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A (continuously updated) collection of references to Hi-C data. Predominantly human/mouse Hi-C data, with replicates.

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Hi-C data

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A (continuously updated) collection of references to Hi-C data. Predominantly human/mouse Hi-C data, with replicates. Please, contribute and get in touch! See MDmisc notes for other programming and genomics-related notes.

Large collections

Lieberman-Aiden lab

All HiC data released by Lieberman-Aiden group. Links to Amazon storage and GEO studies. http://aidenlab.org/data.html

  • Vian, Laura, Aleksandra Pękowska, Suhas S.P. Rao, Kyong-Rim Kieffer-Kwon, Seolkyoung Jung, Laura Baranello, Su-Chen Huang, et al. “The Energetics and Physiological Impact of Cohesin Extrusion.” Cell 173, no. 5 (May 2018) - Architectural stripes, created by extensive loading of cohesin near CTCF anchors, with Nipbl and Rad21 help. Little overlap between B cells and ESCs. Architectural stripes are sites for tumor-inducing TOP2beta DNA breaks. ATP is required for loop extrusion, cohesin translocation, but not required for maintenance, Replication of transcription is not important for loop extrusion. Zebra algorithm for detecting architectural stripes, image analysis, math in Methods. Human lymphoblastoid cells, mouse ESCs, mouse B-cells activated with LPS, CH12 B lymphoma cells, wild-type, treated with hydroxyurea (blocks DNA replication), flavopiridol (blocks transcription, PolII elongation), oligomycin (blocks ATP). Many other data types (e.g., ChIP-seq, ATAC-seq) GSE82144, GSE98119

  • Lieberman-Aiden, Erez, Nynke L. van Berkum, Louise Williams, Maxim Imakaev, Tobias Ragoczy, Agnes Telling, Ido Amit, et al. “Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome.” Science (New York, N.Y.) 326, no. 5950 (October 9, 2009) Gm12878, K562 cells. HindIII, NcoI enzymes. Two-three replicates. GSE18199

  • Rao, Suhas S. P., Miriam H. Huntley, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, et al. “A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping.” Cell 159, no. 7 (December 18, 2014) - Human Gm12878, K562, IMR90, NHEC, HeLa cells, Mouse CH12 cells. Different digestion enzymes (HindIII, NcoI, Mbol, DpnII), different dilutions. Up to 35 biological replicates for Gm12878. GSE63525, Supplementary Table S1. Hi-C meta-data

  • Sanborn, Adrian L., Suhas S. P. Rao, Su-Chen Huang, Neva C. Durand, Miriam H. Huntley, Andrew I. Jewett, Ivan D. Bochkov, et al. “Chromatin Extrusion Explains Key Features of Loop and Domain Formation in Wild-Type and Engineered Genomes.” Proceedings of the National Academy of Sciences of the United States of America 112, no. 47 (November 24, 2015). HAP1, derived from chronic myelogenous leukemia cell line. Replicates. GSE74072

  • Rao, Suhas S.P., Su-Chen Huang, Brian Glenn St Hilaire, Jesse M. Engreitz, Elizabeth M. Perez, Kyong-Rim Kieffer-Kwon, Adrian L. Sanborn, et al. “Cohesin Loss Eliminates All Loop Domains.” Cell 171, no. 2 (2017) - HCT-116 human colorectal carcinoma cells. Timecourse, replicates under different conditions. GSE104334

Leonid Mirny lab

http://mirnylab.mit.edu/

  • Data from multiple studies, in one place, in .cool format: ftp://cooler.csail.mit.edu/coolers
  • Convert to any other format with cooler https://cooler.readthedocs.io/

Bing Ren lab

http://chromosome.sdsc.edu/mouse/hi-c/download.html

Raw and normalized chromatin interaction matrices and TADs defined with DomainCaller. Mouse ES, cortex, Human ES, IMR90 fibroblasts. Two replicates per condition. GEO accession: GSE35156, GSE43070

Feng Yue lab

3D Genome Browser - Classical datasets for TAD/loop identification, provided as raw and normalized matrices, genomic coordinates of TADs/loops, tools for various 3C data analysis.

4D Nucleome Data Portal

Cancer

Tissue-specific

ENCODE

Search query for any type of Hi-C data, e.g., human brain, https://www.encodeproject.org/search/?type=Experiment&assay_slims=3D+chromatin+structure&assay_title=Hi-C&organ_slims=brain

Brain

Cell lines

  • Haarhuis, Judith H.I., Robin H. van der Weide, Vincent A. Blomen, J. Omar Yáñez-Cuna, Mario Amendola, Marjon S. van Ruiten, Peter H.L. Krijger, et al. “The Cohesin Release Factor WAPL Restricts Chromatin Loop Extension.” Cell 169, no. 4 (May 2017): 693-707.e14. https://doi.org/10.1016/j.cell.2017.04.013. - WAPL, cohesin's antagonist, DNA release factor, restricts loop length and prevents looping between incorrectly oriented CTCF sites. Together with SCC2/SCC4 complex, WAPL promotes correct assembly of chromosomal structures. WAPL WT and KO Hi-C, RNA-seq, ChIP-seq for CTCF and SMC1. Also, SCC4 KO and combined SCC4-WAPL KO Hi-C. Potential role of WAPL in mitosis chromosome condensation. Tools: HiC-Pro processing, HICCUPS, HiCseq, DI, SomaticSniper for variant calling. Data (Hi-C in custom paired BED format) : https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95015

  • Grubert, Fabian, Judith B. Zaugg, Maya Kasowski, Oana Ursu, Damek V. Spacek, Alicia R. Martin, Peyton Greenside, et al. “Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions.” Cell 162, no. 5 (August 2015): 1051–65. https://doi.org/10.1016/j.cell.2015.07.048. - seven Hi-C replicates on Gm12878 cell line, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62742

  • Naumova, Natalia, Maxim Imakaev, Geoffrey Fudenberg, Ye Zhan, Bryan R. Lajoie, Leonid A. Mirny, and Job Dekker. “Organization of the Mitotic Chromosome.” Science (New York, N.Y.) 342, no. 6161 (November 22, 2013): 948–53. https://doi.org/10.1126/science.1236083. - E-MTAB-1948 - 5C and Hi-C chromosome conformation capture study on metaphase chromosomes from human HeLa, HFF1 and K562 cell lines across the cell cycle. Two biological and two technical replicates. https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1948/samples/

  • Jessica Zuin et al., “Cohesin and CTCF Differentially Affect Chromatin Architecture and Gene Expression in Human Cells,” Proceedings of the National Academy of Sciences of the United States of America 111, no. 3 (January 21, 2014): 996–1001, https://doi.org/10.1073/pnas.1317788111. - CTCF and cohesin (RAD21 protein) are enriched in TAD boundaries. Depletion experiments. Different effect on inter- and intradomain interactions. Loss of cohesin leads to loss of local interactions, but TADs remained. Loss of CTCF leads to both loss of local and increase in inter-domain interactions. Different gene expression changes. TAD structures remain largely intact. Data: Hi-C, RNA-seq, RAD21 ChIP-seq for control and depleted RAD21 and CTCF in HEK293 hepatocytes. Two replicates in each condition. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44267

Non-human data

  • TADs in Drosophila, Hi-C and RNA-seq in four cell lines of various origin. dCTCF, SMC3, and Su(Hw) are weakly enriched at TAD boundaries. Transcription and active chromatin (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H4K16ac) are associated with TAD boundaries. Also, BEAF-32 and CP190. Hierarchical TADs. Housekeeping genes tend to be near TAD boundaries and in inter-TAD regions. TAD boundary prediction using regression, modeling to associate TADs with bands, investigation of the hierarchy. Heavy use of the Armatus TAD caller. RNA-seq and replicate Hi-C data, high correlation, merged into 20kb resolution.  https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69013
    • Ulianov, Sergey V., Ekaterina E. Khrameeva, Alexey A. Gavrilov, Ilya M. Flyamer, Pavel Kos, Elena A. Mikhaleva, Aleksey A. Penin, et al. “Active Chromatin and Transcription Play a Key Role in Chromosome Partitioning into Topologically Associating Domains.” Genome Research 26, no. 1 (January 2016): 70–84. https://doi.org/10.1101/gr.196006.115.

Differential Hi-C

  • RNA transcription inhibition minimally affects TADs, weakens TAD boundaries. K562, RNAse inhibition before/after crosslinking (bXL/aXL), actinomycin D (complete transcriptional arrest) treatment. Processing using cword, 40kb resolution. Data with replicates of each condition, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114337

  • Comparison of the 3D structure of human and chimpanzee induced puripotent stem cells. Lower-order pairwise interactions are relatively conserved, but higher-order, such as TADs, differ. HiCUP and HOMER for Hi-C data processing to 10kb resolution. cyclic loess normalization, limma for significant interaction definition, Arrowhead on combined replicated wot detect TADs.  Association of differential chromatin interactions with gene expression. PyGenomeTracks for visualization. Workflowr code https://ittaieres.github.io/HiCiPSC/, Processed Hi-C data (4 human and 4 chimp iPSCs) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE122520

  • 3D chromatin reorganization during different types of cellular senescence, replicative (RS) and oncogene-induced (OIS over time course). Senescence-associated heterochromatin loci (SAHFs), formed with the help of DNMT1 via regulation of MMGA2 expression. WI38 primary fibroblasts. OIS - gain in long-range contacts. diffHiC analysis, differential regions enriched in H3K9me3. TADkit for 3D modeling, visualization at https://vre.multiscalegenomics.eu/data_repositories/data_senescence.php. Data (Hi-C replicates, different conditions, timecourse, H3K4me3/H3K9me3/H3K27ac ChIP-seq, RNA-seq) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE130306

    • Sati, Satish, Boyan Bonev, Quentin Szabo, Daniel Jost, Paul Bensadoun, Francois Serra, Vincent Loubiere, et al. “4D Genome Rewiring during Oncogene-Induced and Replicative Senescence.” Molecular Cell, March 2020, S1097276520301556. https://doi.org/10.1016/j.molcel.2020.03.007.

  • X chromosome sex differences in Drosophila. Male X chromosome has two-fold upregulation of gene expression, more mid/long-range interactions, weaker boundaries marked by BEAF-32, CP190, Chromator, and CLAMP, a dosage compensation complex cofactor. Less negative slope in distance-dependent decay of interactions, less clustered top scoring interactions (more randomness), more open structure overall. Local score differentiator (LSD-score) to call differential TAD boundaries in CNV-independent manner - more non-matching boundaries than autosomes, ~20% appearing and ~35% disappearing boundaries. Enrichment in epigenomic marks identified stronger boundary association with MSL (male-specific lethal complex) and CLAMP binding. Many other experimental observations. hiclib, hicpipe processing. R implementation of LSD differential TAD analysis https://bitbucket.org/koustavpal1988/fly_dc_structuralchanges_2018/src/master/, Hi-C data in bedGraph format https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94115 Tweet

    • Pal, Koustav, Mattia Forcato, Daniel Jost, Thomas Sexton, Cédric Vaillant, Elisa Salviato, Emilia Maria Cristina Mazza, Enrico Lugli, Giacomo Cavalli, and Francesco Ferrari. “Global Chromatin Conformation Differences in the Drosophila Dosage Compensated Chromosome X.” Nature Communications 10, no. 1 (December 2019): 5355. https://doi.org/10.1038/s41467-019-13350-8.

  • DNA methylation linked with 3D genomics. Methylation directs PRC-dependent 3D organization of mouse ESCs. Hypomethylation in mouse ESCs driven to naive pluripotency in two inhibitors (2i) is accopmanied by redistribution of polycomb H3K27me3 mark and decompaction of chromatin. Focus on HoxC, HoxD loci. Hi-C data processed with distiller and other cool-related tools. RNA-seq, H3K37me3 ChIPseq of Mouse ESCs grown in serum and 2i conditions. Hi-C data in replicates https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124342

    • McLaughlin, Katy, Ilya M. Flyamer, John P. Thomson, Heidi K. Mjoseng, Ruchi Shukla, Iain Williamson, Graeme R. Grimes, et al. “DNA Methylation Directs Polycomb-Dependent 3D Genome Re-Organization in Naive Pluripotency.” Cell Reports 29, no. 7 (November 2019): 1974-1985.e6. https://doi.org/10.1016/j.celrep.2019.10.031.

  • Hi-C TAD comparison between normal prostate cells (RWPE1) and two prostate cancer cells (C42B, 22Rv1). TADs (TopDom-called) become smaller in cancer, switch epigenetic states. FOXA1 promoter has more loop anchors in cancer. Androgen receptor (AR) locus has chromatin structure changed around it (Figure 6). Loop investigation called with Fit-HiC, motifs (NOMe-seq) enriched in loop-associated enhancers different between normal and cancer. HiTC visualization. Figure 1a, Supplementary Figure 3, 5 - examples/coordinates of TAD boundary/length changes.

  • Data For RWPE1, C42B, 22Rv1 cell lines: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118629. In situ Hi-C, 4-cutter MboI,  replicated, text-based sparse matrices at 10kb and 40kb resolution, raw and ICE-normalized, hg19. H3K9me3, H3K27me3, H3K36me3, RNA-seq.

  • Supplementary data: Data 2 - TAD coordinates and annotations; Data 3 - differentially expressed genes in smaller TADs; Data 4 - gene expression changes in TADs switching epigenomic state; Data 5 - enhancer-promoter loops; Data 6 - coordinates of nucleosome-depleted regions; Data 7 - all differentially expressed genes; Data 8 - target genes of FOXA1-bound enhancers; Data 9 - overexpressed genes with more enhancer-promoter loops

    • Rhie, Suhn Kyong, Andrew A. Perez, Fides D. Lay, Shannon Schreiner, Jiani Shi, Jenevieve Polin, and Peggy J. Farnham. “A High-Resolution 3D Epigenomic Map Reveals Insights into the Creation of the Prostate Cancer Transcriptome.” Nature Communications 10, no. 1 (December 2019): 4154. https://doi.org/10.1038/s41467-019-12079-8.

  • In situ HiC libraries in biological replicates (n=2) for several hematopoietic celltypes (200mio reads per replicate) with a focus on the B cell lineage in mice. The authors investigate the role of the transcription factor Pax5 towards its supervisiory role of organizing the 3D genome architecture throughout B cell differentiation. The raw data are available via https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE99151.

    • Timothy M. Johanson, Aaron T. L. Lun, Hannah D. Coughlan, Tania Tan, Gordon K. Smyth, Stephen L. Nutt & Rhys S. Allan. "Transcription-factor-mediated supervision of global genome architecture maintains B cell identity." Nature Immunology volume 19, pages 1257–1264 (2018). https://www.nature.com/articles/s41590-018-0234-8

Timecourse Hi-C

  • Du, Zhenhai, Hui Zheng, Bo Huang, Rui Ma, Jingyi Wu, Xianglin Zhang, Jing He, et al. “Allelic Reprogramming of 3D Chromatin Architecture during Early Mammalian Development.” Nature 547, no. 7662 (12 2017): 232–35. https://doi.org/10.1038/nature23263. - Developmental time course Hi-C. Mouse early development. low-input Hi-C technology (sisHi-C). TADs are initially absent, then gradually appeared. HiCPro mapping, Pearson correlation on low-resolution matrices, allele resolving. Data:  https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE82185

  • Hug, Clemens B., Alexis G. Grimaldi, Kai Kruse, and Juan M. Vaquerizas. “Chromatin Architecture Emerges during Zygotic Genome Activation Independent of Transcription.” Cell 169, no. 2 (06 2017): 216-228.e19. https://doi.org/10.1016/j.cell.2017.03.024. - TADs appearing during zygotic genome activation, independent of transcription. TAD boundaries are enriched in housekeeping genes, colocalize in 3D. Drosophila. Insulation score for boundary detection. Overlap analysis of TAD boundaries. Processed Hi-C matrices at 5kb resolution (replicates merged, .cool format) and TAD boundaries at nuclear cycle 12, 13, 14, and 3-4 hours post fertilization are at  https://github.com/vaquerizaslab/Hug-et-al-Cell-2017-Supp-Site

  • Ke, Yuwen, Yanan Xu, Xuepeng Chen, Songjie Feng, Zhenbo Liu, Yaoyu Sun, Xuelong Yao, et al. “3D Chromatin Structures of Mature Gametes and Structural Reprogramming during Mammalian Embryogenesis.” Cell 170, no. 2 (July 13, 2017): 367-381.e20. https://doi.org/10.1016/j.cell.2017.06.029. - 3D timecourse changes during embryo development, from zygotic (no TADs, many long-range interactions) to 2-, 4-, 8-cell, blastocyst and E7.5 mature embryos (TADs established after several rounds of DNA replication). A/B compartments associated with un/methylatied CpGs, respectively. PC1, directionality index, insulation score to define compartments and TADs, these metrics increase in magnitude/strength during maturation. Enrichment in CTCF, SMC1, H3K4me3, H3K27ac, H3K9ac, H3K4me1, depletion in H3K9me3, H3K36me3, H3K27me3. The compartment strength is weaker in maternal vs. paternal genomes. Covariance for each gene vs. boundary score across the timecourse. Relative TAD intensity changes. Hi-C and RNA-seq data at different stages, some replicates, http://bigd.big.ac.cn/bioproject/browse/PRJCA000241

  • Paulsen, Jonas, Tharvesh M. Liyakat Ali, Maxim Nekrasov, Erwan Delbarre, Marie-Odile Baudement, Sebastian Kurscheid, David Tremethick, and Philippe Collas. “Long-Range Interactions between Topologically Associating Domains Shape the Four-Dimensional Genome during Differentiation.” Nature Genetics, April 22, 2019. https://doi.org/10.1038/s41588-019-0392-0. - Long-range TAD-TAD interactions form cliques (>3 TAD interacting) are enriched in B compartments and LADs, downregulated gene expression. Graph representation of TAD interactions. Quantifying statistical significance of between-TAD interactions. TAD boundaries are conserved. TAD cliques are dynamic. Permutation test preserving distances. Armatus for TAD detection. hiclib for data processing, Juicebox for visualization. Data: Time course differentiation or human adipose stem cells (day 0, 1, and 3). Hi-C (two replicates), Lamin B1 ChIP-seq, H3K9me3. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE109924. Also used mouse ES differentiation (Bonev 2017), mouse B cell reprogramming (Stadhouders 2018), scHi-C (Nagano 2017)

  • Vara, Covadonga, Andreu Paytuví-Gallart, Yasmina Cuartero, François Le Dily, Francisca Garcia, Judit Salvà-Castro, Laura Gómez-H, et al. “Three-Dimensional Genomic Structure and Cohesin Occupancy Correlate with Transcriptional Activity during Spermatogenesis.” Cell Reports 28, no. 2 (July 2019): 352-367.e9. https://doi.org/10.1016/j.celrep.2019.06.037. - 3D structure changes during spermatogenesis in mouse. Hi-C, RNA-seq, CTCF/REC8/RAD21L ChIP-seq. Description of biology of each stage (Fibroblasts, spermatogonia, leptonema/zygonema, pachynema/diplonema, round spermatids, sperm), and A/B compartment and TAD analysis (TADbit, insulation score), data normalized with ICE. Integration with differential expression. Changes in distribution of CTCF and cohesins (REC8 and RAD21L). Key tools: BBDuk (BBMap), TADbit, HiCExplorer, HiCRep, DeepTools. Data (no replicates) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132054

Promoter-enhancer interactions

  • Promoter-enhancer predictions in 131 cell types and tissues using the Activity-By-Contact (ABC) Model, based on chromatin state (ATAC-seq) and 3D folding (consensus Hi-C). ABC model assumes an element’s quantitative effect on a gene should depend on its strength as an enhancer (Activity) weighted by how often it comes into 3D contact with the promoter of the gene (Contact), and that the relative contribution of an element on a gene’s expression (as assayed by the proportional decrease in expression following CRISPR-inhibition) should depend on that element’s effect divided by the total effect of all elements. Outperforms distance-based methods, 3D-based only, machine learning approaches. Enhancer-promoter predictions for GM12878, K562, liver, LNCAP, mESCs, NCCIT cells, more at Engreitz Lab page. ABC-Enhancer-Gene-Prediction GitHub repository.

  • Genome-wide maps linking disease variants to genes. Activity-By-Contact (ABC) Model. 72 diseases and complex traits (non-specific, no psychiatric), linking 5046 fine-mapped GWAS signals to 2249 genes. 577 genes influence multiple phenotypes. Nearly half enhancers regulate multiple genes.Table S7 - Summary of diseases and traits.Table S9 - ABC-Max predictions for 72 diseases and complex traits.

  • Promoter-enhancer interactions. Promoter-capture Hi-C, 27 human cell lines. Well-formatted data and hg19 genomic coordinates Supplementary material and http://www.3div.kr/capture_hic

    • Jung, Inkyung, Anthony Schmitt, Yarui Diao, Andrew J. Lee, Tristin Liu, Dongchan Yang, Catherine Tan, et al. “A Compendium of Promoter-Centered Long-Range Chromatin Interactions in the Human Genome.” Nature Genetics, September 9, 2019. https://doi.org/10.1038/s41588-019-0494-8.

  • Hi-C promoter capture in 17 blood cell types, sorted. Chromatin interactions are cell type-specific. >50% interactions are one-to-one. Enriched in H3K27ac and H3K4me1 (active enhancers). GWAS loci enriched in PIRs. Table S3 lists prioritized genes/SNPs, for autoimmune diseases. Used CHiCAGO to identify strongly interacting regions. Data has active promoter-enhancer links. More than 2,500 potential disease-associated genes are linked to GWAS SNPs. https://www.chicp.org/

    • Javierre, Biola M., Oliver S. Burren, Steven P. Wilder, Roman Kreuzhuber, Steven M. Hill, Sven Sewitz, Jonathan Cairns, et al. “Lineage-Specific Genome Architecture Links Enhancers and Non-Coding Disease Variants to Target Gene Promoters.” Cell 167, no. 5 (November 17, 2016): 1369-1384.e19. https://doi.org/10.1016/j.cell.2016.09.037.

Single-cell Hi-C

See Notes on single-cell Hi-C technologies, tools, and data repository

CTCF

Notes on CTCF motifs and data

Integrative Hi-C

Misc

  • Consensus Hi-C matrix, FTP, mean of 10 cell line-specific matrices, from Nasser, Joseph, Drew T Bergman, Charles P Fulco, Philine Guckelberger, Benjamin R Doughty, Tejal A Patwardhan, Thouis R Jones, et al. “Genome-Wide Maps of Enhancer Regulation Connect Risk Variants to Disease Genes,” bioRxiv, September 03, 2020

  • Sauerwald, Natalie, and Carl Kingsford. “Quantifying the Similarity of Topological Domains across Normal and Cancer Human Cell Types.” Bioinformatics (Oxford, England) 34, no. 13 (July 1, 2018): i475–83. https://doi.org/10.1093/bioinformatics/bty265. - Analysis of TAD similarity using variation of information (VI) metric as a local distance measure. Defining structurally similar and variable regions. Comparison with previous studies of genomic similarity. Cancer-normal comparison - regions containing pan-cancer genes are structurally conserved in normal-normal pairs, not in cancer-cancer. https://github.com/Kingsford-Group/localtadsim. 23 human Hi-C datasets, Hi-C Pro processed into 100kb matrices, Armatus to call TADs.

  • Sauerwald, Natalie, Akshat Singhal, and Carl Kingsford. “Analysis of the Structural Variability of Topologically Associated Domains as Revealed by Hi-C.” BioRxiv, January 1, 2018, 498972. https://doi.org/10.1101/498972. - TAD variability among 137 Hi-C samples (including replicates, 69 if not) from 9 studies. HiCrep, Jaccard, TADsim to measure similarity. Variability does not come from genetics. Introduction to TADs. 10-70% of TAD boundaries differ between replicates. 20-80% differ between biological conditions. Much less variation across individuals than across tissue types. Lab -specific source of variation - in situ vs. dilution ligation protocols, restriction enzymes not much. HiCpro to 100kb data, ICE-normalization, Armatus for TAD calling. Table 1 - all studies and accession numbers.

  • McCole, Ruth B., Jelena Erceg, Wren Saylor, and Chao-Ting Wu. “Ultraconserved Elements Occupy Specific Arenas of Three-Dimensional Mammalian Genome Organization.” Cell Reports 24, no. 2 (July 10, 2018): 479–88. https://doi.org/10.1016/j.celrep.2018.06.031. - Ultraconserved elements analysis in the context of 3D genomic structures (TADs, boundaries, loop anchors). Enriched (obseerved/expected overlaps) in domains, depleted in boundaries, no enrichment in loops. Separate analysis for exonic, intronic, intergenic UCEs. Human and mouse Hi-C data. Supplementary tables - coordinates of UCEs, more. https://github.com/rmccole/UCEs_genome_organization

    • [McCole_2018] - Supplementary material, https://www.cell.com/action/showImagesData?pii=S2211-1247%2818%2930941-0
    • [mmc2.xlsx] - Table S1. Hi-C Datasets, genomic coordinates of human/mouse pooled domains/boundaries, cell-specific domains/boundaries
    • [mmc3.xlsx] - Table S2. Depletion/Enrichment Analysis. "C" and "D" sheets have genomic coordinates of hg19/mm9 UCEs and their Intergenic/intronic/exonic subsets.

  • Nagano, Takashi, Csilla Várnai, Stefan Schoenfelder, Biola-Maria Javierre, Steven W. Wingett, and Peter Fraser. “Comparison of Hi-C Results Using in-Solution versus in-Nucleus Ligation.” Genome Biology 16 (August 26, 2015): 175. https://doi.org/10.1186/s13059-015-0753-7. - comparing in situ and in solution HiC ligation protocol. Mouse liver cells and human ES cells. Two biological and two technical replicates. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70181

  • Trussart, M., F. Serra, D. Bau, I. Junier, L. Serrano, and M. A. Marti-Renom. “Assessing the Limits of Restraint-Based 3D Modeling of Genomes and Genomic Domains.” Nucleic Acids Research 43, no. 7 (April 20, 2015): 3465–77. https://doi.org/10.1093/nar/gkv221. - TADbit - modeling 3D structures from Hi-C data. Hi-C matrix simulation methods. The contact maps and the underlying structures are at http://sgt.cnag.cat/3dg/datasets/ - simulated and real datasets, text files, square interaction matrices

  • Genomic coordinates of replication domains boundaries (mm9, hg19, multiple cell lines), TAD boundaries (hg19, IMR90, 40kb and 20kb resolution) http://mouseencode.org/publications/mcp05/

  • List of 80 studies (315 Hi-C experiments) from different tissues. Plus 30 extra datasets (Supplementary Table 1). ChIP-seq experiments of histone modification marks, and their QC statistics (Supplementary Table 2). https://academic.oup.com/nar/article/46/D1/D52/4584622#107180936 and http://kobic.kr/3div/statistics. From Yang, Dongchan, Insu Jang, Jinhyuk Choi, Min-Seo Kim, Andrew J. Lee, Hyunwoong Kim, Junghyun Eom, Dongsup Kim, Inkyung Jung, and Byungwook Lee. “3DIV: A 3D-Genome Interaction Viewer and Database.” Nucleic Acids Research 46, no. D1 (January 4, 2018): D52–57. https://doi.org/10.1093/nar/gkx1017.

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