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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may also need:</p>
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<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
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<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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'name' => 'Tagmentase datasheet',
'description' => '<p>Diagenode Tagmentase is a hyperactive transposase with the ability to cut DNA and insert sequences of interest into any target DNA in one step. This enzyme is not loaded with DNA oligos.</p>',
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'name' => 'Transposome assembly using Diagenode Tagmentase',
'description' => '<p><span>Transposome assembly using Diagenode Tagmentase protocol</span></p>',
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'type' => 'Protocol',
'url' => 'files/protocols/PRO-Transposome-Assembly-V2.pdf',
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'id' => '4936',
'name' => 'Technical considerations for cost-effective transposon directed insertion-site sequencing (TraDIS)',
'authors' => 'Kyono Y. et al.',
'description' => '<p><span>Transposon directed insertion-site sequencing (TraDIS), a variant of transposon insertion sequencing commonly known as Tn-Seq, is a high-throughput assay that defines essential bacterial genes across diverse growth conditions. However, the variability between laboratory environments often requires laborious, time-consuming modifications to its protocol. In this technical study, we aimed to refine the protocol by identifying key parameters that can impact the complexity of mutant libraries. Firstly, we discovered that adjusting electroporation parameters including transposome concentration, transposome assembly conditions, and cell densities can significantly improve the recovery of viable mutants for different </span><i>Escherichia coli</i><span><span> </span>strains. Secondly, we found that post-electroporation conditions, such as recovery time and the use of different mediums for selecting mutants may also impact the complexity of viable mutants in the library. Finally, we developed a simplified sequencing library preparation workflow based on a Nextera-TruSeq hybrid design where ~ 80% of sequenced reads correspond to transposon-DNA junctions. The technical improvements presented in our study aim to streamline TraDIS protocols, making this powerful technique more accessible for a wider scientific audience.</span></p>',
'date' => '2024-03-21',
'pmid' => 'https://www.nature.com/articles/s41598-024-57537-6',
'doi' => 'https://doi.org/10.1038/s41598-024-57537-6',
'modified' => '2024-04-10 16:29:00',
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'id' => '4916',
'name' => 'Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy in pancreatic ductal adenocarcinoma',
'authors' => 'Kim IK et al.',
'description' => '<p><span>Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (</span><i>Irf6</i><span>), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.</span></p>',
'date' => '2024-02-20',
'pmid' => 'https://www.nature.com/articles/s41467-024-46048-7',
'doi' => 'https://doi.org/10.1038/s41467-024-46048-7',
'modified' => '2024-02-26 13:39:36',
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'id' => '4897',
'name' => 'CompDuplex: Accurate detection of somatic mutations by duplex-seq with comprehensive genome coverage',
'authors' => 'Muchun Niu et al.',
'description' => '<div class="_dvu6yd">
<section class="_fz2017">
<section class="_protocols-io-draft _lw40b6">
<section class="_protocols-io-draft-app _protocols-io-draft-app-reader _awu6vp">
<section class="_protocols-io-draft-app-editor protocols-io-draft-app-editor-reader">
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<div data-offset-key="c6pdl-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="c6pdl-0-0"><span data-text="true">Somatic mutations continuously accumulate in the human genome, posing vulnerabilities towards aging and increased risk of various diseases. However, accurate detection of somatic mutations at the whole genome scale is still challenging. By tagging and independently sequencing the two complementary strands of DNA, the recent development of duplex-sequencing methods has greatly improved the detection accuracy, however, the limited genome coverage and the compromised compatibility with existing sequencing platforms have constrained the broad applications of these methods.</span></span></div>
</div>
<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="cbilg-0-0">
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<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="bud8b-0-0">
<div data-offset-key="bud8b-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="bud8b-0-0"><span data-text="true">To overcome these technical challenges, here we developed a duplex sequencing method with comprehensive genome coverage, which we refer to as CompDuplex-seq. The streamlined chemistry of CompDuplex assay allows efficient generation of libraries readily compatible with standard Illumina 2x150 paired-end sequencing. In addition, we validated the accuracy of somatic mutation calling and comprehensive genome coverage of CompDuplex by profiling a single-cell expanded clone. To summarize, CompDuplex chemistry supports genome-wide coverage while maintaining high accuracy, which we believe will facilitate the whole genome characterization of somatic mosaicism in various biological systems.</span></span></div>
</div>
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'date' => '2024-01-25',
'pmid' => 'https://www.protocols.io/view/compduplex-accurate-detection-of-somatic-mutations-kxygx3x4og8j/v1',
'doi' => 'dx.doi.org/10.17504/protocols.io.kxygx3x4og8j/v1',
'modified' => '2024-01-29 10:08:44',
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'id' => '4893',
'name' => 'Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans',
'authors' => 'Yuanqing Feng et al.',
'description' => '<p><span>Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for </span><i>MFSD12</i><span>,<span> </span></span><i>HMG20B</i><span>,<span> </span></span><i>OCA2</i><span>,<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span>,<span> </span></span><i>TRPS1</i><span>,<span> </span></span><i>BLOC1S6</i><span><span> </span>and<span> </span></span><i>CYB561A3</i><span><span> </span>that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an<span> </span></span><i>OCA2</i><span><span> </span>enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span><span> </span>and<span> </span></span><i>TRPS1</i><span>, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified<span> </span></span><i>CYB561A3</i><span><span> </span>as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.</span></p>',
'date' => '2024-01-10',
'pmid' => 'https://www.nature.com/articles/s41588-023-01626-1',
'doi' => 'https://doi.org/10.1038/s41588-023-01626-1',
'modified' => '2024-01-15 10:24:09',
'created' => '2024-01-15 10:24:09',
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(int) 4 => array(
'id' => '4879',
'name' => 'A Type II-B Cas9 nuclease with minimized off-targets and reduced chromosomal translocations in vivo',
'authors' => 'Bestas B. et al.',
'description' => '<div id="Abs1" lang="en" class="tsec sec">
<div>
<p id="Par1" class="p p-first-last"><em>Streptococcus pyogenes</em><span> </span>Cas9 (SpCas9) and derived enzymes are widely used as genome editors, but their promiscuous nuclease activity often induces undesired mutations and chromosomal rearrangements. Several strategies for mapping off-target effects have emerged, but they suffer from limited sensitivity. To increase the detection sensitivity, we develop an off-target assessment workflow that uses Duplex Sequencing. The strategy increases sensitivity by one order of magnitude, identifying previously unknown SpCas9’s off-target mutations in the humanized<span> </span><em>PCSK9</em><span> </span>mouse model. To reduce off-target risks, we perform a bioinformatic search and identify a high-fidelity Cas9 variant of the II-B subfamily from<span> </span><em>Parasutterella secunda</em><span> </span>(PsCas9). PsCas9 shows improved specificity as compared to SpCas9 across multiple tested sites, both in vitro and in vivo, including the<span> </span><em>PCSK9</em><span> </span>site. In the future, while PsCas9 will offer an alternative to SpCas9 for research and clinical use, the Duplex Sequencing workflow will enable a more sensitive assessment of Cas9 editing outcomes.</p>
</div>
<div class="sec"><strong class="kwd-title">Subject terms:<span> </span></strong><span class="kwd-text">Genetic engineering, Gene therapy, CRISPR-Cas9 genome editing</span></div>
</div>
<div id="Abs2" lang="en" class="tsec sec"></div>',
'date' => '2023-09-06',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482872/',
'doi' => '10.1038/s41467-023-41240-7',
'modified' => '2023-11-10 15:00:50',
'created' => '2023-11-10 15:00:50',
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(int) 5 => array(
'id' => '4869',
'name' => 'Combined Analysis of mRNA Expression and Open Chromatin in Microglia',
'authors' => 'Scholz R.et al.',
'description' => '<p><span>The advance of single-cell RNA-sequencing technologies in the past years has enabled unprecedented insights into the complexity and heterogeneity of microglial cell states in the homeostatic and diseased brain. This includes rather complex proteomic, metabolomic, morphological, transcriptomic, and epigenetic adaptations to external stimuli and challenges resulting in a novel concept of core microglia properties and functions. To uncover the regulatory programs facilitating the rapid transcriptomic adaptation in response to changes in the local microenvironment, the accessibility of gene bodies and gene regulatory elements can be assessed. Here, we describe the application of a previously published method for simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq) on microglia nuclei isolated from frozen mouse brain tissue.</span></p>',
'date' => '2023-08-29',
'pmid' => 'https://link.springer.com/protocol/10.1007/978-1-0716-3437-0_35',
'doi' => '10.1007/978-1-0716-3437-0_35',
'modified' => '2023-08-31 11:25:45',
'created' => '2023-08-31 11:18:53',
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(int) 6 => array(
'id' => '4877',
'name' => 'Volumetric imaging of an intact organism by a distributed molecular network',
'authors' => 'Nianchao Qian and Joshua A Weinstein',
'description' => '<p><span>Lymphatic, nervous, and tumoral tissues, among others, exhibit physiology that emerges from three-dimensional interactions between genetically unique cells. A technology capable of volumetrically imaging transcriptomes, genotypes, and morphologies in a single de novo measurement would therefore provide a critical view into the biological complexity of living systems. Here we achieve this by extending DNA microscopy, an imaging modality that encodes a spatio-genetic map of a specimen via a massive distributed network of DNA molecules inside it, to three dimensions and multiple length scales in developing zebrafish embryos.</span></p>',
'date' => '2023-08-14',
'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/37645933/',
'doi' => '10.1101/2023.08.11.553025',
'modified' => '2023-11-10 14:45:12',
'created' => '2023-11-10 14:45:12',
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(int) 7 => array(
'id' => '4781',
'name' => 'Spatial epigenome-transcriptome co-profiling of mammalian tissues.',
'authors' => 'Zhang D. et al.',
'description' => '<p>Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.</p>',
'date' => '2023-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36922587',
'doi' => '10.1038/s41586-023-05795-1',
'modified' => '2023-06-13 09:17:26',
'created' => '2023-05-05 12:34:24',
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(int) 8 => array(
'id' => '4757',
'name' => 'Analyzing genomic and epigenetic profiles in single cells by hybridtransposase (scGET-seq).',
'authors' => 'Cittaro D. et al.',
'description' => '<p>scGET-seq simultaneously profiles euchromatin and heterochromatin. scGET-seq exploits the concurrent action of transposase Tn5 and its hybrid form TnH, which targets H3K9me3 domains. Here we present a step-by-step protocol to profile single cells by scGET-seq using a 10× Chromium Controller. We describe steps for transposomes preparation and validation. We detail nuclei preparation and transposition, followed by encapsulation, library preparation, sequencing, and data analysis. For complete details on the use and execution of this protocol, please refer to Tedesco et al. (2022) and de Pretis and Cittaro (2022)..</p>',
'date' => '2023-03-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/37000619',
'doi' => '10.1016/j.xpro.2023.102176',
'modified' => '2023-04-17 09:04:55',
'created' => '2023-04-14 13:41:22',
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(int) 9 => array(
'id' => '4548',
'name' => 'Imaging Chromatin Accessibility by Assay ofTransposase-Accessible Chromatin with Visualization.',
'authors' => 'Miyanari Yusuke',
'description' => '<p>Chromatin accessibility is one of the fundamental structures regulating genome functions including transcription and DNA repair. Recent technological advantages to analyze chromatin accessibility begun to explore the dynamics of local chromatin structures. Here I describe protocols for Assay of Transposase-Accessible Chromatin with Visualization (ATAC-see), which allows us to analyze subnuclear localization of accessible chromatin and quantify accessible chromatin at single-cell level.</p>',
'date' => '2023-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36173568',
'doi' => '10.1007/978-1-0716-2724-2_7',
'modified' => '2022-11-24 10:28:08',
'created' => '2022-11-24 08:49:52',
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[maximum depth reached]
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(int) 10 => array(
'id' => '4654',
'name' => 'Mouse kidney nuclear isolation and library preparation for single-cell combinatorial indexing RNA sequencing',
'authors' => 'Li Haikuo and Humphreys Benjamin D.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq3) enables high-throughput single-nucleus transcriptomic profiling of multiple samples in one experiment. Here, we describe an optimized protocol of mouse kidney nuclei isolation and sci-RNA-seq3 library preparation. The use of a dounce tissue homogenizer enables nuclei extraction with high yield. Fixed nuclei are processed for sci-RNA-seq3, and self-loaded transposome Tn5 is used for tagmentation in library generation. The step-by-step protocol allows researchers to generate scalable single-cell transcriptomic data with common laboratory supplies at low cost.</p>',
'date' => '2022-12-01',
'pmid' => 'https://doi.org/10.1016%2Fj.xpro.2022.101904',
'doi' => '10.1016/j.xpro.2022.101904',
'modified' => '2023-08-01 14:23:49',
'created' => '2023-02-21 09:59:46',
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[maximum depth reached]
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),
(int) 11 => array(
'id' => '4546',
'name' => 'Optimized single-nucleus transcriptional profiling by combinatorialindexing.',
'authors' => 'Martin Beth K et al.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here, we report a simplified, optimized version of the sci-RNA-seq protocol with three rounds of split-pool indexing that is faster, more robust and more sensitive and has a higher yield than the original protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2-3 d, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole-organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a 'Tiny-Sci' protocol for experiments in which input material is very limited.</p>',
'date' => '2022-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36261634',
'doi' => '10.1038/s41596-022-00752-0',
'modified' => '2022-11-24 10:26:25',
'created' => '2022-11-24 08:49:52',
'ProductsPublication' => array(
[maximum depth reached]
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(int) 12 => array(
'id' => '4412',
'name' => 'Spatial profiling of chromatin accessibility in mouse and human tissues',
'authors' => 'Yanxiang Deng et al.',
'description' => '<p><span>Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 1" title="Perkel, J. M. Starfish enterprise: finding RNA patterns in single cells. Nature 572, 549–551 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR1" id="ref-link-section-d163865808e834">1</a></sup><span>. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. Y. & Zhuang, X. W. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR2" id="ref-link-section-d163865808e838">2</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Eng, C. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235–239 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR3" id="ref-link-section-d163865808e838_1">3</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR4" id="ref-link-section-d163865808e838_2">4</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e841">5</a></sup><span>, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 6" title="Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR6" id="ref-link-section-d163865808e845">6</a></sup><span><span> </span>and microfluidic deterministic barcoding</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e849">5</a></sup><span>. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.</span></p>',
'date' => '2022-08-05',
'pmid' => 'https://www.nature.com/articles/s41586-022-05094-1',
'doi' => 'https://doi.org/10.1038/s41586-022-05094-1',
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<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070011), available separately.</p>
<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may also need:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x-1ml">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
</ul>
<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may need also:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
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<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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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
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<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070011), available separately.</p>
<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may also need:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x-1ml">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
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<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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'description' => '<p><span>Transposon directed insertion-site sequencing (TraDIS), a variant of transposon insertion sequencing commonly known as Tn-Seq, is a high-throughput assay that defines essential bacterial genes across diverse growth conditions. However, the variability between laboratory environments often requires laborious, time-consuming modifications to its protocol. In this technical study, we aimed to refine the protocol by identifying key parameters that can impact the complexity of mutant libraries. Firstly, we discovered that adjusting electroporation parameters including transposome concentration, transposome assembly conditions, and cell densities can significantly improve the recovery of viable mutants for different </span><i>Escherichia coli</i><span><span> </span>strains. Secondly, we found that post-electroporation conditions, such as recovery time and the use of different mediums for selecting mutants may also impact the complexity of viable mutants in the library. Finally, we developed a simplified sequencing library preparation workflow based on a Nextera-TruSeq hybrid design where ~ 80% of sequenced reads correspond to transposon-DNA junctions. The technical improvements presented in our study aim to streamline TraDIS protocols, making this powerful technique more accessible for a wider scientific audience.</span></p>',
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'description' => '<p><span>Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (</span><i>Irf6</i><span>), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.</span></p>',
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'description' => '<div class="_dvu6yd">
<section class="_fz2017">
<section class="_protocols-io-draft _lw40b6">
<section class="_protocols-io-draft-app _protocols-io-draft-app-reader _awu6vp">
<section class="_protocols-io-draft-app-editor protocols-io-draft-app-editor-reader">
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<div data-offset-key="c6pdl-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="c6pdl-0-0"><span data-text="true">Somatic mutations continuously accumulate in the human genome, posing vulnerabilities towards aging and increased risk of various diseases. However, accurate detection of somatic mutations at the whole genome scale is still challenging. By tagging and independently sequencing the two complementary strands of DNA, the recent development of duplex-sequencing methods has greatly improved the detection accuracy, however, the limited genome coverage and the compromised compatibility with existing sequencing platforms have constrained the broad applications of these methods.</span></span></div>
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<div data-offset-key="bud8b-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="bud8b-0-0"><span data-text="true">To overcome these technical challenges, here we developed a duplex sequencing method with comprehensive genome coverage, which we refer to as CompDuplex-seq. The streamlined chemistry of CompDuplex assay allows efficient generation of libraries readily compatible with standard Illumina 2x150 paired-end sequencing. In addition, we validated the accuracy of somatic mutation calling and comprehensive genome coverage of CompDuplex by profiling a single-cell expanded clone. To summarize, CompDuplex chemistry supports genome-wide coverage while maintaining high accuracy, which we believe will facilitate the whole genome characterization of somatic mosaicism in various biological systems.</span></span></div>
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'description' => '<p><span>Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for </span><i>MFSD12</i><span>,<span> </span></span><i>HMG20B</i><span>,<span> </span></span><i>OCA2</i><span>,<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span>,<span> </span></span><i>TRPS1</i><span>,<span> </span></span><i>BLOC1S6</i><span><span> </span>and<span> </span></span><i>CYB561A3</i><span><span> </span>that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an<span> </span></span><i>OCA2</i><span><span> </span>enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span><span> </span>and<span> </span></span><i>TRPS1</i><span>, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified<span> </span></span><i>CYB561A3</i><span><span> </span>as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.</span></p>',
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'name' => 'A Type II-B Cas9 nuclease with minimized off-targets and reduced chromosomal translocations in vivo',
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<div>
<p id="Par1" class="p p-first-last"><em>Streptococcus pyogenes</em><span> </span>Cas9 (SpCas9) and derived enzymes are widely used as genome editors, but their promiscuous nuclease activity often induces undesired mutations and chromosomal rearrangements. Several strategies for mapping off-target effects have emerged, but they suffer from limited sensitivity. To increase the detection sensitivity, we develop an off-target assessment workflow that uses Duplex Sequencing. The strategy increases sensitivity by one order of magnitude, identifying previously unknown SpCas9’s off-target mutations in the humanized<span> </span><em>PCSK9</em><span> </span>mouse model. To reduce off-target risks, we perform a bioinformatic search and identify a high-fidelity Cas9 variant of the II-B subfamily from<span> </span><em>Parasutterella secunda</em><span> </span>(PsCas9). PsCas9 shows improved specificity as compared to SpCas9 across multiple tested sites, both in vitro and in vivo, including the<span> </span><em>PCSK9</em><span> </span>site. In the future, while PsCas9 will offer an alternative to SpCas9 for research and clinical use, the Duplex Sequencing workflow will enable a more sensitive assessment of Cas9 editing outcomes.</p>
</div>
<div class="sec"><strong class="kwd-title">Subject terms:<span> </span></strong><span class="kwd-text">Genetic engineering, Gene therapy, CRISPR-Cas9 genome editing</span></div>
</div>
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'description' => '<p><span>The advance of single-cell RNA-sequencing technologies in the past years has enabled unprecedented insights into the complexity and heterogeneity of microglial cell states in the homeostatic and diseased brain. This includes rather complex proteomic, metabolomic, morphological, transcriptomic, and epigenetic adaptations to external stimuli and challenges resulting in a novel concept of core microglia properties and functions. To uncover the regulatory programs facilitating the rapid transcriptomic adaptation in response to changes in the local microenvironment, the accessibility of gene bodies and gene regulatory elements can be assessed. Here, we describe the application of a previously published method for simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq) on microglia nuclei isolated from frozen mouse brain tissue.</span></p>',
'date' => '2023-08-29',
'pmid' => 'https://link.springer.com/protocol/10.1007/978-1-0716-3437-0_35',
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'description' => '<p><span>Lymphatic, nervous, and tumoral tissues, among others, exhibit physiology that emerges from three-dimensional interactions between genetically unique cells. A technology capable of volumetrically imaging transcriptomes, genotypes, and morphologies in a single de novo measurement would therefore provide a critical view into the biological complexity of living systems. Here we achieve this by extending DNA microscopy, an imaging modality that encodes a spatio-genetic map of a specimen via a massive distributed network of DNA molecules inside it, to three dimensions and multiple length scales in developing zebrafish embryos.</span></p>',
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'name' => 'Spatial epigenome-transcriptome co-profiling of mammalian tissues.',
'authors' => 'Zhang D. et al.',
'description' => '<p>Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.</p>',
'date' => '2023-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36922587',
'doi' => '10.1038/s41586-023-05795-1',
'modified' => '2023-06-13 09:17:26',
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'id' => '4757',
'name' => 'Analyzing genomic and epigenetic profiles in single cells by hybridtransposase (scGET-seq).',
'authors' => 'Cittaro D. et al.',
'description' => '<p>scGET-seq simultaneously profiles euchromatin and heterochromatin. scGET-seq exploits the concurrent action of transposase Tn5 and its hybrid form TnH, which targets H3K9me3 domains. Here we present a step-by-step protocol to profile single cells by scGET-seq using a 10× Chromium Controller. We describe steps for transposomes preparation and validation. We detail nuclei preparation and transposition, followed by encapsulation, library preparation, sequencing, and data analysis. For complete details on the use and execution of this protocol, please refer to Tedesco et al. (2022) and de Pretis and Cittaro (2022)..</p>',
'date' => '2023-03-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/37000619',
'doi' => '10.1016/j.xpro.2023.102176',
'modified' => '2023-04-17 09:04:55',
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(int) 9 => array(
'id' => '4548',
'name' => 'Imaging Chromatin Accessibility by Assay ofTransposase-Accessible Chromatin with Visualization.',
'authors' => 'Miyanari Yusuke',
'description' => '<p>Chromatin accessibility is one of the fundamental structures regulating genome functions including transcription and DNA repair. Recent technological advantages to analyze chromatin accessibility begun to explore the dynamics of local chromatin structures. Here I describe protocols for Assay of Transposase-Accessible Chromatin with Visualization (ATAC-see), which allows us to analyze subnuclear localization of accessible chromatin and quantify accessible chromatin at single-cell level.</p>',
'date' => '2023-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36173568',
'doi' => '10.1007/978-1-0716-2724-2_7',
'modified' => '2022-11-24 10:28:08',
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'id' => '4654',
'name' => 'Mouse kidney nuclear isolation and library preparation for single-cell combinatorial indexing RNA sequencing',
'authors' => 'Li Haikuo and Humphreys Benjamin D.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq3) enables high-throughput single-nucleus transcriptomic profiling of multiple samples in one experiment. Here, we describe an optimized protocol of mouse kidney nuclei isolation and sci-RNA-seq3 library preparation. The use of a dounce tissue homogenizer enables nuclei extraction with high yield. Fixed nuclei are processed for sci-RNA-seq3, and self-loaded transposome Tn5 is used for tagmentation in library generation. The step-by-step protocol allows researchers to generate scalable single-cell transcriptomic data with common laboratory supplies at low cost.</p>',
'date' => '2022-12-01',
'pmid' => 'https://doi.org/10.1016%2Fj.xpro.2022.101904',
'doi' => '10.1016/j.xpro.2022.101904',
'modified' => '2023-08-01 14:23:49',
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'id' => '4546',
'name' => 'Optimized single-nucleus transcriptional profiling by combinatorialindexing.',
'authors' => 'Martin Beth K et al.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here, we report a simplified, optimized version of the sci-RNA-seq protocol with three rounds of split-pool indexing that is faster, more robust and more sensitive and has a higher yield than the original protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2-3 d, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole-organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a 'Tiny-Sci' protocol for experiments in which input material is very limited.</p>',
'date' => '2022-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36261634',
'doi' => '10.1038/s41596-022-00752-0',
'modified' => '2022-11-24 10:26:25',
'created' => '2022-11-24 08:49:52',
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(int) 12 => array(
'id' => '4412',
'name' => 'Spatial profiling of chromatin accessibility in mouse and human tissues',
'authors' => 'Yanxiang Deng et al.',
'description' => '<p><span>Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 1" title="Perkel, J. M. Starfish enterprise: finding RNA patterns in single cells. Nature 572, 549–551 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR1" id="ref-link-section-d163865808e834">1</a></sup><span>. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. Y. & Zhuang, X. W. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR2" id="ref-link-section-d163865808e838">2</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Eng, C. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235–239 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR3" id="ref-link-section-d163865808e838_1">3</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR4" id="ref-link-section-d163865808e838_2">4</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e841">5</a></sup><span>, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 6" title="Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR6" id="ref-link-section-d163865808e845">6</a></sup><span><span> </span>and microfluidic deterministic barcoding</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e849">5</a></sup><span>. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.</span></p>',
'date' => '2022-08-05',
'pmid' => 'https://www.nature.com/articles/s41586-022-05094-1',
'doi' => 'https://doi.org/10.1038/s41586-022-05094-1',
'modified' => '2022-08-23 11:54:39',
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(int) 13 => array(
'id' => '4389',
'name' => 'Spatially resolved epigenome-transcriptome co-profiling of mammalian tissues at the cellular level',
'authors' => 'Fan Rong et al.',
'description' => '<p>Emerging spatial technologies including spatial transcriptomics and spatial epigenomics are becoming powerful tools for profiling cellular states in the tissue context. However, current methods capture only one layer of omics information at a time precluding the possibility to examine the mechanistic relationship across the cental dogma of molecular biology. Here, we present two spatial multi-omics technologies for spatially resolved genome-wide joint mapping of epigenome and transcriptome by coprofiling chromatin accessibility and gene expression (spatial-ATAC-RNA-seq) or histone modification and gene expression (spatial-CUT\&Tag-RNA-seq) on the same tissue section at a resolution near single cells. They were applied to embryonic and neonatal mouse brain as well as adult human brain to map how epigenetic states or modifications regulate cell type and dynamics in tissue. Although distinct tissue features were identified by either spatial epigenome or spatial transcriptome alone with high concordance, we observed their differential roles in defining cell states. In general, epigenetic state proceeds the development of transcriptional phenotype in relation to epigenetic lineage priming. We also observed high expression canonical markers such as PROX1 in the granular cell layer of the human hippocampus showed low chromatin accessibility that corresponded to a low level of RNA turnover rate, highlighting a divergent need for open chromatin or transcription to control cell identity and dynamics. Spatial epigenome-transcriptome co-profiling is a highly informative tool to study the mechanism of gene expression regulation in tissue and may enable a wide range of applications in life science and biomedical research.</p>',
'date' => '2022-06-13',
'pmid' => 'https://www.researchsquare.com/article/rs-1728747/v1',
'doi' => '10.21203/rs.3.rs-1728747/v1',
'modified' => '2022-08-11 15:20:45',
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'id' => '4101',
'name' => 'Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues',
'authors' => 'Liguo Zhang et al.',
'description' => '<p>Prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and recurrence of PCR-positive tests have been widely reported in patients after recovery from COVID-19, but some of these patients do not appear to shed infectious virus. We investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the DNA of human cells in culture and that transcription of the integrated sequences might account for some of the positive PCR tests seen in patients. In support of this hypothesis, we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral–host chimeric transcripts. The integration and transcription of viral sequences may thus contribute to the detection of viral RNA by PCR in patients after infection and clinical recovery. Because we have detected only subgenomic sequences derived mainly from the 3′ end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from the integrated subgenomic SARS-CoV-2 sequences.</p>',
'date' => '2021-05-25',
'pmid' => 'https://www.pnas.org/content/118/21/e2105968118',
'doi' => 'https://doi.org/10.1073/pnas.2105968118',
'modified' => '2021-06-24 09:49:41',
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'name' => 'T-RHEX-RNAseq – A tagmentation-based, rRNA blocked, randomhexamer primed RNAseq method for generating stranded RNAseq librariesdirectly from very low numbers of lysed cells',
'authors' => 'Gustafsson Charlotte et al.',
'description' => '<p>Background: RNA sequencing has become the mainstay for studies of gene expression. Still, analysis of rare cells with random hexamer priming – to allow analysis of a broader range of transcripts – remains challenging. Results: We here describe a tagmentation-based, rRNA blocked, random hexamer primed RNAseq approach (T-RHEX-RNAseq) for generating stranded RNAseq libraries from very low numbers of FACS sorted cells without RNA purification steps. Conclusion: T-RHEX-RNAseq provides an easy-to-use, time efficient and automation compatible method for generating stranded RNAseq libraries from rare cells.</p>',
'date' => '0000-00-00',
'pmid' => 'https://doi.org/10.1101%2F2022.10.20.513000',
'doi' => '10.1101/2022.10.20.513000',
'modified' => '2023-03-13 10:57:55',
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'author' => 'Rebekka Scholz et al. Combined Analysis of mRNA Expression and Open Chromatin in Microglia. Methods Mol Biol. 2024;2713:543-571. ',
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'name' => 'Tagmentase (Tn5 transposase) - unloaded',
'description' => '<div class="extra-spaced"><center><img alt="Tagmentase (Tn5 transposase)" src="https://www.diagenode.com/img/banners/banner-tagmentase.jpg" caption="false" width="787" height="236" /></center></div>
<div class="row">
<div class="small-12 medium-8 large-8 columns"><br />
<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070011), available separately.</p>
<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
</div>
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<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may also need:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x-1ml">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
</ul>
<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<div class="small-12 medium-12 large-12 columns">
<p><img alt="Tn5 transposase" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure-1a.jpg" style="display: block; margin-left: auto; margin-right: auto;" width="653" height="282" /></p>
<p><img alt="Tagmentase Tn5 transposase" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure-1b.jpg" style="display: block; margin-left: auto; margin-right: auto;" width="645" height="278" /></p>
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</div>
<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
</div>
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<div class="row">
<div class="small-12 medium-12 large-12 columns"><center><img alt="Tn5 transposase perfect for NGS" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure2.jpg" width="754" height="492" /></center></div>
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<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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ProductsController::slug() - APP/Controller/ProductsController.php, line 1052
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'description' => '<p><span>Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (</span><i>Irf6</i><span>), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.</span></p>',
'date' => '2024-02-20',
'pmid' => 'https://www.nature.com/articles/s41467-024-46048-7',
'doi' => 'https://doi.org/10.1038/s41467-024-46048-7',
'modified' => '2024-02-26 13:39:36',
'created' => '2024-02-26 13:39:36',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 2 => array(
'id' => '4897',
'name' => 'CompDuplex: Accurate detection of somatic mutations by duplex-seq with comprehensive genome coverage',
'authors' => 'Muchun Niu et al.',
'description' => '<div class="_dvu6yd">
<section class="_fz2017">
<section class="_protocols-io-draft _lw40b6">
<section class="_protocols-io-draft-app _protocols-io-draft-app-reader _awu6vp">
<section class="_protocols-io-draft-app-editor protocols-io-draft-app-editor-reader">
<div class="DraftEditor-root">
<div class="DraftEditor-editorContainer">
<div aria-label="" class="public-DraftEditor-content" contenteditable="false" spellcheck="false">
<div data-contents="true">
<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="c6pdl-0-0">
<div data-offset-key="c6pdl-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="c6pdl-0-0"><span data-text="true">Somatic mutations continuously accumulate in the human genome, posing vulnerabilities towards aging and increased risk of various diseases. However, accurate detection of somatic mutations at the whole genome scale is still challenging. By tagging and independently sequencing the two complementary strands of DNA, the recent development of duplex-sequencing methods has greatly improved the detection accuracy, however, the limited genome coverage and the compromised compatibility with existing sequencing platforms have constrained the broad applications of these methods.</span></span></div>
</div>
<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="cbilg-0-0">
<div data-offset-key="cbilg-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="cbilg-0-0"> </span></div>
</div>
<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="bud8b-0-0">
<div data-offset-key="bud8b-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="bud8b-0-0"><span data-text="true">To overcome these technical challenges, here we developed a duplex sequencing method with comprehensive genome coverage, which we refer to as CompDuplex-seq. The streamlined chemistry of CompDuplex assay allows efficient generation of libraries readily compatible with standard Illumina 2x150 paired-end sequencing. In addition, we validated the accuracy of somatic mutation calling and comprehensive genome coverage of CompDuplex by profiling a single-cell expanded clone. To summarize, CompDuplex chemistry supports genome-wide coverage while maintaining high accuracy, which we believe will facilitate the whole genome characterization of somatic mosaicism in various biological systems.</span></span></div>
</div>
</div>
</div>
</div>
</div>
<span id="placeholder-desc-draft-abstract"></span></section>
</section>
</section>
</section>
</div>
<section class="_e296pg">
<div id="step-sticky-section" class="_j60wwa">
<div class="_1oxfq56"></div>
<div class="_wcbn92"></div>
</div>
</section>',
'date' => '2024-01-25',
'pmid' => 'https://www.protocols.io/view/compduplex-accurate-detection-of-somatic-mutations-kxygx3x4og8j/v1',
'doi' => 'dx.doi.org/10.17504/protocols.io.kxygx3x4og8j/v1',
'modified' => '2024-01-29 10:08:44',
'created' => '2024-01-29 10:08:44',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 3 => array(
'id' => '4893',
'name' => 'Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans',
'authors' => 'Yuanqing Feng et al.',
'description' => '<p><span>Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for </span><i>MFSD12</i><span>,<span> </span></span><i>HMG20B</i><span>,<span> </span></span><i>OCA2</i><span>,<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span>,<span> </span></span><i>TRPS1</i><span>,<span> </span></span><i>BLOC1S6</i><span><span> </span>and<span> </span></span><i>CYB561A3</i><span><span> </span>that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an<span> </span></span><i>OCA2</i><span><span> </span>enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span><span> </span>and<span> </span></span><i>TRPS1</i><span>, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified<span> </span></span><i>CYB561A3</i><span><span> </span>as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.</span></p>',
'date' => '2024-01-10',
'pmid' => 'https://www.nature.com/articles/s41588-023-01626-1',
'doi' => 'https://doi.org/10.1038/s41588-023-01626-1',
'modified' => '2024-01-15 10:24:09',
'created' => '2024-01-15 10:24:09',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 4 => array(
'id' => '4879',
'name' => 'A Type II-B Cas9 nuclease with minimized off-targets and reduced chromosomal translocations in vivo',
'authors' => 'Bestas B. et al.',
'description' => '<div id="Abs1" lang="en" class="tsec sec">
<div>
<p id="Par1" class="p p-first-last"><em>Streptococcus pyogenes</em><span> </span>Cas9 (SpCas9) and derived enzymes are widely used as genome editors, but their promiscuous nuclease activity often induces undesired mutations and chromosomal rearrangements. Several strategies for mapping off-target effects have emerged, but they suffer from limited sensitivity. To increase the detection sensitivity, we develop an off-target assessment workflow that uses Duplex Sequencing. The strategy increases sensitivity by one order of magnitude, identifying previously unknown SpCas9’s off-target mutations in the humanized<span> </span><em>PCSK9</em><span> </span>mouse model. To reduce off-target risks, we perform a bioinformatic search and identify a high-fidelity Cas9 variant of the II-B subfamily from<span> </span><em>Parasutterella secunda</em><span> </span>(PsCas9). PsCas9 shows improved specificity as compared to SpCas9 across multiple tested sites, both in vitro and in vivo, including the<span> </span><em>PCSK9</em><span> </span>site. In the future, while PsCas9 will offer an alternative to SpCas9 for research and clinical use, the Duplex Sequencing workflow will enable a more sensitive assessment of Cas9 editing outcomes.</p>
</div>
<div class="sec"><strong class="kwd-title">Subject terms:<span> </span></strong><span class="kwd-text">Genetic engineering, Gene therapy, CRISPR-Cas9 genome editing</span></div>
</div>
<div id="Abs2" lang="en" class="tsec sec"></div>',
'date' => '2023-09-06',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482872/',
'doi' => '10.1038/s41467-023-41240-7',
'modified' => '2023-11-10 15:00:50',
'created' => '2023-11-10 15:00:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 5 => array(
'id' => '4869',
'name' => 'Combined Analysis of mRNA Expression and Open Chromatin in Microglia',
'authors' => 'Scholz R.et al.',
'description' => '<p><span>The advance of single-cell RNA-sequencing technologies in the past years has enabled unprecedented insights into the complexity and heterogeneity of microglial cell states in the homeostatic and diseased brain. This includes rather complex proteomic, metabolomic, morphological, transcriptomic, and epigenetic adaptations to external stimuli and challenges resulting in a novel concept of core microglia properties and functions. To uncover the regulatory programs facilitating the rapid transcriptomic adaptation in response to changes in the local microenvironment, the accessibility of gene bodies and gene regulatory elements can be assessed. Here, we describe the application of a previously published method for simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq) on microglia nuclei isolated from frozen mouse brain tissue.</span></p>',
'date' => '2023-08-29',
'pmid' => 'https://link.springer.com/protocol/10.1007/978-1-0716-3437-0_35',
'doi' => '10.1007/978-1-0716-3437-0_35',
'modified' => '2023-08-31 11:25:45',
'created' => '2023-08-31 11:18:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 6 => array(
'id' => '4877',
'name' => 'Volumetric imaging of an intact organism by a distributed molecular network',
'authors' => 'Nianchao Qian and Joshua A Weinstein',
'description' => '<p><span>Lymphatic, nervous, and tumoral tissues, among others, exhibit physiology that emerges from three-dimensional interactions between genetically unique cells. A technology capable of volumetrically imaging transcriptomes, genotypes, and morphologies in a single de novo measurement would therefore provide a critical view into the biological complexity of living systems. Here we achieve this by extending DNA microscopy, an imaging modality that encodes a spatio-genetic map of a specimen via a massive distributed network of DNA molecules inside it, to three dimensions and multiple length scales in developing zebrafish embryos.</span></p>',
'date' => '2023-08-14',
'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/37645933/',
'doi' => '10.1101/2023.08.11.553025',
'modified' => '2023-11-10 14:45:12',
'created' => '2023-11-10 14:45:12',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 7 => array(
'id' => '4781',
'name' => 'Spatial epigenome-transcriptome co-profiling of mammalian tissues.',
'authors' => 'Zhang D. et al.',
'description' => '<p>Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.</p>',
'date' => '2023-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36922587',
'doi' => '10.1038/s41586-023-05795-1',
'modified' => '2023-06-13 09:17:26',
'created' => '2023-05-05 12:34:24',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 8 => array(
'id' => '4757',
'name' => 'Analyzing genomic and epigenetic profiles in single cells by hybridtransposase (scGET-seq).',
'authors' => 'Cittaro D. et al.',
'description' => '<p>scGET-seq simultaneously profiles euchromatin and heterochromatin. scGET-seq exploits the concurrent action of transposase Tn5 and its hybrid form TnH, which targets H3K9me3 domains. Here we present a step-by-step protocol to profile single cells by scGET-seq using a 10× Chromium Controller. We describe steps for transposomes preparation and validation. We detail nuclei preparation and transposition, followed by encapsulation, library preparation, sequencing, and data analysis. For complete details on the use and execution of this protocol, please refer to Tedesco et al. (2022) and de Pretis and Cittaro (2022)..</p>',
'date' => '2023-03-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/37000619',
'doi' => '10.1016/j.xpro.2023.102176',
'modified' => '2023-04-17 09:04:55',
'created' => '2023-04-14 13:41:22',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 9 => array(
'id' => '4548',
'name' => 'Imaging Chromatin Accessibility by Assay ofTransposase-Accessible Chromatin with Visualization.',
'authors' => 'Miyanari Yusuke',
'description' => '<p>Chromatin accessibility is one of the fundamental structures regulating genome functions including transcription and DNA repair. Recent technological advantages to analyze chromatin accessibility begun to explore the dynamics of local chromatin structures. Here I describe protocols for Assay of Transposase-Accessible Chromatin with Visualization (ATAC-see), which allows us to analyze subnuclear localization of accessible chromatin and quantify accessible chromatin at single-cell level.</p>',
'date' => '2023-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36173568',
'doi' => '10.1007/978-1-0716-2724-2_7',
'modified' => '2022-11-24 10:28:08',
'created' => '2022-11-24 08:49:52',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 10 => array(
'id' => '4654',
'name' => 'Mouse kidney nuclear isolation and library preparation for single-cell combinatorial indexing RNA sequencing',
'authors' => 'Li Haikuo and Humphreys Benjamin D.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq3) enables high-throughput single-nucleus transcriptomic profiling of multiple samples in one experiment. Here, we describe an optimized protocol of mouse kidney nuclei isolation and sci-RNA-seq3 library preparation. The use of a dounce tissue homogenizer enables nuclei extraction with high yield. Fixed nuclei are processed for sci-RNA-seq3, and self-loaded transposome Tn5 is used for tagmentation in library generation. The step-by-step protocol allows researchers to generate scalable single-cell transcriptomic data with common laboratory supplies at low cost.</p>',
'date' => '2022-12-01',
'pmid' => 'https://doi.org/10.1016%2Fj.xpro.2022.101904',
'doi' => '10.1016/j.xpro.2022.101904',
'modified' => '2023-08-01 14:23:49',
'created' => '2023-02-21 09:59:46',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 11 => array(
'id' => '4546',
'name' => 'Optimized single-nucleus transcriptional profiling by combinatorialindexing.',
'authors' => 'Martin Beth K et al.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here, we report a simplified, optimized version of the sci-RNA-seq protocol with three rounds of split-pool indexing that is faster, more robust and more sensitive and has a higher yield than the original protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2-3 d, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole-organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a 'Tiny-Sci' protocol for experiments in which input material is very limited.</p>',
'date' => '2022-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36261634',
'doi' => '10.1038/s41596-022-00752-0',
'modified' => '2022-11-24 10:26:25',
'created' => '2022-11-24 08:49:52',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 12 => array(
'id' => '4412',
'name' => 'Spatial profiling of chromatin accessibility in mouse and human tissues',
'authors' => 'Yanxiang Deng et al.',
'description' => '<p><span>Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 1" title="Perkel, J. M. Starfish enterprise: finding RNA patterns in single cells. Nature 572, 549–551 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR1" id="ref-link-section-d163865808e834">1</a></sup><span>. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. Y. & Zhuang, X. W. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR2" id="ref-link-section-d163865808e838">2</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Eng, C. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235–239 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR3" id="ref-link-section-d163865808e838_1">3</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR4" id="ref-link-section-d163865808e838_2">4</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e841">5</a></sup><span>, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 6" title="Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR6" id="ref-link-section-d163865808e845">6</a></sup><span><span> </span>and microfluidic deterministic barcoding</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e849">5</a></sup><span>. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.</span></p>',
'date' => '2022-08-05',
'pmid' => 'https://www.nature.com/articles/s41586-022-05094-1',
'doi' => 'https://doi.org/10.1038/s41586-022-05094-1',
'modified' => '2022-08-23 11:54:39',
'created' => '2022-08-23 11:54:39',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 13 => array(
'id' => '4389',
'name' => 'Spatially resolved epigenome-transcriptome co-profiling of mammalian tissues at the cellular level',
'authors' => 'Fan Rong et al.',
'description' => '<p>Emerging spatial technologies including spatial transcriptomics and spatial epigenomics are becoming powerful tools for profiling cellular states in the tissue context. However, current methods capture only one layer of omics information at a time precluding the possibility to examine the mechanistic relationship across the cental dogma of molecular biology. Here, we present two spatial multi-omics technologies for spatially resolved genome-wide joint mapping of epigenome and transcriptome by coprofiling chromatin accessibility and gene expression (spatial-ATAC-RNA-seq) or histone modification and gene expression (spatial-CUT\&Tag-RNA-seq) on the same tissue section at a resolution near single cells. They were applied to embryonic and neonatal mouse brain as well as adult human brain to map how epigenetic states or modifications regulate cell type and dynamics in tissue. Although distinct tissue features were identified by either spatial epigenome or spatial transcriptome alone with high concordance, we observed their differential roles in defining cell states. In general, epigenetic state proceeds the development of transcriptional phenotype in relation to epigenetic lineage priming. We also observed high expression canonical markers such as PROX1 in the granular cell layer of the human hippocampus showed low chromatin accessibility that corresponded to a low level of RNA turnover rate, highlighting a divergent need for open chromatin or transcription to control cell identity and dynamics. Spatial epigenome-transcriptome co-profiling is a highly informative tool to study the mechanism of gene expression regulation in tissue and may enable a wide range of applications in life science and biomedical research.</p>',
'date' => '2022-06-13',
'pmid' => 'https://www.researchsquare.com/article/rs-1728747/v1',
'doi' => '10.21203/rs.3.rs-1728747/v1',
'modified' => '2022-08-11 15:20:45',
'created' => '2022-08-11 12:14:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 14 => array(
'id' => '4101',
'name' => 'Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues',
'authors' => 'Liguo Zhang et al.',
'description' => '<p>Prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and recurrence of PCR-positive tests have been widely reported in patients after recovery from COVID-19, but some of these patients do not appear to shed infectious virus. We investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the DNA of human cells in culture and that transcription of the integrated sequences might account for some of the positive PCR tests seen in patients. In support of this hypothesis, we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral–host chimeric transcripts. The integration and transcription of viral sequences may thus contribute to the detection of viral RNA by PCR in patients after infection and clinical recovery. Because we have detected only subgenomic sequences derived mainly from the 3′ end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from the integrated subgenomic SARS-CoV-2 sequences.</p>',
'date' => '2021-05-25',
'pmid' => 'https://www.pnas.org/content/118/21/e2105968118',
'doi' => 'https://doi.org/10.1073/pnas.2105968118',
'modified' => '2021-06-24 09:49:41',
'created' => '2021-06-24 09:45:16',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 15 => array(
'id' => '4641',
'name' => 'T-RHEX-RNAseq – A tagmentation-based, rRNA blocked, randomhexamer primed RNAseq method for generating stranded RNAseq librariesdirectly from very low numbers of lysed cells',
'authors' => 'Gustafsson Charlotte et al.',
'description' => '<p>Background: RNA sequencing has become the mainstay for studies of gene expression. Still, analysis of rare cells with random hexamer priming – to allow analysis of a broader range of transcripts – remains challenging. Results: We here describe a tagmentation-based, rRNA blocked, random hexamer primed RNAseq approach (T-RHEX-RNAseq) for generating stranded RNAseq libraries from very low numbers of FACS sorted cells without RNA purification steps. Conclusion: T-RHEX-RNAseq provides an easy-to-use, time efficient and automation compatible method for generating stranded RNAseq libraries from rare cells.</p>',
'date' => '0000-00-00',
'pmid' => 'https://doi.org/10.1101%2F2022.10.20.513000',
'doi' => '10.1101/2022.10.20.513000',
'modified' => '2023-03-13 10:57:55',
'created' => '2023-02-21 09:59:46',
'ProductsPublication' => array(
[maximum depth reached]
)
)
),
'Testimonial' => array(
(int) 0 => array(
'id' => '84',
'name' => 'Tagmentase',
'description' => '<p>We experienced strong purity and activity differences between in-house produced Tn5 batches and<strong> switched to buying Tn5 from Diagenode</strong><span> </span>with<span> </span><strong><u>higher activity and small batch effects</u></strong><span> </span>only.</p>',
'author' => 'Rebekka Scholz et al. Combined Analysis of mRNA Expression and Open Chromatin in Microglia. Methods Mol Biol. 2024;2713:543-571. ',
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'modified' => '2023-10-05 14:25:52',
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<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070011), available separately.</p>
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<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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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
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<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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'description' => '<p>Diagenode offers innovative DNA library preparation solutions such as a hyperactive tagmentase and the “capture and amplification by tailing and switching” (CATS), a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of DNA. Our powerfull ChIP-seq library preparation kits are also a great solution for low input DNA library preparation (discover our <a href="https://www.diagenode.com/en/categories/library-preparation-for-ChIP-seq">Diagenode MicroPlex family</a>). </p>
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'description' => '<p><span>Transposon directed insertion-site sequencing (TraDIS), a variant of transposon insertion sequencing commonly known as Tn-Seq, is a high-throughput assay that defines essential bacterial genes across diverse growth conditions. However, the variability between laboratory environments often requires laborious, time-consuming modifications to its protocol. In this technical study, we aimed to refine the protocol by identifying key parameters that can impact the complexity of mutant libraries. Firstly, we discovered that adjusting electroporation parameters including transposome concentration, transposome assembly conditions, and cell densities can significantly improve the recovery of viable mutants for different </span><i>Escherichia coli</i><span><span> </span>strains. Secondly, we found that post-electroporation conditions, such as recovery time and the use of different mediums for selecting mutants may also impact the complexity of viable mutants in the library. Finally, we developed a simplified sequencing library preparation workflow based on a Nextera-TruSeq hybrid design where ~ 80% of sequenced reads correspond to transposon-DNA junctions. The technical improvements presented in our study aim to streamline TraDIS protocols, making this powerful technique more accessible for a wider scientific audience.</span></p>',
'date' => '2024-03-21',
'pmid' => 'https://www.nature.com/articles/s41598-024-57537-6',
'doi' => 'https://doi.org/10.1038/s41598-024-57537-6',
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'name' => 'Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy in pancreatic ductal adenocarcinoma',
'authors' => 'Kim IK et al.',
'description' => '<p><span>Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (</span><i>Irf6</i><span>), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.</span></p>',
'date' => '2024-02-20',
'pmid' => 'https://www.nature.com/articles/s41467-024-46048-7',
'doi' => 'https://doi.org/10.1038/s41467-024-46048-7',
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'name' => 'CompDuplex: Accurate detection of somatic mutations by duplex-seq with comprehensive genome coverage',
'authors' => 'Muchun Niu et al.',
'description' => '<div class="_dvu6yd">
<section class="_fz2017">
<section class="_protocols-io-draft _lw40b6">
<section class="_protocols-io-draft-app _protocols-io-draft-app-reader _awu6vp">
<section class="_protocols-io-draft-app-editor protocols-io-draft-app-editor-reader">
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<div data-offset-key="c6pdl-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="c6pdl-0-0"><span data-text="true">Somatic mutations continuously accumulate in the human genome, posing vulnerabilities towards aging and increased risk of various diseases. However, accurate detection of somatic mutations at the whole genome scale is still challenging. By tagging and independently sequencing the two complementary strands of DNA, the recent development of duplex-sequencing methods has greatly improved the detection accuracy, however, the limited genome coverage and the compromised compatibility with existing sequencing platforms have constrained the broad applications of these methods.</span></span></div>
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<div class=" align-justify" data-block="true" data-editor="desc-draft-abstract" data-offset-key="bud8b-0-0">
<div data-offset-key="bud8b-0-0" class="public-DraftStyleDefault-block public-DraftStyleDefault-ltr"><span data-offset-key="bud8b-0-0"><span data-text="true">To overcome these technical challenges, here we developed a duplex sequencing method with comprehensive genome coverage, which we refer to as CompDuplex-seq. The streamlined chemistry of CompDuplex assay allows efficient generation of libraries readily compatible with standard Illumina 2x150 paired-end sequencing. In addition, we validated the accuracy of somatic mutation calling and comprehensive genome coverage of CompDuplex by profiling a single-cell expanded clone. To summarize, CompDuplex chemistry supports genome-wide coverage while maintaining high accuracy, which we believe will facilitate the whole genome characterization of somatic mosaicism in various biological systems.</span></span></div>
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'doi' => 'dx.doi.org/10.17504/protocols.io.kxygx3x4og8j/v1',
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'name' => 'Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans',
'authors' => 'Yuanqing Feng et al.',
'description' => '<p><span>Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for </span><i>MFSD12</i><span>,<span> </span></span><i>HMG20B</i><span>,<span> </span></span><i>OCA2</i><span>,<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span>,<span> </span></span><i>TRPS1</i><span>,<span> </span></span><i>BLOC1S6</i><span><span> </span>and<span> </span></span><i>CYB561A3</i><span><span> </span>that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an<span> </span></span><i>OCA2</i><span><span> </span>enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of<span> </span></span><i>MITF</i><span>,<span> </span></span><i>LEF1</i><span><span> </span>and<span> </span></span><i>TRPS1</i><span>, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified<span> </span></span><i>CYB561A3</i><span><span> </span>as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.</span></p>',
'date' => '2024-01-10',
'pmid' => 'https://www.nature.com/articles/s41588-023-01626-1',
'doi' => 'https://doi.org/10.1038/s41588-023-01626-1',
'modified' => '2024-01-15 10:24:09',
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'name' => 'A Type II-B Cas9 nuclease with minimized off-targets and reduced chromosomal translocations in vivo',
'authors' => 'Bestas B. et al.',
'description' => '<div id="Abs1" lang="en" class="tsec sec">
<div>
<p id="Par1" class="p p-first-last"><em>Streptococcus pyogenes</em><span> </span>Cas9 (SpCas9) and derived enzymes are widely used as genome editors, but their promiscuous nuclease activity often induces undesired mutations and chromosomal rearrangements. Several strategies for mapping off-target effects have emerged, but they suffer from limited sensitivity. To increase the detection sensitivity, we develop an off-target assessment workflow that uses Duplex Sequencing. The strategy increases sensitivity by one order of magnitude, identifying previously unknown SpCas9’s off-target mutations in the humanized<span> </span><em>PCSK9</em><span> </span>mouse model. To reduce off-target risks, we perform a bioinformatic search and identify a high-fidelity Cas9 variant of the II-B subfamily from<span> </span><em>Parasutterella secunda</em><span> </span>(PsCas9). PsCas9 shows improved specificity as compared to SpCas9 across multiple tested sites, both in vitro and in vivo, including the<span> </span><em>PCSK9</em><span> </span>site. In the future, while PsCas9 will offer an alternative to SpCas9 for research and clinical use, the Duplex Sequencing workflow will enable a more sensitive assessment of Cas9 editing outcomes.</p>
</div>
<div class="sec"><strong class="kwd-title">Subject terms:<span> </span></strong><span class="kwd-text">Genetic engineering, Gene therapy, CRISPR-Cas9 genome editing</span></div>
</div>
<div id="Abs2" lang="en" class="tsec sec"></div>',
'date' => '2023-09-06',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482872/',
'doi' => '10.1038/s41467-023-41240-7',
'modified' => '2023-11-10 15:00:50',
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'name' => 'Combined Analysis of mRNA Expression and Open Chromatin in Microglia',
'authors' => 'Scholz R.et al.',
'description' => '<p><span>The advance of single-cell RNA-sequencing technologies in the past years has enabled unprecedented insights into the complexity and heterogeneity of microglial cell states in the homeostatic and diseased brain. This includes rather complex proteomic, metabolomic, morphological, transcriptomic, and epigenetic adaptations to external stimuli and challenges resulting in a novel concept of core microglia properties and functions. To uncover the regulatory programs facilitating the rapid transcriptomic adaptation in response to changes in the local microenvironment, the accessibility of gene bodies and gene regulatory elements can be assessed. Here, we describe the application of a previously published method for simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq) on microglia nuclei isolated from frozen mouse brain tissue.</span></p>',
'date' => '2023-08-29',
'pmid' => 'https://link.springer.com/protocol/10.1007/978-1-0716-3437-0_35',
'doi' => '10.1007/978-1-0716-3437-0_35',
'modified' => '2023-08-31 11:25:45',
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'name' => 'Volumetric imaging of an intact organism by a distributed molecular network',
'authors' => 'Nianchao Qian and Joshua A Weinstein',
'description' => '<p><span>Lymphatic, nervous, and tumoral tissues, among others, exhibit physiology that emerges from three-dimensional interactions between genetically unique cells. A technology capable of volumetrically imaging transcriptomes, genotypes, and morphologies in a single de novo measurement would therefore provide a critical view into the biological complexity of living systems. Here we achieve this by extending DNA microscopy, an imaging modality that encodes a spatio-genetic map of a specimen via a massive distributed network of DNA molecules inside it, to three dimensions and multiple length scales in developing zebrafish embryos.</span></p>',
'date' => '2023-08-14',
'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/37645933/',
'doi' => '10.1101/2023.08.11.553025',
'modified' => '2023-11-10 14:45:12',
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'name' => 'Spatial epigenome-transcriptome co-profiling of mammalian tissues.',
'authors' => 'Zhang D. et al.',
'description' => '<p>Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.</p>',
'date' => '2023-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36922587',
'doi' => '10.1038/s41586-023-05795-1',
'modified' => '2023-06-13 09:17:26',
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'name' => 'Analyzing genomic and epigenetic profiles in single cells by hybridtransposase (scGET-seq).',
'authors' => 'Cittaro D. et al.',
'description' => '<p>scGET-seq simultaneously profiles euchromatin and heterochromatin. scGET-seq exploits the concurrent action of transposase Tn5 and its hybrid form TnH, which targets H3K9me3 domains. Here we present a step-by-step protocol to profile single cells by scGET-seq using a 10× Chromium Controller. We describe steps for transposomes preparation and validation. We detail nuclei preparation and transposition, followed by encapsulation, library preparation, sequencing, and data analysis. For complete details on the use and execution of this protocol, please refer to Tedesco et al. (2022) and de Pretis and Cittaro (2022)..</p>',
'date' => '2023-03-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/37000619',
'doi' => '10.1016/j.xpro.2023.102176',
'modified' => '2023-04-17 09:04:55',
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'name' => 'Imaging Chromatin Accessibility by Assay ofTransposase-Accessible Chromatin with Visualization.',
'authors' => 'Miyanari Yusuke',
'description' => '<p>Chromatin accessibility is one of the fundamental structures regulating genome functions including transcription and DNA repair. Recent technological advantages to analyze chromatin accessibility begun to explore the dynamics of local chromatin structures. Here I describe protocols for Assay of Transposase-Accessible Chromatin with Visualization (ATAC-see), which allows us to analyze subnuclear localization of accessible chromatin and quantify accessible chromatin at single-cell level.</p>',
'date' => '2023-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36173568',
'doi' => '10.1007/978-1-0716-2724-2_7',
'modified' => '2022-11-24 10:28:08',
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'name' => 'Mouse kidney nuclear isolation and library preparation for single-cell combinatorial indexing RNA sequencing',
'authors' => 'Li Haikuo and Humphreys Benjamin D.',
'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq3) enables high-throughput single-nucleus transcriptomic profiling of multiple samples in one experiment. Here, we describe an optimized protocol of mouse kidney nuclei isolation and sci-RNA-seq3 library preparation. The use of a dounce tissue homogenizer enables nuclei extraction with high yield. Fixed nuclei are processed for sci-RNA-seq3, and self-loaded transposome Tn5 is used for tagmentation in library generation. The step-by-step protocol allows researchers to generate scalable single-cell transcriptomic data with common laboratory supplies at low cost.</p>',
'date' => '2022-12-01',
'pmid' => 'https://doi.org/10.1016%2Fj.xpro.2022.101904',
'doi' => '10.1016/j.xpro.2022.101904',
'modified' => '2023-08-01 14:23:49',
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'name' => 'Optimized single-nucleus transcriptional profiling by combinatorialindexing.',
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'description' => '<p>Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here, we report a simplified, optimized version of the sci-RNA-seq protocol with three rounds of split-pool indexing that is faster, more robust and more sensitive and has a higher yield than the original protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2-3 d, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole-organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a 'Tiny-Sci' protocol for experiments in which input material is very limited.</p>',
'date' => '2022-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36261634',
'doi' => '10.1038/s41596-022-00752-0',
'modified' => '2022-11-24 10:26:25',
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'id' => '4412',
'name' => 'Spatial profiling of chromatin accessibility in mouse and human tissues',
'authors' => 'Yanxiang Deng et al.',
'description' => '<p><span>Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 1" title="Perkel, J. M. Starfish enterprise: finding RNA patterns in single cells. Nature 572, 549–551 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR1" id="ref-link-section-d163865808e834">1</a></sup><span>. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. Y. & Zhuang, X. W. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR2" id="ref-link-section-d163865808e838">2</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Eng, C. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235–239 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR3" id="ref-link-section-d163865808e838_1">3</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" title="Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR4" id="ref-link-section-d163865808e838_2">4</a>,<a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e841">5</a></sup><span>, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 6" title="Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR6" id="ref-link-section-d163865808e845">6</a></sup><span><span> </span>and microfluidic deterministic barcoding</span><sup><a data-track="click" data-track-action="reference anchor" data-track-label="link" data-test="citation-ref" aria-label="Reference 5" title="Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020)." href="https://www.nature.com/articles/s41586-022-05094-1#ref-CR5" id="ref-link-section-d163865808e849">5</a></sup><span>. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.</span></p>',
'date' => '2022-08-05',
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'name' => 'Spatially resolved epigenome-transcriptome co-profiling of mammalian tissues at the cellular level',
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'description' => '<p>Emerging spatial technologies including spatial transcriptomics and spatial epigenomics are becoming powerful tools for profiling cellular states in the tissue context. However, current methods capture only one layer of omics information at a time precluding the possibility to examine the mechanistic relationship across the cental dogma of molecular biology. Here, we present two spatial multi-omics technologies for spatially resolved genome-wide joint mapping of epigenome and transcriptome by coprofiling chromatin accessibility and gene expression (spatial-ATAC-RNA-seq) or histone modification and gene expression (spatial-CUT\&Tag-RNA-seq) on the same tissue section at a resolution near single cells. They were applied to embryonic and neonatal mouse brain as well as adult human brain to map how epigenetic states or modifications regulate cell type and dynamics in tissue. Although distinct tissue features were identified by either spatial epigenome or spatial transcriptome alone with high concordance, we observed their differential roles in defining cell states. In general, epigenetic state proceeds the development of transcriptional phenotype in relation to epigenetic lineage priming. We also observed high expression canonical markers such as PROX1 in the granular cell layer of the human hippocampus showed low chromatin accessibility that corresponded to a low level of RNA turnover rate, highlighting a divergent need for open chromatin or transcription to control cell identity and dynamics. Spatial epigenome-transcriptome co-profiling is a highly informative tool to study the mechanism of gene expression regulation in tissue and may enable a wide range of applications in life science and biomedical research.</p>',
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'description' => '<p>Prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and recurrence of PCR-positive tests have been widely reported in patients after recovery from COVID-19, but some of these patients do not appear to shed infectious virus. We investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the DNA of human cells in culture and that transcription of the integrated sequences might account for some of the positive PCR tests seen in patients. In support of this hypothesis, we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral–host chimeric transcripts. The integration and transcription of viral sequences may thus contribute to the detection of viral RNA by PCR in patients after infection and clinical recovery. Because we have detected only subgenomic sequences derived mainly from the 3′ end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from the integrated subgenomic SARS-CoV-2 sequences.</p>',
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<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070011), available separately.</p>
<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
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<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may also need:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x-1ml">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
</ul>
<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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<p>Diagenode Tagmentase is a hyperactive Tn5 transposase with the potential to enhance epigenetic studies. Its ability to cut DNA and insert sequences of interest in one step makes it the perfect companion for Next-Generation Sequencing experiments using powerful technologies such as ATAC-seq, ChIPmentation, CHANGE-seq and other. The enzyme is not loaded with DNA oligos, providing flexibility of application. To ensure optimal results the concentration may be adjusted with Diagenode <a href="https://www.diagenode.com/en/p/tagmentase-dilution-buffer">Tagmentase Dilution Buffer</a> (Cat. No. C01070010), available separately.</p>
<p><a href="https://www.diagenode.com/files/protocols/PRO-Transposome-Assembly-V2.pdf" target="_blank">Protocol for transposome assembly</a></p>
<p>Using Diagenode’s Tagmentase (Tn5 transposase) you may need also:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-1x">Tagmentation Buffer (1x)</a></li>
<li><a href="https://www.diagenode.com/en/p/tagmentation-buffer-2x">Tagmentation Buffer (2x)</a></li>
<li><a href="https://www.diagenode.com/en/p/24-unique-dual-indexes-for-tagmented-libraries-set1">24 UDI for tagmented libraries</a></li>
</ul>
<p>Looking for loaded Tagmentase? Please go to <a href="https://www.diagenode.com/en/p/tagmentase-loaded-30">Tagmentase (Tn5 transposase) - loaded</a>.</p>',
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<p><img alt="Tn5 transposase" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure-1a.jpg" style="display: block; margin-left: auto; margin-right: auto;" width="653" height="282" /></p>
<p><img alt="Tagmentase Tn5 transposase" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure-1b.jpg" style="display: block; margin-left: auto; margin-right: auto;" width="645" height="278" /></p>
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<p><strong>Figure 1: Efficient fragmentation of the lambda DNA after incubation with the Tagmentase</strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with diluted Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). Profiles show the size of lambda DNA before (A) and after treatment with Tagmentase (B).</p>
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<div class="small-12 medium-12 large-12 columns"><center><img alt="Tn5 transposase perfect for NGS" src="https://www.diagenode.com/img/product/reagents/tagmentase-figure2.jpg" width="754" height="492" /></center></div>
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<p><strong>Figure 2: Fragmentation efficiency depending on the amount of Tagmentase </strong><br />For fragmentation, 100 ng of DNA from bacteriophage lambda were incubated with Diagenode Tagmentase (Cat. No. C01070010) and Tagmentation buffer (1x) (Cat. No. C01019042) for 7 min at 55°C. The Tagmentase was previously diluted with the Tagmentase Dilution Buffer (Cat. No.) at ¼ and 1/16 dilutions. The reaction was stopped by addition of SDS (0.2% final concentration). After clean-up using AMPure XP beads (Beckman Coulter) on Diagenode IP-Star robot, the size of the DNA was assessed on Fragment Analyzer (Agilent), using the HS Large Fragment 50kb Kit (Agilent). The migration of the samples shows variations of the size distribution according to the amount of Tagmentase used for the reaction.</p>
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