Cited by 169Genomics and Chromatin DynamicsChromosomal and Genetic VariationsGenomic variations and chromosomal abnormalities

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Comparison of Hi-C results using in-solution versus in-nucleus ligation

Open access

Nagano, Takashi, Várnai, Csilla, Schoenfelder, Stefan, Javierre, Biola-Maria, Wingett, Steven W., Fraser, Peter·2015·Genome Biology

DOI 10.1186/s13059-015-0753-7PMC PMC4580221

Open this paper in CoChat — free account Open PDF

Abstract

BACKGROUND: Chromosome conformation capture and various derivative methods such as 4C, 5C and Hi-C have emerged as standard tools to analyze the three-dimensional organization of the genome in the nucleus. These methods employ ligation of diluted cross-linked chromatin complexes, intended to favor proximity-dependent, intra-complex ligation. During development of single-cell Hi-C, we devised an alternative Hi-C protocol with ligation in preserved nuclei rather than in solution. Here we directly compare Hi-C methods employing in-nucleus ligation with the standard in-solution ligation. RESULTS: We show in-nucleus ligation results in consistently lower levels of inter-chromosomal contacts. Through chromatin mixing experiments we show that a significantly large fraction of inter-chromosomal contacts are the result of spurious ligation events formed during in-solution ligation. In-nucleus ligation significantly reduces this source of experimental noise, and results in improved reproducibility between replicates. We also find that in-nucleus ligation eliminates restriction fragment length bias found with in-solution ligation. These improvements result in greater reproducibility of long-range intra-chromosomal and inter-chromosomal contacts, as well as enhanced detection of structural features such as topologically associated domain boundaries. CONCLUSIONS: We conclude that in-nucleus ligation captures chromatin interactions more consistently over a wider range of distances, and significantly reduces both experimental noise and bias. In-nucleus ligation creates higher quality Hi-C libraries while simplifying the experimental procedure. We suggest that the entire range of 3C applications are likely to show similar benefits from in-nucleus ligation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1186/s13059-015-0753-7

Cites

26 of 26 references verified0 citation errors · 0 not checkable

Statistics

Fig. 1 The frequencies of mapped and filtered trans-chromosomal di-tags (%trans). The percentage of trans-chromosomal di-tags in the Hi-C datasets in this study employing in-solution ligation (ISL; blue), in-nucleus ligation (INL; red) and random ligation (RL; black). Additional datasets from the publications indicated are shown with blue (in-solution ligation), red (in-nucleus ligation), green (TCC) or orange (single-cell Hi-C with in-nucleus ligation)CC BY · PubMed Central

Fig. 2 In-nucleus ligation reduces noise from Hi-C datasets. a The frequencies of hybrid mouse-human di-tags obtained from the mixture of mouse and human cells by in-solution (ISL; blue) and in-nucleus (INL; red) ligation experiments, compared with the mean hybrid di-tag frequencies in unmixed mouse or human samples (single species; white, with standard deviation). b Scatter plots comparing the log2 binned interaction counts for mouse datasets at 10 Mb resolution (top panels), and topologically associated domain (TAD) scale (bottom panels). Colors represent interaction distances according to the color bar shown; red dots represent trans-chromosomal interactions, black dots represent intra-TAD interactions in bottom panels. Dashed lines show the interaction counts corrected for the difference in the total counts. c The ratio of far-cis (>20 Mb) to all cis-chromosomal interaction counts plotted against the ratio of trans-chromosomal to all interaction counts (Pearson R > 0.98)CC BY · PubMed Central

Fig. 3 Reproducibility of cis-chromosomal interactions between replicates. Cis-chromosomal interaction frequency density as a function of the genomic distance for in-solution ligation (ISL; blue) and in-nucleus ligation (INL; red), for mouse foetal liver (a) and human ES cell samples (b). The error bars show one standard deviation from the mean of all chromosomes. c Top panel: Spearman correlation coefficient between replicates as a function of genomic distance. Bottom panel: deviation from expected slope (DES) as a function of genomic distanceCC BY · PubMed Central

Fig. 4 Experimental GC content bias. The mouse in-solution (ISL), in-nucleus (INL) and random (RL) ligations are compared for GC content-related bias matrices, calculated using the Hi-C matrix correction [21], employing a 100-kb bin resolutionCC BY · PubMed Central

Fig. 5 Experimental fragment length bias. The mouse and human in-solution (ISL), in-nucleus (INL) and TCC ligation datasets are compared for fragment length bias matrices, calculated using the Hi-C matrix correction [21], employing a 100-kb bin resolution. a Mouse foetal liver. b Human ES cells. c GM12878 human lymphoblastoid cells [4]CC BY · PubMed Central

Fig. 6 Normalized Hi-C matrices with compartments. Normalized matrices for mouse chromosome 9 from the indicated datasets with the first principal component indicated A and B compartments (defined by Lieberman-Aiden et al. [15]), at the top and left of each map. INL in-nucleus ligation, ISL in-solution ligation, RL random ligationCC BY · PubMed Central

Fig. 7 Reproducibility of the corrected Hi-C matrices. Element-wise comparison of coverage-corrected (a–f) and coverage- and distance-corrected (g–l) Hi-C matrices as indicated. The scatter plots show the log2-corrected counts in one dataset against the corresponding count values in the second dataset, for all cis-chromosomal (blue to green color varying with genomic distance) and trans-chromosomal (red) bin interaction counts. The correction of Imakaev et al. [22] was applied, using a bin resolution of 10 Mb. INL in-nucleus ligation, ISL in-solution ligation, RL random ligationCC BY · PubMed Central

Fig. 8 Comparison of TAD boundary recognition. Average coverage- and distance-corrected Hi-C interaction profiles around TAD boundaries (top panels). Averaged standard score of the interaction directionality indices around TAD boundaries (line graphs). Venn diagrams of boundaries detected in the datasets as shown. Zoomed in views of randomly selected TADs from mouse chromosome 9 for each category (bottom panels). a TAD boundaries detected in both in-nucleus ligation (INL) and both in-solution ligation (ISL) replicates. b TAD boundaries detected by both ISL replicates only. c TAD boundaries detected by both INL replicates onlyCC BY · PubMed Central

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
Spatial partitioning of the regulatory landscape of the X-inactivation centre
Nora, E. P., Lajoie, B. R., Schulz, E. G., Giorgetti, L., Okamoto, I., Servant, N., Piolot, T., van Berkum, N. L., Meisig, J., Sedat, J., et al. (2012) · Nature · doi:10.1038/nature11049 · Cited by 2,895
Three-dimensional folding and functional organization principles of the Drosophila genome
Sexton, T., Yaffe, E., Kenigsberg, E., Bantignies, F., Leblanc, B., Hoichman, M., Parrinello, H., Tanay, A., & Cavalli, G. (2012) · Cell · doi:10.1016/j.cell.2012.01.010 · Cited by 1,983
Single-cell Hi-C reveals cell-to-cell variability in chromosome structure
Nagano, T., Lubling, Y., Stevens, T. J., Schoenfelder, S., Yaffe, E., Dean, W., Laue, E. D., Tanay, A., & Fraser, P. (2013) · Nature · doi:10.1038/nature12593 · Cited by 1,589
Self-citation
Iterative correction of Hi-C data reveals hallmarks of chromosome organization
Imakaev, M., Fudenberg, G., McCord, R. P., Naumova, N., Goloborodko, A., Lajoie, B. R., Dekker, J., & Mirny, L. A. (2012) · Nature Methods · doi:10.1038/nmeth.2148 · Cited by 1,423
A map of the cis-regulatory sequences in the mouse genome
Shen, Y., Yue, F., McCleary, D. F., Ye, Z., Edsall, L., Kuan, S., Wagner, U., Dixon, J., Lee, L., Lobanenkov, V. V., et al. (2012) · Nature · doi:10.1038/nature11243 · Cited by 1,361 · cited 1×
“This was done by multiplying the eigenvector by −1 if the Pearson correlation coefficient of the eigenvector and the H3K4me3 histone modification mark ChIPseq [19, 28] profile was negative.”
Method
Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
Aird, D., Ross, M. G., Chen, W.-S., Danielsson, M., Fennell, T., Russ, C., Jaffe, D. B., Nusbaum, C., & Gnirke, A. (2011) · Genome Biology · doi:10.1186/gb-2011-12-2-r18 · Cited by 1,174
Exploring the three-dimensional organization of genomes: Interpreting chromatin interaction data
Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3454 · Cited by 1,068
Comparative Hi-C Reveals that CTCF Underlies Evolution of Chromosomal Domain Architecture
Vietri Rudan, M., Barrington, C., Henderson, S., Ernst, C., Odom, D. T., Tanay, A., & Hadjur, S. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.02.004 · Cited by 680 · cited 1×
“trans-chromosomal contacts to be intermediate between in-solution and in-nucleus Hi-C ligation [10, 13, 14, 20].”
Background
Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture
Yaffe, E., & Tanay, A. (2011) · Nature Genetics · doi:10.1038/ng.947 · Cited by 614
Spatial Organization of the Mouse Genome and Its Role in Recurrent Chromosomal Translocations
Zhang, Y., McCord, R. P., Ho, Y.-J., Lajoie, B. R., Hildebrand, D. G., Simon, A. C., Becker, M. S., Alt, F. W., & Dekker, J. (2012) · Cell · doi:10.1016/j.cell.2012.02.002 · Cited by 572
Genome architectures revealed by tethered chromosome conformation capture and population-based modeling
Kalhor, R., Tjong, H., Jayathilaka, N., Alber, F., & Chen, L. (2011) · Nature Biotechnology · doi:10.1038/nbt.2057 · Cited by 554
The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements
Schoenfelder, S., Furlan-Magaril, M., Mifsud, B., Tavares-Cadete, F., Sugar, R., Javierre, B.-M., Nagano, T., Katsman, Y., Sakthidevi, M., Wingett, S. W., et al. (2015) · Genome Research · doi:10.1101/gr.185272.114 · Cited by 460
Self-citation
Cohesin-mediated interactions organize chromosomal domain architecture
Sofueva, S., Yaffe, E., Chan, W., Georgopoulou, D., Vietri Rudan, M., Mira‐Bontenbal, H., Pollard, S. M., Schroth, G. P., Tanay, A., & Hadjur, S. (2013) · The EMBO Journal · doi:10.1038/emboj.2013.237 · Cited by 394
The three 'C' s of chromosome conformation capture: controls, controls, controls
Dekker, J. (2005) · Nature Methods · doi:10.1038/nmeth823 · Cited by 358
Whole-genome haplotype reconstruction using proximity-ligation and shotgun sequencing
Selvaraj, S., Dixon, J. R., Bansal, V., & Ren, B. (2013) · Nature Biotechnology · doi:10.1038/nbt.2728 · Cited by 294
Targeted sequencing by proximity ligation for comprehensive variant detection and local haplotyping
de Vree, P. J. P., de Wit, E., Yilmaz, M., van de Heijning, M., Klous, P., Verstegen, M. J. A. M., Wan, Y., Teunissen, H., Krijger, P. H. L., Geeven, G., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2959 · Cited by 274
Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-CPreprint
Dryden, N. H., Broome, L. R., Dudbridge, F., Johnson, N., Orr, N., Schoenfelder, S., Nagano, T., Andrews, S., Wingett, S., Kozarewa, I., et al. (2014) · Genome Research · doi:10.1101/gr.175034.114 · Cited by 261
Self-citation
Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci
Jäger, R., Migliorini, G., Henrion, M., Kandaswamy, R., Speedy, H. E., Heindl, A., Whiffin, N., Carnicer, M. J., Broome, L. R., Dryden, N. H., et al. (2015) · Nature Communications · doi:10.1038/ncomms7178 · Cited by 216
Self-citation
A chromatin insulator driving three-dimensional Polycomb response element (PRE) contacts and Polycomb association with the chromatin fiber
Comet, I. V., Schuettengruber, B., Sexton, T., & Cavalli, G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002059108 · Cited by 126
Disclosure of a structural milieu for the proximity ligation reveals the elusive nature of an active chromatin hub
Gavrilov, A. A., Gushchanskaya, E. S., Strelkova, O., Zhironkina, O., Kireev, I. I., Iarovaia, O. V., & Razin, S. V. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt067 · Cited by 87
SnapShot: Chromosome Conformation Capture
Hakim, O., & Misteli, T. (2012) · Cell · doi:10.1016/j.cell.2012.02.019 · Cited by 64

Research works printed but not linked: 1

Datasets deposited at Gene Expression Omnibus, GSE70181. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=wtmfywywjrshbip&acc=GSE70181 .

Sorted by citations

HiChIP: efficient and sensitive analysis of protein-directed genome architecture
Mumbach, M. R., Rubin, A. J., Flynn, R. A., Dai, C., Khavari, P. A., Greenleaf, W. J., & Chang, H. Y. (2016) · Nature Methods · doi:10.1038/nmeth.3999 · Cited by 1,139
Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters
Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.037 · Cited by 1,046
Self-citation
YY1 Is a Structural Regulator of Enhancer-Promoter Loops
Weintraub, A. S., Li, C. H., Zamudio, A. V., Sigova, A. A., Hannett, N. M., Day, D. S., Abraham, B. J., Cohen, M. A., Nabet, B., Buckley, D. L., et al. (2017) · Cell · doi:10.1016/j.cell.2017.11.008 · Cited by 992
Topologically associating domains and chromatin loops depend on cohesin and are regulated by CTCF, WAPL, and PDS5 proteins
Wutz, G., Várnai, C., Nagasaka, K., Cisneros, D. A., Stocsits, R. R., Tang, W., Schoenfelder, S., Jessberger, G., Muhar, M., Hossain, M. J., et al. (2017) · The EMBO Journal · doi:10.15252/embj.201798004 · Cited by 864
Self-citation
Cell-cycle dynamics of chromosomal organization at single-cell resolution
Nagano, T., Lubling, Y., Várnai, C., Dudley, C., Leung, W., Baran, Y., Mendelson Cohen, N., Wingett, S., Fraser, P., & Tanay, A. (2017) · Nature · doi:10.1038/nature23001 · Cited by 794
Self-citation

See all 169

Authors: Nagano, T., Várnai, C., Schoenfelder, S., Javierre, B.-M., Wingett, S. W., & Fraser, P.
Affiliations: Babraham Institute (GB)
Corresponding author: Nagano, Takashi
Fraser, Peter
ORCID: Nagano, Takashi
Várnai, Csilla
Schoenfelder, Stefan
Javierre, Biola-Maria
Wingett, Steven W.
Fraser, Peter
Venue: Genome Biology
Publisher: Springer Science and Business Media LLC
Published: 2015-08-26
Volume: 16
Issue: 1
Pages: 175-175
ISSN: 1465-6906 (ISSN-L)
1474-760X
DOI: 10.1186/s13059-015-0753-7
PMC: PMC4580221
OpenAlex: W2116261028
Cited by: 166
References: 26
Citations by year: 2026: 4 · 2025: 5 · 2024: 8 · 2023: 8 · 2022: 11 · 2021: 20 · 2020: 17 · 2019: 23 · 2018: 25 · 2017: 27 · 2016: 12 · 2015: 5
FWCI: 9.99
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (tdm)
Locations: Genome biology (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
Apollo (University of Cambridge) (submittedVersion, cc-by)
Apollo (cc-by)
Funders: European Research Council (111608)
BBSRC (BBS/E/B/000C0405)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Keywords: Hi-C, chromosome conformation capture, 3D genome organization, topologically associating domains, single-cell Hi-C
MeSH terms: Animals, Cell Nucleus, Cells, Cultured, Chromatin, Humans, Mice, Inbred C57BL, Genomics, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Comparison of Hi-C results using in-solution versus in-nucleus ligation

Abstract

Overview

Integrity signals

Figures

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks