーションによるライブラリー作製から始まります。 次のステップでは、エマルジョンPCR（emPCR）を実施して、ビーズの表面上の個々の鋳型DNA分子をクローン的に増幅。 emPCRでは、個々の鋳型DNAをPCR試薬と混合し、水中油型エマルジョン内の疎水性シェルで囲まれた水性液滴内のプライマーコートビーズを、配列決定のためにロードするスライドガラスの表面にランダムに付着。 この技術は、シークエンシングプライマーへのライゲーションで競合する4つの蛍光標識されたジ塩基プローブのセットを使用します。</p>
<h3><a href="http://454.com/products/technology.asp" target="_blank">454</a></h3>
<p>454は、大規模並列パイロシーケンシングを利用しています。 始めに全ゲノムDNAまたは標的遺伝子断片の300〜800bp断片のライブラリー調製します。 次に、DNAフラグメントへのアダプターの付着および単一のDNA鎖の分離。 その後アダプターに連結されたDNAフラグメントをエマルジョンベースのクローン増幅（emPCR）で処理し、DNAライブラリーフラグメントをミクロンサイズのビーズ上に配置します。 各DNA結合ビーズを光ファイバーチップ上のウェルに入れ、器具に挿入します。 4つのDNAヌクレオチドは、配列決定操作中に固定された順序で連続して加えられ、並行して配列決定されます。</p>
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<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3´ end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode’s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching”</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg. </span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>® - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing. <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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'description' => '<div class="row"><div class="small-12 medium-4 large-4 columns"><div class="panel"><h3><em>lncRNAs in cancer</em></h3><p class="text-left">Gastrointestinal cancer: Gastrointestinal cancers occur as a result of dysregulated signaling pathways and cellular processes, such as the cell cycle or apoptosis. LncRNAs can regulate proliferation of gastrointestinal cancer through interacting with RNA targets, localization to chromatin, or binding to proteins. Read more about Long non-coding RNAs: crucial regulators of gastrointestinal cancer cell proliferation</p><h3><em>microRNAs in cancer</em></h3><p class="text-left">miR-155 has been found overexpressed in many cancer types including hematopoietic cancers, breast, lung and colon cancer<br /><br /> <a href="https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf">https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf</a></p></div></div><div class="small-12 medium-8 large-8 columns"><center><img src="https://www.diagenode.com/img/cancer/long-non-coding-rna.jpg" width="550" height="345" /></center><p></p><p>Various non-coding RNAs (ncRNAs) have been found to function as key regulators for transcription, chromatin remodelling, and post-transcriptional modification, thus making them relevant in oncogenesis, both as tumor suppressors and as drivers. For example, a number of microRNAs (miRNAs), one of the more well-studied types of ncRNAs, have been identified as potential cancer biomarkers and clinical targets. Other ncRNAs, such as long noncoding RNAs are involved in cancer regulation and proliferation. Understanding the role of ncRNAs will be critical for cancer research and therapeutic development.</p></div></div>',
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<p><img src="https://www.diagenode.com/img/areas/toxicology.jpg" /></p>
</div>
<h2>Epigenetics in environmental toxicology</h2>
<p>The fact that environmental factors induce DNA mutations that may lead to disease is well-established and will have tremendous benefits when incorporated into various environmental safety and health assessments. Environmental factors such as dietary intake, drugs, stress, or exposure to toxins, can cause epigenetic changes by possibly altering how transcription factors bind to DNA or changing the structure of the histones that DNA wraps around. These structural changes can affect gene activity or gene expression. A number of environmental factors have been investigated for their effect on epigenetic changes including phthalates, toxic metals, smoking, air pollution, jet fuel, environmental stress, and a high fat diet. Effects on epigenetic mechanisms, DNA methylation patterns, histone modifications, miRNA expression have been documented as a result. The table below (Marczylo et al, 2016 and Society of Toxicology, 2018) summarizes a few of the studies that have been done for putative environmentally-induced epigenetic toxicity in humans or rat/mouse.</p>
<p class="extra-spaced">In the future, incorporating epigenetic evaluation into toxicity tests can increase the safety of both food and environmental substances.</p>
<table class="extra-spaced">
<tbody>
<tr>
<th style="text-align: center;">Toxin/exposure</th>
<th style="text-align: center;">Species/stage of exposure/effect</th>
<th style="text-align: center;">Phenotype</th>
<th style="text-align: center;">Epigenetic change</th>
<th style="text-align: center;">Reference(s)</th>
</tr>
<tr>
<td>Air pollution</td>
<td style="text-align: center;">Human/childhood/childhood</td>
<td style="text-align: center;">Asthma</td>
<td style="text-align: center;">Epigenetic mechanisms</td>
<td style="text-align: left;">Somineni et al. (2016)</td>
</tr>
<tr style="text-align: center;">
<td style="text-align: left;">BPA</td>
<td>Human/in utero/childhood</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">DNA methylation</td>
<td style="text-align: left;">Kundakovic (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Formaldehyde</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Alzheimer’s</td>
<td style="text-align: center;">Epigenetic mechanisms and DNA methylation</td>
<td>Tong et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Methylmercury</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">Histone modifications and DNA methylation</td>
<td>Onishchenko (2008)</td>
</tr>
<tr style="text-align: center;">
<td>Arsenic</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Skin disorder</td>
<td style="text-align: center;">DNA methylation</td>
<td>Paul et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Nickel</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">NSCLC survival</td>
<td style="text-align: center;">miRNA</td>
<td>Chiou et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Polycyclic aromatic hydrocarbons</td>
<td style="text-align: center;">Human/adult/adult</td>
<td style="text-align: center;">Chromosome aberrations - PBL</td>
<td style="text-align: center;">DNA methylation</td>
<td>Yang et al. (2012)</td>
</tr>
<tr style="text-align: center;">
<td>Various phthalates</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Decreased testosterone/gonadal</td>
<td style="text-align: center;">DNA methylation and histone modifications</td>
<td>Kilcoyne et al. (2014) Martinez-Arguelles et al. (2009), Papoutsis et al. (2015), Takeda et al. (2012), Yoshioka et al. (2011)</td>
</tr>
<tr style="text-align: center;">
<td>Smoking</td>
<td style="text-align: center;">Human/Lifetime/adult</td>
<td style="text-align: center;">COPD and tumor</td>
<td style="text-align: center;">Epigenetic mechanisms, DNA methylation, miRNA</td>
<td>Lin (2010), Ostrow (2013) Shenker (2013), Xie et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Alcohol</td>
<td style="text-align: center;">Rodent/lifetime and in utero</td>
<td style="text-align: center;">Nuerological, cardiac, behavior, stem cell</td>
<td style="text-align: center;">Histone modification and miRNA</td>
<td>Ignacio et al. (2014), Middleton et al. (2012), Leu et al. (2014), Pascual et al. (2011), Peng et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>High fat diet</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Diet preference</td>
<td style="text-align: center;">DNA methylation and miRNAs</td>
<td>Baselga-Escudero (2015), Carlin et al. (2013), Vucetic et al. (2010)</td>
</tr>
<tr>
<td style="text-align: left;">Under-nourishment</td>
<td style="text-align: center;">Rodent/adult/adult</td>
<td style="text-align: center;">Hepatic</td>
<td style="text-align: center;">miRNAs</td>
<td>Tryndyak et al. (2016)</td>
</tr>
</tbody>
</table>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<h3>Diagenode products for your epigenomics research in Toxicology</h3>
<div class="row">
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #099f92; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/chromatin-function">Chromatin analysis</a></h3>
<center><a href="https://www.diagenode.com/en/categories/chromatin-function"><img src="https://www.diagenode.com/img/cancer/chromatin-icon.png" /></a></center>
<p class="text-left">Understand the effects on chromatin and histone modifcations</p>
</div>
<ul>
<li>New to ChIP? <a href="https://www.diagenode.com/en/pages/portal/chip">Learn more</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-shearing">Chromatin shearing optimization</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-immunoprecipitation">Chromatin Immunoprecipitation</a></li>
<li>Validated <a href="https://www.diagenode.com/en/categories/antibodies">Antibodies</a></li>
<li><a href="https://www.diagenode.com/en/categories/library-preparation">Library preparation</a></li>
</ul>
</div>
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #30415c; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
<center><a href="https://www.diagenode.com/en/categories/dna-methylation"><img src="https://www.diagenode.com/img/cancer/dna-icon.png" /></a></center>
<p class="text-left">Analyze DNA methylation and the effects of environmental toxins</p>
</div>
<ul>
<li><a href="https://www.diagenode.com/en/categories/bisulfite-conversion">Bisulfite sequencing</a></li>
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<p class="text-left">Discover noncoding RNAs and miRNAs in the regulation of gene expression</p>
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<h2>Epigenetics and Cancer</h2>
<p>Epigenetic processes control the normal development and maintenance of gene expression in a number of organisms. However, disruption of epigenetic mechanisms may alter gene function, potentially leading to cellular transformations that lead to tumorigenesis. Cancer is a multistep process from a succession of processes that alter the growth of normal cells. In cancer, epigenetic reprogramming occurs at multiple levels including nuclear organization and nucleosome positioning, DNA methylation, modification of histones, alteration of epigenetic regulators such as transcription factor binding, and non-coding RNA, such as microRNA.</p>
<p>Epigenetic modifications are reversible and potential treatments could be geared to alter irregular transcription factor binding, DNA methylation or histone acetylation. Accurate study with a versatile number of tools is essential for the study of epigenetics including sound sample preparation and analysis methodologies for DNA methylation such as with immunoprecipitation or bisulfite sequencing, chromatin analysis with chromatin immunoprecipitation (ChIP) combined with qPCR or sequencing, and RNA modification study. As researchers elucidate the mechanisms and specific modifications associated with cancer, it may be possible to target abnormal modifications in cells with minimal damage to normal cells, making the prospect of epigenetic therapy increasingly promising.</p>
<h3>Diagenode products for your epigenomics research in Cancer</h3>
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<p class="text-left">Understand the role of chromatin in cancer regulation</p>
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<p class="text-left">Analyze DNA methylation and the effects on oncogenesis and tumor suppression</p>
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<li><a href="https://www.diagenode.com/en/categories/dna-methylation-profiling-services">DNA methylation services</a></li>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in cancer</p>
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<h2>Epigenetics in Neuroscience</h2>
<p>Neuroscience and epigenetics are at an exciting crossroads. Current research has shown that epigenetic mechanisms play a critical role in both behavior and the development and function of the nervous system. Histone modifications, changes in DNA methylation, and non-coding RNAs regulate various stages of neurogenesis and brain development while aberrant epigenetic regulation has been implicated in a number of neurological and brain disorders (Yao et, al. Nature Reviews Neuroscience, 2016).</p>
<p>Neuroscientists seek to uncover how epigenetic marks and transcriptional changes regulate gene expression to influence changes in areas such as behavior and the development of neural pathways and brain structures. Understanding how epigenetics affects nervous system function requires an integrative approach incorporating multiple levels of analysis. For example, research has uncovered the role of transcription factors, non-coding RNAs, and other molecules that mediate learning and memory. In addition, chromatin modifications and non-coding RNAs have been shown to influence epigenetic mechanisms in neurogenesis.</p>
<p>Understanding the molecular components and environmental conditions that affect epigenetic change will eventually provide the basis to develop therapies to treat neurological and psychiatric conditions. As neuroscientists learn how changes in chromatin architecture affect transcriptional regulation and gene expression, the link between the epigenome and the various areas in neuroscience will become clearer.</p>
<h3><span class="diacol">Neuroscience and epigenetics intersect in a number of areas: </span></h3>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#memory"> <i class="fa fa-square-o"></i> Epigenetics in memory, memory disorders, and learning</a>
<div id="memory" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms underlying learning and the inheritance of learned behaviors</strong></p>
<p>In this review, researchers outline epigenetic mechanisms by which gene expression is regulated in animals and humans. Using fear learning as a framework, they show how such mechanisms underlie learning and stress responsiveness. Finally, they discuss how epigenetic mechanisms might inform us about the transgenerational inheritance of behavioral traits that are being increasingly reported. Trends in Neuroscience, 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
<blockquote><br />
<p><strong>Epigenetic regulation of memory formation and maintenance</strong></p>
<p>In the last decade, epigenetic markers like DNA methylation and post-translational modifications of histone tails have emerged as important regulators of the memory process. Their ability to regulate gene transcription dynamically in response to neuronal activation supports the consolidation of long-term memory.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2779706/" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#schizophrenia"> <i class="fa fa-square-o"></i> Schizophrenia</a>
<div id="schizophrenia" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in schizophrenia</strong></p>
<p>In this review, the authors present an overview of schizophrenia and discuss the role of nature versus nurture in its pathology, where ‘nature’ is considered to be inherited or genetic vulnerability to schizophrenia, and ‘nurture’ is proposed to exert its effects through epigenetic mechanisms. Second, they define DNA methylation and discuss the evidence for its role in schizophrenia. Third, they define posttranslational histone modifications and discuss their place in schizophrenia. This research is likely to lead to the development of epigenetic therapy, which holds the promise of alleviating cognitive deficits associated with schizophrenia. Biochimica and Biophysica Acta, 2009.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#addiction"> <i class="fa fa-square-o"></i> Addiction disorder</a>
<div id="addiction" class="content">
<blockquote><br />
<p><strong>Epigenetics of addiction: Epigenetic study untangles addiction and relapse in the brain</strong></p>
<p>New research uncovers an epigenetic reason why drug users who attempt to quit are prone to relapse despite negative consequences to their health and livelihood. The findings help to explain how casual drug use can produce long-lasting brain changes that increase vulnerability to relapse in individuals suffering from substance use disorders. Science Daily, September 2017.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.sciencedaily.com/releases/2017/09/170927123612.htm" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#neurogenesis"> <i class="fa fa-square-o"></i> Neurogenesis</a>
<div id="neurogenesis" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in neurogenesis</strong></p>
<p>Epigenetic mechanisms — including DNA and histone modifications, as well as regulation by non-coding RNAs — have pivotal roles in different stages of neurogenesis. The authors also briefly cover the emerging field of epitranscriptomics, which involves modifications of mRNAs and long non-coding RNAs.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-017-0365-z">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#depression"> <i class="fa fa-square-o"></i> Depression</a>
<div id="depression" class="content">
<blockquote><br />
<p><strong>Epigenetics of depression</strong></p>
<p>Major depressive disorder (MDD) is a leading cause of disability worldwide and is associated with poor psychological, medical, and socioeconomic outcomes. This review presents the evidence supporting a role for epigenetic effects in MDD and in treatment response. Prog Mol Biol Transl Sci. 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25410543">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#other"> <i class="fa fa-square-o"></i> Other disorders such as Rett’s, Autism, Parkinson’s, Huntington’s </a>
<div id="other" class="content">
<blockquote>
<p><strong>Parkinson’s disease</strong></p>
<p>DNA methylation in Parkinson's disease</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/27120258">Read more</a></p>
</blockquote>
<blockquote>
<p><strong>Rett’s Syndrome</strong></p>
<p>Epigenetic regulation of memory by acetylation and methylation of chromatin: implications in neurological disorders, aging, and addiction</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/24777294">Read more</a></p>
</blockquote>
</div>
</li>
</ul>
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<h3>Diagenode products for your epigenomics research in Neuroscience</h3>
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<p class="text-left">Understand the role of chromatin in neuroscience</p>
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<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
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<p class="text-left">Analyze DNA methylation and the effects on neurogenesis, brain development, and more</p>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression</p>
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<div class="extra-spaced">
<h2>Epigenetic Regulation in Plants</h2>
<p>Plants utilize a number of gene regulation mechanisms to ensure proper development, function, growth, and survival under different environmental conditions. Plants depend on changes in gene expression to respond to environmental stimuli, in which the full repertoire of histone modifications, DNA methylation, and small ncRNAs play an important role in epigenetic regulation.</p>
<p>Studying the epigenetics of model plants such as Arabidopsis thaliana have allowed researchers to understand pathways that maintain chromatin modifications as well as the mapping of modifications such as DNA methylation on a genome-wide scale. Small RNAs have also been implicated in playing a role in the distribution of chromatin modifications, and RNA may also play a role in the complex epigenetic interactions that occur between homologous sequences (Moazed et al, 2009). In the future, by understanding epigenetic control, researchers can uncover the research necessary to improve plant growth, yields, and transformation efficiency especially in the face of climate change and other environmental factors.</p>
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<h3 style="font-weight: 100; margin-top: 0;">Chromatin</h3>
<p>Chromatin consists of nucleosomes formed by a complex of histone proteins and DNA, which allows the packaging of DNA into the nucleus. The less condensed euchromatin represents transcriptionally active regions, while heterochromatin is usually inactive (Vaillant and Paszkowski, 2007). Chromatin state is known to be influenced by both DNA methylation and histone modifications which in turn impact gene expression and the structure of chromosomes. In a recent study, the role of chromatin modifications during plant reproduction elucidated 3-dimensional chromosome reorganization mediated by histones and DNA methylation (Dukowic-Schulze et al. 2017). In addition, gibberellins have been shown in increasing the level of histone acetylation, which affects regions of chromatin involved in maize seed germination (Zheng et al. 2017). Another study reports a novel function of a tomato histone deacetylase gene in the regulation of fruit ripening (Guo et al. 2017).</p>
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<p>In addition, multigene families encode transcription factors, with members found throughout the genome or clustered on the same chromosome. Numerous DNA binding proteins that interact with plant promoters have been identified -- some are similar to well-characterized transcription factors in animals or yeast, while others are unique to plants. For example, diverse members of the subfamily X of the plant-specific ethylene response factor (ERF) transcription factors coordinate stress signaling with wound repair activation. Tissue repair is also enhanced through a protein complex of ERF and GRAS TFs (Heyman et. al,.2018). A compilation of known plant transcription factors can be found in the plant transcription factor database at http://plntfdb.bio.uni-potsdam.de/v3.0/.</p>
</div>
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<h3 style="font-weight: 100; margin-top: 0;">RNA</h3>
<p>Recent research shows that a number of classes of small RNAs are key epigenetic regulators. In many cases, small RNAs have been implicated in DNA methylation and chromatin modification (Meyer, 2015). In addition, the role of small RNAs has been implicated in plant stress tolerance (Kumar et al., 2017). López-Galiano et al also provided insight into a coordinated function of a miRNA gene and histone modifications in regulating the expression of a WRKY transcription factor in response to stress.</p>
<p>RNA interference (RNAi) is another epigenetic mechanism that leads to small RNA generation, which mediates gene silencing at the post-transcriptional level. RNAi technology has immense potential for plant disease resistance.</p>
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<h3 style="font-weight: 100; margin-top: 0;">DNA methylation</h3>
<p>Plants, unlike animals, have three sites that can be methylated G, CHG (H can be A, C, T), and CHH (Law and Jacobsen, 2010). DNA methylation has attracted particular interest. In Arabidopsis, one-third of methylated genes occur in transcribed regions, and 5% of genes are methylated in promoter regions, suggesting that many of these are epigenetically regulated. (Zhang et al., 2006).</p>
<p>There are thousands of differentially methylated regions (DMRs) that influence phenotype by influencing gene expression. The analysis of epigenetic recombinant inbred line (epiRIL) plants from Arabidopsis points to the evidence of the influence of DMRs. An epiRIL results from crossing two genetically identical plants with differing DNA methylation levels (with one parent as a homozygous mutant for an essential DNA methylation maintenance gene). The offspring of these plants have similar genomes that vary only in methylation levels. Many traits have been studied using epiRILs -- flowering time, plant height, and response to abiotic stress, some of which have now been mapped to DMRs (Zhang et al. 2018)</p>
<p>Regulation by DNA methylation has been shown to be important in many aspects of plant development and response such as vernalization, hybrid vigor, and self-incompatibility (Itabashi et al. 2017). For example, vernalization treatments have shown reduced DNA methylation and subsequent initiation of flowering (Burn et al., 1993). Stress can also influence DNA methylation in plants as a response to environmental stimuli. (Steward et al., 2002; Song et al., 2012). A high degree of DNA methylation has also suggested the role in the improvement of plant fitness under different environmental conditions (Saéz-Laguna et al., 2014). In addition, methylation can affect normal fruit and hypomethylation predicts homeotic transformation and loss of fruit yield (Ong-Abdullah et al., 2015)</p>
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<p>DNA demethylation has also been implied in various aspects of plant development including pollen tube formation, embryogenesis, fruit ripening, stomatal development, and nodule formation ( Li et al. 2017). Demethylation of rice genomic DNA caused an altered pattern of gene expression, inducing dwarf plants (Sano et al., 1990).</p>
<p>Epigenetic modifications contribute to the stability and survival of the plants and their ability to adapt in different environmental conditions.</p>
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<h3>Diagenode products for your epigenomics research in plants</h3>
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<p class="text-left">DNA methylation and demethylation and the effects on plant response and function</p>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression in plants</p>
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<h3>References</h3>
<p><small> Burn, J. et al (1993). DNA methylation, vernalization, and the initiation of flowering. Proc. Natl. Acad. Sci. U.S.A. 90, 287–291. doi: 10.1006/scdb.1996.0055 </small></p>
<p><small> Dukowic-Schulze S, Liu C, Chen C (2017) Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2222-0</small></p>
<p><small> Guo J et al (2017) A histone deacetylase gene, SlHDA3, acts as a negative regulator of fruit ripening and carotenoid accumulation. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2211-3</small></p>
<p><small> Heyman J, et.al (2018) Journal of Cell Science Emerging role of the plant ERF transcription factors in coordinating wound defense responses and repair doi: 10.1242/jcs.208215</small></p>
<p><small> Itabashi E, Osabe K, Fujimoto R, Kakizaki T (2017) Epigenetic regulation of agronomical traits in Brassicaceae. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2223-z</small></p>
<p><small> Kumar V et al (2017) Plant small RNAs: the essential epigenetic regulators of gene expression for salt-stress responses and tolerance. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2210-4</small></p>
<p><small> Law, J. A., and Jacobsen, S. E. (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11, 204–220. doi: 10.1038/nrg2719</small></p>
<p><small> Meyer, P. (2015). Epigenetic variation and environmental change. J. Exp. Bot. 66, 3541–3548. doi: 10.1093/jxb/eru502</small></p>
<p><small> Moazed, D. (2009) Small RNAs in transcriptional gene silencing and genome defence. Nature. doi: 10.1038/nature07756</small></p>
<p><small> Ong-Abdullah et al. (2015). Loss of Karma transposon methylation underlies the mantled somaclonal variant of oil palm. Nature 525, 533–537. doi: 10.1038/nature15365</small></p>
<p><small> Saéz-Laguna et al. (2014). Epigenetic variability in the genetically uniform forest tree species. PLoS One 9:e103145. doi: 10.1371/journal.pone.0103145</small></p>
<p><small> Sano, H. et al. (1990). A single treatment of rice seedlings with 5-azacytidine induces heritable dwarfism and undermethylation of genomic DNA. Mol. Gen. Genet. 220, 441–447. doi: 10.1007/BF00391751</small></p>
<p><small> Song, J et al (2012). Vernalization – A cold-induced epigenetic switch. J. Cell Sci. 125, 3723–3731. doi: 10.1242/jcs.084764</small></p>
<p><small> Steward, N et al. (2002). Periodic DNA methylation in maize nucleosomes and demethylation by environmental stress. J. Biol. Chem. 277, 37741–37746. doi: 10.1074/jbc.M204050200</small></p>
<p><small> Vaillant, I., and Paszkowski, J. (2007). Role of histone and DNA methylation in gene regulation. Curr. Opin. Plant Biol. 10, 528–533. doi: 10.1016/j.pbi.2007.06.008</small></p>
<p><small> Zhang, et al. (2006). Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201. doi: 10.1016/j.cell.2006.08.003</small></p>
<p><small> Zhang et al. 2018 Understanding the evolutionary potential of epigenetic variation: a comparison of heritable phenotypic variation in epiRILs, RILs, and natural ecotypes of Arabidopsis thaliana. Heredity 121, 257–265 (2018) doi:10.1038/s41437-018-0095-9</small></p>
<p><small> Zheng X et al (2017) Histone acetylation is involved in GA-mediated 45S rDNA decondensation in maize aleurone layers. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2207-z</small></p>
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<li><span><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex 24 Single Indexes for Illumina - Set #B">D-Plex 24 Single Indexes for Illumina - Set #B (25-48)</a></span></li>
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<p><span>With each set of indexes, you can multiplex up to 24.</span></p>
<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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<p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
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'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'description' => '<p style="text-align: left;"><span>D-Plex Single Indexes Module - Set A includes PCR primers with <span>24</span><span><span> barcodes (i7 index)</span> for library multiplexing</span> with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. </span></p>
<p style="text-align: left;"><span>These single indexes (SI) were designed and validated to fit the D-Plex technology for Illumina sequencing. Addition of a unique molecular identifier (UMI) sequence enables the accurate bioinformatic identification and removal of PCR duplicates from amplified libraries.</span></p>
<p><span>Two sets are available separately: </span></p>
<ul>
<li><span>C05030010 - </span>D-Plex Single Indexes for Illumina - Set A</li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-single-indexes-set-b" title="D-Plex 24 Single Indexes for Illumina - Set #B">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
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<p><span>Each set can be used for library multiplexing up to 24. <span>Set A and Set B can be used simultaneously for library multiplexing up to 48.</span></span></p>
<p><span>Read more about the </span><a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a><span>.</span><span> </span></p>',
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<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
<p>Benefits of the MicroChIP DiaPure columns:</p>
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<p>Successful ChIP-seq results generated on 50,000 of K562 cells using True MicroChIP technology. ChIP has been performed accordingly to True MicroChIP protocol (Diagenode, Cat. No. C01010130), including DNA purification using the MicroChIP DiaPure columns. For the library preparation the MicroPlex Library Preparation Kit (Diagenode, Cat. No. C05010001) has been used. The below figure shows the peaks from ChIP-seq experiments using the following Diagenode antibodies: H3K4me1 (C15410194), H3K9/14ac (C15410200), H3K27ac (C15410196) and H3K36me3 (C15410192).</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'description' => '<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2 style="font-size: 22px;">DNA断片化、ライブラリー調製、自動化：NGSのワンストップショップ</h2>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-12 medium-12 large-12 columns">
<h4>1. 断片化装置を選択してください：150 bp〜75 kbの範囲でDNAを断片化します。</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-pico-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/bioruptor_pico.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/megaruptor2-1-unit"><img src="https://www.diagenode.com/img/product/shearing_technologies/B06010001_megaruptor2.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-one-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/br-one-profil.png" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns">5μlまで断片化：150 bp〜2 kb<br />NGS DNAライブラリー調製およびFFPE核酸抽出に最適で、</td>
<td class="small-4 medium-4 large-4 columns">2 kb〜75 kbの範囲をできます。<br />メイトペアライブラリー調製および長いフラグメントDNAシーケンシングに最適で、この軽量デスクトップデバイスで</td>
<td class="small-4 medium-4 large-4 columns">20または50μlの断片化が可能です。</td>
</tr>
</tbody>
</table>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-8 medium-8 large-8 columns">
<h4>2. 最適化されたライブラリー調整キットを選択してください。</h4>
</th>
<th class="small-4 medium-4 large-4 columns">
<h4>3. ライブラリー前処理自動化を選択して、比類のないデータ再現性を実感</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><img src="https://www.diagenode.com/img/product/kits/microPlex_library_preparation.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/ideal-library-preparation-kit-x24-incl-index-primer-set-1-24-rxns"><img src="https://www.diagenode.com/img/product/kits/box_kit.jpg" style="display: block; margin-left: auto; margin-right: auto;" height="173" width="250" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/sx-8g-ip-star-compact-automated-system-1-unit"><img src="https://www.diagenode.com/img/product/automation/B03000002%20_ipstar_compact.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">50pgの低入力：MicroPlex Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">5ng以上：iDeal Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">Achieve great NGS data easily</td>
</tr>
</tbody>
</table>
</div>
</div>
<blockquote>
<div class="row">
<div class="small-12 medium-12 large-12 columns"><span class="label" style="margin-bottom: 16px; margin-left: -22px; font-size: 15px;">DiagenodeがNGS研究にぴったりなプロバイダーである理由</span>
<p>Diagenodeは15年以上もエピジェネティクス研究に専念、専門としています。 ChIP研究クロマチン用のユニークな断片化システムの開発から始まり、 専門知識を活かし、5μlのせん断体積まで可能で、NGS DNAライブラリーの調製に最適な最先端DNA断片化装置の開発にたどり着きました。 我々は以来、ChIP-seq、Methyl-seq、NGSライブラリー調製用キットを研究開発し、業界をリードする免疫沈降研究と同様に、ライブラリー調製を自動化および完結させる独自の自動化システムを開発にも成功しました。</p>
<ul>
<li>信頼されるせん断装置</li>
<li>様々なインプットからのライブラリ作成キット</li>
<li>独自の自動化デバイス</li>
</ul>
</div>
</div>
</blockquote>
<div class="row">
<div class="small-12 columns">
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#panel1a">次世代シーケンシングへの理解とその専門知識</a>
<div id="panel1a" class="content">
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><strong>次世代シーケンシング (NGS)</strong> ）は、著しいスケールとハイスループットでシーケンシングを行い、1日に数十億もの塩基生成を可能にします。 NGSのハイスループットは迅速でありながら正確で、再現性のあるデータセットを実現し、さらにシーケンシング費用を削減します。 NGSは、ゲノムシーケンシング、ゲノム再シーケンシング、デノボシーケンシング、トランスクリプトームシーケンシング、その他にDNA-タンパク質相互作用の検出やエピゲノムなどを示します。 指数関数的に増加するシーケンシングデータの需要は、計算分析の障害や解釈、データストレージなどの課題を解決します。</p>
<p>アプリケーションおよび出発物質に応じて、数百万から数十億の鋳型DNA分子を大規模に並行してシーケンシングすることが可能です。その為に、異なる化学物質を使用するいくつかの市販のNGSプラットフォームを利用することができます。 NGSプラットフォームの種類によっては、事前準備とライブラリー作成が必要です。</p>
<p>NGSにとっても、特にデータ処理と分析に関した大きな課題はあります。第3世代技術はゲノミクス研究にさらに革命を起こすであろうと大きく期待されています。</p>
</div>
</div>
<div class="row">
<div class="small-6 medium-6 large-6 columns">
<p><strong>NGS アプリケーション</strong></p>
<ul>
<li>全ゲノム配列決定</li>
<li>デノボシーケンシング</li>
<li>標的配列</li>
<li>Exomeシーケンシング</li>
<li>トランスクリプトーム配列決定</li>
<li>ゲノム配列決定</li>
<li>ミトコンドリア配列決定</li>
<li>DNA-タンパク質相互作用（ChIP-seq</li>
<li>バリアント検出</li>
<li>ゲノム仕上げ</li>
</ul>
</div>
<div class="small-6 medium-6 large-6 columns">
<p><strong>研究分野におけるNGS:</strong></p>
<ul>
<li>腫瘍学</li>
<li>リプロダクティブ・ヘルス</li>
<li>法医学ゲノミクス</li>
<li>アグリゲノミックス</li>
<li>複雑な病気</li>
<li>微生物ゲノミクス</li>
<li>食品・環境ゲノミクス</li>
<li>創薬ゲノミクス - パーソナライズド・メディカル</li>
</ul>
</div>
<div class="small-12 medium-12 large-12 columns">
<p><strong>NGSの用語</strong></p>
<dl>
<dt>リード（読み取り）</dt>
<dd>この装置から得られた連続した単一のストレッチ</dd>
<dt>断片リード</dt>
<dd>フラグメントライブラリからの読み込み。 シーケンシングプラットフォームに応じて、読み取りは通常約100〜300bp。</dd>
<dt>断片ペアエンドリード</dt>
<dd>断片ライブラリーからDNA断片の各末端2つの読み取り。</dd>
<dt>メイトペアリード</dt>
<dd>大きなDNA断片（通常は予め定義されたサイズ範囲）の各末端から2つの読み取り。</dd>
<dt>カバレッジ（例）</dt>
<dd>30×適用範囲とは、参照ゲノム中の各塩基対が平均30回の読み取りを示す。</dd>
</dl>
</div>
</div>
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2>NGSプラットフォーム</h2>
<h3><a href="http://www.illumina.com" target="_blank">イルミナ</a></h3>
<p>イルミナは、クローン的に増幅された鋳型DNA（クラスター）上に位置する、蛍光標識された可逆的鎖ターミネーターヌクレオチドを用いた配列別合成技術を使用。 DNAクラスターは、ガラスフローセルの表面上に固定化され、 ワークフローは、4つのヌクレオチド（それぞれ異なる蛍光色素で標識された）の組み込み、4色イメージング、色素や末端基の切断、取り込み、イメージングなどを繰り返します。フローセルは大規模な並列配列決定を受ける。 この方法により、単一蛍光標識されたヌクレオチドの制御添加によるモノヌクレオチドのエラーを回避する可能性があります。 読み取りの長さは、通常約100〜150 bpです。</p>
<h3><a href="http://www.lifetechnologies.com" target="_blank">イオン トレント</a></h3>
<p>イオントレントは、半導体技術チップを用いて、合成中にヌクレオチドを取り込む際に放出されたプロトンを検出します。 これは、イオン球粒子と呼ばれるビーズの表面にエマルションPCR（emPCR）を使用し、リンクされた特定のアダプターを用いてDNA断片を増幅します。 各ビーズは1種類のDNA断片で覆われていて、異なるDNA断片を有するビーズは次いで、チップの陽子感知ウェル内に配置されます。 チップには一度に4つのヌクレオチドのうちの1つが浸水し、このプロセスは異なるヌクレオチドで15秒ごとに繰り返されます。 配列決定の間に4つの塩基の各々が1つずつ導入されます、組み込みの場合はプロトンが放出され、電圧信号が取り込みに比例して検出されます。.</p>
<h3><a href="http://www.pacificbiosciences.com" target="_blank">パシフィック バイオサイエンス</a></h3>
<p>パシフィックバイオサイエンスでは、20kbを超える塩基対の読み取りも、単一分子リアルタイム（SMRT）シーケンシングによる構造および細胞タイプの変化を観察することができます。 このプラットフォームでは、超長鎖二本鎖DNA（dsDNA）断片が、Megaruptor（登録商標）のようなDiagenode装置を用いたランダムシアリングまたは目的の標的領域の増幅によって生成されます。 SMRTbellライブラリーは、ユニバーサルヘアピンアダプターをDNA断片の各末端に連結することによって生成します。 サイズ選択条件による洗浄ステップの後、配列決定プライマーをSMRTbellテンプレートにアニーリングし、鋳型DNAに結合したDNAポリメラーゼを含む配列決定を、蛍光標識ヌクレオチドの存在下で開始。 各塩基が取り込まれると、異なる蛍光のパルスをリアルタイムで検出します。</p>
<h3><a href="https://nanoporetech.com" target="_blank">オックスフォード ナノポア</a></h3>
<p>Oxford Nanoporeは、単一のDNA分子配列決定に基づく技術を開発します。その技術により生物学的分子、すなわちDNAが一群の電気抵抗性高分子膜として位置するナノスケールの孔（ナノ細孔）またはその近くを通過し、イオン電流が変化します。 この変化に関する情報は、例えば4つのヌクレオチド（AまたはG r CまたはT）ならびに修飾されたヌクレオチドすべてを区別することによって分子情報に訳されます。 シーケンシングミニオンデバイスのフローセルは、数百個のナノポアチャネルのセンサアレイを含みます。 DNAサンプルは、Diagenode社のMegaruptor（登録商標）を用いてランダムシアリングによって生成され得る超長鎖DNAフラグメントが必要です。</p>
<h3><a href="http://www.lifetechnologies.com/be/en/home/life-science/sequencing/next-generation-sequencing/solid-next-generation-sequencing.html" target="_blank">SOLiD</a></h3>
<p>SOLiDは、ユニークな化学作用により、何千という個々のDNA分子の同時配列決定を可能にします。 それは、アダプター対ライブラリーのフラグメントが適切で、せん断されたゲノムDNAへのアダプターのライゲーションによるライブラリー作製から始まります。 次のステップでは、エマルジョンPCR（emPCR）を実施して、ビーズの表面上の個々の鋳型DNA分子をクローン的に増幅。 emPCRでは、個々の鋳型DNAをPCR試薬と混合し、水中油型エマルジョン内の疎水性シェルで囲まれた水性液滴内のプライマーコートビーズを、配列決定のためにロードするスライドガラスの表面にランダムに付着。 この技術は、シークエンシングプライマーへのライゲーションで競合する4つの蛍光標識されたジ塩基プローブのセットを使用します。</p>
<h3><a href="http://454.com/products/technology.asp" target="_blank">454</a></h3>
<p>454は、大規模並列パイロシーケンシングを利用しています。 始めに全ゲノムDNAまたは標的遺伝子断片の300〜800bp断片のライブラリー調製します。 次に、DNAフラグメントへのアダプターの付着および単一のDNA鎖の分離。 その後アダプターに連結されたDNAフラグメントをエマルジョンベースのクローン増幅（emPCR）で処理し、DNAライブラリーフラグメントをミクロンサイズのビーズ上に配置します。 各DNA結合ビーズを光ファイバーチップ上のウェルに入れ、器具に挿入します。 4つのDNAヌクレオチドは、配列決定操作中に固定された順序で連続して加えられ、並行して配列決定されます。</p>
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<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3´ end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode’s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching”</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg. </span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>® - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing. <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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'description' => '<div class="row"><div class="small-12 medium-4 large-4 columns"><div class="panel"><h3><em>lncRNAs in cancer</em></h3><p class="text-left">Gastrointestinal cancer: Gastrointestinal cancers occur as a result of dysregulated signaling pathways and cellular processes, such as the cell cycle or apoptosis. LncRNAs can regulate proliferation of gastrointestinal cancer through interacting with RNA targets, localization to chromatin, or binding to proteins. Read more about Long non-coding RNAs: crucial regulators of gastrointestinal cancer cell proliferation</p><h3><em>microRNAs in cancer</em></h3><p class="text-left">miR-155 has been found overexpressed in many cancer types including hematopoietic cancers, breast, lung and colon cancer<br /><br /> <a href="https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf">https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf</a></p></div></div><div class="small-12 medium-8 large-8 columns"><center><img src="https://www.diagenode.com/img/cancer/long-non-coding-rna.jpg" width="550" height="345" /></center><p></p><p>Various non-coding RNAs (ncRNAs) have been found to function as key regulators for transcription, chromatin remodelling, and post-transcriptional modification, thus making them relevant in oncogenesis, both as tumor suppressors and as drivers. For example, a number of microRNAs (miRNAs), one of the more well-studied types of ncRNAs, have been identified as potential cancer biomarkers and clinical targets. Other ncRNAs, such as long noncoding RNAs are involved in cancer regulation and proliferation. Understanding the role of ncRNAs will be critical for cancer research and therapeutic development.</p></div></div>',
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<p><img src="https://www.diagenode.com/img/areas/toxicology.jpg" /></p>
</div>
<h2>Epigenetics in environmental toxicology</h2>
<p>The fact that environmental factors induce DNA mutations that may lead to disease is well-established and will have tremendous benefits when incorporated into various environmental safety and health assessments. Environmental factors such as dietary intake, drugs, stress, or exposure to toxins, can cause epigenetic changes by possibly altering how transcription factors bind to DNA or changing the structure of the histones that DNA wraps around. These structural changes can affect gene activity or gene expression. A number of environmental factors have been investigated for their effect on epigenetic changes including phthalates, toxic metals, smoking, air pollution, jet fuel, environmental stress, and a high fat diet. Effects on epigenetic mechanisms, DNA methylation patterns, histone modifications, miRNA expression have been documented as a result. The table below (Marczylo et al, 2016 and Society of Toxicology, 2018) summarizes a few of the studies that have been done for putative environmentally-induced epigenetic toxicity in humans or rat/mouse.</p>
<p class="extra-spaced">In the future, incorporating epigenetic evaluation into toxicity tests can increase the safety of both food and environmental substances.</p>
<table class="extra-spaced">
<tbody>
<tr>
<th style="text-align: center;">Toxin/exposure</th>
<th style="text-align: center;">Species/stage of exposure/effect</th>
<th style="text-align: center;">Phenotype</th>
<th style="text-align: center;">Epigenetic change</th>
<th style="text-align: center;">Reference(s)</th>
</tr>
<tr>
<td>Air pollution</td>
<td style="text-align: center;">Human/childhood/childhood</td>
<td style="text-align: center;">Asthma</td>
<td style="text-align: center;">Epigenetic mechanisms</td>
<td style="text-align: left;">Somineni et al. (2016)</td>
</tr>
<tr style="text-align: center;">
<td style="text-align: left;">BPA</td>
<td>Human/in utero/childhood</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">DNA methylation</td>
<td style="text-align: left;">Kundakovic (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Formaldehyde</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Alzheimer’s</td>
<td style="text-align: center;">Epigenetic mechanisms and DNA methylation</td>
<td>Tong et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Methylmercury</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">Histone modifications and DNA methylation</td>
<td>Onishchenko (2008)</td>
</tr>
<tr style="text-align: center;">
<td>Arsenic</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Skin disorder</td>
<td style="text-align: center;">DNA methylation</td>
<td>Paul et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Nickel</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">NSCLC survival</td>
<td style="text-align: center;">miRNA</td>
<td>Chiou et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Polycyclic aromatic hydrocarbons</td>
<td style="text-align: center;">Human/adult/adult</td>
<td style="text-align: center;">Chromosome aberrations - PBL</td>
<td style="text-align: center;">DNA methylation</td>
<td>Yang et al. (2012)</td>
</tr>
<tr style="text-align: center;">
<td>Various phthalates</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Decreased testosterone/gonadal</td>
<td style="text-align: center;">DNA methylation and histone modifications</td>
<td>Kilcoyne et al. (2014) Martinez-Arguelles et al. (2009), Papoutsis et al. (2015), Takeda et al. (2012), Yoshioka et al. (2011)</td>
</tr>
<tr style="text-align: center;">
<td>Smoking</td>
<td style="text-align: center;">Human/Lifetime/adult</td>
<td style="text-align: center;">COPD and tumor</td>
<td style="text-align: center;">Epigenetic mechanisms, DNA methylation, miRNA</td>
<td>Lin (2010), Ostrow (2013) Shenker (2013), Xie et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Alcohol</td>
<td style="text-align: center;">Rodent/lifetime and in utero</td>
<td style="text-align: center;">Nuerological, cardiac, behavior, stem cell</td>
<td style="text-align: center;">Histone modification and miRNA</td>
<td>Ignacio et al. (2014), Middleton et al. (2012), Leu et al. (2014), Pascual et al. (2011), Peng et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>High fat diet</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Diet preference</td>
<td style="text-align: center;">DNA methylation and miRNAs</td>
<td>Baselga-Escudero (2015), Carlin et al. (2013), Vucetic et al. (2010)</td>
</tr>
<tr>
<td style="text-align: left;">Under-nourishment</td>
<td style="text-align: center;">Rodent/adult/adult</td>
<td style="text-align: center;">Hepatic</td>
<td style="text-align: center;">miRNAs</td>
<td>Tryndyak et al. (2016)</td>
</tr>
</tbody>
</table>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<h3>Diagenode products for your epigenomics research in Toxicology</h3>
<div class="row">
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #099f92; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/chromatin-function">Chromatin analysis</a></h3>
<center><a href="https://www.diagenode.com/en/categories/chromatin-function"><img src="https://www.diagenode.com/img/cancer/chromatin-icon.png" /></a></center>
<p class="text-left">Understand the effects on chromatin and histone modifcations</p>
</div>
<ul>
<li>New to ChIP? <a href="https://www.diagenode.com/en/pages/portal/chip">Learn more</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-shearing">Chromatin shearing optimization</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-immunoprecipitation">Chromatin Immunoprecipitation</a></li>
<li>Validated <a href="https://www.diagenode.com/en/categories/antibodies">Antibodies</a></li>
<li><a href="https://www.diagenode.com/en/categories/library-preparation">Library preparation</a></li>
</ul>
</div>
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #30415c; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
<center><a href="https://www.diagenode.com/en/categories/dna-methylation"><img src="https://www.diagenode.com/img/cancer/dna-icon.png" /></a></center>
<p class="text-left">Analyze DNA methylation and the effects of environmental toxins</p>
</div>
<ul>
<li><a href="https://www.diagenode.com/en/categories/bisulfite-conversion">Bisulfite sequencing</a></li>
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<p class="text-left">Discover noncoding RNAs and miRNAs in the regulation of gene expression</p>
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<h2>Epigenetics and Cancer</h2>
<p>Epigenetic processes control the normal development and maintenance of gene expression in a number of organisms. However, disruption of epigenetic mechanisms may alter gene function, potentially leading to cellular transformations that lead to tumorigenesis. Cancer is a multistep process from a succession of processes that alter the growth of normal cells. In cancer, epigenetic reprogramming occurs at multiple levels including nuclear organization and nucleosome positioning, DNA methylation, modification of histones, alteration of epigenetic regulators such as transcription factor binding, and non-coding RNA, such as microRNA.</p>
<p>Epigenetic modifications are reversible and potential treatments could be geared to alter irregular transcription factor binding, DNA methylation or histone acetylation. Accurate study with a versatile number of tools is essential for the study of epigenetics including sound sample preparation and analysis methodologies for DNA methylation such as with immunoprecipitation or bisulfite sequencing, chromatin analysis with chromatin immunoprecipitation (ChIP) combined with qPCR or sequencing, and RNA modification study. As researchers elucidate the mechanisms and specific modifications associated with cancer, it may be possible to target abnormal modifications in cells with minimal damage to normal cells, making the prospect of epigenetic therapy increasingly promising.</p>
<h3>Diagenode products for your epigenomics research in Cancer</h3>
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<p class="text-left">Understand the role of chromatin in cancer regulation</p>
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<p class="text-left">Analyze DNA methylation and the effects on oncogenesis and tumor suppression</p>
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<li><a href="https://www.diagenode.com/en/categories/dna-methylation-profiling-services">DNA methylation services</a></li>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in cancer</p>
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<h2>Epigenetics in Neuroscience</h2>
<p>Neuroscience and epigenetics are at an exciting crossroads. Current research has shown that epigenetic mechanisms play a critical role in both behavior and the development and function of the nervous system. Histone modifications, changes in DNA methylation, and non-coding RNAs regulate various stages of neurogenesis and brain development while aberrant epigenetic regulation has been implicated in a number of neurological and brain disorders (Yao et, al. Nature Reviews Neuroscience, 2016).</p>
<p>Neuroscientists seek to uncover how epigenetic marks and transcriptional changes regulate gene expression to influence changes in areas such as behavior and the development of neural pathways and brain structures. Understanding how epigenetics affects nervous system function requires an integrative approach incorporating multiple levels of analysis. For example, research has uncovered the role of transcription factors, non-coding RNAs, and other molecules that mediate learning and memory. In addition, chromatin modifications and non-coding RNAs have been shown to influence epigenetic mechanisms in neurogenesis.</p>
<p>Understanding the molecular components and environmental conditions that affect epigenetic change will eventually provide the basis to develop therapies to treat neurological and psychiatric conditions. As neuroscientists learn how changes in chromatin architecture affect transcriptional regulation and gene expression, the link between the epigenome and the various areas in neuroscience will become clearer.</p>
<h3><span class="diacol">Neuroscience and epigenetics intersect in a number of areas: </span></h3>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#memory"> <i class="fa fa-square-o"></i> Epigenetics in memory, memory disorders, and learning</a>
<div id="memory" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms underlying learning and the inheritance of learned behaviors</strong></p>
<p>In this review, researchers outline epigenetic mechanisms by which gene expression is regulated in animals and humans. Using fear learning as a framework, they show how such mechanisms underlie learning and stress responsiveness. Finally, they discuss how epigenetic mechanisms might inform us about the transgenerational inheritance of behavioral traits that are being increasingly reported. Trends in Neuroscience, 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
<blockquote><br />
<p><strong>Epigenetic regulation of memory formation and maintenance</strong></p>
<p>In the last decade, epigenetic markers like DNA methylation and post-translational modifications of histone tails have emerged as important regulators of the memory process. Their ability to regulate gene transcription dynamically in response to neuronal activation supports the consolidation of long-term memory.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2779706/" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#schizophrenia"> <i class="fa fa-square-o"></i> Schizophrenia</a>
<div id="schizophrenia" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in schizophrenia</strong></p>
<p>In this review, the authors present an overview of schizophrenia and discuss the role of nature versus nurture in its pathology, where ‘nature’ is considered to be inherited or genetic vulnerability to schizophrenia, and ‘nurture’ is proposed to exert its effects through epigenetic mechanisms. Second, they define DNA methylation and discuss the evidence for its role in schizophrenia. Third, they define posttranslational histone modifications and discuss their place in schizophrenia. This research is likely to lead to the development of epigenetic therapy, which holds the promise of alleviating cognitive deficits associated with schizophrenia. Biochimica and Biophysica Acta, 2009.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#addiction"> <i class="fa fa-square-o"></i> Addiction disorder</a>
<div id="addiction" class="content">
<blockquote><br />
<p><strong>Epigenetics of addiction: Epigenetic study untangles addiction and relapse in the brain</strong></p>
<p>New research uncovers an epigenetic reason why drug users who attempt to quit are prone to relapse despite negative consequences to their health and livelihood. The findings help to explain how casual drug use can produce long-lasting brain changes that increase vulnerability to relapse in individuals suffering from substance use disorders. Science Daily, September 2017.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.sciencedaily.com/releases/2017/09/170927123612.htm" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#neurogenesis"> <i class="fa fa-square-o"></i> Neurogenesis</a>
<div id="neurogenesis" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in neurogenesis</strong></p>
<p>Epigenetic mechanisms — including DNA and histone modifications, as well as regulation by non-coding RNAs — have pivotal roles in different stages of neurogenesis. The authors also briefly cover the emerging field of epitranscriptomics, which involves modifications of mRNAs and long non-coding RNAs.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-017-0365-z">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#depression"> <i class="fa fa-square-o"></i> Depression</a>
<div id="depression" class="content">
<blockquote><br />
<p><strong>Epigenetics of depression</strong></p>
<p>Major depressive disorder (MDD) is a leading cause of disability worldwide and is associated with poor psychological, medical, and socioeconomic outcomes. This review presents the evidence supporting a role for epigenetic effects in MDD and in treatment response. Prog Mol Biol Transl Sci. 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25410543">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#other"> <i class="fa fa-square-o"></i> Other disorders such as Rett’s, Autism, Parkinson’s, Huntington’s </a>
<div id="other" class="content">
<blockquote>
<p><strong>Parkinson’s disease</strong></p>
<p>DNA methylation in Parkinson's disease</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/27120258">Read more</a></p>
</blockquote>
<blockquote>
<p><strong>Rett’s Syndrome</strong></p>
<p>Epigenetic regulation of memory by acetylation and methylation of chromatin: implications in neurological disorders, aging, and addiction</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/24777294">Read more</a></p>
</blockquote>
</div>
</li>
</ul>
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<h3>Diagenode products for your epigenomics research in Neuroscience</h3>
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<p class="text-left">Understand the role of chromatin in neuroscience</p>
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<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
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<p class="text-left">Analyze DNA methylation and the effects on neurogenesis, brain development, and more</p>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression</p>
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<div class="extra-spaced">
<h2>Epigenetic Regulation in Plants</h2>
<p>Plants utilize a number of gene regulation mechanisms to ensure proper development, function, growth, and survival under different environmental conditions. Plants depend on changes in gene expression to respond to environmental stimuli, in which the full repertoire of histone modifications, DNA methylation, and small ncRNAs play an important role in epigenetic regulation.</p>
<p>Studying the epigenetics of model plants such as Arabidopsis thaliana have allowed researchers to understand pathways that maintain chromatin modifications as well as the mapping of modifications such as DNA methylation on a genome-wide scale. Small RNAs have also been implicated in playing a role in the distribution of chromatin modifications, and RNA may also play a role in the complex epigenetic interactions that occur between homologous sequences (Moazed et al, 2009). In the future, by understanding epigenetic control, researchers can uncover the research necessary to improve plant growth, yields, and transformation efficiency especially in the face of climate change and other environmental factors.</p>
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<h3 style="font-weight: 100; margin-top: 0;">Chromatin</h3>
<p>Chromatin consists of nucleosomes formed by a complex of histone proteins and DNA, which allows the packaging of DNA into the nucleus. The less condensed euchromatin represents transcriptionally active regions, while heterochromatin is usually inactive (Vaillant and Paszkowski, 2007). Chromatin state is known to be influenced by both DNA methylation and histone modifications which in turn impact gene expression and the structure of chromosomes. In a recent study, the role of chromatin modifications during plant reproduction elucidated 3-dimensional chromosome reorganization mediated by histones and DNA methylation (Dukowic-Schulze et al. 2017). In addition, gibberellins have been shown in increasing the level of histone acetylation, which affects regions of chromatin involved in maize seed germination (Zheng et al. 2017). Another study reports a novel function of a tomato histone deacetylase gene in the regulation of fruit ripening (Guo et al. 2017).</p>
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<p>In addition, multigene families encode transcription factors, with members found throughout the genome or clustered on the same chromosome. Numerous DNA binding proteins that interact with plant promoters have been identified -- some are similar to well-characterized transcription factors in animals or yeast, while others are unique to plants. For example, diverse members of the subfamily X of the plant-specific ethylene response factor (ERF) transcription factors coordinate stress signaling with wound repair activation. Tissue repair is also enhanced through a protein complex of ERF and GRAS TFs (Heyman et. al,.2018). A compilation of known plant transcription factors can be found in the plant transcription factor database at http://plntfdb.bio.uni-potsdam.de/v3.0/.</p>
</div>
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<h3 style="font-weight: 100; margin-top: 0;">RNA</h3>
<p>Recent research shows that a number of classes of small RNAs are key epigenetic regulators. In many cases, small RNAs have been implicated in DNA methylation and chromatin modification (Meyer, 2015). In addition, the role of small RNAs has been implicated in plant stress tolerance (Kumar et al., 2017). López-Galiano et al also provided insight into a coordinated function of a miRNA gene and histone modifications in regulating the expression of a WRKY transcription factor in response to stress.</p>
<p>RNA interference (RNAi) is another epigenetic mechanism that leads to small RNA generation, which mediates gene silencing at the post-transcriptional level. RNAi technology has immense potential for plant disease resistance.</p>
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<h3 style="font-weight: 100; margin-top: 0;">DNA methylation</h3>
<p>Plants, unlike animals, have three sites that can be methylated G, CHG (H can be A, C, T), and CHH (Law and Jacobsen, 2010). DNA methylation has attracted particular interest. In Arabidopsis, one-third of methylated genes occur in transcribed regions, and 5% of genes are methylated in promoter regions, suggesting that many of these are epigenetically regulated. (Zhang et al., 2006).</p>
<p>There are thousands of differentially methylated regions (DMRs) that influence phenotype by influencing gene expression. The analysis of epigenetic recombinant inbred line (epiRIL) plants from Arabidopsis points to the evidence of the influence of DMRs. An epiRIL results from crossing two genetically identical plants with differing DNA methylation levels (with one parent as a homozygous mutant for an essential DNA methylation maintenance gene). The offspring of these plants have similar genomes that vary only in methylation levels. Many traits have been studied using epiRILs -- flowering time, plant height, and response to abiotic stress, some of which have now been mapped to DMRs (Zhang et al. 2018)</p>
<p>Regulation by DNA methylation has been shown to be important in many aspects of plant development and response such as vernalization, hybrid vigor, and self-incompatibility (Itabashi et al. 2017). For example, vernalization treatments have shown reduced DNA methylation and subsequent initiation of flowering (Burn et al., 1993). Stress can also influence DNA methylation in plants as a response to environmental stimuli. (Steward et al., 2002; Song et al., 2012). A high degree of DNA methylation has also suggested the role in the improvement of plant fitness under different environmental conditions (Saéz-Laguna et al., 2014). In addition, methylation can affect normal fruit and hypomethylation predicts homeotic transformation and loss of fruit yield (Ong-Abdullah et al., 2015)</p>
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<p>DNA demethylation has also been implied in various aspects of plant development including pollen tube formation, embryogenesis, fruit ripening, stomatal development, and nodule formation ( Li et al. 2017). Demethylation of rice genomic DNA caused an altered pattern of gene expression, inducing dwarf plants (Sano et al., 1990).</p>
<p>Epigenetic modifications contribute to the stability and survival of the plants and their ability to adapt in different environmental conditions.</p>
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<h3>Diagenode products for your epigenomics research in plants</h3>
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<p class="text-left">DNA methylation and demethylation and the effects on plant response and function</p>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression in plants</p>
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<h3>References</h3>
<p><small> Burn, J. et al (1993). DNA methylation, vernalization, and the initiation of flowering. Proc. Natl. Acad. Sci. U.S.A. 90, 287–291. doi: 10.1006/scdb.1996.0055 </small></p>
<p><small> Dukowic-Schulze S, Liu C, Chen C (2017) Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2222-0</small></p>
<p><small> Guo J et al (2017) A histone deacetylase gene, SlHDA3, acts as a negative regulator of fruit ripening and carotenoid accumulation. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2211-3</small></p>
<p><small> Heyman J, et.al (2018) Journal of Cell Science Emerging role of the plant ERF transcription factors in coordinating wound defense responses and repair doi: 10.1242/jcs.208215</small></p>
<p><small> Itabashi E, Osabe K, Fujimoto R, Kakizaki T (2017) Epigenetic regulation of agronomical traits in Brassicaceae. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2223-z</small></p>
<p><small> Kumar V et al (2017) Plant small RNAs: the essential epigenetic regulators of gene expression for salt-stress responses and tolerance. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2210-4</small></p>
<p><small> Law, J. A., and Jacobsen, S. E. (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11, 204–220. doi: 10.1038/nrg2719</small></p>
<p><small> Meyer, P. (2015). Epigenetic variation and environmental change. J. Exp. Bot. 66, 3541–3548. doi: 10.1093/jxb/eru502</small></p>
<p><small> Moazed, D. (2009) Small RNAs in transcriptional gene silencing and genome defence. Nature. doi: 10.1038/nature07756</small></p>
<p><small> Ong-Abdullah et al. (2015). Loss of Karma transposon methylation underlies the mantled somaclonal variant of oil palm. Nature 525, 533–537. doi: 10.1038/nature15365</small></p>
<p><small> Saéz-Laguna et al. (2014). Epigenetic variability in the genetically uniform forest tree species. PLoS One 9:e103145. doi: 10.1371/journal.pone.0103145</small></p>
<p><small> Sano, H. et al. (1990). A single treatment of rice seedlings with 5-azacytidine induces heritable dwarfism and undermethylation of genomic DNA. Mol. Gen. Genet. 220, 441–447. doi: 10.1007/BF00391751</small></p>
<p><small> Song, J et al (2012). Vernalization – A cold-induced epigenetic switch. J. Cell Sci. 125, 3723–3731. doi: 10.1242/jcs.084764</small></p>
<p><small> Steward, N et al. (2002). Periodic DNA methylation in maize nucleosomes and demethylation by environmental stress. J. Biol. Chem. 277, 37741–37746. doi: 10.1074/jbc.M204050200</small></p>
<p><small> Vaillant, I., and Paszkowski, J. (2007). Role of histone and DNA methylation in gene regulation. Curr. Opin. Plant Biol. 10, 528–533. doi: 10.1016/j.pbi.2007.06.008</small></p>
<p><small> Zhang, et al. (2006). Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201. doi: 10.1016/j.cell.2006.08.003</small></p>
<p><small> Zhang et al. 2018 Understanding the evolutionary potential of epigenetic variation: a comparison of heritable phenotypic variation in epiRILs, RILs, and natural ecotypes of Arabidopsis thaliana. Heredity 121, 257–265 (2018) doi:10.1038/s41437-018-0095-9</small></p>
<p><small> Zheng X et al (2017) Histone acetylation is involved in GA-mediated 45S rDNA decondensation in maize aleurone layers. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2207-z</small></p>
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<li><span><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex 24 Single Indexes for Illumina - Set #B">D-Plex 24 Single Indexes for Illumina - Set #B (25-48)</a></span></li>
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<p><span>With each set of indexes, you can multiplex up to 24.</span></p>
<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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<p><span>Diagenode’s D-Plex Single Indexes for Illumina have to be used with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. D-Plex </span><span>has been extensively validated for small RNA-seq library prep from total or small RNA with those two sets of single indexes Illumina compatible: </span></p>
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<p><span>With<span> </span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>, get your library ready from <strong>low input</strong> in <strong>one-tube one-day </strong>protocol (click the link to read more).</span></p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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<p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
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'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'description' => '<p style="text-align: left;"><span>D-Plex Single Indexes Module - Set A includes PCR primers with <span>24</span><span><span> barcodes (i7 index)</span> for library multiplexing</span> with the <a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank" title="D-Plex Small RNA-seq Kit">D-Plex Small RNA-seq Kit</a>. </span></p>
<p style="text-align: left;"><span>These single indexes (SI) were designed and validated to fit the D-Plex technology for Illumina sequencing. Addition of a unique molecular identifier (UMI) sequence enables the accurate bioinformatic identification and removal of PCR duplicates from amplified libraries.</span></p>
<p><span>Two sets are available separately: </span></p>
<ul>
<li><span>C05030010 - </span>D-Plex Single Indexes for Illumina - Set A</li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-single-indexes-set-b" title="D-Plex 24 Single Indexes for Illumina - Set #B">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
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<p><span>Each set can be used for library multiplexing up to 24. <span>Set A and Set B can be used simultaneously for library multiplexing up to 48.</span></span></p>
<p><span>Read more about the </span><a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a><span>.</span><span> </span></p>',
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<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
<p>Benefits of the MicroChIP DiaPure columns:</p>
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<p>Successful ChIP-seq results generated on 50,000 of K562 cells using True MicroChIP technology. ChIP has been performed accordingly to True MicroChIP protocol (Diagenode, Cat. No. C01010130), including DNA purification using the MicroChIP DiaPure columns. For the library preparation the MicroPlex Library Preparation Kit (Diagenode, Cat. No. C05010001) has been used. The below figure shows the peaks from ChIP-seq experiments using the following Diagenode antibodies: H3K4me1 (C15410194), H3K9/14ac (C15410200), H3K27ac (C15410196) and H3K36me3 (C15410192).</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'description' => '<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2 style="font-size: 22px;">DNA断片化、ライブラリー調製、自動化：NGSのワンストップショップ</h2>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-12 medium-12 large-12 columns">
<h4>1. 断片化装置を選択してください：150 bp〜75 kbの範囲でDNAを断片化します。</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-pico-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/bioruptor_pico.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/megaruptor2-1-unit"><img src="https://www.diagenode.com/img/product/shearing_technologies/B06010001_megaruptor2.jpg" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/bioruptor-one-sonication-device"><img src="https://www.diagenode.com/img/product/shearing_technologies/br-one-profil.png" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns">5μlまで断片化：150 bp〜2 kb<br />NGS DNAライブラリー調製およびFFPE核酸抽出に最適で、</td>
<td class="small-4 medium-4 large-4 columns">2 kb〜75 kbの範囲をできます。<br />メイトペアライブラリー調製および長いフラグメントDNAシーケンシングに最適で、この軽量デスクトップデバイスで</td>
<td class="small-4 medium-4 large-4 columns">20または50μlの断片化が可能です。</td>
</tr>
</tbody>
</table>
<table class="small-12 medium-12 large-12 columns">
<tbody>
<tr>
<th class="small-8 medium-8 large-8 columns">
<h4>2. 最適化されたライブラリー調整キットを選択してください。</h4>
</th>
<th class="small-4 medium-4 large-4 columns">
<h4>3. ライブラリー前処理自動化を選択して、比類のないデータ再現性を実感</h4>
</th>
</tr>
<tr style="background-color: #ffffff;">
<td class="small-12 medium-12 large-12 columns"></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns"><a href="../p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><img src="https://www.diagenode.com/img/product/kits/microPlex_library_preparation.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/ideal-library-preparation-kit-x24-incl-index-primer-set-1-24-rxns"><img src="https://www.diagenode.com/img/product/kits/box_kit.jpg" style="display: block; margin-left: auto; margin-right: auto;" height="173" width="250" /></a></td>
<td class="small-4 medium-4 large-4 columns"><a href="../p/sx-8g-ip-star-compact-automated-system-1-unit"><img src="https://www.diagenode.com/img/product/automation/B03000002%20_ipstar_compact.png" style="display: block; margin-left: auto; margin-right: auto;" /></a></td>
</tr>
<tr>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">50pgの低入力：MicroPlex Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">5ng以上：iDeal Library Preparation Kit</td>
<td class="small-4 medium-4 large-4 columns" style="text-align: center;">Achieve great NGS data easily</td>
</tr>
</tbody>
</table>
</div>
</div>
<blockquote>
<div class="row">
<div class="small-12 medium-12 large-12 columns"><span class="label" style="margin-bottom: 16px; margin-left: -22px; font-size: 15px;">DiagenodeがNGS研究にぴったりなプロバイダーである理由</span>
<p>Diagenodeは15年以上もエピジェネティクス研究に専念、専門としています。 ChIP研究クロマチン用のユニークな断片化システムの開発から始まり、 専門知識を活かし、5μlのせん断体積まで可能で、NGS DNAライブラリーの調製に最適な最先端DNA断片化装置の開発にたどり着きました。 我々は以来、ChIP-seq、Methyl-seq、NGSライブラリー調製用キットを研究開発し、業界をリードする免疫沈降研究と同様に、ライブラリー調製を自動化および完結させる独自の自動化システムを開発にも成功しました。</p>
<ul>
<li>信頼されるせん断装置</li>
<li>様々なインプットからのライブラリ作成キット</li>
<li>独自の自動化デバイス</li>
</ul>
</div>
</div>
</blockquote>
<div class="row">
<div class="small-12 columns">
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#panel1a">次世代シーケンシングへの理解とその専門知識</a>
<div id="panel1a" class="content">
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><strong>次世代シーケンシング (NGS)</strong> ）は、著しいスケールとハイスループットでシーケンシングを行い、1日に数十億もの塩基生成を可能にします。 NGSのハイスループットは迅速でありながら正確で、再現性のあるデータセットを実現し、さらにシーケンシング費用を削減します。 NGSは、ゲノムシーケンシング、ゲノム再シーケンシング、デノボシーケンシング、トランスクリプトームシーケンシング、その他にDNA-タンパク質相互作用の検出やエピゲノムなどを示します。 指数関数的に増加するシーケンシングデータの需要は、計算分析の障害や解釈、データストレージなどの課題を解決します。</p>
<p>アプリケーションおよび出発物質に応じて、数百万から数十億の鋳型DNA分子を大規模に並行してシーケンシングすることが可能です。その為に、異なる化学物質を使用するいくつかの市販のNGSプラットフォームを利用することができます。 NGSプラットフォームの種類によっては、事前準備とライブラリー作成が必要です。</p>
<p>NGSにとっても、特にデータ処理と分析に関した大きな課題はあります。第3世代技術はゲノミクス研究にさらに革命を起こすであろうと大きく期待されています。</p>
</div>
</div>
<div class="row">
<div class="small-6 medium-6 large-6 columns">
<p><strong>NGS アプリケーション</strong></p>
<ul>
<li>全ゲノム配列決定</li>
<li>デノボシーケンシング</li>
<li>標的配列</li>
<li>Exomeシーケンシング</li>
<li>トランスクリプトーム配列決定</li>
<li>ゲノム配列決定</li>
<li>ミトコンドリア配列決定</li>
<li>DNA-タンパク質相互作用（ChIP-seq</li>
<li>バリアント検出</li>
<li>ゲノム仕上げ</li>
</ul>
</div>
<div class="small-6 medium-6 large-6 columns">
<p><strong>研究分野におけるNGS:</strong></p>
<ul>
<li>腫瘍学</li>
<li>リプロダクティブ・ヘルス</li>
<li>法医学ゲノミクス</li>
<li>アグリゲノミックス</li>
<li>複雑な病気</li>
<li>微生物ゲノミクス</li>
<li>食品・環境ゲノミクス</li>
<li>創薬ゲノミクス - パーソナライズド・メディカル</li>
</ul>
</div>
<div class="small-12 medium-12 large-12 columns">
<p><strong>NGSの用語</strong></p>
<dl>
<dt>リード（読み取り）</dt>
<dd>この装置から得られた連続した単一のストレッチ</dd>
<dt>断片リード</dt>
<dd>フラグメントライブラリからの読み込み。 シーケンシングプラットフォームに応じて、読み取りは通常約100〜300bp。</dd>
<dt>断片ペアエンドリード</dt>
<dd>断片ライブラリーからDNA断片の各末端2つの読み取り。</dd>
<dt>メイトペアリード</dt>
<dd>大きなDNA断片（通常は予め定義されたサイズ範囲）の各末端から2つの読み取り。</dd>
<dt>カバレッジ（例）</dt>
<dd>30×適用範囲とは、参照ゲノム中の各塩基対が平均30回の読み取りを示す。</dd>
</dl>
</div>
</div>
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<h2>NGSプラットフォーム</h2>
<h3><a href="http://www.illumina.com" target="_blank">イルミナ</a></h3>
<p>イルミナは、クローン的に増幅された鋳型DNA（クラスター）上に位置する、蛍光標識された可逆的鎖ターミネーターヌクレオチドを用いた配列別合成技術を使用。 DNAクラスターは、ガラスフローセルの表面上に固定化され、 ワークフローは、4つのヌクレオチド（それぞれ異なる蛍光色素で標識された）の組み込み、4色イメージング、色素や末端基の切断、取り込み、イメージングなどを繰り返します。フローセルは大規模な並列配列決定を受ける。 この方法により、単一蛍光標識されたヌクレオチドの制御添加によるモノヌクレオチドのエラーを回避する可能性があります。 読み取りの長さは、通常約100〜150 bpです。</p>
<h3><a href="http://www.lifetechnologies.com" target="_blank">イオン トレント</a></h3>
<p>イオントレントは、半導体技術チップを用いて、合成中にヌクレオチドを取り込む際に放出されたプロトンを検出します。 これは、イオン球粒子と呼ばれるビーズの表面にエマルションPCR（emPCR）を使用し、リンクされた特定のアダプターを用いてDNA断片を増幅します。 各ビーズは1種類のDNA断片で覆われていて、異なるDNA断片を有するビーズは次いで、チップの陽子感知ウェル内に配置されます。 チップには一度に4つのヌクレオチドのうちの1つが浸水し、このプロセスは異なるヌクレオチドで15秒ごとに繰り返されます。 配列決定の間に4つの塩基の各々が1つずつ導入されます、組み込みの場合はプロトンが放出され、電圧信号が取り込みに比例して検出されます。.</p>
<h3><a href="http://www.pacificbiosciences.com" target="_blank">パシフィック バイオサイエンス</a></h3>
<p>パシフィックバイオサイエンスでは、20kbを超える塩基対の読み取りも、単一分子リアルタイム（SMRT）シーケンシングによる構造および細胞タイプの変化を観察することができます。 このプラットフォームでは、超長鎖二本鎖DNA（dsDNA）断片が、Megaruptor（登録商標）のようなDiagenode装置を用いたランダムシアリングまたは目的の標的領域の増幅によって生成されます。 SMRTbellライブラリーは、ユニバーサルヘアピンアダプターをDNA断片の各末端に連結することによって生成します。 サイズ選択条件による洗浄ステップの後、配列決定プライマーをSMRTbellテンプレートにアニーリングし、鋳型DNAに結合したDNAポリメラーゼを含む配列決定を、蛍光標識ヌクレオチドの存在下で開始。 各塩基が取り込まれると、異なる蛍光のパルスをリアルタイムで検出します。</p>
<h3><a href="https://nanoporetech.com" target="_blank">オックスフォード ナノポア</a></h3>
<p>Oxford Nanoporeは、単一のDNA分子配列決定に基づく技術を開発します。その技術により生物学的分子、すなわちDNAが一群の電気抵抗性高分子膜として位置するナノスケールの孔（ナノ細孔）またはその近くを通過し、イオン電流が変化します。 この変化に関する情報は、例えば4つのヌクレオチド（AまたはG r CまたはT）ならびに修飾されたヌクレオチドすべてを区別することによって分子情報に訳されます。 シーケンシングミニオンデバイスのフローセルは、数百個のナノポアチャネルのセンサアレイを含みます。 DNAサンプルは、Diagenode社のMegaruptor（登録商標）を用いてランダムシアリングによって生成され得る超長鎖DNAフラグメントが必要です。</p>
<h3><a href="http://www.lifetechnologies.com/be/en/home/life-science/sequencing/next-generation-sequencing/solid-next-generation-sequencing.html" target="_blank">SOLiD</a></h3>
<p>SOLiDは、ユニークな化学作用により、何千という個々のDNA分子の同時配列決定を可能にします。 それは、アダプター対ライブラリーのフラグメントが適切で、せん断されたゲノムDNAへのアダプターのライゲーションによるライブラリー作製から始まります。 次のステップでは、エマルジョンPCR（emPCR）を実施して、ビーズの表面上の個々の鋳型DNA分子をクローン的に増幅。 emPCRでは、個々の鋳型DNAをPCR試薬と混合し、水中油型エマルジョン内の疎水性シェルで囲まれた水性液滴内のプライマーコートビーズを、配列決定のためにロードするスライドガラスの表面にランダムに付着。 この技術は、シークエンシングプライマーへのライゲーションで競合する4つの蛍光標識されたジ塩基プローブのセットを使用します。</p>
<h3><a href="http://454.com/products/technology.asp" target="_blank">454</a></h3>
<p>454は、大規模並列パイロシーケンシングを利用しています。 始めに全ゲノムDNAまたは標的遺伝子断片の300〜800bp断片のライブラリー調製します。 次に、DNAフラグメントへのアダプターの付着および単一のDNA鎖の分離。 その後アダプターに連結されたDNAフラグメントをエマルジョンベースのクローン増幅（emPCR）で処理し、DNAライブラリーフラグメントをミクロンサイズのビーズ上に配置します。 各DNA結合ビーズを光ファイバーチップ上のウェルに入れ、器具に挿入します。 4つのDNAヌクレオチドは、配列決定操作中に固定された順序で連続して加えられ、並行して配列決定されます。</p>
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<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3´ end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode’s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching”</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg. </span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>® - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing. <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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'description' => '<div class="row"><div class="small-12 medium-4 large-4 columns"><div class="panel"><h3><em>lncRNAs in cancer</em></h3><p class="text-left">Gastrointestinal cancer: Gastrointestinal cancers occur as a result of dysregulated signaling pathways and cellular processes, such as the cell cycle or apoptosis. LncRNAs can regulate proliferation of gastrointestinal cancer through interacting with RNA targets, localization to chromatin, or binding to proteins. Read more about Long non-coding RNAs: crucial regulators of gastrointestinal cancer cell proliferation</p><h3><em>microRNAs in cancer</em></h3><p class="text-left">miR-155 has been found overexpressed in many cancer types including hematopoietic cancers, breast, lung and colon cancer<br /><br /> <a href="https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf">https://www.cell.com/trends/molecular-medicine/pdf/S1471-4914(14)00101-4.pdf</a></p></div></div><div class="small-12 medium-8 large-8 columns"><center><img src="https://www.diagenode.com/img/cancer/long-non-coding-rna.jpg" width="550" height="345" /></center><p></p><p>Various non-coding RNAs (ncRNAs) have been found to function as key regulators for transcription, chromatin remodelling, and post-transcriptional modification, thus making them relevant in oncogenesis, both as tumor suppressors and as drivers. For example, a number of microRNAs (miRNAs), one of the more well-studied types of ncRNAs, have been identified as potential cancer biomarkers and clinical targets. Other ncRNAs, such as long noncoding RNAs are involved in cancer regulation and proliferation. Understanding the role of ncRNAs will be critical for cancer research and therapeutic development.</p></div></div>',
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<p><img src="https://www.diagenode.com/img/areas/toxicology.jpg" /></p>
</div>
<h2>Epigenetics in environmental toxicology</h2>
<p>The fact that environmental factors induce DNA mutations that may lead to disease is well-established and will have tremendous benefits when incorporated into various environmental safety and health assessments. Environmental factors such as dietary intake, drugs, stress, or exposure to toxins, can cause epigenetic changes by possibly altering how transcription factors bind to DNA or changing the structure of the histones that DNA wraps around. These structural changes can affect gene activity or gene expression. A number of environmental factors have been investigated for their effect on epigenetic changes including phthalates, toxic metals, smoking, air pollution, jet fuel, environmental stress, and a high fat diet. Effects on epigenetic mechanisms, DNA methylation patterns, histone modifications, miRNA expression have been documented as a result. The table below (Marczylo et al, 2016 and Society of Toxicology, 2018) summarizes a few of the studies that have been done for putative environmentally-induced epigenetic toxicity in humans or rat/mouse.</p>
<p class="extra-spaced">In the future, incorporating epigenetic evaluation into toxicity tests can increase the safety of both food and environmental substances.</p>
<table class="extra-spaced">
<tbody>
<tr>
<th style="text-align: center;">Toxin/exposure</th>
<th style="text-align: center;">Species/stage of exposure/effect</th>
<th style="text-align: center;">Phenotype</th>
<th style="text-align: center;">Epigenetic change</th>
<th style="text-align: center;">Reference(s)</th>
</tr>
<tr>
<td>Air pollution</td>
<td style="text-align: center;">Human/childhood/childhood</td>
<td style="text-align: center;">Asthma</td>
<td style="text-align: center;">Epigenetic mechanisms</td>
<td style="text-align: left;">Somineni et al. (2016)</td>
</tr>
<tr style="text-align: center;">
<td style="text-align: left;">BPA</td>
<td>Human/in utero/childhood</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">DNA methylation</td>
<td style="text-align: left;">Kundakovic (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Formaldehyde</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Alzheimer’s</td>
<td style="text-align: center;">Epigenetic mechanisms and DNA methylation</td>
<td>Tong et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Methylmercury</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Behavior</td>
<td style="text-align: center;">Histone modifications and DNA methylation</td>
<td>Onishchenko (2008)</td>
</tr>
<tr style="text-align: center;">
<td>Arsenic</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">Skin disorder</td>
<td style="text-align: center;">DNA methylation</td>
<td>Paul et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Nickel</td>
<td style="text-align: center;">Human/lifetime/adult</td>
<td style="text-align: center;">NSCLC survival</td>
<td style="text-align: center;">miRNA</td>
<td>Chiou et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>Polycyclic aromatic hydrocarbons</td>
<td style="text-align: center;">Human/adult/adult</td>
<td style="text-align: center;">Chromosome aberrations - PBL</td>
<td style="text-align: center;">DNA methylation</td>
<td>Yang et al. (2012)</td>
</tr>
<tr style="text-align: center;">
<td>Various phthalates</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Decreased testosterone/gonadal</td>
<td style="text-align: center;">DNA methylation and histone modifications</td>
<td>Kilcoyne et al. (2014) Martinez-Arguelles et al. (2009), Papoutsis et al. (2015), Takeda et al. (2012), Yoshioka et al. (2011)</td>
</tr>
<tr style="text-align: center;">
<td>Smoking</td>
<td style="text-align: center;">Human/Lifetime/adult</td>
<td style="text-align: center;">COPD and tumor</td>
<td style="text-align: center;">Epigenetic mechanisms, DNA methylation, miRNA</td>
<td>Lin (2010), Ostrow (2013) Shenker (2013), Xie et al. (2014)</td>
</tr>
<tr style="text-align: center;">
<td>Alcohol</td>
<td style="text-align: center;">Rodent/lifetime and in utero</td>
<td style="text-align: center;">Nuerological, cardiac, behavior, stem cell</td>
<td style="text-align: center;">Histone modification and miRNA</td>
<td>Ignacio et al. (2014), Middleton et al. (2012), Leu et al. (2014), Pascual et al. (2011), Peng et al. (2015)</td>
</tr>
<tr style="text-align: center;">
<td>High fat diet</td>
<td style="text-align: center;">Rodent/in utero/adult</td>
<td style="text-align: center;">Diet preference</td>
<td style="text-align: center;">DNA methylation and miRNAs</td>
<td>Baselga-Escudero (2015), Carlin et al. (2013), Vucetic et al. (2010)</td>
</tr>
<tr>
<td style="text-align: left;">Under-nourishment</td>
<td style="text-align: center;">Rodent/adult/adult</td>
<td style="text-align: center;">Hepatic</td>
<td style="text-align: center;">miRNAs</td>
<td>Tryndyak et al. (2016)</td>
</tr>
</tbody>
</table>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<h3>Diagenode products for your epigenomics research in Toxicology</h3>
<div class="row">
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #099f92; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/chromatin-function">Chromatin analysis</a></h3>
<center><a href="https://www.diagenode.com/en/categories/chromatin-function"><img src="https://www.diagenode.com/img/cancer/chromatin-icon.png" /></a></center>
<p class="text-left">Understand the effects on chromatin and histone modifcations</p>
</div>
<ul>
<li>New to ChIP? <a href="https://www.diagenode.com/en/pages/portal/chip">Learn more</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-shearing">Chromatin shearing optimization</a></li>
<li><a href="https://www.diagenode.com/en/categories/chromatin-immunoprecipitation">Chromatin Immunoprecipitation</a></li>
<li>Validated <a href="https://www.diagenode.com/en/categories/antibodies">Antibodies</a></li>
<li><a href="https://www.diagenode.com/en/categories/library-preparation">Library preparation</a></li>
</ul>
</div>
<div class="small-12 medium-4 large-4 columns text-left">
<div class="panel" style="border-color: #30415c; height: 275px;">
<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
<center><a href="https://www.diagenode.com/en/categories/dna-methylation"><img src="https://www.diagenode.com/img/cancer/dna-icon.png" /></a></center>
<p class="text-left">Analyze DNA methylation and the effects of environmental toxins</p>
</div>
<ul>
<li><a href="https://www.diagenode.com/en/categories/bisulfite-conversion">Bisulfite sequencing</a></li>
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<p class="text-left">Discover noncoding RNAs and miRNAs in the regulation of gene expression</p>
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<h2>Epigenetics and Cancer</h2>
<p>Epigenetic processes control the normal development and maintenance of gene expression in a number of organisms. However, disruption of epigenetic mechanisms may alter gene function, potentially leading to cellular transformations that lead to tumorigenesis. Cancer is a multistep process from a succession of processes that alter the growth of normal cells. In cancer, epigenetic reprogramming occurs at multiple levels including nuclear organization and nucleosome positioning, DNA methylation, modification of histones, alteration of epigenetic regulators such as transcription factor binding, and non-coding RNA, such as microRNA.</p>
<p>Epigenetic modifications are reversible and potential treatments could be geared to alter irregular transcription factor binding, DNA methylation or histone acetylation. Accurate study with a versatile number of tools is essential for the study of epigenetics including sound sample preparation and analysis methodologies for DNA methylation such as with immunoprecipitation or bisulfite sequencing, chromatin analysis with chromatin immunoprecipitation (ChIP) combined with qPCR or sequencing, and RNA modification study. As researchers elucidate the mechanisms and specific modifications associated with cancer, it may be possible to target abnormal modifications in cells with minimal damage to normal cells, making the prospect of epigenetic therapy increasingly promising.</p>
<h3>Diagenode products for your epigenomics research in Cancer</h3>
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<p class="text-left">Understand the role of chromatin in cancer regulation</p>
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<p class="text-left">Analyze DNA methylation and the effects on oncogenesis and tumor suppression</p>
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<li><a href="https://www.diagenode.com/en/categories/dna-methylation-profiling-services">DNA methylation services</a></li>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in cancer</p>
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<h2>Epigenetics in Neuroscience</h2>
<p>Neuroscience and epigenetics are at an exciting crossroads. Current research has shown that epigenetic mechanisms play a critical role in both behavior and the development and function of the nervous system. Histone modifications, changes in DNA methylation, and non-coding RNAs regulate various stages of neurogenesis and brain development while aberrant epigenetic regulation has been implicated in a number of neurological and brain disorders (Yao et, al. Nature Reviews Neuroscience, 2016).</p>
<p>Neuroscientists seek to uncover how epigenetic marks and transcriptional changes regulate gene expression to influence changes in areas such as behavior and the development of neural pathways and brain structures. Understanding how epigenetics affects nervous system function requires an integrative approach incorporating multiple levels of analysis. For example, research has uncovered the role of transcription factors, non-coding RNAs, and other molecules that mediate learning and memory. In addition, chromatin modifications and non-coding RNAs have been shown to influence epigenetic mechanisms in neurogenesis.</p>
<p>Understanding the molecular components and environmental conditions that affect epigenetic change will eventually provide the basis to develop therapies to treat neurological and psychiatric conditions. As neuroscientists learn how changes in chromatin architecture affect transcriptional regulation and gene expression, the link between the epigenome and the various areas in neuroscience will become clearer.</p>
<h3><span class="diacol">Neuroscience and epigenetics intersect in a number of areas: </span></h3>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#memory"> <i class="fa fa-square-o"></i> Epigenetics in memory, memory disorders, and learning</a>
<div id="memory" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms underlying learning and the inheritance of learned behaviors</strong></p>
<p>In this review, researchers outline epigenetic mechanisms by which gene expression is regulated in animals and humans. Using fear learning as a framework, they show how such mechanisms underlie learning and stress responsiveness. Finally, they discuss how epigenetic mechanisms might inform us about the transgenerational inheritance of behavioral traits that are being increasingly reported. Trends in Neuroscience, 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
<blockquote><br />
<p><strong>Epigenetic regulation of memory formation and maintenance</strong></p>
<p>In the last decade, epigenetic markers like DNA methylation and post-translational modifications of histone tails have emerged as important regulators of the memory process. Their ability to regulate gene transcription dynamically in response to neuronal activation supports the consolidation of long-term memory.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2779706/" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#schizophrenia"> <i class="fa fa-square-o"></i> Schizophrenia</a>
<div id="schizophrenia" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in schizophrenia</strong></p>
<p>In this review, the authors present an overview of schizophrenia and discuss the role of nature versus nurture in its pathology, where ‘nature’ is considered to be inherited or genetic vulnerability to schizophrenia, and ‘nurture’ is proposed to exert its effects through epigenetic mechanisms. Second, they define DNA methylation and discuss the evidence for its role in schizophrenia. Third, they define posttranslational histone modifications and discuss their place in schizophrenia. This research is likely to lead to the development of epigenetic therapy, which holds the promise of alleviating cognitive deficits associated with schizophrenia. Biochimica and Biophysica Acta, 2009.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25544352" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#addiction"> <i class="fa fa-square-o"></i> Addiction disorder</a>
<div id="addiction" class="content">
<blockquote><br />
<p><strong>Epigenetics of addiction: Epigenetic study untangles addiction and relapse in the brain</strong></p>
<p>New research uncovers an epigenetic reason why drug users who attempt to quit are prone to relapse despite negative consequences to their health and livelihood. The findings help to explain how casual drug use can produce long-lasting brain changes that increase vulnerability to relapse in individuals suffering from substance use disorders. Science Daily, September 2017.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.sciencedaily.com/releases/2017/09/170927123612.htm" target="_blank">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#neurogenesis"> <i class="fa fa-square-o"></i> Neurogenesis</a>
<div id="neurogenesis" class="content">
<blockquote><br />
<p><strong>Epigenetic mechanisms in neurogenesis</strong></p>
<p>Epigenetic mechanisms — including DNA and histone modifications, as well as regulation by non-coding RNAs — have pivotal roles in different stages of neurogenesis. The authors also briefly cover the emerging field of epitranscriptomics, which involves modifications of mRNAs and long non-coding RNAs.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-017-0365-z">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#depression"> <i class="fa fa-square-o"></i> Depression</a>
<div id="depression" class="content">
<blockquote><br />
<p><strong>Epigenetics of depression</strong></p>
<p>Major depressive disorder (MDD) is a leading cause of disability worldwide and is associated with poor psychological, medical, and socioeconomic outcomes. This review presents the evidence supporting a role for epigenetic effects in MDD and in treatment response. Prog Mol Biol Transl Sci. 2014.</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/25410543">Read more</a></p>
</blockquote>
</div>
</li>
<li class="accordion-navigation"><a href="#other"> <i class="fa fa-square-o"></i> Other disorders such as Rett’s, Autism, Parkinson’s, Huntington’s </a>
<div id="other" class="content">
<blockquote>
<p><strong>Parkinson’s disease</strong></p>
<p>DNA methylation in Parkinson's disease</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/27120258">Read more</a></p>
</blockquote>
<blockquote>
<p><strong>Rett’s Syndrome</strong></p>
<p>Epigenetic regulation of memory by acetylation and methylation of chromatin: implications in neurological disorders, aging, and addiction</p>
<p><i class="fa fa-arrow-circle-right"></i> <a href="https://www.ncbi.nlm.nih.gov/pubmed/24777294">Read more</a></p>
</blockquote>
</div>
</li>
</ul>
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<h3>Diagenode products for your epigenomics research in Neuroscience</h3>
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<p class="text-left">Understand the role of chromatin in neuroscience</p>
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<h3 class="text-center"><a href="https://www.diagenode.com/en/categories/dna-methylation" style="color: #30415c;">DNA methylation</a></h3>
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<p class="text-left">Analyze DNA methylation and the effects on neurogenesis, brain development, and more</p>
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<h3 class="text-center"><span class="darkgrey">Non-coding RNAs</span></h3>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression</p>
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<div class="extra-spaced">
<h2>Epigenetic Regulation in Plants</h2>
<p>Plants utilize a number of gene regulation mechanisms to ensure proper development, function, growth, and survival under different environmental conditions. Plants depend on changes in gene expression to respond to environmental stimuli, in which the full repertoire of histone modifications, DNA methylation, and small ncRNAs play an important role in epigenetic regulation.</p>
<p>Studying the epigenetics of model plants such as Arabidopsis thaliana have allowed researchers to understand pathways that maintain chromatin modifications as well as the mapping of modifications such as DNA methylation on a genome-wide scale. Small RNAs have also been implicated in playing a role in the distribution of chromatin modifications, and RNA may also play a role in the complex epigenetic interactions that occur between homologous sequences (Moazed et al, 2009). In the future, by understanding epigenetic control, researchers can uncover the research necessary to improve plant growth, yields, and transformation efficiency especially in the face of climate change and other environmental factors.</p>
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<h3 style="font-weight: 100; margin-top: 0;">Chromatin</h3>
<p>Chromatin consists of nucleosomes formed by a complex of histone proteins and DNA, which allows the packaging of DNA into the nucleus. The less condensed euchromatin represents transcriptionally active regions, while heterochromatin is usually inactive (Vaillant and Paszkowski, 2007). Chromatin state is known to be influenced by both DNA methylation and histone modifications which in turn impact gene expression and the structure of chromosomes. In a recent study, the role of chromatin modifications during plant reproduction elucidated 3-dimensional chromosome reorganization mediated by histones and DNA methylation (Dukowic-Schulze et al. 2017). In addition, gibberellins have been shown in increasing the level of histone acetylation, which affects regions of chromatin involved in maize seed germination (Zheng et al. 2017). Another study reports a novel function of a tomato histone deacetylase gene in the regulation of fruit ripening (Guo et al. 2017).</p>
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<p>In addition, multigene families encode transcription factors, with members found throughout the genome or clustered on the same chromosome. Numerous DNA binding proteins that interact with plant promoters have been identified -- some are similar to well-characterized transcription factors in animals or yeast, while others are unique to plants. For example, diverse members of the subfamily X of the plant-specific ethylene response factor (ERF) transcription factors coordinate stress signaling with wound repair activation. Tissue repair is also enhanced through a protein complex of ERF and GRAS TFs (Heyman et. al,.2018). A compilation of known plant transcription factors can be found in the plant transcription factor database at http://plntfdb.bio.uni-potsdam.de/v3.0/.</p>
</div>
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<h3 style="font-weight: 100; margin-top: 0;">RNA</h3>
<p>Recent research shows that a number of classes of small RNAs are key epigenetic regulators. In many cases, small RNAs have been implicated in DNA methylation and chromatin modification (Meyer, 2015). In addition, the role of small RNAs has been implicated in plant stress tolerance (Kumar et al., 2017). López-Galiano et al also provided insight into a coordinated function of a miRNA gene and histone modifications in regulating the expression of a WRKY transcription factor in response to stress.</p>
<p>RNA interference (RNAi) is another epigenetic mechanism that leads to small RNA generation, which mediates gene silencing at the post-transcriptional level. RNAi technology has immense potential for plant disease resistance.</p>
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<h3 style="font-weight: 100; margin-top: 0;">DNA methylation</h3>
<p>Plants, unlike animals, have three sites that can be methylated G, CHG (H can be A, C, T), and CHH (Law and Jacobsen, 2010). DNA methylation has attracted particular interest. In Arabidopsis, one-third of methylated genes occur in transcribed regions, and 5% of genes are methylated in promoter regions, suggesting that many of these are epigenetically regulated. (Zhang et al., 2006).</p>
<p>There are thousands of differentially methylated regions (DMRs) that influence phenotype by influencing gene expression. The analysis of epigenetic recombinant inbred line (epiRIL) plants from Arabidopsis points to the evidence of the influence of DMRs. An epiRIL results from crossing two genetically identical plants with differing DNA methylation levels (with one parent as a homozygous mutant for an essential DNA methylation maintenance gene). The offspring of these plants have similar genomes that vary only in methylation levels. Many traits have been studied using epiRILs -- flowering time, plant height, and response to abiotic stress, some of which have now been mapped to DMRs (Zhang et al. 2018)</p>
<p>Regulation by DNA methylation has been shown to be important in many aspects of plant development and response such as vernalization, hybrid vigor, and self-incompatibility (Itabashi et al. 2017). For example, vernalization treatments have shown reduced DNA methylation and subsequent initiation of flowering (Burn et al., 1993). Stress can also influence DNA methylation in plants as a response to environmental stimuli. (Steward et al., 2002; Song et al., 2012). A high degree of DNA methylation has also suggested the role in the improvement of plant fitness under different environmental conditions (Saéz-Laguna et al., 2014). In addition, methylation can affect normal fruit and hypomethylation predicts homeotic transformation and loss of fruit yield (Ong-Abdullah et al., 2015)</p>
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<p>DNA demethylation has also been implied in various aspects of plant development including pollen tube formation, embryogenesis, fruit ripening, stomatal development, and nodule formation ( Li et al. 2017). Demethylation of rice genomic DNA caused an altered pattern of gene expression, inducing dwarf plants (Sano et al., 1990).</p>
<p>Epigenetic modifications contribute to the stability and survival of the plants and their ability to adapt in different environmental conditions.</p>
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<h3>Diagenode products for your epigenomics research in plants</h3>
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<p class="text-left">DNA methylation and demethylation and the effects on plant response and function</p>
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<p class="text-left">Discover noncoding RNAs in the regulation of gene expression in plants</p>
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<h3>References</h3>
<p><small> Burn, J. et al (1993). DNA methylation, vernalization, and the initiation of flowering. Proc. Natl. Acad. Sci. U.S.A. 90, 287–291. doi: 10.1006/scdb.1996.0055 </small></p>
<p><small> Dukowic-Schulze S, Liu C, Chen C (2017) Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2222-0</small></p>
<p><small> Guo J et al (2017) A histone deacetylase gene, SlHDA3, acts as a negative regulator of fruit ripening and carotenoid accumulation. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2211-3</small></p>
<p><small> Heyman J, et.al (2018) Journal of Cell Science Emerging role of the plant ERF transcription factors in coordinating wound defense responses and repair doi: 10.1242/jcs.208215</small></p>
<p><small> Itabashi E, Osabe K, Fujimoto R, Kakizaki T (2017) Epigenetic regulation of agronomical traits in Brassicaceae. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2223-z</small></p>
<p><small> Kumar V et al (2017) Plant small RNAs: the essential epigenetic regulators of gene expression for salt-stress responses and tolerance. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2210-4</small></p>
<p><small> Law, J. A., and Jacobsen, S. E. (2010). Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11, 204–220. doi: 10.1038/nrg2719</small></p>
<p><small> Meyer, P. (2015). Epigenetic variation and environmental change. J. Exp. Bot. 66, 3541–3548. doi: 10.1093/jxb/eru502</small></p>
<p><small> Moazed, D. (2009) Small RNAs in transcriptional gene silencing and genome defence. Nature. doi: 10.1038/nature07756</small></p>
<p><small> Ong-Abdullah et al. (2015). Loss of Karma transposon methylation underlies the mantled somaclonal variant of oil palm. Nature 525, 533–537. doi: 10.1038/nature15365</small></p>
<p><small> Saéz-Laguna et al. (2014). Epigenetic variability in the genetically uniform forest tree species. PLoS One 9:e103145. doi: 10.1371/journal.pone.0103145</small></p>
<p><small> Sano, H. et al. (1990). A single treatment of rice seedlings with 5-azacytidine induces heritable dwarfism and undermethylation of genomic DNA. Mol. Gen. Genet. 220, 441–447. doi: 10.1007/BF00391751</small></p>
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<p><small> Steward, N et al. (2002). Periodic DNA methylation in maize nucleosomes and demethylation by environmental stress. J. Biol. Chem. 277, 37741–37746. doi: 10.1074/jbc.M204050200</small></p>
<p><small> Vaillant, I., and Paszkowski, J. (2007). Role of histone and DNA methylation in gene regulation. Curr. Opin. Plant Biol. 10, 528–533. doi: 10.1016/j.pbi.2007.06.008</small></p>
<p><small> Zhang, et al. (2006). Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201. doi: 10.1016/j.cell.2006.08.003</small></p>
<p><small> Zhang et al. 2018 Understanding the evolutionary potential of epigenetic variation: a comparison of heritable phenotypic variation in epiRILs, RILs, and natural ecotypes of Arabidopsis thaliana. Heredity 121, 257–265 (2018) doi:10.1038/s41437-018-0095-9</small></p>
<p><small> Zheng X et al (2017) Histone acetylation is involved in GA-mediated 45S rDNA decondensation in maize aleurone layers. Plant Cell Rep. https://dx.doi.org/10.1007/s00299-017-2207-z</small></p>
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