ATAC 基因组在原发性人类 T 淋巴细胞中的染色体全易接近染色质
Summary
转-可获得的染色质结合高通量测序 (ATAC-seq) 是一个基因组范围的方法, 以揭示可获得的染色质。这是一个 step-by 步骤的 ATAC-seq 协议, 从分子到最终的计算分析, 优化为人类淋巴细胞 (Th1/Th2)。这一协议可以被研究人员采用, 而无需事先经验的下一代测序方法。
Abstract
用高通量测序法 (ATAC-seq) 测定转可接触染色质是一种用于鉴别染色质开放 (可接近) 区域的方法。这些区域代表调控的脱氧核糖核酸元素 (例如, 促进者, 促进者, 轨迹控制区域, 绝缘体) 转录因素束缚。绘制可访问的染色质景观是一个强有力的方法, 以揭示活动的调控元素的整个基因组。这一信息作为一种无偏见的方法, 以发现网络的相关转录因子和机制的染色质结构, 控制基因表达程序。ATAC-seq 是一个强大的和敏感的替代 dnasei I 超敏分析结合下一代测序 (dnasei-seq) 和甲醛辅助分离的调节元素 (自由放任) 染色体全基因组分析micrococcal 核酸敏感点 (MNase-seq) 的可访问性和测序, 以确定核定位。我们提出了一个详细的 ATAC-seq 协议优化人类原免疫细胞即CD4+ 淋巴细胞 (T 帮助 1 (Th1) 和 Th2 细胞)。这个全面的协议从细胞收获开始, 然后描述染色质 tagmentation 的分子过程, 样品准备为下一代测序, 并且也包括方法和考虑为用于的计算分析解释结果。此外, 为了节省时间和金钱, 我们引入了质量控制措施, 在排序前评估 ATAC 序列库。重要的是, 本协议中提出的原则允许它适应其他人类免疫和免疫的原细胞和细胞系。这些准则对于那些不精通下一代测序方法的实验室也将是有用的。
Introduction
ATAC-seq1,2是一种健壮的方法, 可以识别管理3开放染色质区域和核定位。此信息用于推断转录因子的位置、身份和活动。该方法的灵敏度测量染色质结构的数量变化, 允许研究染色质因子的活性, 包括染色质 remodelers 和修饰剂, 以及转录活性的 RNA 聚合酶 II1。因此, ATAC-seq 提供了一个强大的和无偏的方法来破译机制, 控制转录调控的任何细胞类型的利益。我们描述了 ATAC-seq 对初级人类 Th1 和 Th2 细胞的适应。
在 ATAC-seq, 多动 Tn5 转加载与适配器为下一代测序 (NGS) 夫妇的 dna 标记的 dna 与适配器 (即, “tagmentation” 进程)1。在 PCR 扩增后, 生成的 DNA 库就可以进行下一代测序 (图 1)。通过对 ATAC 序列测序的局部富集分析, 可以检测到可获得的染色质的优先 tagmentation。
相对于其他测量染色质可及性和小定位的方法, 例如 dnasei-seq4、自由 seq5和 MNase-seq6, 对较少起始材料的试验程序和要求, 具有促进在包括人类主要细胞在内的多个生物系统中使用 ATAC-seq1,7和临床样本8, 以及单细胞生物体9, 植物10, 果蝇11和各种哺乳动物12。
通过分析它们的结合序列图案的丰富性, 或者结合 ATAC 和染色质沉淀 (芯片), 再加上高通量 DNA 测序 (芯片-seq)。这种方法能够识别在小鼠13中对造血有重要影响的谱系特异转录因子。ATAC 的无偏和全球性质允许研究生物中的基因调控, 因为这些试剂如芯片分析的抗体无法获得。例如, 通过研究人类和黑猩猩的脑神经嵴细胞, 在cis调控区域中发现了进化变体14, 早期小鼠的调节元素发育变化胚胎发生15, 在单细胞C. owzarzaki9的生命周期中的调控环境的变化, 以及在20哺乳动物种类中的促进剂和促进剂的演变12。
ATAC-seq 也被用于测量单个细胞中染色质的可及性, 从而揭示细胞群中的变异性, 这通常会躲过基因组范围的研究7,16。此外, ATAC 可用于研究在疾病情况下 DNA 调控区发生的变化, 其中样本稀少。例如, ATAC-seq 可用于研究急性髓细胞白血病 (AML)17或Ras驱动的发生11的发病过程中的调节环境变化。
Protocol
所有的程序都是在宜兰大学的机构审查委员会批准的, 《议定书》遵循委员会批准实验的准则. 1. 纯化 Na 和 #239; ve 人类 CD4+ 细胞和极化到 T 帮助器 1 (Th1) 和 Th2 细胞 注意: 这里我们描述从冷冻人外周血单个核细胞 (PBMCs) 开始的过程。第一步包括使用微和列来隔离 CD4+ 细胞, 通常给我们提供超过95% 的 CD4+ 细胞。但是, 根据每个实验室的首选协议, 此步骤可?…
Representative Results
该协议的最终结果是一个典型的 3-20 ng/µL 的 ATAC-seq 库。当运行在一个系统的 DNA 完整性分析 (见材料表/设备), 他们显示类似梯形外观2 (图 3A)。DNA 片段的平均大小通常是 ~ 450-530 bp。 在执行下一代测序之前, 对 ATAC 序列库进行适当的质量控制对于节省时间和金钱是很重要的。…
Discussion
本文所描述的 ATAC-seq 协议已经成功地用于对原细胞 (人 Th1、Th2 细胞和 B 细胞) 以及培养细胞系 (MCF10A 人乳腺癌细胞和 U261 胶质母细胞) 的染色质的分析。将 ATAC-seq 应用到其他细胞类型可能需要一些协议优化, 特别是在裂解步骤中。如果非离子洗涤剂浓度过高, 线粒体 DNA 污染的比例可能会更高。通过减少裂解液中的洗涤剂浓度而不降低细胞核的屈服率, 可以减少这种情况。在我们的经验, 裂解缓冲?…
Divulgazioni
The authors have nothing to disclose.
Acknowledgements
这项工作得到以色列科学基金会 (赠款 748/14)、居里夫人综合赠款 (FP7-PEOPLE-20013-CIG-618763) 和计划和预算编制委员会的核心方案和以色列科学基金会赠款41/11 的支持。
Materials
| 50 mL tubes | Lumitron | LUM-CFT011500-P | Can be from other vendors. |
| Microtubes | Axygen Inc | MCT-175-C | Can be from other vendors. |
| 25 mL serological pipettes | Corning Costar | 4489 | Can be from other vendors. |
| Tissue culture flask | Lumitron | LUM-TCF-012-250-P | Can be from other vendors. |
| Countes Automated Cell Counter | Invitrogen | C10227 | |
| NucleoSpin Tissue | MACHEREY-NAGEL | 740952.5 | |
| Peripheral blood mononuclear cells (PBMC) | ATCC | PCS800011 | Can be from other vendors. |
| RPMI 1640 Medium | Biological Industries | 01-103-1A | Can be from other vendors. |
| L-Glutamine Solution (200 mM) | Biological Industries | 03-020-1B | Can be from other vendors. |
| Penicillin-Streptomycin | Biological Industries | 03-031-1B | Can be from other vendors. |
| Fetal Bovine Serum (FBS), Heat Inactivated, European Grade | Biological Industries | 04-127-1 | Can be from other vendors. |
| MACS CD4 microbeads, human | Miltenyi Biotec | 130-045-101 | |
| MACS MS columns | Miltenyi Biotec | 130-042-201 | |
| Anti-Human CD4 FITC | Biogems | 06121-50 | |
| Mouse IgG1 Isotype Control FITC | Biogems | 44212-50 | |
| Anti-Human CD3 (OKT3) | Tonbo biosciences | 40-0037 | |
| Anti-Human CD28 SAFIRE Purified | Biogems | 10311-25 | |
| Recombinant Human IL2 | Peprotech | 200-02 | |
| Recombinant Human IL4 | Peprotech | 200-04 | |
| Recombinant Human IL12 p70 | Peprotech | 200-12 | |
| In Vivo Ready Anti-Human IL-4 (MP4-25D2) | Tonbo | 40-7048 | |
| LEAF Purified anti-human IFN-γ | BioLegend | 506513 | |
| NaCl, analytical grade | Carlo Erba | 479687 | Can be from other vendors. |
| Magnesium chloride, Hexahydrate, molecular biology grade | Calbiochem | 442611 | Can be from other vendors. |
| EDTA | MP Biomedicals | 800682 | Can be from other vendors. |
| Tris, ultra pure, 99.9% pure | MP Biomedicals | 819620 | Can be from other vendors. |
| NP-40 alternative (Nonylphenyl Polyethylene Glycol) | Calbiochem | 492016 | Can be from other vendors. |
| Protease Inhibitors | Sigma | P2714 | this protease inhibitor coctail is a powder. To make 100 x solution dilute in 1 mL of molecular-biology grade water. |
| Magnetic solid phase reverse immobilization beads: AMPure XP beads | Beckman | 63881 | |
| PCR purification kit | HyLabs | EX-GP200 | Can be from other vendors. |
| Nextera DNA Library Preparation Kit (TDE1 transposase and TD buffer) | Illumina | FC-121-1030 | |
| NEBNext High-Fidelity 2 x PCR Master Mix | New England BioLabs | M0541 | |
| NEBNext Q5 Hot Start HiFi PCR Master Mix | New England BioLabs | M0543 | |
| SYBR Green I | Invitrogen | S7585 | |
| CFX Connect Real-Time PCR Detection System | Bio-rad | 185-5200 | Can be from other vendors. |
| CFX Manager Software | Bio-rad | 1845000 | |
| master mix for qPCR: iTaq Universal SYBR Green Supermix | Bio-rad | 172-5124 | Can be from other vendors. |
| Qubit fluorometer 2.0 | Invitrogen | Q32866 | |
| Qubit dsDNA HS Assay Kit | Invitrogen | Q32854 | |
| Magnet for eppendorf tubes | Invitrogen | 12321D | Can be from other vendors. |
| Swing bucket cooling centrifuge with the buckets for 15 mL falcon tubes and eppendorf tubes | Thermo Scientific | 75004527 | Could be from other vendors. It is important that it has buckets for eppendorf tubes. |
| Thermo-shaker | MRC | Can be from other vendors. | |
| High Sensitivity D1000 ScreenTape | Agilent Technologies | 5067-5584 | |
| High Sensitivity D1000 Reagents | Agilent Technologies | 5067-5585 | |
| 4200 TapeStation system | Agilent Technologies | G2991AA | Tape-based platform for electrophoresis |
| High Sensitivity DNA kit | Agilent Technologies | 5067-4626 | Reagent for high-sensitivity TapeStation analysis |
| Primer name and sequence | Company | ||
| Ad1_noMX: 5'-AATGATACGGCGACCACCGAGA TCTACACTCGTCGGCAGCGTC AGATGTG-3' |
IDT | Ad1-noMx: 5'-P5 sequence-transposase sequence-3' | |
| Ad2.1_TAAGGCGA: 5'-CAAGCAGAAGACGGCATACGAG AT[TCGCCTTA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.1_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.2_CGTACTAG: 5'-CAAGCAGAAGACGGCATACGAG AT[CTAGTACG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.2_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.3_AGGCAGAA: 5'-CAAGCAGAAGACGGCATACGA GAT[TTCTGCCT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.3_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.4_TCCTGAGC: 5'-CAAGCAGAAGACGGCATACGAG AT[GCTCAGGA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.4_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.5_GGACTCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGAGTCC]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.5_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.6_TAGGCATG: 5'-CAAGCAGAAGACGGCATACGA GAT[CATGCCTA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.6_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.7_CTCTCTAC: 5'-CAAGCAGAAGACGGCATACGA GAT[GTAGAGAG]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.7_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.8_CAGAGAGG: 5'-CAAGCAGAAGACGGCATACGA GAT[CCTCTCTG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.8_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.9_GCTACGCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGCGTAGC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.9_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.10_CGAGGCTG: 5'-CAAGCAGAAGACGGCATACG AGAT[CAGCCTCG]GTCTCGTGG GCTCGGAGATGT-3' |
IDT | Ad2.10_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.11_AAGAGGCA: 5'-CAAGCAGAAGACGGCATACG AGAT[TGCCTCTT]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.11_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.12_GTAGAGGA: 5'-CAAGCAGAAGACGGCATACG AGAT[TCCTCTAC]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.12_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.13_GTCGTGAT: 5'-CAAGCAGAAGACGGCATACGA GAT[ATCACGAC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.13_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.14_ACCACTGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACAGTGGT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.14_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.15_TGGATCTG: 5'- CAAGCAGAAGACGGCATACGA GAT[CAGATCCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.15_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.16_CCGTTTGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACAAACGG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.16_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.17_TGCTGGGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACCCAGCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.17_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.18_GAGGGGTT: 5'-CAAGCAGAAGACGGCATACGA GAT[AACCCCTC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.18_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.19_AGGTTGGG: 5'-CAAGCAGAAGACGGCATACGA GAT[CCCAACCT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.19_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.20_GTGTGGTG: 5'-CAAGCAGAAGACGGCATACGA GAT[CACCACAC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.20_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.21_TGGGTTTC: 5'-CAAGCAGAAGACGGCATACGA GAT[GAAACCCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.21_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.22_TGGTCACA: 5'- CAAGCAGAAGACGGCATACGA GAT[TGTGACCA]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.22_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.23_TTGACCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGGTCAA]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.23_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| Ad2.24_CCACTCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGAGTGG]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.24_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
| F1: 5'-CCTTTTTATTTGCCCATACACTC-3' | IDT | ||
| R1: 5'-CCCAGATAGAAAGTTGGAGAGG-3' | IDT | ||
| F2: 5'-TTGAGGGATGCCATAACAGTC-3' | IDT | ||
| R2: 5'-CTGCTGAACAACATCCTTCAC-3' | IDT | ||
| F3: 5'-GGTTTGCAGGTTGCGTTG-3' | IDT | ||
| R3: 5'-AGAGGAATCTGGGAGTGACG-3' | IDT | ||
| F4: 5'-TGCTCATTCCGTTTCCCTAC-3' | IDT | ||
| R4: 5'-AGCCGGAAAGAAAGTTCCTG-3' | IDT |
Riferimenti
- Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 10 (12), 1213-1218 (2013).
- Buenrostro, J. D., Wu, B., Chang, H. Y., Greenleaf, W. J. ATAC-seq: A method for assaying chromatin accessibility genome-wide. Curr Protoc Mol Biol. , 21.29.1-21.29.9 (2015).
- Thurman, R. E., Rynes, E., et al. The accessible chromatin landscape of the human genome. Nature. 489 (7414), 75-82 (2012).
- Song, L., Crawford, G. E. DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb Protoc. (2), (2010).
- Simon, J. M., Giresi, P. G., Davis, I. J., Lieb, J. D. Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA. Nat Protoc. 7 (2), 256-267 (2012).
- Cui, K., Zhao, K. Genome-Wide Approaches to Determining Nucleosome Occupancy in Metazoans Using MNase-Seq. Methods Mol Biol. 833, 413-419 (2012).
- Qu, K., et al. Individuality and Variation of Personal Regulomes in Primary Human T Cells. Cell Syst. 1 (1), 51-61 (2015).
- Scharer, C. D., et al. ATAC-seq on biobanked specimens defines a unique chromatin accessibility structure in naïve SLE B cells. Sci Rep. 6, 27030 (2016).
- Sebé-Pedrós, A., et al. The Dynamic Regulatory Genome of Capsaspora and the Origin of Animal Multicellularity. Cell. 165 (5), 1224-1237 (2016).
- Lu, Z., Hofmeister, B. T., Vollmers, C., DuBois, R. M., Schmitz, R. J. Combining ATAC-seq with nuclei sorting for discovery of cis-regulatory regions in plant genomes. Nucleic Acids Res. 45 (6), e41 (2016).
- Davie, K., et al. Discovery of Transcription Factors and Regulatory Regions Driving In Vivo Tumor Development by ATAC-seq and FAIRE-seq Open Chromatin Profiling. PLOS Genet. 11 (2), (2015).
- Villar, D., et al. Enhancer Evolution across 20 Mammalian Species. Cell. 160 (3), 554-566 (2015).
- Lara-Astiaso, D., et al. Chromatin state dynamics during blood formation. Science. 345 (6199), 943-949 (2014).
- Prescott, S. L., et al. Enhancer Divergence and cis-Regulatory Evolution in the Human and Chimp Neural Crest. Cell. 163 (1), 68-83 (2015).
- Wu, J., et al. The landscape of accessible chromatin in mammalian preimplantation embryos. Nature. 534 (7609), 652-657 (2016).
- Buenrostro, J. D., et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature. 523 (7561), 486-490 (2015).
- Corces, M. R., et al. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat Genet. 48 (10), 1193-1203 (2016).
- Jenner, R. G., et al. The transcription factors T-bet and GATA-3 control alternative pathways of T-cell differentiation through a shared set of target genes. Proc Natl Acad Sci USA. 106 (42), 17876-17881 (2009).
- DeAngelis, M. M., Wang, D. G., Hawkins, T. L. Solid-phase reversible immobilization for the isolation of PCR products. Nucleic Acids Res. 23 (22), 4742-4743 (1995).
- Aird, D., et al. Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Genome Biol. 12 (2), R18 (2011).
- Langmead, B., Trapnell, C., Pop, M., Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10 (3), R25 (2009).
- Li, H., Handsaker, B., et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 25 (16), 2078-2079 (2009).
- Quinlan, A. R., Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 26 (6), 841-842 (2010).
- Zhang, Y., et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biol. 9 (9), R137 (2008).
- Meyer, C. A., Shirley Liu, X. Identifying and mitigating bias in next-generation sequencing methods for chromatin biology. Nat Rev Genet. 15 (11), 709-721 (2014).
- He, H. H., et al. Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification. Nat Methods. 11 (1), 73-78 (2013).
- Madrigal, P. On Accounting for Sequence-Specific Bias in Genome-Wide Chromatin Accessibility Experiments: Recent Advances and Contradictions. Front Bioeng Biotechnol. 3, 1-4 (2015).
- Qin, Q., et al. ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline. BMC Bioinformatics. 17 (1), (2016).
- Bao, X., et al. A novel ATAC-seq approach reveals lineage-specific reinforcement of the open chromatin landscape via cooperation between BAF and p63. Genome Biol. 16 (1), 284 (2015).
- Maurano, M. T., et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 337 (6099), 1190-1195 (2012).
Citazione di questo articolo
Grbesa, I., Tannenbaum, M., Sarusi-Portuguez, A., Schwartz, M., Hakim, O. Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq. J. Vis. Exp. (129), e56313, doi:10.3791/56313 (2017).