Summary

研究稀缺细胞群中以启动子为中心的时空基因组结构的集成工作流程

Published: April 21, 2023
doi:

Summary

基因表达由基因启动子与远端调控元件的相互作用调节。在这里,我们解释了低输入捕获Hi-C(liCHi-C)如何允许在稀有细胞类型中鉴定这些相互作用,这些相互作用以前是无法测量的。

Abstract

时空基因转录受到远端调控元件(如增强子和消音器)的严格调控,这些元件依赖于与靶基因启动子的物理接近来控制转录。虽然这些调控元件很容易识别,但它们的靶基因很难预测,因为它们中的大多数是细胞类型特异性的,并且可能在线性基因组序列中被数百个千碱基分开,跳过其他非靶基因。几年来,启动子捕获Hi-C(PCHi-C)一直是远端调控元件与其靶基因关联的黄金标准。然而,PCHi-C依赖于数百万个细胞的可用性,禁止研究稀有细胞群,例如通常从原代组织获得的细胞群。为了克服这一限制,已经开发了低输入捕获Hi-C(liCHi-C),这是一种经济高效且可定制的方法来识别控制基因组每个基因的远端调控元件库。liCHi-C依赖于与PCHi-C类似的实验和计算框架,但通过采用最小的试管更换,修改试剂浓度和体积,以及交换或消除步骤,它可以在文库构建过程中实现最小的材料损失。总的来说,liCHi-C能够在发育生物学和细胞功能的背景下研究基因调控和时空基因组组织。

Introduction

时间基因表达驱动细胞分化,并最终推动生物体发育,其改变与多种疾病密切相关1,2345。基因转录受调控元件作用的精细调控,调控元件可分为近端(即基因启动子)和远端(例如增强子或消音器),后者通常位于远离其靶基因的位置,并通过染色质环与它们发生物理相互作用以调节基因表达678

基因组中远端调控区域的鉴定是一个被广泛同意的问题,因为这些区域具有特定的组蛋白修饰910,11并且包含特定的转录因子识别基序,作为它们的招募平台121314此外,在增强子和超级增强子1516的情况下,它们还具有低核小体占用率1718并转录为非编码eRNA1920

尽管如此,每个远端调控元件的靶基因更难预测。通常情况下,远端调控元件与其靶标之间的相互作用是细胞类型和刺激特异性的21,22,跨越数百千碱基,在任何方向上桥接其他基因23,24,25,甚至可以位于其靶基因或其他非干预基因的内含子区域内2627.此外,远端调控元件也可以同时控制多个基因,反之亦然2829。这种位置复杂性阻碍了它们之间的调控关联,因此,每种细胞类型中每个调控元件的大多数靶标仍然是未知的。

近年来,用于研究染色质相互作用的染色体构象捕获(3C)技术的发展出现了显着的繁荣。其中使用最广泛的Hi-C允许生成细胞基因组每个片段之间所有相互作用的图谱30。然而,为了检测限制性片段水平上的显着相互作用,Hi-C依赖于超深度测序,禁止将其用于常规研究单个基因的调控环境。为了克服这种经济限制,已经出现了几种基于富集的3C技术,例如ChIA-PET31,HiChIP 32及其低输入对应物HiCuT33这些技术依赖于使用抗体来富集由特定蛋白质介导的全基因组相互作用。尽管如此,这些3C技术的独特之处也是其应用的祸根;用户依赖于目标蛋白质的高质量抗体的可用性,并且无法比较蛋白质结合是动态的条件。

启动子捕获Hi-C(PCHi-C)是另一种基于富集的3C技术,可规避这些限制3435。通过采用生物素化RNA探针富集系统,PCHi-C能够生成全基因组高分辨率基因组区域文库,这些文库与28,650个人类或27,595个小鼠注释的基因启动子(也称为启动子相互作用组)相互作用。这种方法允许人们在活性和非活性启动子的限制性片段水平分辨率下检测显着的长程相互作用,并可靠地比较任何条件之间的启动子相互作用组,而与组蛋白修饰或蛋白质结合的动力学无关。近年来,PCHi-C已被广泛用于鉴定细胞分化过程中的启动子相互作用组重组3637,鉴定转录因子3839的作用机制,并发现通过非编码变异40,4142434445在疾病中失调的新潜在基因和途径46,47,48,以及新的驱动程序非编码突变4950此外,通过仅修改捕获系统,该技术可以根据生物学问题进行定制,以询问任何相互作用组(例如,增强子相互作用组51或非编码改变的相互作用组4152)。

然而,PCHi-C依赖于至少2000万个细胞来执行该技术,这阻止了对稀缺细胞群的研究,例如经常用于发育生物学和临床应用的细胞群。出于这个原因,我们开发了低输入捕获Hi-C(liCHi-C),这是一种基于PCHi-C实验框架的具有成本效益和可定制的新方法,用于生成具有低细胞输入的高分辨率启动子相互作用组。通过以最少的试管更换进行实验,交换或消除原始PCHi-C方案中的步骤,大幅减少反应体积并修改试剂浓度,文库复杂性最大化,并且可以生成低至50,000个细胞的高质量文库53

低输入捕获Hi-C(liCHi-C)已针对PCHi-C进行基准测试,并用于阐明人类造血细胞分化过程中启动子相互作用组重新布线,发现潜在的新疾病相关基因和因非编码改变而失调的途径,并检测染色体异常53。这里详细介绍了分步协议和通过该技术的不同质量控制,直到库的最终生成及其计算分析。

Protocol

为确保最小的材料损失,(1)使用DNA低结合管和吸头(参见 材料表),(2)将试剂放在管壁上,而不是将吸头引入样品内部,(3)如果可能,通过倒置而不是上下移液样品混合样品,然后向下旋转以回收样品。 1. 细胞固定 悬浮生长的细胞收获 50,000 至 100 万个细胞,并将它们放入 DNA 低结合的 1.5 mL 管中。注意:用于本研究的细胞…

Representative Results

liCHi-C提供了生成高质量和分辨率的全基因组启动子相互作用组文库的可能性,只需50,000个细胞53。这是通过 – 除了大幅减少反应体积和在整个方案中使用DNA低结合塑料器皿 – 从原始方案中消除不必要的步骤来实现的,在这些步骤中会发生显着的材料损失。这些包括脱钩后的苯酚纯化,生物素去除以及随后的苯酚-氯仿纯化和乙醇沉淀。除此之外,重新组织Hi-C文库制备的步骤(生…

Discussion

liCHi-C提供了使用PCHi-C的类似实验框架生成高分辨率启动子相互作用组库的能力,但细胞数量大大减少。通过消除不必要的步骤,例如苯酚纯化和生物素去除,可以极大地实现这一点。在经典的核内连接Hi-C方案57 及其随后的衍生技术PCHi-C中,生物素从非连接的限制性内切性片段中去除,以避免拉下随后没有信息的DNA片段。跳过这部分及其随后的DNA纯化不会显着降低有效读数的百?…

Declarações

The authors have nothing to disclose.

Acknowledgements

我们感谢哈维尔实验室的其他成员对手稿的反馈。我们感谢CERCA计划,加泰罗尼亚将军和Josep Carreras基金会的机构支持。这项工作由FEDER/西班牙科学与创新部(RTI2018-094788-A-I00),欧洲血液学协会(4823998)和西班牙抗癌协会(AECC)LABAE21981JAVI资助。BMJ由La Caixa银行基金会青年领袖项目(LCF/BQ/PI19/11690001)资助,LR由AGAUR FI奖学金(2019FI-B00017)资助,LT-D由FPI奖学金(PRE2019-088005)资助。我们感谢巴塞罗那自治大学的生物化学和分子生物学博士课程的支持。没有一个资助者在实验设计或手稿写作的任何时候都参与其中。

Materials

0.4 mM Biotin-14-dATP Invitrogen 19524-016
0.5 M EDTA pH 8.0 Invitrogen AM9260G
1 M Tris pH 8.0 Invitrogen AM9855G
10x NEBuffer 2 New England Biolabs B7002S Referenced as restriction buffer 2 in the manuscript
10x PBS Fisher Scientific BP3994
10x T4 DNA ligase reaction buffer New England Biolabs B0202S
16% formaldehyde solution (w/v), methanol-free Thermo Scientific 28908
20 mg/mL Bovine Serum Albumin New England Biolabs B9000S
5 M NaCl Invitrogen AM9760G
5PRIME Phase Lock Gel Light tubes Qiuantabio 2302820 For phenol-chloroform purification in section 4 (DNA purification). Phase Lock Gel tubes are a commercial type of tubes specially designed to maximize DNA recovery after phenol-chloroform purifications while avoiding carryover of contaminants in the organic phase by containing a resin of intermediate density which settles between the organic and aqueous phase and isolates them. PLG tubes should be spun at 12,000 x g for 30 s before use to ensure that the resin is well-placed at the bottom of the tube
Adapters and PCR primers for library amplification Integrated DNA Technologies Bought as individual primers with PAGE purification for NGS
Cell scrappers Nunc 179693 Or any other brand
Centrifuge (fixed-angle rotor for 1.5 mL tubes) Any brand
CHiCAGO R package 1.14.0
CleanNGS beads CleanNA CNGS-0050
dATP, dCTP, dGTP, dTTP Promega U120A, U121A, U122A, U123A Or any other brand
DNA LoBind tube, 1.5 mL Eppendorf 30108051
DNA LoBind tube, 2 mL Eppendorf 30108078
DNA polymerase I large (Klenow) fragment 5000 units/mL New England Biolabs M0210L
Dynabeads MyOne Streptavidin C1 beads Invitrogen 65002 For biotin pull-down of the pre-captured library in section 8 (biotin pull-down)
Dynabeads MyOne Streptavidin T1 beads Invitrogen 65602 For biotin pull-down of the post-captured library in section 11 (biotin pull-down and PCR amplification)
DynaMag-2 Invitrogen 12321D Or any other magnet suitable for 1.5 ml tubeL
Ethanol absolute VWR 20821.321
FBS, qualified Gibco 10270-106 Or any other brand
Glycine Fisher BioReagents BP381-1
GlycoBlue Coprecipitant Invitrogen AM9515 Used for DNA coprecipitation in section 4 (DNA purification)
HiCUP 0.8.2
HindIII, 100 U/µL New England Biolabs R0104T
IGEPAL CA-630 Sigma-Aldrich I8896-50ML
Klenow EXO- 5000 units/mL New England Biolabs M0212L
Low-retention filter tips (10 µL, 20 µL, 200 µL and 1000 µL) ZeroTip PMT233010, PMT252020, PMT231200, PMT252000
M220 Focused-ultrasonicator Covaris 500295
Micro TUBE AFA Fiber Pre-slit snap cap 6 x 16 mm vials Covaris 520045 For sonication in section 6 (sonication)
NheI-HF, 100 U/µL New England Biolabs R3131M
Nuclease-free molecular biology grade water Sigma-Aldrich W4502
PCR primers for quality controls Integrated DNA Technologies
PCR strips and caps Agilent Technologies 410022, 401425
Phenol: Chloroform: Isoamyl Alcohol 25:24:1, Saturated with 10 mM Tris, pH 8.0, 1 mM EDTA Sigma-Aldrich P3803
Phusion High-Fidelity PCR Master Mix with HF Buffer New England Biolabs M0531L For amplification of the library in sections 9 (dATP-tailing, adapter ligation and PCR amplification)
and 11 (biotin pull-down and PCR amplification)
Protease inhibitor cocktail (EDTA-free) Roche 11873580001
Proteinase K, recombinant, PCR grade Roche 3115836001
Qubit 1x dsDNA High Sensitivity kit Invitrogen Q33230 For DNA quantification after precipitation in section 4 (DNA purification)
Qubit assay tubes Invitrogen Q32856
rCutsmart buffer New England Biolabs B6004S
RPMI Medium 1640 1x + GlutaMAX Gibco 61870-010 Or any other brand
SDS – Solution 10% for molecular biology PanReac AppliChem A0676
Sodium acetate pH 5.2 Sigma-Aldrich S7899-100ML
SureSelect custom 3-5.9 Mb library Agilent Technologies 5190-4831 Custom designed mouse or human capture system, used for the capture
SureSelect Target Enrichment Box 1 Agilent Technologies 5190-8645 Used for the capture
SureSelect Target Enrichment Kit ILM PE Full Adapter Agilent Technologies 931107 Used for the capture
T4 DNA ligase 1 U/µL Invitrogen 15224025 For ligation in section 3 (ligation and decrosslink)
T4 DNA ligase 2000000/mL New England Biolabs M0202T For ligation in section 9 (dATP-tailing, adapter ligation and PCR amplification)
T4 DNA polymerase 3000 units/mL New England Biolabs M0203L
T4 PNK 10000 units/mL New England Biolabs M0201L
Tapestation 4200 instrument Agilent Technologies For automated electrophoresis in section 9 (dATP-tailing, adapter ligation, and PCR amplification) and
section 11
(Biotin pull-down and PCR amplification). Any other automated electrophoresis system is valid
Tapestation reagents Agilent Technologies 5067-5582, 5067-5583, 5067-5584, 5067-5585, For automated electrophoresis in section 9 (dATP-tailing, adapter ligation, and PCR amplification) and
section 11
(Biotin pull-down and PCR amplification). Any other automated electrophoresis system is valid
Triton X-100 for molecular biology PanReac AppliChem A4975
Tween 20 Sigma-Aldrich P9416-50ML

Referências

  1. Hatton, C. S., et al. α-thalassemia caused by a large (62 kb) deletion upstream of the human α globin gene cluster. Blood. 76 (1), 221-227 (1990).
  2. Toikkanen, S., Helin, H., Isola, J., Joensuu, H. Prognostic significance of HER-2 oncoprotein expression in breast cancer: A 30-year follow-up. Journal of Clinical Oncology. 10 (7), 1044-1048 (1992).
  3. Church, C., et al. Overexpression of Fto leads to increased food intake and results in obesity. Nature Genetics. 42 (12), 1086-1092 (2010).
  4. Bhatia, S., et al. Disruption of autoregulatory feedback by a mutation in a remote, ultraconserved PAX6 enhancer causes aniridia. American Journal of Human Genetics. 93 (6), 1126-1134 (2013).
  5. Herranz, D., et al. A NOTCH1-driven MYC enhancer promotes T cell development, transformation and acute lymphoblastic leukemia. Nature Medicine. 20 (10), 1130-1137 (2014).
  6. Carter, D., Chakalova, L., Osborne, C. S., Dai, Y. F., Fraser, P. Long-range chromatin regulatory interactions in vivo. Nature Genetics. 32 (4), 623-626 (2002).
  7. Rao, S. S. P., et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 159 (7), 1665-1680 (2014).
  8. Schoenfelder, S., Fraser, P. Long-range enhancer-promoter contacts in gene expression control. Nature Reviews Genetics. 20 (8), 437-455 (2019).
  9. Heintzman, N. D., et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nature Genetics. 39 (3), 311-318 (2007).
  10. Zentner, G. E., Tesar, P. J., Scacheri, P. C. Epigenetic signatures distinguish multiple classes of enhancers with distinct cellular functions. Genome Research. 21 (8), 1273-1283 (2011).
  11. Creyghton, M. P., et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proceedings of the National Academy of Sciences. 107 (50), 21931-21936 (2010).
  12. McPherson, C. E., Shim, E. Y., Friedman, D. S., Zaret, K. S. An active tissue-specific enhancer and bound transcription factors existing in a precisely positioned nucleosomal array. Cell. 75 (2), 387-398 (1993).
  13. He, A., Kong, S. W., Ma, Q., Pu, W. T. Co-occupancy by multiple cardiac transcription factors identifies transcriptional enhancers active in heart. Proceedings of the National Academy of Sciences. 108 (14), 5632-5637 (2011).
  14. Dogan, N., et al. Occupancy by key transcription factors is a more accurate predictor of enhancer activity than histone modifications or chromatin accessibility. Epigenetics and Chromatin. 8, 16 (2015).
  15. Whyte, W. A., et al. transcription factors and mediator establish super-enhancers at key cell identity genes. Cell. 153 (2), 307-319 (2013).
  16. Hnisz, D., et al. Super-enhancers in the control of cell identity and disease. Cell. 155 (4), 934-947 (2013).
  17. He, H. H., et al. Nucleosome dynamics define transcriptional enhancers. Nature Genetics. 42 (4), 343-347 (2010).
  18. Song, L., et al. Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity. Genome Research. 21 (10), 1757-1767 (2011).
  19. De Santa, F., et al. A large fraction of extragenic RNA Pol II transcription sites overlap enhancers. PLoS Biology. 8 (5), e1000384 (2010).
  20. Kim, T. K., et al. Widespread transcription at neuronal activity-regulated enhancers. Nature. 465 (7295), 182-187 (2010).
  21. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 489 (7414), 57-74 (2012).
  22. Wu, H., et al. Tissue-specific RNA expression marks distant-acting developmental enhancers. PLoS Genetics. 10 (9), e1004610 (2014).
  23. Banerji, J., Rusconi, S., Schaffner, W. Expression of a β-globin gene is enhanced by remote SV40 DNA sequences. Cell. 27 (2), 299-308 (1981).
  24. Amano, T., et al. Chromosomal dynamics at the Shh locus: limb bud-specific differential regulation of competence and active transcription. Developmental Cell. 16 (1), 47-57 (2009).
  25. Shi, J., et al. Role of SWI/SNF in acute leukemia maintenance and enhancer-mediated Myc regulation. Genes and Development. 27 (24), 2648-2662 (2013).
  26. Lettice, L. A., et al. A long-range Shh enhancer regulates expression in the developing limb and fin and is associated with preaxial polydactyly. Human Molecular Genetics. 12 (14), 1725-1735 (2003).
  27. Tuvikene, J., et al. Intronic enhancer region governs transcript-specific Bdnf expression in rodent neurons. eLife. 10, e65161 (2021).
  28. Tasic, B., et al. Promoter choice determines splice site selection in protocadherin α and γ pre-mRNA splicing. Molecular Cell. 10 (1), 21-33 (2002).
  29. Perry, M. W., Boettiger, A. N., Levine, M. Multiple enhancers ensure precision of gap gene-expression patterns in the Drosophila embryo. Proceedings of the National Academy of Sciences. 108 (33), 13570-13575 (2011).
  30. Lieberman-Aiden, E., et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 326 (5950), 289-293 (2009).
  31. Fullwood, M. J., et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature. 462 (7269), 58-64 (2009).
  32. Mumbach, M. R., et al. HiChIP: Efficient and sensitive analysis of protein-directed genome architecture. Nature Methods. 13 (11), 919-922 (2016).
  33. Sati, S., et al. HiCuT: An efficient and low input method to identify protein-directed chromatin interactions. PLoS Genetics. 18 (3), e1010121 (2022).
  34. Schoenfelder, S., et al. The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements. Genome Research. 25 (4), 582-597 (2015).
  35. Schoenfelder, S., Javierre, B. M., Furlan-Magaril, M., Wingett, S. W., Fraser, P. Promoter capture Hi-C: High-resolution, genome-wide profiling of promoter interactions. Journal of Visualized Experiments. (136), e57320 (2018).
  36. Rubin, A. J., et al. Lineage-specific dynamic and pre-established enhancer-promoter contacts cooperate in terminal differentiation. Nature Genetics. 49 (10), 1522-1528 (2017).
  37. Siersbæk, R., et al. Dynamic rewiring of promoter-anchored chromatin loops during adipocyte differentiation. Molecular Cell. 66 (3), 420-435 (2017).
  38. Schoenfelder, S., et al. Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome. Nature Genetics. 47 (10), 1179-1186 (2015).
  39. Zhang, N., et al. Muscle progenitor specification and myogenic differentiation are associated with changes in chromatin topology. Nature Communications. 11 (1), 6222 (2020).
  40. Javierre, B. M., et al. Lineage-specific genome architecture links enhancers and non-coding disease variants to target gene promoters. Cell. 167 (5), 1369-1384 (2016).
  41. Jäger, R., et al. Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci. Nature Communications. 6, 6178 (2015).
  42. Martin, P., et al. Identifying causal genes at the multiple sclerosis associated region 6q23 using capture Hi-C. PLoS One. 11 (11), e0166923 (2016).
  43. Burren, O. S., et al. Chromosome contacts in activated T cells identify autoimmune disease candidate genes. Genome Biology. 18 (1), 165 (2017).
  44. Choy, M. K., et al. Promoter interactome of human embryonic stem cell-derived cardiomyocytes connects GWAS regions to cardiac gene networks. Nature Communications. 9 (1), 2526 (2018).
  45. Miguel-Escalada, I., et al. Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes. Nature Genetics. 51 (7), 1137-1148 (2019).
  46. Law, P. J., et al. Association analyses identify 31 new risk loci for colorectal cancer susceptibility. Nature Communications. 10 (1), 2154 (2019).
  47. Speedy, H. E., et al. Insight into genetic predisposition to chronic lymphocytic leukemia from integrative epigenomics. Nature Communications. 10 (1), 3615 (2019).
  48. Li, T., et al. Epigenomics and transcriptomics of systemic sclerosis CD4+ T cells reveal long-range dysregulation of key inflammatory pathways mediated by disease-associated susceptibility loci. Genome Medicine. 12 (1), 81 (2020).
  49. Orlando, G., et al. Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer. Nature Genetics. 50 (10), 1375-1380 (2018).
  50. Cornish, A. J., et al. Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C. Blood Advances. 3 (1), 21-32 (2019).
  51. Madsen, J. G. S., et al. Highly interconnected enhancer communities control lineage-determining genes in human mesenchymal stem cells. Nature Genetics. 52 (11), 1227-1238 (2020).
  52. Dryden, N. H., et al. Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C. Genome Research. 24 (11), 1854-1868 (2014).
  53. Tomás-Daza, L., et al. Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution. Nature Communications. 14 (1), 268 (2023).
  54. Lee, P. Y., Costumbrado, J., Hsu, C. Y., Kim, Y. H. Agarose gel electrophoresis for the separation of DNA fragments. Journal of Visualized Experiments. 62 (62), e3923 (2012).
  55. Bronner, I. F., Quail, M. A. Best practices for Illumina library preparation. Current Protocols in Human Genetics. 102 (1), 86 (2019).
  56. Wingett, S., et al. HiCUP: pipeline for mapping and processing Hi-C data. F1000Research. 4, 1310 (2015).
  57. Nagano, T., et al. Comparison of Hi-C results using in-solution versus in-nucleus ligation. Genome Biology. 16 (1), 175 (2015).
  58. Cairns, J., et al. CHiCAGO: Robust detection of DNA looping interactions in Capture Hi-C data. Genome Biology. 17 (1), 127 (2016).
  59. Freire-Pritchett, P., et al. Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools. Nature Protocols. 16 (9), 4144-4176 (2021).
  60. Kihm, A. J., et al. An abundant erythroid protein that stabilizes free α-haemoglobin. Nature. 417 (6890), 758-763 (2002).
  61. Feng, L., et al. Molecular mechanism of AHSP-mediated stabilization of α-hemoglobin. Cell. 119 (5), 629-640 (2004).
  62. Favero, M. E., Costa, F. F. Alpha-hemoglobin-stabilizing protein: An erythroid molecular chaperone. Biochemistry Research International. 2011, 373859 (2011).
  63. Li, D., et al. WashU Epigenome Browser update 2022. Nucleic Acids Research. 50 (W1), W774-W781 (2022).
  64. Mifsud, B., et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nature Genetics. 47 (6), 598-606 (2015).
  65. Nagano, T., et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature. 502 (7469), 59-64 (2013).
  66. Tan, L., Xing, D., Chang, C. H., Li, H., Xie, X. S. 3D genome structures of single diploid human cells. Science. 361 (6405), 924 (2018).
  67. Ramani, V., et al. Massively multiplex single-cell Hi-C. Nature Methods. 14 (3), 263-266 (2017).
  68. Díaz, N., et al. Chromatin conformation analysis of primary patient tissue using a low input Hi-C method. Nature Communications. 9 (1), 4938 (2018).
  69. Lu, L., Jin, F. Easy Hi-C: A low-input method for capturing genome organization. Methods in Molecular Biology. 2599, 113-125 (2023).
check_url/pt/65316?article_type=t

Play Video

Citar este artigo
Rovirosa, L., Tomás-Daza, L., Urmeneta, B., Valencia, A., Javierre, B. M. An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations. J. Vis. Exp. (194), e65316, doi:10.3791/65316 (2023).

View Video