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'description' => '<p>The DNA Methylation control package includes unmethylated and in vitro methylated DNA together with specific primer sets for assessing the efficiency of your non-plant MeDIP experiments (Methylated DNA Immunoprecipitation) carried out with Diagenode’s <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" target="_blank">MagMeDIP qPCR</a> and <a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a>. These controls are made from <em>A. thaliana</em> BAC.</p>
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<p> </p>
<div class="small-12 medium-4 large-4 columns"><center></center><center></center><center></center><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" alt="Click here to read more about MeDIP " caption="false" width="80%" /></a></center></div>
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<h3 style="text-align: justify;">Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline" style="text-align: justify;">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
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<p>Perform <strong>MeDIP</strong> (<strong>Me</strong>thylated <strong>D</strong>NA <strong>I</strong>mmuno<strong>p</strong>recipitation) followed by qPCR or NGS to estimate DNA methylation status of your sample using a highly sensitive 5-methylcytosine antibody. Our MagMeDIP kit contains high quality reagents to get the highest enrichment of methylated DNA with an optimized user-friendly protocol.</p>
</div>
</div>
<h3><span>Features</span></h3>
<ul>
<li>Starting DNA amount: <strong>10 ng – 1 µg</strong></li>
<li>Content: <strong>all reagents included</strong> for DNA extraction, immunoprecipitation (including the 5-mC antibody, spike-in controls and their corresponding qPCR primer pairs) as well as DNA isolation after IP.</li>
<li>Application: <strong>qPCR</strong> and <strong>NGS</strong></li>
<li>Robust method, <strong>superior enrichment</strong>, and easy-to-use protocol</li>
<li><strong>High reproducibility</strong> between replicates and repetitive experiments</li>
<li>Compatible with <strong>all species </strong></li>
</ul>',
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'info1' => '<p>DNA methylation occurs primarily as 5-methylcytosine (5-mC), and the Diagenode MagMeDIP Kit takes advantage of a specific antibody targeting this 5-mC to immunoprecipitate methylated DNA, which can be thereafter directly analyzed by qPCR or Next-Generation Sequencing (NGS).</p>
<h3><span>How it works</span></h3>
<p>In brief, after the cell collection and lysis, the genomic DNA is extracted, sheared, and then denatured. In the next step the antibody directed against 5 methylcytosine and antibody binding beads are used for immunoselection and immunoprecipitation of methylated DNA fragments. Then, the IP’d methylated DNA is isolated and can be used for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
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<ul>
<li><strong>Complete kit</strong> including DNA extraction module, IP antibody and reagents, DNA isolation buffer</li>
<li><strong>Quality control of the IP:</strong> due to methylated and unmethylated DNA spike-in controls and their associated qPCR primers</li>
<li><strong>Easy to use</strong> with user-friendly magnetic beads and rack</li>
<li><strong>Highly validated protocol</strong></li>
<li>Automated protocol supplied</li>
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<center><img src="https://www.diagenode.com/img/product/kits/fig1-magmedipkit.png" width="85%" alt="Methylated DNA Immunoprecipitation" caption="false" /></center>
<p style="font-size: 0.9em;"><em><strong>Figure 1.</strong> Immunoprecipitation results obtained with Diagenode MagMeDIP Kit</em></p>
<p style="font-size: 0.9em;">MeDIP assays were performed manually using 1 µg or 50 ng gDNA from blood cells with the MagMeDIP kit (Diagenode). The IP was performed with the Methylated and Unmethylated spike-in controls included in the kit, together with the human DNA samples. The DNA was isolated/purified using DIB. Afterwards, qPCR was performed using the primer pairs included in this kit.</p>
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'info3' => '<p>For DNA methylation analysis on the whole genome, MagMeDIP kit can be coupled with Next-Generation Sequencing. To perform MeDIP-sequencing we recommend the following strategy:</p>
<ul style="list-style-type: circle;">
<li>Choose a library preparation solution which is compatible with the starting amount of DNA you are planning to use (from 10 ng to 1 μg). It can be a home-made solution or a commercial one.</li>
<li>Choose the indexing system that fits your needs considering the following features:</li>
<ul>
<ul>
<ul>
<li>Single-indexing, combinatorial dual-indexing or unique dual-indexing</li>
<li>Number of barcodes</li>
<li>Full-length adaptors containing the barcodes or barcoding at the final amplification step</li>
<li>Presence / absence of Unique Molecular Identifiers (for PCR duplicates removal)</li>
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<li>Standard library preparation protocols are compatible with double-stranded DNA only, therefore the first steps of the library preparation (end repair, A-tailing, adaptor ligation and clean-up) will have to be performed on sheared DNA, before the IP.</li>
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<p style="padding-left: 30px;"><strong>CAUTION:</strong> As the immunoprecipitation step occurs at the middle of the library preparation workflow, single-tube solutions for library preparation are usually not compatible with MeDIP-sequencing.</p>
<ul style="list-style-type: circle;">
<li>For DNA isolation after the IP, we recommend using the <a href="https://www.diagenode.com/en/p/ipure-kit-v2-x24" title="IPure kit v2">IPure kit v2</a> (available separately, Cat. No. C03010014) instead of DNA isolation Buffer.</li>
</ul>
<ul style="list-style-type: circle;">
<li>Perform library amplification after the DNA isolation following the standard protocol of the chosen library preparation solution.</li>
</ul>
<h3><span>MeDIP-seq workflow</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/MeDIP-seq-workflow.png" width="110%" alt="MagMeDIP qPCR Kit x10 workflow" caption="false" /></center>
<h3><span>Example of results</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/medip-specificity.png" alt="MagMeDIP qPCR Kit Result" caption="false" width="951" height="488" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 1. qPCR analysis of external spike-in DNA controls (methylated and unmethylated) after IP.</strong> Samples were prepared using 1μg – 100ng -10ng sheared human gDNA with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-saturation-analysis.png" alt=" MagMeDIP kit " caption="false" width="951" height="461" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 2. Saturation analysis.</strong> Clean reads were aligned to the human genome (hg19) using Burrows-Wheeler aligner (BWA) algorithm after which duplicated and unmapped reads were removed resulting in a mapping efficiency >98% for all samples. Quality and validity check of the mapped MeDIP-seq data was performed using MEDIPS R package. Saturation plots show that all sets of reads have sufficient complexity and depth to saturate the coverage profile of the reference genome and that this is reproducible between replicates and repetitive experiments (data shown for 50 ng gDNA input: left panel = replicate a, right panel = replicate b).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-libraries-prep.png" alt="MagMeDIP x10 " caption="false" width="951" height="708" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 3. Sequencing profiles of MeDIP-seq libraries prepared from different starting amounts of sheared gDNA on the positive and negative methylated control regions.</strong> MeDIP-seq libraries were prepared from decreasing starting amounts of gDNA (1 μg (green), 50 ng (red), and 10ng (blue)) originating from human blood with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode). IP and corresponding INPUT samples were sequenced on Illumina NovaSeq SP with 2x50 PE reads. The reads were mapped to the human genome (hg19) with bwa and the alignments were loaded into IGV (the tracks use an identical scale). The top IGV figure shows the TSH2B (also known as H2BC1) gene (marked by blue boxes in the bottom track) and its surroundings. The TSH2B gene is coding for a histone variant that does not occur in blood cells, and it is known to be silenced by methylation. Accordingly, we see a high coverage in the vicinity of this gene. The bottom IGV figure shows the GADPH locus (marked by blue boxes in the bottom track) and its surroundings. The GADPH gene is a highly active transcription region and should not be methylated, resulting in no reads accumulation following MeDIP-seq experiment.</p>
<p></p>
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<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
<p><em><strong>NOTE</strong>: These spike-in controls are the ones directly provided in <span>Diagenode’s </span><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a><span><span> </span>and<span> </span></span><a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a><span>.</span></em></p>',
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<div class="small-12 medium-3 large-3 columns"><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" /></a></center></div>
<div class="small-12 medium-9 large-9 columns">
<h3>Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
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<div class="row">
<div class="large-12 columns"><span>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</span><br />
<h2></h2>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-seq-package-V2-x10" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>
</div>
</div>
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<div class="gtx-trans-icon"></div>
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<div class="large-12 columns">
<div style="text-align: justify;" class="small-12 medium-8 large-8 columns">
<h2>Complete solutions for DNA methylation studies</h2>
<p>Whether you are experienced or new to the field of DNA methylation, Diagenode has everything you need to make your assay as easy and convenient as possible while ensuring consistent data between samples and experiments. Diagenode offers sonication instruments, reagent kits, high quality antibodies, and high-throughput automation capability to address all of your specific DNA methylation analysis requirements.</p>
</div>
<div class="small-12 medium-4 large-4 columns text-center"><a href="../landing-pages/dna-methylation-grant-applications"><img src="https://www.diagenode.com/img/banners/banner-dna-grant.png" alt="" /></a></div>
<div style="text-align: justify;" class="small-12 medium-12 large-12 columns">
<p>DNA methylation was the first discovered epigenetic mark and is the most widely studied topic in epigenetics. <em>In vivo</em>, DNA is methylated following DNA replication and is involved in a number of biological processes including the regulation of imprinted genes, X chromosome inactivation. and tumor suppressor gene silencing in cancer cells. Methylation often occurs in cytosine-guanine rich regions of DNA (CpG islands), which are commonly upstream of promoter regions.</p>
</div>
<div class="small-12 medium-12 large-12 columns"><br /><br />
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#dnamethyl"><i class="fa fa-caret-right"></i> Learn more</a>
<div id="dnamethyl" class="content">5-methylcytosine (5-mC) has been known for a long time as the only modification of DNA for epigenetic regulation. In 2009, however, Kriaucionis discovered a second methylated cytosine, 5-hydroxymethylcytosine (5-hmC). The so-called 6th base, is generated by enzymatic conversion of 5-methylcytosine (5-mC) into 5-hydroxymethylcytosine by the TET family of oxygenases. Early reports suggested that 5-hmC may represent an intermediate of active demethylation in a new pathway which demethylates DNA, converting 5-mC to cytosine. Recent evidence fuel this hypothesis suggesting that further oxidation of the hydroxymethyl group leads to a formyl or carboxyl group followed by either deformylation or decarboxylation. The formyl and carboxyl groups of 5-formylcytosine (5-fC) and 5-carboxylcytosine (5-caC) could be enzymatically removed without excision of the base.
<p class="text-center"><img src="https://www.diagenode.com/img/categories/kits_dna/dna_methylation_variants.jpg" /></p>
</div>
</li>
</ul>
<br />
<h2>Main DNA methylation technologies</h2>
<p style="text-align: justify;">Overview of the <span style="font-weight: 400;">three main approaches for studying DNA methylation.</span></p>
<div class="row">
<ol>
<li style="font-weight: 400;"><span style="font-weight: 400;">Chemical modification with bisulfite – Bisulfite conversion</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Enrichment of methylated DNA (including MeDIP and MBD)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Treatment with methylation-sensitive or dependent restriction enzymes</span></li>
</ol>
<p><span style="font-weight: 400;"> </span></p>
<div class="row">
<table>
<thead>
<tr>
<th></th>
<th>Description</th>
<th width="350">Features</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Bisulfite conversion</strong></td>
<td><span style="font-weight: 400;">Chemical conversion of unmethylated cytosine to uracil. Methylated cytosines are protected from this conversion allowing to determine DNA methylation at single nucleotide resolution.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Single nucleotide resolution</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Quantitative analysis - methylation rate (%)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Gold standard and well studied</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><b>Methylated DNA enrichment</b></td>
<td><span style="font-weight: 400;">(Hydroxy-)Methylated DNA is enriched by using specific antibodies (hMeDIP or MeDIP) or proteins (MBD) that specifically bind methylated CpG sites in fragmented genomic DNA.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Resolution depends on the fragment size of the enriched methylated DNA (300 bp)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Qualitative analysis</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><strong>Restriction enzyme-based digestion</strong></td>
<td><span style="font-weight: 400;">Use of (hydroxy)methylation-sensitive or (hydroxy)methylation-dependent restriction enzymes for DNA methylation analysis at specific sites.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Determination of methylation status is limited by the enzyme recognition site</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Easy to use</span></li>
</ul>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="row"></div>
</div>
</div>
<div class="large-12 columns"></div>
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<p>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</p>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
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'name' => 'Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation',
'authors' => 'Piera Grisolia et al.',
'description' => '<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Background</h3>
<p>Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylated DNA Immunoprecipitation and High-Throughput Sequencing (cfMeDIP-seq), may be informative in characterizing breast cancer in patients with BRCA1/2 germline mutations for early cancer detection and response to therapy.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Methods</h3>
<p>We enrolled 23 BC patients with germline mutation of BRCA1 and BRCA2 genes, 19 healthy controls without BRCA1/2 mutation, and two healthy individuals who carried BRCA1/2 mutations. Blood samples were collected for all study subjects at the diagnosis, and plasma was isolated by centrifugation. Cell-free DNA was extracted from 1 mL of plasma, and cfMeDIP-seq was performed for each sample. Shallow whole genome sequencing was performed on the immuno-precipitated samples. Then, the differentially methylated 300-bp regions (DMRs) between 25 BRCA germline mutation carriers and 19 non-carriers were identified. DMRs were compared with tumor-specific regions from public datasets to perform an unbiased analysis. Finally, two statistical classifiers were trained based on the GLMnet and random forest model to evaluate if the identified DMRs could discriminate BRCA-positive from healthy samples.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Results</h3>
<p>We identified 7,095 hypermethylated and 212 hypomethylated regions in 25 BRCA germline mutation carriers compared to 19 controls. These regions discriminate tumors from healthy samples with high accuracy and sensitivity. We show that the circulating tumor DNA of BRCA1/2 mutant breast cancers is characterized by the hypomethylation of genes involved in DNA repair and cell cycle. We uncovered the TFs associated with these DRMs and identified that proteins of the Erythroblast Transformation Specific (ETS) family are particularly active in the hypermethylated regions. Finally, we assessed that these regions could discriminate between BRCA positives from healthy samples with an AUC of 0.95, a sensitivity of 88%, and a specificity of 94.74%.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Conclusions</h3>
<p>Our study emphasizes the importance of tumor cell-derived DNA methylation in BC, reporting a different methylation profile between patients carrying mutations in BRCA1, BRCA2, and wild-type controls. Our minimally invasive approach could allow early cancer diagnosis, assessment of minimal residual disease, and monitoring of response to therapy.</p>',
'date' => '2024-10-15',
'pmid' => 'https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05734-2',
'doi' => 'https://doi.org/10.1186/s12967-024-05734-2',
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'name' => 'Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and </span><em>FOSL1</em><span><span> </span>expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.</span></p>',
'date' => '2024-06-25',
'pmid' => 'https://www.cell.com/cell-reports/fulltext/S2211-1247(24)00678-8',
'doi' => 'https://doi.org/10.1016/j.celrep.2024.114350',
'modified' => '2024-06-24 10:33:29',
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'name' => 'Detecting small cell transformation in patients with advanced EGFR mutant lung adenocarcinoma through epigenomic cfDNA profiling',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free (cf)DNA-based approach to non-invasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3, methylated DNA immunoprecipitation sequencing (MeDIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 ml aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n=24,424), DNA methylation (n=3,298), and chromatin accessibility (n=16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate non-invasive discrimination between patients with EGFRm LUAD versus tSCLC (AUROC=0.82-0.87). A multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 ml of patient plasma.</span></p>',
'date' => '2024-06-24',
'pmid' => 'https://aacrjournals.org/clincancerres/article/doi/10.1158/1078-0432.CCR-24-0466/746147/Detecting-small-cell-transformation-in-patients',
'doi' => 'https://doi.org/10.1158/1078-0432.CCR-24-0466',
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'name' => 'Prostate cancer detection through unbiased capture of methylated cell-free DNA',
'authors' => 'Ermira Lleshi et al.',
'description' => '<p><span>Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localised cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localised and 88.7% (79/89) of metastatic cancer patients in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signalling. This demonstrates the potential of circulating tumour DNA methylation for prostate cancer detection and prognostication.</span></p>',
'date' => '2024-06-20',
'pmid' => 'https://www.sciencedirect.com/science/article/pii/S2589004224015554',
'doi' => 'https://doi.org/10.1016/j.isci.2024.110330',
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'name' => 'Cell-free DNA methylation-defined prognostic subgroups in small celllung cancer identified by leukocyte methylation subtraction',
'authors' => 'Ul Haq Sami et al.',
'description' => '<p>Small cell lung cancer (SCLC) methylome is understudied. Here, we comprehensively profile SCLC using cell-free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq). Cell-free DNA (cfDNA) from plasma of 74 SCLC patients pre-treatment and from 20 non-cancer participants, genomic DNA (gDNA) from peripheral blood leukocytes from the same 74 patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX) underwent cfMeDIP-seq. PeRIpheral blood leukocyte MEthylation (PRIME) subtraction to improve tumour specificity. SCLC cfDNA methylation is distinct from non-cancer but correlates with CDX tumor methylation. PRIME and k-means consensus identified two methylome clusters with prognostic associations that related to axon guidance, neuroactive ligand−receptor interaction, pluripotency of stem cells, and differentially methylated at long noncoding RNA and other repeats features. We comprehensively profiled the SCLC methylome in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.</p>',
'date' => '2022-11-01',
'pmid' => 'https://doi.org/10.1016%2Fj.isci.2022.105487',
'doi' => '10.1016/j.isci.2022.105487',
'modified' => '2022-11-18 12:35:39',
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'id' => '4420',
'name' => 'cfDNA methylome profiling for detection and subtyping of small cell lungcancers.',
'authors' => 'Chemi Francesca et al.',
'description' => '<p>Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.</p>',
'date' => '2022-08-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35941262',
'doi' => '10.1038/s43018-022-00415-9',
'modified' => '2022-09-27 14:46:40',
'created' => '2022-09-08 16:32:20',
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'id' => '3773',
'name' => 'Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA.',
'authors' => 'Shen SY, Burgener JM, Bratman SV, De Carvalho DD',
'description' => '<p>Circulating cell-free DNA (cfDNA) comprises small DNA fragments derived from normal and tumor tissue that are released into the bloodstream. Recently, methylation profiling of cfDNA as a liquid biopsy tool has been gaining prominence due to the presence of tissue-specific markers in cfDNA. We have previously reported cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as a sensitive, low-input, cost-efficient and bisulfite-free approach to profiling DNA methylomes of plasma cfDNA. cfMeDIP-seq is an extension of a previously published MeDIP-seq protocol and is adapted to allow for methylome profiling of samples with low input (ranging from 1 to 10 ng) of DNA, which is enabled by the addition of 'filler DNA' before immunoprecipitation. This protocol is not limited to plasma cfDNA; it can also be applied to other samples that are naturally sheared and at low availability (e.g., urinary cfDNA and cerebrospinal fluid cfDNA), and is potentially applicable to other applications beyond cancer detection, including prenatal diagnostics, cardiology and monitoring of immune response. The protocol presented here should enable any standard molecular laboratory to generate cfMeDIP-seq libraries from plasma cfDNA in ~3-4 d.</p>',
'date' => '2019-08-30',
'pmid' => 'http://www.pubmed.gov/31471598',
'doi' => '10.1038/s41596-019-0202-2',
'modified' => '2019-10-02 17:07:45',
'created' => '2019-10-02 16:16:55',
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(int) 7 => array(
'id' => '3560',
'name' => 'DNA methylation and genetic degeneration of the Y chromosome in the dioecious plant Silene latifolia.',
'authors' => 'Rodríguez Lorenzo JL, Hobza R, Vyskot B',
'description' => '<p>BACKGROUND: S. latifolia is a model organism for the study of sex chromosome evolution in plants. Its sex chromosomes include large regions in which recombination became gradually suppressed. The regions tend to expand over time resulting in the formation of evolutionary strata. Non-recombination and later accumulation of repetitive sequences is a putative cause of the size increase in the Y chromosome. Gene decay and accumulation of repetitive DNA are identified as key evolutionary events. Transposons in the X and Y chromosomes are distributed differently and there is a regulation of transposon insertion by DNA methylation of the target sequences, this points to an important role of DNA methylation during sex chromosome evolution in Silene latifolia. The aim of this study was to elucidate whether the reduced expression of the Y allele in S. latifolia is caused by genetic degeneration or if the cause is methylation triggered by transposons and repetitive sequences. RESULTS: Gene expression analysis in S. latifolia males has shown expression bias in both X and Y alleles. To determine whether these differences are caused by genetic degeneration or methylation spread by transposons and repetitive sequences, we selected several sex-linked genes with varying degrees of degeneration and from different evolutionary strata. Immunoprecipitation of methylated DNA (MeDIP) from promoter, exon and intron regions was used and validated through bisulfite sequencing. We found DNA methylation in males, and only in the promoter of genes of stratum I (older). The Y alleles in genes of stratum I were methylation enriched compared to X alleles. There was also abundant and high percentage methylation in the CHH context in most sequences, indicating de novo methylation through the RdDM pathway. CONCLUSIONS: We speculate that TE accumulation and not gene decay is the cause of DNA methylation in the S. latifolia Y sex chromosome with influence on the process of heterochromatinization.</p>',
'date' => '2018-07-16',
'pmid' => 'http://www.pubmed.gov/30012097',
'doi' => '10.1186/s12864-018-4936-y',
'modified' => '2019-03-25 11:22:31',
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'description' => '<p>The DNA Methylation control package includes unmethylated and in vitro methylated DNA together with specific primer sets for assessing the efficiency of your non-plant MeDIP experiments (Methylated DNA Immunoprecipitation) carried out with Diagenode’s <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" target="_blank">MagMeDIP qPCR</a> and <a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a>. These controls are made from <em>A. thaliana</em> BAC.</p>
<p><em><strong>CAUTION </strong>: However these controls are compatible with (Auto) MagMeDIP qPCR Kit, these are not the same as the ones directly provided with the kit. Please always use controls with their respective primers.</em></p>',
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'description' => '<p><a href="https://www.diagenode.com/files/products/kits/magmedip-kit-manual-C02010020-21.pdf"><img src="https://www.diagenode.com/img/buttons/bt-manual.png" /></a></p>
<p> </p>
<div class="small-12 medium-4 large-4 columns"><center></center><center></center><center></center><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" alt="Click here to read more about MeDIP " caption="false" width="80%" /></a></center></div>
<div class="small-12 medium-8 large-8 columns">
<h3 style="text-align: justify;">Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline" style="text-align: justify;">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
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<p></p>
<p></p>
<p></p>
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<p>Perform <strong>MeDIP</strong> (<strong>Me</strong>thylated <strong>D</strong>NA <strong>I</strong>mmuno<strong>p</strong>recipitation) followed by qPCR or NGS to estimate DNA methylation status of your sample using a highly sensitive 5-methylcytosine antibody. Our MagMeDIP kit contains high quality reagents to get the highest enrichment of methylated DNA with an optimized user-friendly protocol.</p>
</div>
</div>
<h3><span>Features</span></h3>
<ul>
<li>Starting DNA amount: <strong>10 ng – 1 µg</strong></li>
<li>Content: <strong>all reagents included</strong> for DNA extraction, immunoprecipitation (including the 5-mC antibody, spike-in controls and their corresponding qPCR primer pairs) as well as DNA isolation after IP.</li>
<li>Application: <strong>qPCR</strong> and <strong>NGS</strong></li>
<li>Robust method, <strong>superior enrichment</strong>, and easy-to-use protocol</li>
<li><strong>High reproducibility</strong> between replicates and repetitive experiments</li>
<li>Compatible with <strong>all species </strong></li>
</ul>',
'label1' => 'MagMeDIP workflow',
'info1' => '<p>DNA methylation occurs primarily as 5-methylcytosine (5-mC), and the Diagenode MagMeDIP Kit takes advantage of a specific antibody targeting this 5-mC to immunoprecipitate methylated DNA, which can be thereafter directly analyzed by qPCR or Next-Generation Sequencing (NGS).</p>
<h3><span>How it works</span></h3>
<p>In brief, after the cell collection and lysis, the genomic DNA is extracted, sheared, and then denatured. In the next step the antibody directed against 5 methylcytosine and antibody binding beads are used for immunoselection and immunoprecipitation of methylated DNA fragments. Then, the IP’d methylated DNA is isolated and can be used for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<center><img src="https://www.diagenode.com/img/product/kits/MagMeDIP-workflow.png" width="70%" alt="5-methylcytosine" caption="false" /></center>
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'info2' => '<p>The kit MagMeDIP contains all reagents necessary for a complete MeDIP-qPCR workflow. Two MagMeDIP protocols have been validated: for manual processing as well as for automated processing, using the Diagenode’s IP-Star Compact Automated System (please refer to the kit manual).</p>
<ul>
<li><strong>Complete kit</strong> including DNA extraction module, IP antibody and reagents, DNA isolation buffer</li>
<li><strong>Quality control of the IP:</strong> due to methylated and unmethylated DNA spike-in controls and their associated qPCR primers</li>
<li><strong>Easy to use</strong> with user-friendly magnetic beads and rack</li>
<li><strong>Highly validated protocol</strong></li>
<li>Automated protocol supplied</li>
</ul>
<center><img src="https://www.diagenode.com/img/product/kits/fig1-magmedipkit.png" width="85%" alt="Methylated DNA Immunoprecipitation" caption="false" /></center>
<p style="font-size: 0.9em;"><em><strong>Figure 1.</strong> Immunoprecipitation results obtained with Diagenode MagMeDIP Kit</em></p>
<p style="font-size: 0.9em;">MeDIP assays were performed manually using 1 µg or 50 ng gDNA from blood cells with the MagMeDIP kit (Diagenode). The IP was performed with the Methylated and Unmethylated spike-in controls included in the kit, together with the human DNA samples. The DNA was isolated/purified using DIB. Afterwards, qPCR was performed using the primer pairs included in this kit.</p>
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'info3' => '<p>For DNA methylation analysis on the whole genome, MagMeDIP kit can be coupled with Next-Generation Sequencing. To perform MeDIP-sequencing we recommend the following strategy:</p>
<ul style="list-style-type: circle;">
<li>Choose a library preparation solution which is compatible with the starting amount of DNA you are planning to use (from 10 ng to 1 μg). It can be a home-made solution or a commercial one.</li>
<li>Choose the indexing system that fits your needs considering the following features:</li>
<ul>
<ul>
<ul>
<li>Single-indexing, combinatorial dual-indexing or unique dual-indexing</li>
<li>Number of barcodes</li>
<li>Full-length adaptors containing the barcodes or barcoding at the final amplification step</li>
<li>Presence / absence of Unique Molecular Identifiers (for PCR duplicates removal)</li>
</ul>
</ul>
</ul>
<li>Standard library preparation protocols are compatible with double-stranded DNA only, therefore the first steps of the library preparation (end repair, A-tailing, adaptor ligation and clean-up) will have to be performed on sheared DNA, before the IP.</li>
</ul>
<p style="padding-left: 30px;"><strong>CAUTION:</strong> As the immunoprecipitation step occurs at the middle of the library preparation workflow, single-tube solutions for library preparation are usually not compatible with MeDIP-sequencing.</p>
<ul style="list-style-type: circle;">
<li>For DNA isolation after the IP, we recommend using the <a href="https://www.diagenode.com/en/p/ipure-kit-v2-x24" title="IPure kit v2">IPure kit v2</a> (available separately, Cat. No. C03010014) instead of DNA isolation Buffer.</li>
</ul>
<ul style="list-style-type: circle;">
<li>Perform library amplification after the DNA isolation following the standard protocol of the chosen library preparation solution.</li>
</ul>
<h3><span>MeDIP-seq workflow</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/MeDIP-seq-workflow.png" width="110%" alt="MagMeDIP qPCR Kit x10 workflow" caption="false" /></center>
<h3><span>Example of results</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/medip-specificity.png" alt="MagMeDIP qPCR Kit Result" caption="false" width="951" height="488" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 1. qPCR analysis of external spike-in DNA controls (methylated and unmethylated) after IP.</strong> Samples were prepared using 1μg – 100ng -10ng sheared human gDNA with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-saturation-analysis.png" alt=" MagMeDIP kit " caption="false" width="951" height="461" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 2. Saturation analysis.</strong> Clean reads were aligned to the human genome (hg19) using Burrows-Wheeler aligner (BWA) algorithm after which duplicated and unmapped reads were removed resulting in a mapping efficiency >98% for all samples. Quality and validity check of the mapped MeDIP-seq data was performed using MEDIPS R package. Saturation plots show that all sets of reads have sufficient complexity and depth to saturate the coverage profile of the reference genome and that this is reproducible between replicates and repetitive experiments (data shown for 50 ng gDNA input: left panel = replicate a, right panel = replicate b).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-libraries-prep.png" alt="MagMeDIP x10 " caption="false" width="951" height="708" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 3. Sequencing profiles of MeDIP-seq libraries prepared from different starting amounts of sheared gDNA on the positive and negative methylated control regions.</strong> MeDIP-seq libraries were prepared from decreasing starting amounts of gDNA (1 μg (green), 50 ng (red), and 10ng (blue)) originating from human blood with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode). IP and corresponding INPUT samples were sequenced on Illumina NovaSeq SP with 2x50 PE reads. The reads were mapped to the human genome (hg19) with bwa and the alignments were loaded into IGV (the tracks use an identical scale). The top IGV figure shows the TSH2B (also known as H2BC1) gene (marked by blue boxes in the bottom track) and its surroundings. The TSH2B gene is coding for a histone variant that does not occur in blood cells, and it is known to be silenced by methylation. Accordingly, we see a high coverage in the vicinity of this gene. The bottom IGV figure shows the GADPH locus (marked by blue boxes in the bottom track) and its surroundings. The GADPH gene is a highly active transcription region and should not be methylated, resulting in no reads accumulation following MeDIP-seq experiment.</p>
<p></p>
<ul>
<ul>
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'meta_description' => 'Perform Methylated DNA Immunoprecipitation (MeDIP) to estimate DNA methylation status of your sample using highly specific 5-mC antibody. This kit allows the preparation of cfMeDIP-seq libraries.',
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'name' => 'DNA methylation control package V2',
'description' => '<p><a href="https://www.diagenode.com/files/products/kits/Datasheet_DNA-methylation-control-package-V2.pdf"><img src="https://www.diagenode.com/img/buttons/bt-manual.png" /></a></p>
<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
<p><em><strong>NOTE</strong>: These spike-in controls are the ones directly provided in <span>Diagenode’s </span><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a><span><span> </span>and<span> </span></span><a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a><span>.</span></em></p>',
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<div class="small-12 medium-3 large-3 columns"><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" /></a></center></div>
<div class="small-12 medium-9 large-9 columns">
<h3>Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
</div>
</div>
<div class="row">
<div class="large-12 columns"><span>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</span><br />
<h2></h2>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-seq-package-V2-x10" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>
</div>
</div>
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<div class="large-12 columns">
<div style="text-align: justify;" class="small-12 medium-8 large-8 columns">
<h2>Complete solutions for DNA methylation studies</h2>
<p>Whether you are experienced or new to the field of DNA methylation, Diagenode has everything you need to make your assay as easy and convenient as possible while ensuring consistent data between samples and experiments. Diagenode offers sonication instruments, reagent kits, high quality antibodies, and high-throughput automation capability to address all of your specific DNA methylation analysis requirements.</p>
</div>
<div class="small-12 medium-4 large-4 columns text-center"><a href="../landing-pages/dna-methylation-grant-applications"><img src="https://www.diagenode.com/img/banners/banner-dna-grant.png" alt="" /></a></div>
<div style="text-align: justify;" class="small-12 medium-12 large-12 columns">
<p>DNA methylation was the first discovered epigenetic mark and is the most widely studied topic in epigenetics. <em>In vivo</em>, DNA is methylated following DNA replication and is involved in a number of biological processes including the regulation of imprinted genes, X chromosome inactivation. and tumor suppressor gene silencing in cancer cells. Methylation often occurs in cytosine-guanine rich regions of DNA (CpG islands), which are commonly upstream of promoter regions.</p>
</div>
<div class="small-12 medium-12 large-12 columns"><br /><br />
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#dnamethyl"><i class="fa fa-caret-right"></i> Learn more</a>
<div id="dnamethyl" class="content">5-methylcytosine (5-mC) has been known for a long time as the only modification of DNA for epigenetic regulation. In 2009, however, Kriaucionis discovered a second methylated cytosine, 5-hydroxymethylcytosine (5-hmC). The so-called 6th base, is generated by enzymatic conversion of 5-methylcytosine (5-mC) into 5-hydroxymethylcytosine by the TET family of oxygenases. Early reports suggested that 5-hmC may represent an intermediate of active demethylation in a new pathway which demethylates DNA, converting 5-mC to cytosine. Recent evidence fuel this hypothesis suggesting that further oxidation of the hydroxymethyl group leads to a formyl or carboxyl group followed by either deformylation or decarboxylation. The formyl and carboxyl groups of 5-formylcytosine (5-fC) and 5-carboxylcytosine (5-caC) could be enzymatically removed without excision of the base.
<p class="text-center"><img src="https://www.diagenode.com/img/categories/kits_dna/dna_methylation_variants.jpg" /></p>
</div>
</li>
</ul>
<br />
<h2>Main DNA methylation technologies</h2>
<p style="text-align: justify;">Overview of the <span style="font-weight: 400;">three main approaches for studying DNA methylation.</span></p>
<div class="row">
<ol>
<li style="font-weight: 400;"><span style="font-weight: 400;">Chemical modification with bisulfite – Bisulfite conversion</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Enrichment of methylated DNA (including MeDIP and MBD)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Treatment with methylation-sensitive or dependent restriction enzymes</span></li>
</ol>
<p><span style="font-weight: 400;"> </span></p>
<div class="row">
<table>
<thead>
<tr>
<th></th>
<th>Description</th>
<th width="350">Features</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Bisulfite conversion</strong></td>
<td><span style="font-weight: 400;">Chemical conversion of unmethylated cytosine to uracil. Methylated cytosines are protected from this conversion allowing to determine DNA methylation at single nucleotide resolution.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Single nucleotide resolution</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Quantitative analysis - methylation rate (%)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Gold standard and well studied</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><b>Methylated DNA enrichment</b></td>
<td><span style="font-weight: 400;">(Hydroxy-)Methylated DNA is enriched by using specific antibodies (hMeDIP or MeDIP) or proteins (MBD) that specifically bind methylated CpG sites in fragmented genomic DNA.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Resolution depends on the fragment size of the enriched methylated DNA (300 bp)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Qualitative analysis</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><strong>Restriction enzyme-based digestion</strong></td>
<td><span style="font-weight: 400;">Use of (hydroxy)methylation-sensitive or (hydroxy)methylation-dependent restriction enzymes for DNA methylation analysis at specific sites.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Determination of methylation status is limited by the enzyme recognition site</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Easy to use</span></li>
</ul>
</td>
</tr>
</tbody>
</table>
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<div class="row"></div>
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<p>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</p>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>',
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'name' => 'Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation',
'authors' => 'Piera Grisolia et al.',
'description' => '<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Background</h3>
<p>Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylated DNA Immunoprecipitation and High-Throughput Sequencing (cfMeDIP-seq), may be informative in characterizing breast cancer in patients with BRCA1/2 germline mutations for early cancer detection and response to therapy.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Methods</h3>
<p>We enrolled 23 BC patients with germline mutation of BRCA1 and BRCA2 genes, 19 healthy controls without BRCA1/2 mutation, and two healthy individuals who carried BRCA1/2 mutations. Blood samples were collected for all study subjects at the diagnosis, and plasma was isolated by centrifugation. Cell-free DNA was extracted from 1 mL of plasma, and cfMeDIP-seq was performed for each sample. Shallow whole genome sequencing was performed on the immuno-precipitated samples. Then, the differentially methylated 300-bp regions (DMRs) between 25 BRCA germline mutation carriers and 19 non-carriers were identified. DMRs were compared with tumor-specific regions from public datasets to perform an unbiased analysis. Finally, two statistical classifiers were trained based on the GLMnet and random forest model to evaluate if the identified DMRs could discriminate BRCA-positive from healthy samples.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Results</h3>
<p>We identified 7,095 hypermethylated and 212 hypomethylated regions in 25 BRCA germline mutation carriers compared to 19 controls. These regions discriminate tumors from healthy samples with high accuracy and sensitivity. We show that the circulating tumor DNA of BRCA1/2 mutant breast cancers is characterized by the hypomethylation of genes involved in DNA repair and cell cycle. We uncovered the TFs associated with these DRMs and identified that proteins of the Erythroblast Transformation Specific (ETS) family are particularly active in the hypermethylated regions. Finally, we assessed that these regions could discriminate between BRCA positives from healthy samples with an AUC of 0.95, a sensitivity of 88%, and a specificity of 94.74%.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Conclusions</h3>
<p>Our study emphasizes the importance of tumor cell-derived DNA methylation in BC, reporting a different methylation profile between patients carrying mutations in BRCA1, BRCA2, and wild-type controls. Our minimally invasive approach could allow early cancer diagnosis, assessment of minimal residual disease, and monitoring of response to therapy.</p>',
'date' => '2024-10-15',
'pmid' => 'https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05734-2',
'doi' => 'https://doi.org/10.1186/s12967-024-05734-2',
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'name' => 'Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and </span><em>FOSL1</em><span><span> </span>expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.</span></p>',
'date' => '2024-06-25',
'pmid' => 'https://www.cell.com/cell-reports/fulltext/S2211-1247(24)00678-8',
'doi' => 'https://doi.org/10.1016/j.celrep.2024.114350',
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'name' => 'Detecting small cell transformation in patients with advanced EGFR mutant lung adenocarcinoma through epigenomic cfDNA profiling',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free (cf)DNA-based approach to non-invasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3, methylated DNA immunoprecipitation sequencing (MeDIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 ml aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n=24,424), DNA methylation (n=3,298), and chromatin accessibility (n=16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate non-invasive discrimination between patients with EGFRm LUAD versus tSCLC (AUROC=0.82-0.87). A multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 ml of patient plasma.</span></p>',
'date' => '2024-06-24',
'pmid' => 'https://aacrjournals.org/clincancerres/article/doi/10.1158/1078-0432.CCR-24-0466/746147/Detecting-small-cell-transformation-in-patients',
'doi' => 'https://doi.org/10.1158/1078-0432.CCR-24-0466',
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'name' => 'Prostate cancer detection through unbiased capture of methylated cell-free DNA',
'authors' => 'Ermira Lleshi et al.',
'description' => '<p><span>Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localised cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localised and 88.7% (79/89) of metastatic cancer patients in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signalling. This demonstrates the potential of circulating tumour DNA methylation for prostate cancer detection and prognostication.</span></p>',
'date' => '2024-06-20',
'pmid' => 'https://www.sciencedirect.com/science/article/pii/S2589004224015554',
'doi' => 'https://doi.org/10.1016/j.isci.2024.110330',
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'name' => 'Cell-free DNA methylation-defined prognostic subgroups in small celllung cancer identified by leukocyte methylation subtraction',
'authors' => 'Ul Haq Sami et al.',
'description' => '<p>Small cell lung cancer (SCLC) methylome is understudied. Here, we comprehensively profile SCLC using cell-free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq). Cell-free DNA (cfDNA) from plasma of 74 SCLC patients pre-treatment and from 20 non-cancer participants, genomic DNA (gDNA) from peripheral blood leukocytes from the same 74 patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX) underwent cfMeDIP-seq. PeRIpheral blood leukocyte MEthylation (PRIME) subtraction to improve tumour specificity. SCLC cfDNA methylation is distinct from non-cancer but correlates with CDX tumor methylation. PRIME and k-means consensus identified two methylome clusters with prognostic associations that related to axon guidance, neuroactive ligand−receptor interaction, pluripotency of stem cells, and differentially methylated at long noncoding RNA and other repeats features. We comprehensively profiled the SCLC methylome in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.</p>',
'date' => '2022-11-01',
'pmid' => 'https://doi.org/10.1016%2Fj.isci.2022.105487',
'doi' => '10.1016/j.isci.2022.105487',
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'name' => 'cfDNA methylome profiling for detection and subtyping of small cell lungcancers.',
'authors' => 'Chemi Francesca et al.',
'description' => '<p>Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.</p>',
'date' => '2022-08-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35941262',
'doi' => '10.1038/s43018-022-00415-9',
'modified' => '2022-09-27 14:46:40',
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(int) 6 => array(
'id' => '3773',
'name' => 'Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA.',
'authors' => 'Shen SY, Burgener JM, Bratman SV, De Carvalho DD',
'description' => '<p>Circulating cell-free DNA (cfDNA) comprises small DNA fragments derived from normal and tumor tissue that are released into the bloodstream. Recently, methylation profiling of cfDNA as a liquid biopsy tool has been gaining prominence due to the presence of tissue-specific markers in cfDNA. We have previously reported cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as a sensitive, low-input, cost-efficient and bisulfite-free approach to profiling DNA methylomes of plasma cfDNA. cfMeDIP-seq is an extension of a previously published MeDIP-seq protocol and is adapted to allow for methylome profiling of samples with low input (ranging from 1 to 10 ng) of DNA, which is enabled by the addition of 'filler DNA' before immunoprecipitation. This protocol is not limited to plasma cfDNA; it can also be applied to other samples that are naturally sheared and at low availability (e.g., urinary cfDNA and cerebrospinal fluid cfDNA), and is potentially applicable to other applications beyond cancer detection, including prenatal diagnostics, cardiology and monitoring of immune response. The protocol presented here should enable any standard molecular laboratory to generate cfMeDIP-seq libraries from plasma cfDNA in ~3-4 d.</p>',
'date' => '2019-08-30',
'pmid' => 'http://www.pubmed.gov/31471598',
'doi' => '10.1038/s41596-019-0202-2',
'modified' => '2019-10-02 17:07:45',
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'id' => '3560',
'name' => 'DNA methylation and genetic degeneration of the Y chromosome in the dioecious plant Silene latifolia.',
'authors' => 'Rodríguez Lorenzo JL, Hobza R, Vyskot B',
'description' => '<p>BACKGROUND: S. latifolia is a model organism for the study of sex chromosome evolution in plants. Its sex chromosomes include large regions in which recombination became gradually suppressed. The regions tend to expand over time resulting in the formation of evolutionary strata. Non-recombination and later accumulation of repetitive sequences is a putative cause of the size increase in the Y chromosome. Gene decay and accumulation of repetitive DNA are identified as key evolutionary events. Transposons in the X and Y chromosomes are distributed differently and there is a regulation of transposon insertion by DNA methylation of the target sequences, this points to an important role of DNA methylation during sex chromosome evolution in Silene latifolia. The aim of this study was to elucidate whether the reduced expression of the Y allele in S. latifolia is caused by genetic degeneration or if the cause is methylation triggered by transposons and repetitive sequences. RESULTS: Gene expression analysis in S. latifolia males has shown expression bias in both X and Y alleles. To determine whether these differences are caused by genetic degeneration or methylation spread by transposons and repetitive sequences, we selected several sex-linked genes with varying degrees of degeneration and from different evolutionary strata. Immunoprecipitation of methylated DNA (MeDIP) from promoter, exon and intron regions was used and validated through bisulfite sequencing. We found DNA methylation in males, and only in the promoter of genes of stratum I (older). The Y alleles in genes of stratum I were methylation enriched compared to X alleles. There was also abundant and high percentage methylation in the CHH context in most sequences, indicating de novo methylation through the RdDM pathway. CONCLUSIONS: We speculate that TE accumulation and not gene decay is the cause of DNA methylation in the S. latifolia Y sex chromosome with influence on the process of heterochromatinization.</p>',
'date' => '2018-07-16',
'pmid' => 'http://www.pubmed.gov/30012097',
'doi' => '10.1186/s12864-018-4936-y',
'modified' => '2019-03-25 11:22:31',
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'name' => 'Protection of CpG islands from DNA methylation is DNA-encoded and evolutionarily conserved',
'authors' => 'Long HK, King HW, Patient RK, Odom DT, Klose RJ',
'description' => '<p>DNA methylation is a repressive epigenetic modification that covers vertebrate genomes. Regions known as CpG islands (CGIs), which are refractory to DNA methylation, are often associated with gene promoters and play central roles in gene regulation. Yet how CGIs in their normal genomic context evade the DNA methylation machinery and whether these mechanisms are evolutionarily conserved remains enigmatic. To address these fundamental questions we exploited a transchromosomic animal model and genomic approaches to understand how the hypomethylated state is formed <em>in vivo</em> and to discover whether mechanisms governing CGI formation are evolutionarily conserved. Strikingly, insertion of a human chromosome into mouse revealed that promoter-associated CGIs are refractory to DNA methylation regardless of host species, demonstrating that DNA sequence plays a central role in specifying the hypomethylated state through evolutionarily conserved mechanisms. In contrast, elements distal to gene promoters exhibited more variable methylation between host species, uncovering a widespread dependence on nucleotide frequency and occupancy of DNA-binding transcription factors in shaping the DNA methylation landscape away from gene promoters. This was exemplified by young CpG rich lineage-restricted repeat sequences that evaded DNA methylation in the absence of co-evolved mechanisms targeting methylation to these sequences, and species specific DNA binding events that protected against DNA methylation in CpG poor regions. Finally, transplantation of mouse chromosomal fragments into the evolutionarily distant zebrafish uncovered the existence of a mechanistically conserved and DNA-encoded logic which shapes CGI formation across vertebrate species.</p>',
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<p> </p>
<div class="small-12 medium-4 large-4 columns"><center></center><center></center><center></center><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" alt="Click here to read more about MeDIP " caption="false" width="80%" /></a></center></div>
<div class="small-12 medium-8 large-8 columns">
<h3 style="text-align: justify;">Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline" style="text-align: justify;">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
</div>
<p></p>
<p></p>
<p></p>
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<div class="small-12 medium-8 large-8 columns"><br />
<p>Perform <strong>MeDIP</strong> (<strong>Me</strong>thylated <strong>D</strong>NA <strong>I</strong>mmuno<strong>p</strong>recipitation) followed by qPCR or NGS to estimate DNA methylation status of your sample using a highly sensitive 5-methylcytosine antibody. Our MagMeDIP kit contains high quality reagents to get the highest enrichment of methylated DNA with an optimized user-friendly protocol.</p>
</div>
</div>
<h3><span>Features</span></h3>
<ul>
<li>Starting DNA amount: <strong>10 ng – 1 µg</strong></li>
<li>Content: <strong>all reagents included</strong> for DNA extraction, immunoprecipitation (including the 5-mC antibody, spike-in controls and their corresponding qPCR primer pairs) as well as DNA isolation after IP.</li>
<li>Application: <strong>qPCR</strong> and <strong>NGS</strong></li>
<li>Robust method, <strong>superior enrichment</strong>, and easy-to-use protocol</li>
<li><strong>High reproducibility</strong> between replicates and repetitive experiments</li>
<li>Compatible with <strong>all species </strong></li>
</ul>',
'label1' => 'MagMeDIP workflow',
'info1' => '<p>DNA methylation occurs primarily as 5-methylcytosine (5-mC), and the Diagenode MagMeDIP Kit takes advantage of a specific antibody targeting this 5-mC to immunoprecipitate methylated DNA, which can be thereafter directly analyzed by qPCR or Next-Generation Sequencing (NGS).</p>
<h3><span>How it works</span></h3>
<p>In brief, after the cell collection and lysis, the genomic DNA is extracted, sheared, and then denatured. In the next step the antibody directed against 5 methylcytosine and antibody binding beads are used for immunoselection and immunoprecipitation of methylated DNA fragments. Then, the IP’d methylated DNA is isolated and can be used for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<center><img src="https://www.diagenode.com/img/product/kits/MagMeDIP-workflow.png" width="70%" alt="5-methylcytosine" caption="false" /></center>
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'label2' => 'MeDIP-qPCR',
'info2' => '<p>The kit MagMeDIP contains all reagents necessary for a complete MeDIP-qPCR workflow. Two MagMeDIP protocols have been validated: for manual processing as well as for automated processing, using the Diagenode’s IP-Star Compact Automated System (please refer to the kit manual).</p>
<ul>
<li><strong>Complete kit</strong> including DNA extraction module, IP antibody and reagents, DNA isolation buffer</li>
<li><strong>Quality control of the IP:</strong> due to methylated and unmethylated DNA spike-in controls and their associated qPCR primers</li>
<li><strong>Easy to use</strong> with user-friendly magnetic beads and rack</li>
<li><strong>Highly validated protocol</strong></li>
<li>Automated protocol supplied</li>
</ul>
<center><img src="https://www.diagenode.com/img/product/kits/fig1-magmedipkit.png" width="85%" alt="Methylated DNA Immunoprecipitation" caption="false" /></center>
<p style="font-size: 0.9em;"><em><strong>Figure 1.</strong> Immunoprecipitation results obtained with Diagenode MagMeDIP Kit</em></p>
<p style="font-size: 0.9em;">MeDIP assays were performed manually using 1 µg or 50 ng gDNA from blood cells with the MagMeDIP kit (Diagenode). The IP was performed with the Methylated and Unmethylated spike-in controls included in the kit, together with the human DNA samples. The DNA was isolated/purified using DIB. Afterwards, qPCR was performed using the primer pairs included in this kit.</p>
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'info3' => '<p>For DNA methylation analysis on the whole genome, MagMeDIP kit can be coupled with Next-Generation Sequencing. To perform MeDIP-sequencing we recommend the following strategy:</p>
<ul style="list-style-type: circle;">
<li>Choose a library preparation solution which is compatible with the starting amount of DNA you are planning to use (from 10 ng to 1 μg). It can be a home-made solution or a commercial one.</li>
<li>Choose the indexing system that fits your needs considering the following features:</li>
<ul>
<ul>
<ul>
<li>Single-indexing, combinatorial dual-indexing or unique dual-indexing</li>
<li>Number of barcodes</li>
<li>Full-length adaptors containing the barcodes or barcoding at the final amplification step</li>
<li>Presence / absence of Unique Molecular Identifiers (for PCR duplicates removal)</li>
</ul>
</ul>
</ul>
<li>Standard library preparation protocols are compatible with double-stranded DNA only, therefore the first steps of the library preparation (end repair, A-tailing, adaptor ligation and clean-up) will have to be performed on sheared DNA, before the IP.</li>
</ul>
<p style="padding-left: 30px;"><strong>CAUTION:</strong> As the immunoprecipitation step occurs at the middle of the library preparation workflow, single-tube solutions for library preparation are usually not compatible with MeDIP-sequencing.</p>
<ul style="list-style-type: circle;">
<li>For DNA isolation after the IP, we recommend using the <a href="https://www.diagenode.com/en/p/ipure-kit-v2-x24" title="IPure kit v2">IPure kit v2</a> (available separately, Cat. No. C03010014) instead of DNA isolation Buffer.</li>
</ul>
<ul style="list-style-type: circle;">
<li>Perform library amplification after the DNA isolation following the standard protocol of the chosen library preparation solution.</li>
</ul>
<h3><span>MeDIP-seq workflow</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/MeDIP-seq-workflow.png" width="110%" alt="MagMeDIP qPCR Kit x10 workflow" caption="false" /></center>
<h3><span>Example of results</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/medip-specificity.png" alt="MagMeDIP qPCR Kit Result" caption="false" width="951" height="488" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 1. qPCR analysis of external spike-in DNA controls (methylated and unmethylated) after IP.</strong> Samples were prepared using 1μg – 100ng -10ng sheared human gDNA with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-saturation-analysis.png" alt=" MagMeDIP kit " caption="false" width="951" height="461" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 2. Saturation analysis.</strong> Clean reads were aligned to the human genome (hg19) using Burrows-Wheeler aligner (BWA) algorithm after which duplicated and unmapped reads were removed resulting in a mapping efficiency >98% for all samples. Quality and validity check of the mapped MeDIP-seq data was performed using MEDIPS R package. Saturation plots show that all sets of reads have sufficient complexity and depth to saturate the coverage profile of the reference genome and that this is reproducible between replicates and repetitive experiments (data shown for 50 ng gDNA input: left panel = replicate a, right panel = replicate b).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-libraries-prep.png" alt="MagMeDIP x10 " caption="false" width="951" height="708" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 3. Sequencing profiles of MeDIP-seq libraries prepared from different starting amounts of sheared gDNA on the positive and negative methylated control regions.</strong> MeDIP-seq libraries were prepared from decreasing starting amounts of gDNA (1 μg (green), 50 ng (red), and 10ng (blue)) originating from human blood with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode). IP and corresponding INPUT samples were sequenced on Illumina NovaSeq SP with 2x50 PE reads. The reads were mapped to the human genome (hg19) with bwa and the alignments were loaded into IGV (the tracks use an identical scale). The top IGV figure shows the TSH2B (also known as H2BC1) gene (marked by blue boxes in the bottom track) and its surroundings. The TSH2B gene is coding for a histone variant that does not occur in blood cells, and it is known to be silenced by methylation. Accordingly, we see a high coverage in the vicinity of this gene. The bottom IGV figure shows the GADPH locus (marked by blue boxes in the bottom track) and its surroundings. The GADPH gene is a highly active transcription region and should not be methylated, resulting in no reads accumulation following MeDIP-seq experiment.</p>
<p></p>
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'meta_description' => 'Perform Methylated DNA Immunoprecipitation (MeDIP) to estimate DNA methylation status of your sample using highly specific 5-mC antibody. This kit allows the preparation of cfMeDIP-seq libraries.',
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<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
<p><em><strong>NOTE</strong>: These spike-in controls are the ones directly provided in <span>Diagenode’s </span><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a><span><span> </span>and<span> </span></span><a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a><span>.</span></em></p>',
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'description' => '<div class="row extra-spaced">
<div class="small-12 medium-3 large-3 columns"><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" /></a></center></div>
<div class="small-12 medium-9 large-9 columns">
<h3>Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
</div>
</div>
<div class="row">
<div class="large-12 columns"><span>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</span><br />
<h2></h2>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-seq-package-V2-x10" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>
</div>
</div>
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'meta_description' => 'Methylated DNA immunoprecipitation method is based on the affinity purification of methylated DNA using an antibody directed against 5 methylcytosine (5-mC). ',
'meta_title' => 'Methylated DNA immunoprecipitation(MeDIP) - Dna methylation | Diagenode',
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<div class="large-12 columns">
<div style="text-align: justify;" class="small-12 medium-8 large-8 columns">
<h2>Complete solutions for DNA methylation studies</h2>
<p>Whether you are experienced or new to the field of DNA methylation, Diagenode has everything you need to make your assay as easy and convenient as possible while ensuring consistent data between samples and experiments. Diagenode offers sonication instruments, reagent kits, high quality antibodies, and high-throughput automation capability to address all of your specific DNA methylation analysis requirements.</p>
</div>
<div class="small-12 medium-4 large-4 columns text-center"><a href="../landing-pages/dna-methylation-grant-applications"><img src="https://www.diagenode.com/img/banners/banner-dna-grant.png" alt="" /></a></div>
<div style="text-align: justify;" class="small-12 medium-12 large-12 columns">
<p>DNA methylation was the first discovered epigenetic mark and is the most widely studied topic in epigenetics. <em>In vivo</em>, DNA is methylated following DNA replication and is involved in a number of biological processes including the regulation of imprinted genes, X chromosome inactivation. and tumor suppressor gene silencing in cancer cells. Methylation often occurs in cytosine-guanine rich regions of DNA (CpG islands), which are commonly upstream of promoter regions.</p>
</div>
<div class="small-12 medium-12 large-12 columns"><br /><br />
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#dnamethyl"><i class="fa fa-caret-right"></i> Learn more</a>
<div id="dnamethyl" class="content">5-methylcytosine (5-mC) has been known for a long time as the only modification of DNA for epigenetic regulation. In 2009, however, Kriaucionis discovered a second methylated cytosine, 5-hydroxymethylcytosine (5-hmC). The so-called 6th base, is generated by enzymatic conversion of 5-methylcytosine (5-mC) into 5-hydroxymethylcytosine by the TET family of oxygenases. Early reports suggested that 5-hmC may represent an intermediate of active demethylation in a new pathway which demethylates DNA, converting 5-mC to cytosine. Recent evidence fuel this hypothesis suggesting that further oxidation of the hydroxymethyl group leads to a formyl or carboxyl group followed by either deformylation or decarboxylation. The formyl and carboxyl groups of 5-formylcytosine (5-fC) and 5-carboxylcytosine (5-caC) could be enzymatically removed without excision of the base.
<p class="text-center"><img src="https://www.diagenode.com/img/categories/kits_dna/dna_methylation_variants.jpg" /></p>
</div>
</li>
</ul>
<br />
<h2>Main DNA methylation technologies</h2>
<p style="text-align: justify;">Overview of the <span style="font-weight: 400;">three main approaches for studying DNA methylation.</span></p>
<div class="row">
<ol>
<li style="font-weight: 400;"><span style="font-weight: 400;">Chemical modification with bisulfite – Bisulfite conversion</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Enrichment of methylated DNA (including MeDIP and MBD)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Treatment with methylation-sensitive or dependent restriction enzymes</span></li>
</ol>
<p><span style="font-weight: 400;"> </span></p>
<div class="row">
<table>
<thead>
<tr>
<th></th>
<th>Description</th>
<th width="350">Features</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Bisulfite conversion</strong></td>
<td><span style="font-weight: 400;">Chemical conversion of unmethylated cytosine to uracil. Methylated cytosines are protected from this conversion allowing to determine DNA methylation at single nucleotide resolution.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Single nucleotide resolution</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Quantitative analysis - methylation rate (%)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Gold standard and well studied</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><b>Methylated DNA enrichment</b></td>
<td><span style="font-weight: 400;">(Hydroxy-)Methylated DNA is enriched by using specific antibodies (hMeDIP or MeDIP) or proteins (MBD) that specifically bind methylated CpG sites in fragmented genomic DNA.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Resolution depends on the fragment size of the enriched methylated DNA (300 bp)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Qualitative analysis</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><strong>Restriction enzyme-based digestion</strong></td>
<td><span style="font-weight: 400;">Use of (hydroxy)methylation-sensitive or (hydroxy)methylation-dependent restriction enzymes for DNA methylation analysis at specific sites.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Determination of methylation status is limited by the enzyme recognition site</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Easy to use</span></li>
</ul>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="row"></div>
</div>
</div>
<div class="large-12 columns"></div>
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<p>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</p>
<h2>How it works</h2>
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<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
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'id' => '4989',
'name' => 'Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation',
'authors' => 'Piera Grisolia et al.',
'description' => '<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Background</h3>
<p>Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylated DNA Immunoprecipitation and High-Throughput Sequencing (cfMeDIP-seq), may be informative in characterizing breast cancer in patients with BRCA1/2 germline mutations for early cancer detection and response to therapy.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Methods</h3>
<p>We enrolled 23 BC patients with germline mutation of BRCA1 and BRCA2 genes, 19 healthy controls without BRCA1/2 mutation, and two healthy individuals who carried BRCA1/2 mutations. Blood samples were collected for all study subjects at the diagnosis, and plasma was isolated by centrifugation. Cell-free DNA was extracted from 1 mL of plasma, and cfMeDIP-seq was performed for each sample. Shallow whole genome sequencing was performed on the immuno-precipitated samples. Then, the differentially methylated 300-bp regions (DMRs) between 25 BRCA germline mutation carriers and 19 non-carriers were identified. DMRs were compared with tumor-specific regions from public datasets to perform an unbiased analysis. Finally, two statistical classifiers were trained based on the GLMnet and random forest model to evaluate if the identified DMRs could discriminate BRCA-positive from healthy samples.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Results</h3>
<p>We identified 7,095 hypermethylated and 212 hypomethylated regions in 25 BRCA germline mutation carriers compared to 19 controls. These regions discriminate tumors from healthy samples with high accuracy and sensitivity. We show that the circulating tumor DNA of BRCA1/2 mutant breast cancers is characterized by the hypomethylation of genes involved in DNA repair and cell cycle. We uncovered the TFs associated with these DRMs and identified that proteins of the Erythroblast Transformation Specific (ETS) family are particularly active in the hypermethylated regions. Finally, we assessed that these regions could discriminate between BRCA positives from healthy samples with an AUC of 0.95, a sensitivity of 88%, and a specificity of 94.74%.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Conclusions</h3>
<p>Our study emphasizes the importance of tumor cell-derived DNA methylation in BC, reporting a different methylation profile between patients carrying mutations in BRCA1, BRCA2, and wild-type controls. Our minimally invasive approach could allow early cancer diagnosis, assessment of minimal residual disease, and monitoring of response to therapy.</p>',
'date' => '2024-10-15',
'pmid' => 'https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05734-2',
'doi' => 'https://doi.org/10.1186/s12967-024-05734-2',
'modified' => '2024-10-18 11:43:43',
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'name' => 'Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and </span><em>FOSL1</em><span><span> </span>expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.</span></p>',
'date' => '2024-06-25',
'pmid' => 'https://www.cell.com/cell-reports/fulltext/S2211-1247(24)00678-8',
'doi' => 'https://doi.org/10.1016/j.celrep.2024.114350',
'modified' => '2024-06-24 10:33:29',
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'name' => 'Detecting small cell transformation in patients with advanced EGFR mutant lung adenocarcinoma through epigenomic cfDNA profiling',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free (cf)DNA-based approach to non-invasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3, methylated DNA immunoprecipitation sequencing (MeDIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 ml aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n=24,424), DNA methylation (n=3,298), and chromatin accessibility (n=16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate non-invasive discrimination between patients with EGFRm LUAD versus tSCLC (AUROC=0.82-0.87). A multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 ml of patient plasma.</span></p>',
'date' => '2024-06-24',
'pmid' => 'https://aacrjournals.org/clincancerres/article/doi/10.1158/1078-0432.CCR-24-0466/746147/Detecting-small-cell-transformation-in-patients',
'doi' => 'https://doi.org/10.1158/1078-0432.CCR-24-0466',
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'name' => 'Prostate cancer detection through unbiased capture of methylated cell-free DNA',
'authors' => 'Ermira Lleshi et al.',
'description' => '<p><span>Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localised cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localised and 88.7% (79/89) of metastatic cancer patients in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signalling. This demonstrates the potential of circulating tumour DNA methylation for prostate cancer detection and prognostication.</span></p>',
'date' => '2024-06-20',
'pmid' => 'https://www.sciencedirect.com/science/article/pii/S2589004224015554',
'doi' => 'https://doi.org/10.1016/j.isci.2024.110330',
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'name' => 'Cell-free DNA methylation-defined prognostic subgroups in small celllung cancer identified by leukocyte methylation subtraction',
'authors' => 'Ul Haq Sami et al.',
'description' => '<p>Small cell lung cancer (SCLC) methylome is understudied. Here, we comprehensively profile SCLC using cell-free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq). Cell-free DNA (cfDNA) from plasma of 74 SCLC patients pre-treatment and from 20 non-cancer participants, genomic DNA (gDNA) from peripheral blood leukocytes from the same 74 patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX) underwent cfMeDIP-seq. PeRIpheral blood leukocyte MEthylation (PRIME) subtraction to improve tumour specificity. SCLC cfDNA methylation is distinct from non-cancer but correlates with CDX tumor methylation. PRIME and k-means consensus identified two methylome clusters with prognostic associations that related to axon guidance, neuroactive ligand−receptor interaction, pluripotency of stem cells, and differentially methylated at long noncoding RNA and other repeats features. We comprehensively profiled the SCLC methylome in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.</p>',
'date' => '2022-11-01',
'pmid' => 'https://doi.org/10.1016%2Fj.isci.2022.105487',
'doi' => '10.1016/j.isci.2022.105487',
'modified' => '2022-11-18 12:35:39',
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'name' => 'cfDNA methylome profiling for detection and subtyping of small cell lungcancers.',
'authors' => 'Chemi Francesca et al.',
'description' => '<p>Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.</p>',
'date' => '2022-08-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35941262',
'doi' => '10.1038/s43018-022-00415-9',
'modified' => '2022-09-27 14:46:40',
'created' => '2022-09-08 16:32:20',
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'name' => 'Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA.',
'authors' => 'Shen SY, Burgener JM, Bratman SV, De Carvalho DD',
'description' => '<p>Circulating cell-free DNA (cfDNA) comprises small DNA fragments derived from normal and tumor tissue that are released into the bloodstream. Recently, methylation profiling of cfDNA as a liquid biopsy tool has been gaining prominence due to the presence of tissue-specific markers in cfDNA. We have previously reported cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as a sensitive, low-input, cost-efficient and bisulfite-free approach to profiling DNA methylomes of plasma cfDNA. cfMeDIP-seq is an extension of a previously published MeDIP-seq protocol and is adapted to allow for methylome profiling of samples with low input (ranging from 1 to 10 ng) of DNA, which is enabled by the addition of 'filler DNA' before immunoprecipitation. This protocol is not limited to plasma cfDNA; it can also be applied to other samples that are naturally sheared and at low availability (e.g., urinary cfDNA and cerebrospinal fluid cfDNA), and is potentially applicable to other applications beyond cancer detection, including prenatal diagnostics, cardiology and monitoring of immune response. The protocol presented here should enable any standard molecular laboratory to generate cfMeDIP-seq libraries from plasma cfDNA in ~3-4 d.</p>',
'date' => '2019-08-30',
'pmid' => 'http://www.pubmed.gov/31471598',
'doi' => '10.1038/s41596-019-0202-2',
'modified' => '2019-10-02 17:07:45',
'created' => '2019-10-02 16:16:55',
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'id' => '3560',
'name' => 'DNA methylation and genetic degeneration of the Y chromosome in the dioecious plant Silene latifolia.',
'authors' => 'Rodríguez Lorenzo JL, Hobza R, Vyskot B',
'description' => '<p>BACKGROUND: S. latifolia is a model organism for the study of sex chromosome evolution in plants. Its sex chromosomes include large regions in which recombination became gradually suppressed. The regions tend to expand over time resulting in the formation of evolutionary strata. Non-recombination and later accumulation of repetitive sequences is a putative cause of the size increase in the Y chromosome. Gene decay and accumulation of repetitive DNA are identified as key evolutionary events. Transposons in the X and Y chromosomes are distributed differently and there is a regulation of transposon insertion by DNA methylation of the target sequences, this points to an important role of DNA methylation during sex chromosome evolution in Silene latifolia. The aim of this study was to elucidate whether the reduced expression of the Y allele in S. latifolia is caused by genetic degeneration or if the cause is methylation triggered by transposons and repetitive sequences. RESULTS: Gene expression analysis in S. latifolia males has shown expression bias in both X and Y alleles. To determine whether these differences are caused by genetic degeneration or methylation spread by transposons and repetitive sequences, we selected several sex-linked genes with varying degrees of degeneration and from different evolutionary strata. Immunoprecipitation of methylated DNA (MeDIP) from promoter, exon and intron regions was used and validated through bisulfite sequencing. We found DNA methylation in males, and only in the promoter of genes of stratum I (older). The Y alleles in genes of stratum I were methylation enriched compared to X alleles. There was also abundant and high percentage methylation in the CHH context in most sequences, indicating de novo methylation through the RdDM pathway. CONCLUSIONS: We speculate that TE accumulation and not gene decay is the cause of DNA methylation in the S. latifolia Y sex chromosome with influence on the process of heterochromatinization.</p>',
'date' => '2018-07-16',
'pmid' => 'http://www.pubmed.gov/30012097',
'doi' => '10.1186/s12864-018-4936-y',
'modified' => '2019-03-25 11:22:31',
'created' => '2019-03-21 14:12:08',
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(int) 8 => array(
'id' => '2900',
'name' => 'Protection of CpG islands from DNA methylation is DNA-encoded and evolutionarily conserved',
'authors' => 'Long HK, King HW, Patient RK, Odom DT, Klose RJ',
'description' => '<p>DNA methylation is a repressive epigenetic modification that covers vertebrate genomes. Regions known as CpG islands (CGIs), which are refractory to DNA methylation, are often associated with gene promoters and play central roles in gene regulation. Yet how CGIs in their normal genomic context evade the DNA methylation machinery and whether these mechanisms are evolutionarily conserved remains enigmatic. To address these fundamental questions we exploited a transchromosomic animal model and genomic approaches to understand how the hypomethylated state is formed <em>in vivo</em> and to discover whether mechanisms governing CGI formation are evolutionarily conserved. Strikingly, insertion of a human chromosome into mouse revealed that promoter-associated CGIs are refractory to DNA methylation regardless of host species, demonstrating that DNA sequence plays a central role in specifying the hypomethylated state through evolutionarily conserved mechanisms. In contrast, elements distal to gene promoters exhibited more variable methylation between host species, uncovering a widespread dependence on nucleotide frequency and occupancy of DNA-binding transcription factors in shaping the DNA methylation landscape away from gene promoters. This was exemplified by young CpG rich lineage-restricted repeat sequences that evaded DNA methylation in the absence of co-evolved mechanisms targeting methylation to these sequences, and species specific DNA binding events that protected against DNA methylation in CpG poor regions. Finally, transplantation of mouse chromosomal fragments into the evolutionarily distant zebrafish uncovered the existence of a mechanistically conserved and DNA-encoded logic which shapes CGI formation across vertebrate species.</p>',
'date' => '2016-04-15',
'pmid' => 'http://nar.oxfordjournals.org/content/early/2016/04/15/nar.gkw258.abstract',
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<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
<p><em><strong>NOTE</strong>: These spike-in controls are the ones directly provided in <span>Diagenode’s </span><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a><span><span> </span>and<span> </span></span><a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a><span>.</span></em></p>',
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<p> </p>
<div class="small-12 medium-4 large-4 columns"><center></center><center></center><center></center><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" alt="Click here to read more about MeDIP " caption="false" width="80%" /></a></center></div>
<div class="small-12 medium-8 large-8 columns">
<h3 style="text-align: justify;">Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline" style="text-align: justify;">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
</div>
<p></p>
<p></p>
<p></p>
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<div class="small-12 medium-8 large-8 columns"><br />
<p>Perform <strong>MeDIP</strong> (<strong>Me</strong>thylated <strong>D</strong>NA <strong>I</strong>mmuno<strong>p</strong>recipitation) followed by qPCR or NGS to estimate DNA methylation status of your sample using a highly sensitive 5-methylcytosine antibody. Our MagMeDIP kit contains high quality reagents to get the highest enrichment of methylated DNA with an optimized user-friendly protocol.</p>
</div>
</div>
<h3><span>Features</span></h3>
<ul>
<li>Starting DNA amount: <strong>10 ng – 1 µg</strong></li>
<li>Content: <strong>all reagents included</strong> for DNA extraction, immunoprecipitation (including the 5-mC antibody, spike-in controls and their corresponding qPCR primer pairs) as well as DNA isolation after IP.</li>
<li>Application: <strong>qPCR</strong> and <strong>NGS</strong></li>
<li>Robust method, <strong>superior enrichment</strong>, and easy-to-use protocol</li>
<li><strong>High reproducibility</strong> between replicates and repetitive experiments</li>
<li>Compatible with <strong>all species </strong></li>
</ul>',
'label1' => 'MagMeDIP workflow',
'info1' => '<p>DNA methylation occurs primarily as 5-methylcytosine (5-mC), and the Diagenode MagMeDIP Kit takes advantage of a specific antibody targeting this 5-mC to immunoprecipitate methylated DNA, which can be thereafter directly analyzed by qPCR or Next-Generation Sequencing (NGS).</p>
<h3><span>How it works</span></h3>
<p>In brief, after the cell collection and lysis, the genomic DNA is extracted, sheared, and then denatured. In the next step the antibody directed against 5 methylcytosine and antibody binding beads are used for immunoselection and immunoprecipitation of methylated DNA fragments. Then, the IP’d methylated DNA is isolated and can be used for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<center><img src="https://www.diagenode.com/img/product/kits/MagMeDIP-workflow.png" width="70%" alt="5-methylcytosine" caption="false" /></center>
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'info2' => '<p>The kit MagMeDIP contains all reagents necessary for a complete MeDIP-qPCR workflow. Two MagMeDIP protocols have been validated: for manual processing as well as for automated processing, using the Diagenode’s IP-Star Compact Automated System (please refer to the kit manual).</p>
<ul>
<li><strong>Complete kit</strong> including DNA extraction module, IP antibody and reagents, DNA isolation buffer</li>
<li><strong>Quality control of the IP:</strong> due to methylated and unmethylated DNA spike-in controls and their associated qPCR primers</li>
<li><strong>Easy to use</strong> with user-friendly magnetic beads and rack</li>
<li><strong>Highly validated protocol</strong></li>
<li>Automated protocol supplied</li>
</ul>
<center><img src="https://www.diagenode.com/img/product/kits/fig1-magmedipkit.png" width="85%" alt="Methylated DNA Immunoprecipitation" caption="false" /></center>
<p style="font-size: 0.9em;"><em><strong>Figure 1.</strong> Immunoprecipitation results obtained with Diagenode MagMeDIP Kit</em></p>
<p style="font-size: 0.9em;">MeDIP assays were performed manually using 1 µg or 50 ng gDNA from blood cells with the MagMeDIP kit (Diagenode). The IP was performed with the Methylated and Unmethylated spike-in controls included in the kit, together with the human DNA samples. The DNA was isolated/purified using DIB. Afterwards, qPCR was performed using the primer pairs included in this kit.</p>
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'info3' => '<p>For DNA methylation analysis on the whole genome, MagMeDIP kit can be coupled with Next-Generation Sequencing. To perform MeDIP-sequencing we recommend the following strategy:</p>
<ul style="list-style-type: circle;">
<li>Choose a library preparation solution which is compatible with the starting amount of DNA you are planning to use (from 10 ng to 1 μg). It can be a home-made solution or a commercial one.</li>
<li>Choose the indexing system that fits your needs considering the following features:</li>
<ul>
<ul>
<ul>
<li>Single-indexing, combinatorial dual-indexing or unique dual-indexing</li>
<li>Number of barcodes</li>
<li>Full-length adaptors containing the barcodes or barcoding at the final amplification step</li>
<li>Presence / absence of Unique Molecular Identifiers (for PCR duplicates removal)</li>
</ul>
</ul>
</ul>
<li>Standard library preparation protocols are compatible with double-stranded DNA only, therefore the first steps of the library preparation (end repair, A-tailing, adaptor ligation and clean-up) will have to be performed on sheared DNA, before the IP.</li>
</ul>
<p style="padding-left: 30px;"><strong>CAUTION:</strong> As the immunoprecipitation step occurs at the middle of the library preparation workflow, single-tube solutions for library preparation are usually not compatible with MeDIP-sequencing.</p>
<ul style="list-style-type: circle;">
<li>For DNA isolation after the IP, we recommend using the <a href="https://www.diagenode.com/en/p/ipure-kit-v2-x24" title="IPure kit v2">IPure kit v2</a> (available separately, Cat. No. C03010014) instead of DNA isolation Buffer.</li>
</ul>
<ul style="list-style-type: circle;">
<li>Perform library amplification after the DNA isolation following the standard protocol of the chosen library preparation solution.</li>
</ul>
<h3><span>MeDIP-seq workflow</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/MeDIP-seq-workflow.png" width="110%" alt="MagMeDIP qPCR Kit x10 workflow" caption="false" /></center>
<h3><span>Example of results</span></h3>
<center><img src="https://www.diagenode.com/img/product/kits/medip-specificity.png" alt="MagMeDIP qPCR Kit Result" caption="false" width="951" height="488" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 1. qPCR analysis of external spike-in DNA controls (methylated and unmethylated) after IP.</strong> Samples were prepared using 1μg – 100ng -10ng sheared human gDNA with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-saturation-analysis.png" alt=" MagMeDIP kit " caption="false" width="951" height="461" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 2. Saturation analysis.</strong> Clean reads were aligned to the human genome (hg19) using Burrows-Wheeler aligner (BWA) algorithm after which duplicated and unmapped reads were removed resulting in a mapping efficiency >98% for all samples. Quality and validity check of the mapped MeDIP-seq data was performed using MEDIPS R package. Saturation plots show that all sets of reads have sufficient complexity and depth to saturate the coverage profile of the reference genome and that this is reproducible between replicates and repetitive experiments (data shown for 50 ng gDNA input: left panel = replicate a, right panel = replicate b).</p>
<p></p>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/medip-libraries-prep.png" alt="MagMeDIP x10 " caption="false" width="951" height="708" /></center>
<p></p>
<p style="font-size: 0.9em;"><strong>Figure 3. Sequencing profiles of MeDIP-seq libraries prepared from different starting amounts of sheared gDNA on the positive and negative methylated control regions.</strong> MeDIP-seq libraries were prepared from decreasing starting amounts of gDNA (1 μg (green), 50 ng (red), and 10ng (blue)) originating from human blood with the MagMeDIP kit (Diagenode) and a commercially available library prep kit. DNA isolation after IP has been performed with IPure kit V2 (Diagenode). IP and corresponding INPUT samples were sequenced on Illumina NovaSeq SP with 2x50 PE reads. The reads were mapped to the human genome (hg19) with bwa and the alignments were loaded into IGV (the tracks use an identical scale). The top IGV figure shows the TSH2B (also known as H2BC1) gene (marked by blue boxes in the bottom track) and its surroundings. The TSH2B gene is coding for a histone variant that does not occur in blood cells, and it is known to be silenced by methylation. Accordingly, we see a high coverage in the vicinity of this gene. The bottom IGV figure shows the GADPH locus (marked by blue boxes in the bottom track) and its surroundings. The GADPH gene is a highly active transcription region and should not be methylated, resulting in no reads accumulation following MeDIP-seq experiment.</p>
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<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
<p><em><strong>NOTE</strong>: These spike-in controls are the ones directly provided in <span>Diagenode’s </span><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a><span><span> </span>and<span> </span></span><a href="https://www.diagenode.com/en/p/auto-magmedip-kit-x48-48-rxns" target="_blank">Auto MagMeDIP qPCR Kit</a><span>.</span></em></p>',
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<div class="small-12 medium-3 large-3 columns"><center><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank"><img src="https://www.diagenode.com/img/banners/banner-nature-publication-580.png" /></a></center></div>
<div class="small-12 medium-9 large-9 columns">
<h3>Sensitive tumour detection and classification using plasma cell-free DNA methylomes<br /><a href="https://www.ncbi.nlm.nih.gov/pubmed/30429608" target="_blank">Read the publication</a></h3>
<h3 class="c-article-title u-h1" data-test="article-title" itemprop="name headline">Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA<br /><a href="https://www.nature.com/articles/s41596-019-0202-2" target="_blank" title="cfMeDIP-seq Nature Method">Read the method</a></h3>
</div>
</div>
<div class="row">
<div class="large-12 columns"><span>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</span><br />
<h2></h2>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-seq-package-V2-x10" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>
</div>
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<div class="large-12 columns">
<div style="text-align: justify;" class="small-12 medium-8 large-8 columns">
<h2>Complete solutions for DNA methylation studies</h2>
<p>Whether you are experienced or new to the field of DNA methylation, Diagenode has everything you need to make your assay as easy and convenient as possible while ensuring consistent data between samples and experiments. Diagenode offers sonication instruments, reagent kits, high quality antibodies, and high-throughput automation capability to address all of your specific DNA methylation analysis requirements.</p>
</div>
<div class="small-12 medium-4 large-4 columns text-center"><a href="../landing-pages/dna-methylation-grant-applications"><img src="https://www.diagenode.com/img/banners/banner-dna-grant.png" alt="" /></a></div>
<div style="text-align: justify;" class="small-12 medium-12 large-12 columns">
<p>DNA methylation was the first discovered epigenetic mark and is the most widely studied topic in epigenetics. <em>In vivo</em>, DNA is methylated following DNA replication and is involved in a number of biological processes including the regulation of imprinted genes, X chromosome inactivation. and tumor suppressor gene silencing in cancer cells. Methylation often occurs in cytosine-guanine rich regions of DNA (CpG islands), which are commonly upstream of promoter regions.</p>
</div>
<div class="small-12 medium-12 large-12 columns"><br /><br />
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#dnamethyl"><i class="fa fa-caret-right"></i> Learn more</a>
<div id="dnamethyl" class="content">5-methylcytosine (5-mC) has been known for a long time as the only modification of DNA for epigenetic regulation. In 2009, however, Kriaucionis discovered a second methylated cytosine, 5-hydroxymethylcytosine (5-hmC). The so-called 6th base, is generated by enzymatic conversion of 5-methylcytosine (5-mC) into 5-hydroxymethylcytosine by the TET family of oxygenases. Early reports suggested that 5-hmC may represent an intermediate of active demethylation in a new pathway which demethylates DNA, converting 5-mC to cytosine. Recent evidence fuel this hypothesis suggesting that further oxidation of the hydroxymethyl group leads to a formyl or carboxyl group followed by either deformylation or decarboxylation. The formyl and carboxyl groups of 5-formylcytosine (5-fC) and 5-carboxylcytosine (5-caC) could be enzymatically removed without excision of the base.
<p class="text-center"><img src="https://www.diagenode.com/img/categories/kits_dna/dna_methylation_variants.jpg" /></p>
</div>
</li>
</ul>
<br />
<h2>Main DNA methylation technologies</h2>
<p style="text-align: justify;">Overview of the <span style="font-weight: 400;">three main approaches for studying DNA methylation.</span></p>
<div class="row">
<ol>
<li style="font-weight: 400;"><span style="font-weight: 400;">Chemical modification with bisulfite – Bisulfite conversion</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Enrichment of methylated DNA (including MeDIP and MBD)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Treatment with methylation-sensitive or dependent restriction enzymes</span></li>
</ol>
<p><span style="font-weight: 400;"> </span></p>
<div class="row">
<table>
<thead>
<tr>
<th></th>
<th>Description</th>
<th width="350">Features</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Bisulfite conversion</strong></td>
<td><span style="font-weight: 400;">Chemical conversion of unmethylated cytosine to uracil. Methylated cytosines are protected from this conversion allowing to determine DNA methylation at single nucleotide resolution.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Single nucleotide resolution</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Quantitative analysis - methylation rate (%)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Gold standard and well studied</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><b>Methylated DNA enrichment</b></td>
<td><span style="font-weight: 400;">(Hydroxy-)Methylated DNA is enriched by using specific antibodies (hMeDIP or MeDIP) or proteins (MBD) that specifically bind methylated CpG sites in fragmented genomic DNA.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Resolution depends on the fragment size of the enriched methylated DNA (300 bp)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Qualitative analysis</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Compatible with automation</span></li>
</ul>
</td>
</tr>
<tr>
<td><strong>Restriction enzyme-based digestion</strong></td>
<td><span style="font-weight: 400;">Use of (hydroxy)methylation-sensitive or (hydroxy)methylation-dependent restriction enzymes for DNA methylation analysis at specific sites.</span></td>
<td>
<ul style="list-style-type: circle;">
<li style="font-weight: 400;"><span style="font-weight: 400;">Determination of methylation status is limited by the enzyme recognition site</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Easy to use</span></li>
</ul>
</td>
</tr>
</tbody>
</table>
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<div class="row"></div>
</div>
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<p>The Methylated DNA Immunoprecipitation is based on the affinity purification of methylated and hydroxymethylated DNA using, respectively, an antibody directed against 5-methylcytosine (5-mC) in the case of MeDIP or 5-hydroxymethylcytosine (5-hmC) in the case of hMeDIP.</p>
<h2>How it works</h2>
<p>In brief, Methyl DNA IP is performed as follows: Genomic DNA from cultured cells or tissues is prepared, sheared, and then denatured. Then, immunoselection and immunoprecipitation can take place using the antibody directed against 5 methylcytosine and antibody binding beads. After isolation and purification is performed, the IP’d methylated DNA is ready for any subsequent analysis as qPCR, amplification, hybridization on microarrays or next generation sequencing.</p>
<h2>Applications</h2>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> qPCR analysis</a></div>
<div align="center"><a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns" class="center alert radius button"> NGS analysis </a></div>
<h2>Advantages</h2>
<ul style="font-size: 19px;" class="nobullet">
<li><i class="fa fa-arrow-circle-right"></i> <strong>Unaffected</strong> DNA</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>High enrichment</strong> yield</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>Robust</strong> & <strong>reproducible</strong> techniques</li>
<li><i class="fa fa-arrow-circle-right"></i> <strong>NGS</strong> compatible</li>
</ul>
<h2></h2>',
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'name' => 'Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation',
'authors' => 'Piera Grisolia et al.',
'description' => '<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Background</h3>
<p>Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylated DNA Immunoprecipitation and High-Throughput Sequencing (cfMeDIP-seq), may be informative in characterizing breast cancer in patients with BRCA1/2 germline mutations for early cancer detection and response to therapy.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Methods</h3>
<p>We enrolled 23 BC patients with germline mutation of BRCA1 and BRCA2 genes, 19 healthy controls without BRCA1/2 mutation, and two healthy individuals who carried BRCA1/2 mutations. Blood samples were collected for all study subjects at the diagnosis, and plasma was isolated by centrifugation. Cell-free DNA was extracted from 1 mL of plasma, and cfMeDIP-seq was performed for each sample. Shallow whole genome sequencing was performed on the immuno-precipitated samples. Then, the differentially methylated 300-bp regions (DMRs) between 25 BRCA germline mutation carriers and 19 non-carriers were identified. DMRs were compared with tumor-specific regions from public datasets to perform an unbiased analysis. Finally, two statistical classifiers were trained based on the GLMnet and random forest model to evaluate if the identified DMRs could discriminate BRCA-positive from healthy samples.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Results</h3>
<p>We identified 7,095 hypermethylated and 212 hypomethylated regions in 25 BRCA germline mutation carriers compared to 19 controls. These regions discriminate tumors from healthy samples with high accuracy and sensitivity. We show that the circulating tumor DNA of BRCA1/2 mutant breast cancers is characterized by the hypomethylation of genes involved in DNA repair and cell cycle. We uncovered the TFs associated with these DRMs and identified that proteins of the Erythroblast Transformation Specific (ETS) family are particularly active in the hypermethylated regions. Finally, we assessed that these regions could discriminate between BRCA positives from healthy samples with an AUC of 0.95, a sensitivity of 88%, and a specificity of 94.74%.</p>
<h3 class="c-article__sub-heading" data-test="abstract-sub-heading">Conclusions</h3>
<p>Our study emphasizes the importance of tumor cell-derived DNA methylation in BC, reporting a different methylation profile between patients carrying mutations in BRCA1, BRCA2, and wild-type controls. Our minimally invasive approach could allow early cancer diagnosis, assessment of minimal residual disease, and monitoring of response to therapy.</p>',
'date' => '2024-10-15',
'pmid' => 'https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05734-2',
'doi' => 'https://doi.org/10.1186/s12967-024-05734-2',
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'name' => 'Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and </span><em>FOSL1</em><span><span> </span>expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.</span></p>',
'date' => '2024-06-25',
'pmid' => 'https://www.cell.com/cell-reports/fulltext/S2211-1247(24)00678-8',
'doi' => 'https://doi.org/10.1016/j.celrep.2024.114350',
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'name' => 'Detecting small cell transformation in patients with advanced EGFR mutant lung adenocarcinoma through epigenomic cfDNA profiling',
'authors' => 'Talal El Zarif et al.',
'description' => '<p><span>Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free (cf)DNA-based approach to non-invasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3, methylated DNA immunoprecipitation sequencing (MeDIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 ml aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n=24,424), DNA methylation (n=3,298), and chromatin accessibility (n=16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate non-invasive discrimination between patients with EGFRm LUAD versus tSCLC (AUROC=0.82-0.87). A multi-analyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 ml of patient plasma.</span></p>',
'date' => '2024-06-24',
'pmid' => 'https://aacrjournals.org/clincancerres/article/doi/10.1158/1078-0432.CCR-24-0466/746147/Detecting-small-cell-transformation-in-patients',
'doi' => 'https://doi.org/10.1158/1078-0432.CCR-24-0466',
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'name' => 'Prostate cancer detection through unbiased capture of methylated cell-free DNA',
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'description' => '<p><span>Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localised cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localised and 88.7% (79/89) of metastatic cancer patients in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signalling. This demonstrates the potential of circulating tumour DNA methylation for prostate cancer detection and prognostication.</span></p>',
'date' => '2024-06-20',
'pmid' => 'https://www.sciencedirect.com/science/article/pii/S2589004224015554',
'doi' => 'https://doi.org/10.1016/j.isci.2024.110330',
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'name' => 'Cell-free DNA methylation-defined prognostic subgroups in small celllung cancer identified by leukocyte methylation subtraction',
'authors' => 'Ul Haq Sami et al.',
'description' => '<p>Small cell lung cancer (SCLC) methylome is understudied. Here, we comprehensively profile SCLC using cell-free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq). Cell-free DNA (cfDNA) from plasma of 74 SCLC patients pre-treatment and from 20 non-cancer participants, genomic DNA (gDNA) from peripheral blood leukocytes from the same 74 patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX) underwent cfMeDIP-seq. PeRIpheral blood leukocyte MEthylation (PRIME) subtraction to improve tumour specificity. SCLC cfDNA methylation is distinct from non-cancer but correlates with CDX tumor methylation. PRIME and k-means consensus identified two methylome clusters with prognostic associations that related to axon guidance, neuroactive ligand−receptor interaction, pluripotency of stem cells, and differentially methylated at long noncoding RNA and other repeats features. We comprehensively profiled the SCLC methylome in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.</p>',
'date' => '2022-11-01',
'pmid' => 'https://doi.org/10.1016%2Fj.isci.2022.105487',
'doi' => '10.1016/j.isci.2022.105487',
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'name' => 'cfDNA methylome profiling for detection and subtyping of small cell lungcancers.',
'authors' => 'Chemi Francesca et al.',
'description' => '<p>Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.</p>',
'date' => '2022-08-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35941262',
'doi' => '10.1038/s43018-022-00415-9',
'modified' => '2022-09-27 14:46:40',
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'name' => 'Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA.',
'authors' => 'Shen SY, Burgener JM, Bratman SV, De Carvalho DD',
'description' => '<p>Circulating cell-free DNA (cfDNA) comprises small DNA fragments derived from normal and tumor tissue that are released into the bloodstream. Recently, methylation profiling of cfDNA as a liquid biopsy tool has been gaining prominence due to the presence of tissue-specific markers in cfDNA. We have previously reported cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as a sensitive, low-input, cost-efficient and bisulfite-free approach to profiling DNA methylomes of plasma cfDNA. cfMeDIP-seq is an extension of a previously published MeDIP-seq protocol and is adapted to allow for methylome profiling of samples with low input (ranging from 1 to 10 ng) of DNA, which is enabled by the addition of 'filler DNA' before immunoprecipitation. This protocol is not limited to plasma cfDNA; it can also be applied to other samples that are naturally sheared and at low availability (e.g., urinary cfDNA and cerebrospinal fluid cfDNA), and is potentially applicable to other applications beyond cancer detection, including prenatal diagnostics, cardiology and monitoring of immune response. The protocol presented here should enable any standard molecular laboratory to generate cfMeDIP-seq libraries from plasma cfDNA in ~3-4 d.</p>',
'date' => '2019-08-30',
'pmid' => 'http://www.pubmed.gov/31471598',
'doi' => '10.1038/s41596-019-0202-2',
'modified' => '2019-10-02 17:07:45',
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'name' => 'DNA methylation and genetic degeneration of the Y chromosome in the dioecious plant Silene latifolia.',
'authors' => 'Rodríguez Lorenzo JL, Hobza R, Vyskot B',
'description' => '<p>BACKGROUND: S. latifolia is a model organism for the study of sex chromosome evolution in plants. Its sex chromosomes include large regions in which recombination became gradually suppressed. The regions tend to expand over time resulting in the formation of evolutionary strata. Non-recombination and later accumulation of repetitive sequences is a putative cause of the size increase in the Y chromosome. Gene decay and accumulation of repetitive DNA are identified as key evolutionary events. Transposons in the X and Y chromosomes are distributed differently and there is a regulation of transposon insertion by DNA methylation of the target sequences, this points to an important role of DNA methylation during sex chromosome evolution in Silene latifolia. The aim of this study was to elucidate whether the reduced expression of the Y allele in S. latifolia is caused by genetic degeneration or if the cause is methylation triggered by transposons and repetitive sequences. RESULTS: Gene expression analysis in S. latifolia males has shown expression bias in both X and Y alleles. To determine whether these differences are caused by genetic degeneration or methylation spread by transposons and repetitive sequences, we selected several sex-linked genes with varying degrees of degeneration and from different evolutionary strata. Immunoprecipitation of methylated DNA (MeDIP) from promoter, exon and intron regions was used and validated through bisulfite sequencing. We found DNA methylation in males, and only in the promoter of genes of stratum I (older). The Y alleles in genes of stratum I were methylation enriched compared to X alleles. There was also abundant and high percentage methylation in the CHH context in most sequences, indicating de novo methylation through the RdDM pathway. CONCLUSIONS: We speculate that TE accumulation and not gene decay is the cause of DNA methylation in the S. latifolia Y sex chromosome with influence on the process of heterochromatinization.</p>',
'date' => '2018-07-16',
'pmid' => 'http://www.pubmed.gov/30012097',
'doi' => '10.1186/s12864-018-4936-y',
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'name' => 'Protection of CpG islands from DNA methylation is DNA-encoded and evolutionarily conserved',
'authors' => 'Long HK, King HW, Patient RK, Odom DT, Klose RJ',
'description' => '<p>DNA methylation is a repressive epigenetic modification that covers vertebrate genomes. Regions known as CpG islands (CGIs), which are refractory to DNA methylation, are often associated with gene promoters and play central roles in gene regulation. Yet how CGIs in their normal genomic context evade the DNA methylation machinery and whether these mechanisms are evolutionarily conserved remains enigmatic. To address these fundamental questions we exploited a transchromosomic animal model and genomic approaches to understand how the hypomethylated state is formed <em>in vivo</em> and to discover whether mechanisms governing CGI formation are evolutionarily conserved. Strikingly, insertion of a human chromosome into mouse revealed that promoter-associated CGIs are refractory to DNA methylation regardless of host species, demonstrating that DNA sequence plays a central role in specifying the hypomethylated state through evolutionarily conserved mechanisms. In contrast, elements distal to gene promoters exhibited more variable methylation between host species, uncovering a widespread dependence on nucleotide frequency and occupancy of DNA-binding transcription factors in shaping the DNA methylation landscape away from gene promoters. This was exemplified by young CpG rich lineage-restricted repeat sequences that evaded DNA methylation in the absence of co-evolved mechanisms targeting methylation to these sequences, and species specific DNA binding events that protected against DNA methylation in CpG poor regions. Finally, transplantation of mouse chromosomal fragments into the evolutionarily distant zebrafish uncovered the existence of a mechanistically conserved and DNA-encoded logic which shapes CGI formation across vertebrate species.</p>',
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<p>The DNA methylation control package V2 includes one methylated and one unmethylated spike-in controls together with their corresponding qPCR primer sets that can be added to the DNA sample of interest for any methylation profiling experiment (e.g. with Diagenode's <a href="https://www.diagenode.com/en/p/premium-rrbs-kit-V2-x24">Premium RRBS v2 Kit</a> or <a href="https://www.diagenode.com/en/p/magmedip-kit-x48-48-rxns">MagMeDIP Kit</a>).</p>
<p>Those spike-in controls have been produced using synthetic oligonucleotides and are not homologous to any model species. Therefore, they will not interfere with the DNA sample of interest.</p>
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'name' => 'DNA Methylation control package SDS ES es',
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'url' => 'files/SDS/DNA/SDS-C02040012-DNA_Methylation_control_package-ES-es-GHS_1_0.pdf',
'countries' => 'ES',
'modified' => '2023-01-10 16:57:22',
'created' => '2023-01-10 16:57:22',
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'id' => '5052',
'product_id' => '1898',
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)
)
$publication = array(
'id' => '2900',
'name' => 'Protection of CpG islands from DNA methylation is DNA-encoded and evolutionarily conserved',
'authors' => 'Long HK, King HW, Patient RK, Odom DT, Klose RJ',
'description' => '<p>DNA methylation is a repressive epigenetic modification that covers vertebrate genomes. Regions known as CpG islands (CGIs), which are refractory to DNA methylation, are often associated with gene promoters and play central roles in gene regulation. Yet how CGIs in their normal genomic context evade the DNA methylation machinery and whether these mechanisms are evolutionarily conserved remains enigmatic. To address these fundamental questions we exploited a transchromosomic animal model and genomic approaches to understand how the hypomethylated state is formed <em>in vivo</em> and to discover whether mechanisms governing CGI formation are evolutionarily conserved. Strikingly, insertion of a human chromosome into mouse revealed that promoter-associated CGIs are refractory to DNA methylation regardless of host species, demonstrating that DNA sequence plays a central role in specifying the hypomethylated state through evolutionarily conserved mechanisms. In contrast, elements distal to gene promoters exhibited more variable methylation between host species, uncovering a widespread dependence on nucleotide frequency and occupancy of DNA-binding transcription factors in shaping the DNA methylation landscape away from gene promoters. This was exemplified by young CpG rich lineage-restricted repeat sequences that evaded DNA methylation in the absence of co-evolved mechanisms targeting methylation to these sequences, and species specific DNA binding events that protected against DNA methylation in CpG poor regions. Finally, transplantation of mouse chromosomal fragments into the evolutionarily distant zebrafish uncovered the existence of a mechanistically conserved and DNA-encoded logic which shapes CGI formation across vertebrate species.</p>',
'date' => '2016-04-15',
'pmid' => 'http://nar.oxfordjournals.org/content/early/2016/04/15/nar.gkw258.abstract',
'doi' => '10.1093/nar/gkw258',
'modified' => '2016-04-29 13:25:22',
'created' => '2016-04-29 13:25:22',
'ProductsPublication' => array(
'id' => '1179',
'product_id' => '1898',
'publication_id' => '2900'
)
)
$externalLink = ' <a href="http://nar.oxfordjournals.org/content/early/2016/04/15/nar.gkw258.abstract" target="_blank"><i class="fa fa-external-link"></i></a>'include - APP/View/Products/view.ctp, line 755
View::_evaluate() - CORE/Cake/View/View.php, line 971
View::_render() - CORE/Cake/View/View.php, line 933
View::render() - CORE/Cake/View/View.php, line 473
Controller::render() - CORE/Cake/Controller/Controller.php, line 963
ProductsController::slug() - APP/Controller/ProductsController.php, line 1052
ReflectionMethod::invokeArgs() - [internal], line ??
Controller::invokeAction() - CORE/Cake/Controller/Controller.php, line 491
Dispatcher::_invoke() - CORE/Cake/Routing/Dispatcher.php, line 193
Dispatcher::dispatch() - CORE/Cake/Routing/Dispatcher.php, line 167
[main] - APP/webroot/index.php, line 118
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