Identification of Genetic Variants That Affect Histone Modifications in Human Cells
Abstract
DNA Differences: The extent to which genetic variation affects an individual's phenotype has been difficult to predict because the majority of variation lies outside the coding regions of genes. Now, three studies examine the extent to which genetic variation affects the chromatin of individuals with diverse ancestry and genetic variation (see the Perspective byFurey and Sethupathy).Kasowski et al.(p.750, published online 17 October) examined how genetic variation affects differences in chromatin states and their correlation to histone modifications, as well as more general DNA binding factors.Kilpinen et al.(p.744, published online 17 October) document how genetic variation is linked to allelic specificity in transcription factor binding, histone modifications, and transcription.McVicker et al.(p.747, published online 17 October) identified how quantitative trait loci affect histone modifications in Yoruban individuals and established which specific transcription factors affect such modifications.
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
Cites
Statistics
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?
The locations and sequence content of enhancers provide insights into how non-coding genetic variation may affect gene expression and cellular phenotypes.
“Furthermore, the locations and sequence content of enhancers provide insights into how non-coding genetic variation may affect gene expression and cellular phenotypes (32, 36–38).”
From An environment-dependent transcriptional network specifies human microglia identity (2017) · cites this paper as [37]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Chromatin modifications and their function
Kouzarides, T. (2007) · Cell · doi:10.1016/j.cell.2007.02.005 · Cited by 10,883 · see citing works
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877 · see citing works
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845 · see citing works
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928 · see citing works
Histone modifications at human enhancers reflect global cell-type-specific gene expression
Heintzman, N. D., Hon, G. C., Hawkins, R. D., Kheradpour, P., Stark, A., Harp, L. F., Ye, Z., Lee, L. K., Stuart, R. K., Ching, C. W., et al. (2009) · Nature · doi:10.1038/nature07829 · Cited by 2,533 · see citing works
A unique chromatin signature uncovers early developmental enhancers in humans
Rada-Iglesias, A., Bajpai, R., Swigut, T., Brugmann, S. A., Flynn, R. A., & Wysocka, J. (2011) · Nature · doi:10.1038/nature09692 · Cited by 2,233 · see citing works
Fast and accurate genotype imputation in genome-wide association studies through pre-phasing
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012) · Nature Genetics · doi:10.1038/ng.2354 · Cited by 1,737 · see citing works
The long-range interaction landscape of gene promoters
Sanyal, A., Lajoie, B. R., Jain, G., & Dekker, J. (2012) · Nature · doi:10.1038/nature11279 · Cited by 1,489 · see citing works
Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data.
Degner, J. F., Marioni, J. C., Pai, A. A., Pickrell, J. K., Nkadori, E., Gilad, Y., & Pritchard, J. K. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp579 · Cited by 502 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 24
- [1]ENCODE Project Consortium Nature 489 57 74 2012 22955616 PMC3439153
- [2]Ernst J Nature 473 43 49 2011 21441907 PMC3088773
- [3]Schaub MA Boyle AP Kundaje A Batzoglou S Snyder M Genome Res 22 1748 1759 2012 22955986 PMC3431491
- [4]Kouzarides T Cell 128 693 705 2007 17320507
- [5]Bernstein BE Cell 125 315 326 2006 16630819
- [6]Heintzman ND Nature 459 108 112 2009 19295514 PMC2910248
- [7]Jenuwein T Allis CD Science 293 1074 1080 2001 11498575
- [8]Mikkelsen TS Nature 448 553 560 2007 17603471 PMC2921165
- [9]Rada-Iglesias A Nature 470 279 283 2011 21160473 PMC4445674
- [10]Hoffman MM Nat Methods 9 473 476 2012 22426492 PMC3340533
- [11]Kharchenko PV Nature 471 480 485 2011 21179089 PMC3109908
- [12]Wamstad JA Cell 151 206 220 2012 22981692 PMC3462286
- [13]Henikoff S Shilatifard A Trends Genet 27 389 396 2011 21764166
- [14]Barski A Cell 129 823 837 2007 17512414
- [15]Czermin B Cell 111 185 196 2002 12408863
- [16]Müller J Cell 111 197 208 2002 12408864
- [18]Degner JF Nature 482 390 394 2012 22307276 PMC3501342
- [19]Boyle AP Cell 132 311 322 2008 18243105 PMC2669738
- [20]Gaffney DJ PLOS Genet 8 e1003036 2012 23166509 PMC3499251
- [21]Pickrell JK Nature 464 768 772 2010 20220758 PMC3089435
- [22]Pique-Regi R Genome Res 21 447 455 2011 21106904 PMC3044858
- [23]Reddy TE Genome Res 22 860 869 2012 22300769 PMC3337432
- [24]Arnold P Genome Res 23 60 73 2013 22964890 PMC3530684
- [25]Sanyal A Lajoie BR Jain G Dekker J Nature 489 109 113 2012 22955621 PMC3555147
Cited by
Sorted by citations
Predicting effects of noncoding variants with deep learning–based sequence model
Zhou, J., & Troyanskaya, O. G. (2015) · Nature Methods · doi:10.1038/nmeth.3547 · Cited by 2,338 · see citing works
Function and information content of DNA methylation
Schübeler, D. (2015) · Nature · doi:10.1038/nature14192 · Cited by 2,060 · see citing works
Chromatin architecture reorganization during stem cell differentiation
Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., Ye, Z., Kim, A., Rajagopal, N., Xie, W., et al. (2015) · Nature · doi:10.1038/nature14222 · Cited by 1,646 · see citing works
An environment-dependent transcriptional network specifies human microglia identity
Gosselin, D., Skola, D., Coufal, N. G., Holtman, I. R., Schlachetzki, J. C. M., Sajti, E., Jaeger, B. N., O’Connor, C., Fitzpatrick, C., Pasillas, M. P., et al. (2017) · Science · doi:10.1126/science.aal3222 · Cited by 1,220 · see citing works
Methods of integrating data to uncover genotype-phenotype interactions
Ritchie, M. D., Holzinger, E. R., Li, R., Pendergrass, S. A., & Kim, D. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3868 · Cited by 1,085 · see citing works
The role of regulatory variation in complex traits and disease
Albert, F. W., & Kruglyak, L. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3891 · Cited by 1,047 · see citing works
The selection and function of cell type-specific enhancers
Heinz, S., Romanoski, C. E., Benner, C., & Glass, C. K. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3949 · Cited by 1,010 · see citing works
RNA splicing is a primary link between genetic variation and disease
Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science · doi:10.1126/science.aad9417 · Cited by 660 · see citing works
Self-citationSystems genetics approaches to understand complex traits
Civelek, M., & Lusis, A. J. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3575 · Cited by 621 · see citing works
Gusev, A., Mancuso, N., Won, H., Kousi, M., Finucane, H. K., Reshef, Y., Song, L., Safi, A., Schizophrenia Working Group of the Psychiatric Genomics Consortium, McCarroll, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0092-1 · Cited by 491 · see citing works
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544 · see citing works
Tewhey, R., Kotliar, D., Park, D. S., Liu, B., Winnicki, S., Reilly, S. K., Andersen, K. G., Mikkelsen, T. S., Lander, E. S., Schaffner, S. F., et al. (2016) · Cell · doi:10.1016/j.cell.2016.04.027 · Cited by 480 · see citing works
The Genetics of Transcription Factor DNA Binding Variation
Deplancke, B., Alpern, D., & Gardeux, V. (2016) · Cell · doi:10.1016/j.cell.2016.07.012 · Cited by 390 · see citing works
Batch effects and the effective design of single-cell gene expression studies
Tung, P.-Y., Blischak, J. D., Hsiao, C. J., Knowles, D. A., Burnett, J. E., Pritchard, J. K., & Gilad, Y. (2017) · Scientific Reports · doi:10.1038/srep39921 · Cited by 356 · see citing works
Self-citationTeh, A. L., Pan, H., Chen, L., Ong, M.-L., Dogra, S., Wong, J., MacIsaac, J. L., Mah, S. M., McEwen, L. M., Saw, S.-M., et al. (2014) · Genome Research · doi:10.1101/gr.171439.113 · Cited by 352 · see citing works
Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions
Grubert, F., Zaugg, J. B., Kasowski, M., Ursu, O., Spacek, D. V., Martin, A. R., Greenside, P., Srivas, R., Phanstiel, D. H., Pekowska, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.07.048 · Cited by 319 · see citing works
Population Variation and Genetic Control of Modular Chromatin Architecture in Humans
Waszak, S. M., Delaneau, O., Gschwind, A. R., Kilpinen, H., Raghav, S. K., Witwicki, R. M., Orioli, A., Wiederkehr, M., Panousis, N. I., Yurovsky, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.001 · Cited by 214 · see citing works
Genetic determinants of co-accessible chromatin regions in activated T cells across humans
Gate, R. E., Cheng, C. S., Aiden, A. P., Siba, A., Tabaka, M., Lituiev, D., Machol, I., Gordon, M. G., Subramaniam, M., Shamim, M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0156-2 · Cited by 181 · see citing works
Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants
Zhang, S., Zhang, H., Zhou, Y., Qiao, M., Zhao, S., Kozlova, A., Shi, J., Sanders, A. R., Wang, G., Luo, K., et al. (2020) · Science · doi:10.1126/science.aay3983 · Cited by 127 · see citing works
Discovery and characterization of variance QTLs in human induced pluripotent stem cells
Sarkar, A. K., Tung, P.-Y., Blischak, J. D., Burnett, J. E., Li, Y. I., Stephens, M., & Gilad, Y. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008045 · Cited by 72 · see citing works
Self-citationTranscriptional enhancers and their communication with gene promoters
Ray-Jones, H., & Spivakov, M. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-03903-w · Cited by 81 · see citing works
Sensitive detection of chromatin-altering polymorphisms reveals autoimmune disease mechanisms
del Rosario, R. C.-H., Poschmann, J., Rouam, S. L., Png, E., Khor, C. C., Hibberd, M. L., & Prabhakar, S. (2015) · Nature Methods · doi:10.1038/nmeth.3326 · Cited by 58 · see citing works
Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk
Reshef, Y. A., Finucane, H. K., Kelley, D. R., Gusev, A., Kotliar, D., Ulirsch, J. C., Hormozdiari, F., Nasser, J., O’Connor, L., van de Geijn, B., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0196-7 · Cited by 68 · see citing works
Self-citationLinking the genetic architecture of cytosine modifications with human complex traits
Zhang, X., Moen, E. L., Liu, C., Mu, W., Gamazon, E. R., Delaney, S. M., Wing, C., Godley, L. A., Dolan, M. E., & Zhang, W. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu313 · Cited by 41 · see citing works
- Authors
- McVicker, G., van de Geijn, B., Degner, J. F., Cain, C. E., Banovich, N. E., Raj, A., Lewellen, N., Myrthil, M., Gilad, Y., & Pritchard, J. K.
- Affiliations
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
- Venue
- Science
- Published
- 2013-11-08
- Volume
- 342
- Issue
- 6159
- Pages
- 747-749
- ISSN
- 0036-8075
- 1095-9203
- PMC
- PMC3947669
- Cited by
- 443
- References
- 10
- Language
- en
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
