Name: mapping genome-wide accessible chromatin in primary human t lymphocytes by atac-seq
Uploaded: 2017-11-13T13:00:00.000+00:00
Duration: 9 min 8 s
Description: Watch this Scientific Journal Video about Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq at JoVE.com

هذا العمل معتمد من قبل "مؤسسة العلوم إسرائيل" (منحة 748/14)، ومنح "ماري كوري التكامل" (CIG)-FP7-الناس-20013-CIG-618763 والأساسية برنامج التخطيط و "لجنة الميزانية" و "مؤسسة العلوم إسرائيل" منح رقم 41/11.

<ol>
	<li>Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., Greenleaf, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transposition+of+native+chromatin+for+fast+and+sensitive+epigenomic+profiling+of+open+chromatin,+DNA-binding+proteins+and+nucleosome+position.">Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position.</a> Nat Methods. 10 (12), 1213-1218 (2013).</li><li>Buenrostro, J. D., Wu, B., Chang, H. Y., Greenleaf, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATAC-seq:+A+method+for+assaying+chromatin+accessibility+genome-wide.">ATAC-seq: A method for assaying chromatin accessibility genome-wide.</a> Curr Protoc Mol Biol. , 21.29.1-21.29.9 (2015).</li><li>Thurman, R. E., Rynes, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+accessible+chromatin+landscape+of+the+human+genome.">The accessible chromatin landscape of the human genome.</a> Nature. 489 (7414), 75-82 (2012).</li><li>Song, L., Crawford, G. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNase-seq:+a+high-resolution+technique+for+mapping+active+gene+regulatory+elements+across+the+genome+from+mammalian+cells.">DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells.</a> Cold Spring Harb Protoc. (2), (2010).</li><li>Simon, J. M., Giresi, P. G., Davis, I. J., Lieb, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+formaldehyde-assisted+isolation+of+regulatory+elements+(FAIRE)+to+isolate+active+regulatory+DNA.">Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA.</a> Nat Protoc. 7 (2), 256-267 (2012).</li><li>Cui, K., Zhao, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-Wide+Approaches+to+Determining+Nucleosome+Occupancy+in+Metazoans+Using+MNase-Seq.">Genome-Wide Approaches to Determining Nucleosome Occupancy in Metazoans Using MNase-Seq.</a> Methods Mol Biol. 833, 413-419 (2012).</li><li>Qu, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Individuality+and+Variation+of+Personal+Regulomes+in+Primary+Human+T+Cells.">Individuality and Variation of Personal Regulomes in Primary Human T Cells.</a> Cell Syst. 1 (1), 51-61 (2015).</li><li>Scharer, C. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATAC-seq+on+biobanked+specimens+defines+a+unique+chromatin+accessibility+structure+in+na&#239;ve+SLE+B+cells.">ATAC-seq on biobanked specimens defines a unique chromatin accessibility structure in na&#239;ve SLE B cells.</a> Sci Rep. 6, 27030 (2016).</li><li>Seb&#233;-Pedr&#243;s, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Dynamic+Regulatory+Genome+of+Capsaspora+and+the+Origin+of+Animal+Multicellularity.">The Dynamic Regulatory Genome of Capsaspora and the Origin of Animal Multicellularity.</a> Cell. 165 (5), 1224-1237 (2016).</li><li>Lu, Z., Hofmeister, B. T., Vollmers, C., DuBois, R. M., Schmitz, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combining+ATAC-seq+with+nuclei+sorting+for+discovery+of+cis-regulatory+regions+in+plant+genomes.">Combining ATAC-seq with nuclei sorting for discovery of cis-regulatory regions in plant genomes.</a> Nucleic Acids Res. 45 (6), e41 (2016).</li><li>Davie, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discovery+of+Transcription+Factors+and+Regulatory+Regions+Driving+In+Vivo+Tumor+Development+by+ATAC-seq+and+FAIRE-seq+Open+Chromatin+Profiling.">Discovery of Transcription Factors and Regulatory Regions Driving In Vivo Tumor Development by ATAC-seq and FAIRE-seq Open Chromatin Profiling.</a> PLOS Genet. 11 (2), (2015).</li><li>Villar, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhancer+Evolution+across+20+Mammalian+Species.">Enhancer Evolution across 20 Mammalian Species.</a> Cell. 160 (3), 554-566 (2015).</li><li>Lara-Astiaso, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatin+state+dynamics+during+blood+formation.">Chromatin state dynamics during blood formation.</a> Science. 345 (6199), 943-949 (2014).</li><li>Prescott, S. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhancer+Divergence+and+cis-Regulatory+Evolution+in+the+Human+and+Chimp+Neural+Crest.">Enhancer Divergence and cis-Regulatory Evolution in the Human and Chimp Neural Crest.</a> Cell. 163 (1), 68-83 (2015).</li><li>Wu, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+landscape+of+accessible+chromatin+in+mammalian+preimplantation+embryos.">The landscape of accessible chromatin in mammalian preimplantation embryos.</a> Nature. 534 (7609), 652-657 (2016).</li><li>Buenrostro, J. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+chromatin+accessibility+reveals+principles+of+regulatory+variation.">Single-cell chromatin accessibility reveals principles of regulatory variation.</a> Nature. 523 (7561), 486-490 (2015).</li><li>Corces, M. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lineage-specific+and+single-cell+chromatin+accessibility+charts+human+hematopoiesis+and+leukemia+evolution.">Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution.</a> Nat Genet. 48 (10), 1193-1203 (2016).</li><li>Jenner, R. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+transcription+factors+T-bet+and+GATA-3+control+alternative+pathways+of+T-cell+differentiation+through+a+shared+set+of+target+genes.">The transcription factors T-bet and GATA-3 control alternative pathways of T-cell differentiation through a shared set of target genes.</a> Proc Natl Acad Sci USA. 106 (42), 17876-17881 (2009).</li><li>DeAngelis, M. M., Wang, D. G., Hawkins, T. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solid-phase+reversible+immobilization+for+the+isolation+of+PCR+products.">Solid-phase reversible immobilization for the isolation of PCR products.</a> Nucleic Acids Res. 23 (22), 4742-4743 (1995).</li><li>Aird, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analyzing+and+minimizing+PCR+amplification+bias+in+Illumina+sequencing+libraries.">Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries.</a> Genome Biol. 12 (2), R18 (2011).</li><li>Langmead, B., Trapnell, C., Pop, M., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+and+memory-efficient+alignment+of+short+DNA+sequences+to+the+human+genome.">Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.</a> Genome Biol. 10 (3), R25 (2009).</li><li>Li, H., Handsaker, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Sequence+Alignment/Map+format+and+SAMtools.">The Sequence Alignment/Map format and SAMtools.</a> Bioinformatics. 25 (16), 2078-2079 (2009).</li><li>Quinlan, A. R., Hall, I. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BEDTools:+a+flexible+suite+of+utilities+for+comparing+genomic+features.">BEDTools: a flexible suite of utilities for comparing genomic features.</a> Bioinformatics. 26 (6), 841-842 (2010).</li><li>Zhang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Model-based+Analysis+of+ChIP-Seq+(MACS).">Model-based Analysis of ChIP-Seq (MACS).</a> Genome Biol. 9 (9), R137 (2008).</li><li>Meyer, C. A., Shirley Liu, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+and+mitigating+bias+in+next-generation+sequencing+methods+for+chromatin+biology.">Identifying and mitigating bias in next-generation sequencing methods for chromatin biology.</a> Nat Rev Genet. 15 (11), 709-721 (2014).</li><li>He, H. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Refined+DNase-seq+protocol+and+data+analysis+reveals+intrinsic+bias+in+transcription+factor+footprint+identification.">Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification.</a> Nat Methods. 11 (1), 73-78 (2013).</li><li>Madrigal, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+Accounting+for+Sequence-Specific+Bias+in+Genome-Wide+Chromatin+Accessibility+Experiments:+Recent+Advances+and+Contradictions.">On Accounting for Sequence-Specific Bias in Genome-Wide Chromatin Accessibility Experiments: Recent Advances and Contradictions.</a> Front Bioeng Biotechnol. 3, 1-4 (2015).</li><li>Qin, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChiLin:+a+comprehensive+ChIP-seq+and+DNase-seq+quality+control+and+analysis+pipeline.">ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline.</a> BMC Bioinformatics. 17 (1), (2016).</li><li>Bao, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+ATAC-seq+approach+reveals+lineage-specific+reinforcement+of+the+open+chromatin+landscape+via+cooperation+between+BAF+and+p63.">A novel ATAC-seq approach reveals lineage-specific reinforcement of the open chromatin landscape via cooperation between BAF and p63.</a> Genome Biol. 16 (1), 284 (2015).</li><li>Maurano, M. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+localization+of+common+disease-associated+variation+in+regulatory+DNA.">Systematic localization of common disease-associated variation in regulatory DNA.</a> Science. 337 (6099), 1190-1195 (2012).</li></ol>

الكتاب ليس لها علاقة بالكشف عن.

البروتوكول أتاك-seq الموصوفة هنا قد استخدمت بنجاح لتحليل الكروماتين موجوداً في الخلايا الأولية (Th1 البشرية، Th2 الخلايا، وخلايا ب) فضلا عن خطوط الخلايا المستزرعة (MCF10A خلايا سرطان الثدي البشرية والخلايا جليوبلاستوما U261). تطبيق أتاك-seq لأنواع خلايا أخرى قد تتطلب بعض التحسين البروتوكول، ولا سيم...

أتاك-seq1،2 هو أسلوب قوي يتيح تحديد مناطق الكروماتين فتح التنظيمية3 ونوكليوسومي لتحديد المواقع. يتم تطبيق هذه المعلومات لاستنتاج موقع وهوية، والنشاط من عوامل النسخ. حساسية للأسلوب لقياس التغيرات الكمية في هيكل الكروماتين يتيح دراسة نشاط العوامل الكروماتين، بما في ذلك remodelers الكروماتين والمعدلات، فضلا عن النشاط الترانسكربتي من الحمض النووي الريبي بوليميراز الثاني1. وبالتالي يوفر أتاك-seq نهج قوية وغير منحازة لفك رموز الآليات التي تحكم تنظيم النسخي في أي نوع من الخلايا للفائدة. يصف لنا تكييف أتاك-seq لخلايا Th1 و Th2 البشرية الأساسية.
أتاك-seq، تحميل مفرط Tn5 ترانسبوساسي مع محولات لتفتيت الحمض النووي الأزواج الجيل التالي التسلسل (خ ع) مع وضع علامات الحمض النووي مع محولات (أي، في عملية "تاجمينتيشن")1. وبعد التضخيم بكر، مكتبات الحمض النووي الناجم عن ذلك مستعدون للجيل التالي التسلسل (الشكل 1). تم الكشف عن تاجمينتاتيون تفضيلية من الكروماتين موجوداً بتحليل التخصيب المحلية أتاك-seq ترتيب القراءة.
الإجراءات التجريبية قصيرة ومتطلب لمواد انطلاق أقل، مقارنة بالأساليب الأخرى لقياس إمكانية الوصول الكروماتين ونوكليوسومال لتحديد المواقع مثل seq الدناز4و فير-seq5seq منسى6، قد تشجيع استخدام seq أتاك في النظم البيولوجية متعددة بما في ذلك الخلايا البشرية الابتدائية1،7 والعينات السريرية8، فضلا عن الكائنات الحية أحادي الخلية9،10من النباتات، ذباب الفاكهة11 ، ومختلف الثدييات12.
هوية النسخ يمكن كشف العوامل التي من المحتم أن المكاني موجوداً بتحليل في إثراء زخارف تسلسل الملزمة أو الجمع بين أتاك-seq الكروماتين إيمونوبريسيبيتيشن (رقاقة) تليها (تسلسل الحمض النووي الفائق تشيبسيق). تمكين هذا النهج تحديد عوامل النسخ الخاصة بنسب هامة هيماتوبويسيس في13من الماوس. تتيح طبيعة أتاك-seq غير متحيزة والعالمية دراسة تنظيم الجينات في الكائنات الحية التي لا تتوفر الكواشف مثل الأجسام المضادة لتحليل الرقائق. على سبيل المثال، الاختلافات التطورية في رابطة الدول المستقلة-وحددت المناطق التنظيمية بدراسة الخلايا الجمجمة العصبي كريست من البشر والشمبانزي14، التغيرات الإنمائية في العناصر التنظيمية خلال أوائل الماوس embryogenesis15، والتغيرات في المناظر الطبيعية التنظيمية خلال دورة الحياة من أحادي الخلية أووزارزاكي جيم-9، والتطور من المروجين ومحسنات عبر أنواع الثدييات 2012.
وكان أتاك-seq مفيداً لقياس إمكانية الوصول الكروماتين في الخلايا المفردة، وبالتالي الكشف عن التغير داخل الخلية السكان، التي عادة ما يتهرب من الدراسات على نطاق الجينوم7،16أيضا. وبالإضافة إلى ذلك، يمكن استخدام seq أتاك لدراسة التغيرات التي تحدث في المناطق التنظيمية الحمض النووي في ظروف المرض، التي عينات نادرة. على سبيل المثال، يمكن استخدام seq أتاك لدراسة التغيرات في المناظر الطبيعية التنظيمية أثناء ظهور سرطان الدم النقوي الحاد (AML)17 أو رأس-مدفوعة أونكوجينيسيس11.

<table><tbody><tr><td>50 mL tubes</td><td>Lumitron</td><td>LUM-CFT011500-P</td><td>Can be from other vendors.</td></tr><tr><td>Microtubes</td><td>Axygen Inc</td><td>MCT-175-C</td><td>Can be from other vendors.</td></tr><tr><td>25 mL serological pipettes</td><td>Corning Costar</td><td>4489</td><td>Can be from other vendors.</td></tr><tr><td>Tissue culture flask</td><td>Lumitron</td><td>LUM-TCF-012-250-P</td><td>Can be from other vendors.</td></tr><tr><td>Countes Automated Cell Counter</td><td>Invitrogen</td><td>C10227</td><td></td></tr><tr><td>NucleoSpin Tissue</td><td>MACHEREY-NAGEL</td><td>740952.5</td><td></td></tr><tr><td>Peripheral blood mononuclear cells&amp;nbsp;(PBMC)</td><td>ATCC</td><td>&amp;nbsp;PCS&amp;shy;800&amp;shy;011</td><td>Can be from other vendors.</td></tr><tr><td>RPMI 1640 Medium</td><td>Biological Industries</td><td>01-103-1A</td><td>Can be from other vendors.</td></tr><tr><td>L-Glutamine Solution (200 mM)</td><td>Biological Industries</td><td>03-020-1B</td><td>Can be from other vendors.</td></tr><tr><td>Penicillin-Streptomycin</td><td>Biological Industries</td><td>03-031-1B</td><td>Can be from other vendors.</td></tr><tr><td>Fetal Bovine Serum (FBS),&amp;nbsp;Heat Inactivated, European Grade</td><td>Biological Industries</td><td>04-127-1</td><td>Can be from other vendors.</td></tr><tr><td>MACS CD4 microbeads, human</td><td>Miltenyi Biotec</td><td>130-045-101</td><td></td></tr><tr><td>MACS MS columns</td><td>Miltenyi Biotec</td><td>130-042-201</td><td></td></tr><tr><td>Anti-Human CD4 FITC</td><td>Biogems</td><td>06121-50</td><td></td></tr><tr><td>Mouse IgG1 Isotype Control FITC</td><td>Biogems</td><td>44212-50</td><td></td></tr><tr><td>Anti-Human CD3 (OKT3)</td><td>Tonbo biosciences</td><td>40-0037</td><td></td></tr><tr><td>Anti-Human CD28 SAFIRE Purified</td><td>Biogems</td><td>10311-25</td><td></td></tr><tr><td>Recombinant Human IL2</td><td>Peprotech</td><td>200-02</td><td></td></tr><tr><td>Recombinant Human IL4</td><td>Peprotech</td><td>200-04</td><td></td></tr><tr><td>Recombinant Human IL12 p70</td><td>Peprotech</td><td>200-12</td><td></td></tr><tr><td>In Vivo Ready Anti-Human IL-4 (MP4-25D2)</td><td>Tonbo</td><td>40-7048</td><td></td></tr><tr><td>LEAF&amp;nbsp;Purified anti-human IFN-&amp;gamma;</td><td>BioLegend</td><td>506513</td><td></td></tr><tr><td>NaCl, analytical grade</td><td>Carlo Erba</td><td>479687</td><td>Can be from other vendors.</td></tr><tr><td>Magnesium chloride, Hexahydrate, molecular biology grade</td><td>Calbiochem</td><td>442611</td><td>Can be from other vendors.</td></tr><tr><td>EDTA</td><td>MP Biomedicals</td><td>800682</td><td>Can be from other vendors.</td></tr><tr><td>Tris, ultra pure, 99.9% pure</td><td>MP Biomedicals</td><td>819620</td><td>Can be from other vendors.</td></tr><tr><td>NP-40 alternative (Nonylphenyl Polyethylene Glycol)</td><td>Calbiochem</td><td>492016</td><td>Can be from other vendors.</td></tr><tr><td>Protease Inhibitors</td><td>Sigma</td><td>P2714</td><td>this protease inhibitor coctail is a powder. To make 100 x solution dilute in 1 mL of molecular-biology grade water.</td></tr><tr><td>Magnetic solid phase reverse immobilization beads: AMPure XP beads</td><td>Beckman</td><td>63881</td><td></td></tr><tr><td>PCR purification kit</td><td>HyLabs</td><td>EX-GP200</td><td>Can be from other vendors.</td></tr><tr><td>Nextera DNA Library Preparation Kit (TDE1 transposase and TD buffer)</td><td>Illumina</td><td>FC-121-1030</td><td></td></tr><tr><td>NEBNext High-Fidelity 2 x PCR Master Mix</td><td>New England BioLabs</td><td>M0541</td><td></td></tr><tr><td>NEBNext Q5 Hot Start HiFi PCR Master Mix</td><td>New England BioLabs</td><td>M0543</td><td></td></tr><tr><td>SYBR Green I&amp;nbsp;</td><td>Invitrogen</td><td>S7585</td><td></td></tr><tr><td>&amp;nbsp;CFX Connect Real-Time PCR&amp;nbsp;Detection&amp;nbsp;System</td><td>Bio-rad</td><td>185-5200</td><td>Can be from other vendors.</td></tr><tr><td>CFX Manager Software</td><td>Bio-rad</td><td>1845000</td><td></td></tr><tr><td>master mix for qPCR: iTaq Universal SYBR Green Supermix</td><td>Bio-rad</td><td>172-5124</td><td>Can be from other vendors.</td></tr><tr><td>Qubit fluorometer 2.0</td><td>Invitrogen</td><td>Q32866</td><td></td></tr><tr><td>Qubit dsDNA HS Assay Kit</td><td>Invitrogen</td><td>Q32854</td><td></td></tr><tr><td>Magnet for eppendorf tubes</td><td>Invitrogen</td><td>12321D</td><td>Can be from other vendors.</td></tr><tr><td>Swing bucket cooling centrifuge with the buckets for 15 mL falcon tubes and eppendorf tubes</td><td>Thermo Scientific</td><td>75004527</td><td>Could be from other vendors. It is important that it has buckets for eppendorf tubes.</td></tr><tr><td>Thermo-shaker</td><td>MRC</td><td></td><td>Can be from other vendors.</td></tr><tr><td>High Sensitivity D1000 ScreenTape</td><td>Agilent Technologies</td><td>5067-5584</td><td></td></tr><tr><td>High Sensitivity D1000 Reagents</td><td>Agilent Technologies</td><td>5067-5585</td><td></td></tr><tr><td>4200 TapeStation system</td><td>Agilent Technologies</td><td>G2991AA</td><td>Tape-based platform for&amp;nbsp; electrophoresis</td></tr><tr><td>High Sensitivity DNA kit</td><td>Agilent Technologies</td><td>5067-4626</td><td>Reagent for high-sensitivity TapeStation analysis</td></tr><tr><td></td><td></td><td></td><td></td></tr><tr><td>Primer name and sequence</td><td>Company</td><td></td><td></td></tr><tr><td>Ad1_noMX: 5&#039;-AATGATACGGCGACCACCGAGA&lt;br/&gt; TCTACACTCGTCGGCAGCGTC&lt;br/&gt; AGATGTG-3&#039;</td><td>IDT</td><td></td><td>Ad1-noMx: 5&#039;-P5 sequence-transposase sequence-3&#039;</td></tr><tr><td>Ad2.1_TAAGGCGA: 5&#039;-CAAGCAGAAGACGGCATACGAG&lt;br/&gt; AT[TCGCCTTA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.1_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.2_CGTACTAG: 5&#039;-CAAGCAGAAGACGGCATACGAG&lt;br/&gt; AT[CTAGTACG]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.2_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.3_AGGCAGAA: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[TTCTGCCT]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.3_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.4_TCCTGAGC: 5&#039;-CAAGCAGAAGACGGCATACGAG&lt;br/&gt; AT[GCTCAGGA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.4_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.5_GGACTCCT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[AGGAGTCC]GTCTCGTGGG&lt;br/&gt; CTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.5_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.6_TAGGCATG: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[CATGCCTA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.6_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.7_CTCTCTAC: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[GTAGAGAG]GTCTCGTGGG&lt;br/&gt; CTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.7_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.8_CAGAGAGG: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[CCTCTCTG]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.8_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.9_GCTACGCT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[AGCGTAGC]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.9_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.10_CGAGGCTG: 5&#039;-CAAGCAGAAGACGGCATACG&lt;br/&gt; AGAT[CAGCCTCG]GTCTCGTGG&lt;br/&gt; GCTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.10_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.11_AAGAGGCA: 5&#039;-CAAGCAGAAGACGGCATACG&lt;br/&gt; AGAT[TGCCTCTT]GTCTCGTGGG&lt;br/&gt; CTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.11_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.12_GTAGAGGA: 5&#039;-CAAGCAGAAGACGGCATACG&lt;br/&gt; AGAT[TCCTCTAC]GTCTCGTGGG&lt;br/&gt; CTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.12_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.13_GTCGTGAT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[ATCACGAC]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.13_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.14_ACCACTGT: 5&#039;- CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[ACAGTGGT]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.14_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.15_TGGATCTG: 5&#039;- CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[CAGATCCA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.15_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.16_CCGTTTGT: 5&#039;- CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[ACAAACGG]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.16_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>&amp;nbsp;Ad2.17_TGCTGGGT: 5&#039;- CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[ACCCAGCA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.17_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>&amp;nbsp;Ad2.18_GAGGGGTT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[AACCCCTC]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.18_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.19_AGGTTGGG: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[CCCAACCT]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.19_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>&amp;nbsp;Ad2.20_GTGTGGTG: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[CACCACAC]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.20_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>&amp;nbsp;Ad2.21_TGGGTTTC: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[GAAACCCA]GTCTCGTGGGC&lt;br/&gt; TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.21_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.22_TGGTCACA: 5&#039;- CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[TGTGACCA]GTCTCGTGGGC&lt;br/&gt;TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.22_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.23_TTGACCCT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[AGGGTCAA]GTCTCGTGGGC&lt;br/&gt;TCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.23_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td>Ad2.24_CCACTCCT: 5&#039;-CAAGCAGAAGACGGCATACGA&lt;br/&gt; GAT[AGGAGTGG]GTCTCGTGGG&lt;br/&gt;CTCGGAGATGT-3&#039;</td><td>IDT</td><td></td><td>Ad2.24_expected index sequence read: 5&#039;-P7 sequence-[index sequence]-transposase sequence-3&#039;</td></tr><tr><td></td><td></td><td></td><td></td></tr><tr><td>F1: 5&#039;-CCTTTTTATTTGCCCATACACTC-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>R1: 5&#039;-CCCAGATAGAAAGTTGGAGAGG-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>F2: 5&#039;-TTGAGGGATGCCATAACAGTC-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>R2: 5&#039;-CTGCTGAACAACATCCTTCAC-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>F3: 5&#039;-GGTTTGCAGGTTGCGTTG-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>R3: 5&#039;-AGAGGAATCTGGGAGTGACG-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>F4: 5&#039;-TGCTCATTCCGTTTCCCTAC-3&#039;</td><td>IDT</td><td></td><td></td></tr><tr><td>R4: 5&#039;-AGCCGGAAAGAAAGTTCCTG-3&#039;</td><td>IDT</td><td></td><td></td></tr></tbody></table>

mapping genome-wide accessible chromatin in primary human t lymphocytes by atac-seq

المقايسة "الكروماتين" ترانسبوساسي موجوداً مع التسلسل الفائق (أتاك-seq) أسلوب يستخدم لتحديد مناطق الكروماتين (موجوداً) مفتوحة. وتمثل هذه المناطق التنظيمية عناصر الحمض النووي (مثلاً، المروجين، معززات، موضع مراقبة المناطق، عوازل) للنسخ التي ربط العوامل. رسم الخرائط في الساحة الكروماتين موجوداً نهج قوية للكشف عن العناصر التنظيمية النشطة عبر الجينوم. هذه المعلومات بمثابة نهج غير متحيز لاكتشاف شبكة عوامل النسخ ذات الصلة، والآليات لهيكل الكروماتين التي تنظم برامج التعبير الجيني. أتاك-seq بديل قوية وحساسة الدناز أنا تحليل حساسية مقترنة بالجيل التالي التسلسل (الدناز-seq) وساعدت فورمالدهايد عزل العناصر التنظيمية (فير-seq) لتحليل المجين على نطاق المنظومة من الكروماتين إمكانية الوصول، وتسلسل المواقع الحساسة نوكلاس ميكروكوككال (seq منسى) لتحديد المواقع نوكليوسومي. نقدم بروتوكول أتاك-seq مفصلة الأمثل للخلايا البشرية المناعية الأولية أي خلايا CD4 + الخلايا الليمفاوية (مساعد تي 1 (Th1) وخلايا Th2). هذا البروتوكول شامل يبدأ مع الخلية الحصاد، ثم يصف الإجراء الجزيئية من الكروماتين تاجمينتيشن، إعداد نموذج لتسلسل الجيل المقبل، ويشمل أيضا طرق واعتبارات للتحليلات الحسابية المستخدمة في تفسير النتائج. وعلاوة على ذلك، لتوفير الوقت والمال، قدمنا تدابير مراقبة الجودة لتقييم المكتبة seq أتاك قبل التسلسل. الأهم من ذلك، المبادئ الواردة في هذا البروتوكول تسمح التكيف مع خطوط الخلايا والخلايا الأولية محصنة وغير المتمتعين بالمناعة البشرية الأخرى. كما ستكون هذه المبادئ التوجيهية مفيدة للمختبرات التي لا يتقن مع أساليب تسلسل الجيل القادم.

النتيجة النهائية لهذا البروتوكول مكتبة seq أتاك من عادة 3-20 نانوغرام/ميليلتر. عند تشغيل في وضع نظام لتحليل سلامة الحمض النووي (انظر الجدول للمواد والمعدات)، أنها تظهر مظهر يشبه سلم2 (الشكل 3A). عادة ما يكون متوسط حجم شظايا من الحمض النووي...

Watch this Scientific Journal Video about Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq at JoVE.com

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

المقايسة "الكروماتين" ترانسبوساسي موجوداً إلى جانب التسلسل الفائق (أتاك-seq) أسلوب المجين على نطاق المنظومة لكشف الكروماتين موجوداً. هذا بروتوكول أتاك-seq خطوة بخطوة، من الجزيئية للتحليل الحسابي النهائي، الأمثل للخلايا البشرية الليمفاوية (Th1/Th2). يمكن اعتماد هذا البروتوكول من الباحثين دون خبرة سابقة في أساليب تسلسل الجيل القادم.

رسم خرائط الجينوم المنظومة الكروماتين موجوداً في الخلايا الليمفاوية تي البشرية الأولية التي أتاك-Seq

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions ...

mapping-genome-wide-accessible-chromatin-primary-human-t-lymphocytes

Research

JoVE Journal

Genetics

17.9K Views.  Bar-Ilan University. المقايسة "الكروماتين" ترانسبوساسي موجوداً إلى جانب التسلسل الفائق (أتاك-seq) أسلوب المجين على نطاق المنظومة لكشف الكروماتين موجوداً. هذا بروتوكول أتاك-seq خطوة بخطوة، من الجزيئية للتحليل الحسابي النهائي، الأمثل للخلايا البشرية الليمفاوية (Th1/Th2). يمكن اعتماد هذا ال...

Video: Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

Here, we describe an optimized high-throughput ChIP-sequencing protocol and computational analyses pipeline for the determination of genome-wide chromatin state patterns from frozen tumor tissues and cell lines.

برنامج متكامل لرسم خرائط الجينوم على نطاق الدول الكروماتين استخدام رقاقة الفائق-التسلسل في أنسجة الورم

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of ...

Cancer Research

ATAC-seq Assay with Low Mitochondrial DNA Contamination from Primary Human CD4+ T Lymphocytes

ATAC-seq has become a widely used methodology in the study of epigenetics due to its rapid and simple approach to mapping genome-wide accessible chromatin. In this paper we present an improved ATAC-seq protocol that reduces contaminating mitochondrial DNA reads. While previous ATAC-seq protocols have struggled with an average of 50% contaminating mitochondrial DNA reads, the optimized&#160;lysis buffer introduced in this protocol reduces mitochondrial DNA contamination to an average of 3%. This improved ATAC-seq protocol allows for a near 50% reduction in the sequencing cost. We demonstrate how these high-quality ATAC-seq libraries can be prepared from activated CD4+ lymphocytes, providing step-by-step instructions from CD4+ lymphocyte isolation from whole blood through data analysis. This improved ATAC-seq protocol has been validated in a wide range of cell types and will be of immediate use to researchers studying chromatin accessibility.

Here, we present a protocol to perform an assay for transposase-accessible chromatin sequencing (ATAC-seq) on activated CD4+ human lymphocytes. The protocol has been modified to minimize contaminating mitochondrial DNA reads from 50% to 3% through the introduction of a new lysis buffer.

أتاك-seq المقايسة مع الحمض النووي منخفضة التلوث من الابتدائي البشرية CD4 + تي الخلايا اللمفية

ATAC-seq has become a widely used methodology in the study of epigenetics due to its rapid and simple approach to mapping genome-wide accessible ...

Adipocyte-Specific ATAC-Seq with Adipose Tissues Using Fluorescence-Activated Nucleus Sorting

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a robust technique that enables genome-wide chromatin accessibility profiling. This technique has been useful for understanding the regulatory mechanisms of gene expression in a range of biological processes. Although ATAC-seq has been modified for different types of samples, there have not been effective modifications of ATAC-seq methods for adipose tissues. Challenges with adipose tissues include the complex cellular heterogeneity, large lipid content, and high mitochondrial contamination. To overcome these problems, we have developed a protocol that allows adipocyte-specific ATAC-seq by employing fluorescence-activated nucleus sorting with adipose tissues from the transgenic reporter Nuclear tagging and Translating Ribosome Affinity Purification (NuTRAP) mouse. This protocol produces high-quality data with minimal wasted sequencing reads while reducing the amount of nucleus input and reagents. This paper provides detailed step-by-step instructions for the ATAC-seq method validated for the use of adipocyte nuclei isolated from mouse adipose tissues. This protocol will aid in the investigation of chromatin dynamics in adipocytes upon diverse biological stimulations, which will allow for novel biological insights.

We present a protocol for assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) specifically on adipocytes using nucleus sorting with adipose tissues isolated from transgenic reporter mice with nuclear fluorescence labeling.

ATAC-Seq الخاص بالخلايا الشحمية مع الأنسجة الدهنية باستخدام فرز النواة المنشطة بالفلورة

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a robust technique that enables genome-wide chromatin ...

CATCH-UP: A High-Throughput Upstream-Pipeline for Bulk ATAC-Seq and ChIP-Seq Data

Assay for transposase-accessible chromatin (ATAC) and chromatin immunoprecipitation (ChIP), coupled with next-generation sequencing (NGS), have revolutionized the study of gene regulation. A lack of standardization in the analysis of the highly dimensional datasets generated by these techniques has made reproducibility difficult to achieve, leading to discrepancies in the published, processed data. Part of this problem is due to the diverse range of bioinformatic tools available for the analysis of these types of data. Secondly, a number of different bioinformatic tools are required sequentially to convert raw data into a fully processed and interpretable output, and these tools require varying levels of computational skills. Furthermore, there are many options for quality control that are not uniformly employed during data processing. We address these issues with a complete assay for transposase-accessible chromatin sequencing (ATAC-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) upstream pipeline (CATCH-UP), an easy-to-use, Python-based pipeline for the analysis of bulk ChIP-seq and ATAC-seq datasets from raw fastq files to visualizable bigwig tracks and peaks calls. This pipeline is simple to install and run, requiring minimal computational knowledge. The pipeline is modular, scalable, and parallelizable on various computing infrastructures, allowing for easy reporting of methodology to enable reproducible analysis of novel or published datasets.

ATAC-seq and ChIP-seq allow detailed investigation of gene regulation; however, processing these data types is challenging and often inconsistent between research groups. We present CATCH-UP: an easy-to-use computational pipeline that allows standardized and reproducible data processing and analysis of new and published ATAC/ChIP-seq datasets.

Assay for transposase-accessible chromatin (ATAC) and chromatin immunoprecipitation (ChIP), coupled with next-generation sequencing (NGS), have ...

ATAC-Seq Optimization for Cancer Epigenetics Research

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

ATAC-seq is a DNA sequencing method that uses the hyperactive mutant transposase, Tn5, to map changes in chromatin accessibility mediated by transcription factors. ATAC-seq enables the discovery of the molecular mechanisms underlying phenotypic alterations in cancer cells. This protocol outlines optimization procedures for ATAC-seq in epithelial cell types, including cancer cells.

تحسين ATAC-Seq لأبحاث علم التخلق السرطاني

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the ...

عزل النوى من الخلايا السلفية القلبية للفأر بدقة خلية واحدة

Nuclei Isolation from Mouse Cardiac Progenitor Cells for Epigenome and Gene Expression Profiling at Single-Cell Resolution

The developing heart is a complex structure containing various progenitor cells controlled by complex regulatory mechanisms. The examination of the gene expression and chromatin state of individual cells allows the identification of the cell type and state. Single-cell sequencing approaches have revealed a number of important characteristics of cardiac progenitor cell heterogeneity. However, these methods are generally restricted to fresh tissue, which limits studies with diverse experimental conditions, as the fresh tissue must be processed at once in the same run to reduce the technical variability. Therefore, easy and flexible procedures to produce data from methods such as single-nucleus RNA sequencing (snRNA-seq) and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing (snATAC-seq) are needed in this area. Here, we present a protocol to rapidly isolate nuclei for subsequent single-nuclei dual-omics (combined snRNA-seq and snATAC-seq). This method allows the isolation of nuclei from frozen samples of cardiac progenitor cells and can be combined with platforms that use microfluidic chambers.

تسليط الضوء على المؤلف: عزل النوى من الخلايا السلفية القلبية للفأر من أجل التنميط epigenome والتعبير الجيني بدقة خلية واحدة  

Here, we present a protocol describing cell nuclei preparation. After microdissection and enzymatic dissociation of cardiac tissue into single cells, the progenitor cells were frozen, followed by isolation of pure viable cells, which were used for single-nucleus RNA sequencing and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing analyses.

عزل النوى من الخلايا السلفية القلبية للفأر من أجل التنميط فوق الجينوم والتعبير الجيني بدقة خلية واحدة

The developing heart is a complex structure containing various progenitor cells controlled by complex regulatory mechanisms. The examination of the gene ...

Developmental Biology

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)

ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions.
For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers.
Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq

The combination of chromatin immunoprecipitation and ultra-high-throughput sequencing (ChIP-seq) can identify and map protein-DNA interactions in a given tissue or cell line. Outlined is how to generate a high quality ChIP template for subsequent sequencing, using experience with the transcription factor TCF7L2 as an example.

جيل من جودة عالية لونين القالب الحمض النووي مناعي لتسلسل عالية الإنتاجية (رقاقة وما يليها)

ChIP-sequencing (ChIP-seq) methods directly  offer whole-genome coverage, where combining chromatin immunoprecipitation  (ChIP) and massively parallel ...

Biology

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during development and in disease states. Single-cell RNA sequencing allows us to comprehensively profile gene expression changes observed in retinal development and disease at a cellular level, while single-cell ATAC-Seq allows analysis of chromatin accessibility and transcription factor binding to be profiled at similar resolution. Here the use of these techniques in the developing retina is described, and MULTI-Seq is demonstrated, where individual samples are labeled with a modified oligonucleotide-lipid complex, enabling researchers to both increase the scope of individual experiments and substantially reduce costs.

Here, the authors showcase the utility of MULTI-seq for phenotyping and subsequent paired scRNA-seq and scATAC-seq in characterizing the transcriptomic and chromatin accessibility profiles in retina.

تحليل متعدد الإرسال للتعبير الجيني للشبكية وإمكانية الوصول إلى الكروماتين باستخدام scRNA-Seq و scATAC-Seq

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during ...

رسم خرائط الجينوم المنظومة الكروماتين موجوداً في الخلايا الليمفاوية تي البشرية الأولية التي أتاك-Seq

Summary

Explore More Videos

PLAYLIST