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

Эта работа поддерживается Фондом науки Израиля (Грант 748/14), Мари Кюри интеграции Грант (CIG) - FP7-люди-20013-сиг-618763 и -CORE программа планирования и составления бюджета Комитет и фонд науки Израиль Грант № 41/11.

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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. 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ATAC-seq протокол, описанный здесь успешно применяются для анализа доступных хроматина в Главные ячейки (человека Th1, Th2 клетки и клетки B) а также искусственный клеточных линий (MCF10A молочной железы человека раковые клетки и клетки U261 глиобластома). Применение ATAC-seq в другие типы клеток, может...

ATAC-seq1,2 — надежный метод, который позволяет идентифицировать регулирования3 открытых хроматина регионов и позиционирования нуклеосома. Эта информация применяется для определения местоположения, личность и активности транскрипционных факторов. Чувствительность метода для измерения количественных различий в структуре хроматина позволяет изучение деятельности хроматина факторов, включая хроматина ремонтом и модификаторов, а также транскрипционный анализ деятельности РНК полимеразой II1. Таким образом ATAC-seq обеспечивает мощный и непредвзятого подхода для расшифровки механизмов, которые регулируют регуляцию в любой тип клеток интереса. Мы описываем адаптации ATAC-seq для первичного Th1 и Th2 клетки человека.
В ATAC-seq гиперактивный Tn5 Транспозаза загружен с переходниками для следующего поколения последовательности (НГС) пары фрагментацию ДНК с разметкой ДНК с адаптеров (т.е., процесс «tagmentation»)1. После амплификации PCR в результате библиотеки ДНК готовы для следующего поколения последовательности (рис. 1). Льготные tagmentation доступных хроматина обнаруживается анализ местного обогащения ATAC-seq последовательность читает.
Короткие экспериментальной процедуры и требования для меньше исходного материала, относительно других методов для измерения доступности хроматина и nucleosomal позиционирования DNase-seq4, Фэр seq5и6MNase-seq имеет поощрять использование ATAC-seq в нескольких биологических систем, включая человеческие клетки первичной1,7 и8клинических образцов, а также одноклеточные организмы9,10растений, плодовых мух11 и различных млекопитающих12.
Личность транскрипции, факторы, которые связаны с доступными локусов можно обнаружили анализ обогащения их мотивы последовательности привязки или сочетаются ATAC-seq chromatin иммунопреципитации (чип) следуют высок объём (секвенирование ДНК ChIP-seq). Этот подход позволил идентификации линии специфических транскрипционных факторов важно для кроветворения в мыши13. Беспристрастной и глобальный характер ATAC-seq позволяет изучение гена регулирование в организмов, для которых реагенты, такие как антитела для анализа чипа не доступны. Например, эволюционные изменения в СНГ-регулирования регионах были определены путем изучения черепной нейронные крест клетки человека и шимпанзе14, развития изменения в регуляторных элементов во время ранних мыши Эмбриогенез15, изменения в нормативно-правовой ландшафт во время жизненного цикла одноклеточными C. owzarzaki9и эволюция промоутеров и усилители через 20 млекопитающих видов12.
ATAC-seq также играет важную роль для измерения доступности хроматина в одиночных клетках, таким образом показывая изменчивость в клеточных популяций, который обычно избегает генома общесистемного исследования7,16. Кроме того ATAC-seq может использоваться для изучения изменений, которые происходят в ДНК нормативных областях в условиях заболевания, в которых образцы редки. К примеру, ATAC-seq может использоваться для изучения изменений в нормативно-правовой ландшафт во время наступления острый миелоидный лейкоз (ОМЛ)17 или рас-driven онкогенеза11.

<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

Assay для Транспозаза-доступны Chromatin с высокой пропускной способностью последовательности (ATAC-seq) — это метод, используемый для идентификации открытых (доступный) регионов хроматина. Эти регионы представляют регуляторных элементов ДНК (например, промоутеров, усилители, локус контроля регионов, изоляторы), в котором транскрипции факторов привязки. Отображение доступных хроматина пейзаж является мощный подход для выявления активных нормативных элементов по всему геному. Эта информация служит беспристрастный подход для обнаружения сети соответствующих транскрипционных факторов и механизмов структуры хроматина, которые управляют программами выражения гена. ATAC-seq является надежной и чувствительных альтернативой DNase I Гиперчувствительность анализ в сочетании с следующего поколения последовательности (DNase-seq) и при содействии формальдегида изоляции регуляторных элементов (Фэр seq) для анализа генома общесистемной хроматина доступность и последовательность Микрококковая Нуклеаза чувствительных участков (MNase-seq) для определения позиционирования нуклеосома. Мы представляем подробную ATAC-seq протокол, оптимизированный для человека первичной иммунной клетки т.е. CD4 + лимфоцитов (Т-хелперами 1 (Th1) и Th2 клетки). Этот всеобъемлющий протокол начинается с клетки урожая, а затем описывает молекулярное процедура tagmentation хроматина, пробоподготовка для виртуализации нового поколения и также включает методы и соображения для вычислений анализа используется для интерпретировать полученные результаты. Кроме того чтобы сэкономить время и деньги, мы ввели меры контроля качества для оценки ATAC-seq библиотеки до последовательности. Важно отметить, что принципы, изложенные в настоящем Протоколе позволяют его адаптации в другие клетки человека иммунной и неиммунизированных начальных и клеточных линий. Эти руководящие принципы также будут полезны для лабораторий, которые не владеют методами секвенирование нового поколения.

Окончательный результат этого протокола является библиотека ATAC-seq обычно 3-20 нг/мкл. При запуске в системе для анализа целостности ДНК (см. Таблицу материалов/оборудования), они показывают внешний вид лестницы как2 (рис. 3A). Средний р...

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

Assay для Транспозаза-доступные Chromatin, в сочетании с высокой пропускной способностью последовательности (ATAC-seq) является геном общесистемной методом для выявления доступных хроматина. Это шаг за шагом протокол ATAC-seq, от молекулярных окончательного вычислительной анализу, оптимизированный для лимфоцитов человека (Th1/Th2). Этот протокол может быть принят исследователи без предварительного опыта в методах секвенирование нового поколения.

Картирование генома всей доступной хроматина в основной человеческий Т-лимфоцитов, ATAC-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. Assay для Транспозаза-доступные Chromatin, в сочетании с высокой пропускной способностью последовательности (ATAC-seq) является геном общесистемной методом для выявления доступных хроматина. Это шаг за шагом протокол ATAC-seq, от молекулярных окончательного вычислительн?...

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.

Интегрированная платформа для картирования генома общесистемной Chromatin государств с использованием высокопроизводительный чип последовательности в тканях опухоли

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.

ATAC-seq Assay с низкой митохондриальной ДНК загрязнения от первичного человека CD4 + Т-лимфоцитов

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.

Адипоцит-специфический ATAC-Seq с жировыми тканями с использованием флуоресцентно-активированной сортировки ядер

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.

Оптимизация ATAC-Seq для исследований эпигенетики рака

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

Выделение ядер из клеток-предшественников сердца мышей с разрешением для одной клетки

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.

В центре внимания автора: Выделение ядер из клеток-предшественников сердца мышей для профилирования эпигенома и экспрессии генов с разрешением одной клетки  

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.

Выделение ядер из клеток-предшественников сердца мышей для профилирования эпигенома и экспрессии генов при одноклеточном разрешении

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.

Генерация высших шаблона ДНК хроматина Качество Иммунопреципитация для высокопроизводительного секвенирования (чип-след)

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.

Мультиплексированный анализ экспрессии генов сетчатки и доступности хроматина с использованием scRNA-Seq и scATAC-Seq

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

Картирование генома всей доступной хроматина в основной человеческий Т-лимфоцитов, ATAC-Seq

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