Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response
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Abstract
Regulatory variants are often context specific, modulating gene expression in a subset of possible cellular states. Although these genetic effects can play important roles in disease, the molecular mechanisms underlying context specificity are poorly understood. Here, we identified shared quantitative trait loci (QTLs) for chromatin accessibility and gene expression in human macrophages exposed to IFNγ, Salmonella and IFNγ plus Salmonella. We observed that ~60% of stimulus-specific expression QTLs with a detectable effect on chromatin altered the chromatin accessibility in naive cells, thus suggesting that they perturb enhancer priming. Such variants probably influence binding of cell-type-specific transcription factors, such as PU.1, which can then indirectly alter the binding of stimulus-specific transcription factors, such as NF-κB or STAT2. Thus, although chromatin accessibility assays are powerful for fine-mapping causal regulatory variants, detecting their downstream effects on gene expression will be challenging, requiring profiling of large numbers of stimulated cellular states and time points.
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Variants associated with chromatin accessibility capture stimulus-sensitive signals and explain a significant proportion of heritability, even more so than eQTLs.
“Second, it has been recently shown that the variants associated with chromatin accessibility capture stimulus-sensitive signals and explain a significant proportion of heritability, even more so than eQTLs47,48.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [47]
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Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437 · see citing works
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447 · see citing works
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 · see citing works
Pattern Recognition Receptors and Inflammation
Takeuchi, O., & Akira, S. (2010) · Cell · doi:10.1016/j.cell.2010.01.022 · Cited by 8,895 · see citing works
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422 · see citing works
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585 · see citing works
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336 · see citing works
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · see citing works
Interferon-γ: an overview of signals, mechanisms and functions
Schroder, K., Hertzog, P. J., Ravasi, T., & Hume, D. A. (2004) · Journal of Leukocyte Biology · doi:10.1189/jlb.0603252 · Cited by 4,120 · see citing works
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716 · see citing works
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352 · see citing works
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679 · see citing works
Liu, J. Z., van Sommeren, S., Huang, H., Ng, S. C., Alberts, R., Takahashi, A., Ripke, S., Lee, J. C., Jostins, L., Shah, T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3359 · Cited by 2,603 · see citing works
A high-performance computing toolset for relatedness and principal component analysis of SNP data
Zheng, X., Levine, D., Shen, J., Gogarten, S. M., Laurie, C. C., & Weir, B. S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts606 · Cited by 2,541 · see citing works
Genetics of rheumatoid arthritis contributes to biology and drug discovery
the RACI consortium, Okada, Y., the GARNET consortium, Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., et al. (2014) · Nature · doi:10.1038/nature12873 · Cited by 2,310 · see citing works
Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples
Wagner, G. P., Kin, K., & Lynch, V. J. (2012) · Theory in Biosciences · doi:10.1007/s12064-012-0162-3 · Cited by 2,085 · see citing works
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Farh, K. K.-H., Marson, A., Zhu, J., Kleinewietfeld, M., Housley, W. J., Beik, S., Shoresh, N., Whitton, H., Ryan, R. J. H., Shishkin, A. A., et al. (2015) · Nature · doi:10.1038/nature13835 · Cited by 1,956 · see citing works
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912 · see citing works
Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity
Weirauch, M. T., Yang, A. W. H., Albu, M., Coté, A. G., Montenegro‐Montero, A., Drewe, P., Najafabadi, H. S., Lambert, S. A., Mann, I. K., Cook, K. B., et al. (2014) · Cell · doi:10.1016/j.cell.2014.08.009 · Cited by 1,705 · see citing works
Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads
Jiang, H., Lei, R., Ding, S., & Zhu, S. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-182 · Cited by 1,525 · see citing works
de Lange, K. M., Moutsianas, L., Lee, J. C., Lamb, C. A., Luo, Y., Kennedy, N. A., Jostins, L., Rice, D. L., Gutierrez-Achury, J., Ji, S.-G., et al. (2017) · Nature Genetics · doi:10.1038/ng.3760 · Cited by 1,445 · see citing works
A high-resolution map of the three-dimensional chromatin interactome in human cells
Jin, F., Li, Y., Dixon, J. R., Selvaraj, S., Ye, Z., Lee, A. Y., Yen, C.-A., Schmitt, A. D., Espinoza, C. A., & Ren, B. (2013) · Nature · doi:10.1038/nature12644 · Cited by 1,208 · see citing works
Stegle, O., Parts, L., Piipari, M., Winn, J., & Durbin, R. (2012) · Nature Protocols · doi:10.1038/nprot.2011.457 · Cited by 1,049 · see citing works
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 · see citing works
Bentham, J., Morris, D. L., Graham, D. S. C., Pinder, C. L., Tombleson, P., Behrens, T. W., Martin, J. J., Fairfax, B. P., Knight, J. C., Chen, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3434 · Cited by 990 · see citing works
Hu, X., & Ivashkiv, L. B. (2009) · Immunity · doi:10.1016/j.immuni.2009.09.002 · Cited by 928 · see citing works
Latent Enhancers Activated by Stimulation in Differentiated Cells
Ostuni, R., Piccolo, V., Barozzi, I., Polletti, S., Termanini, A., Bonifacio, S., Curina, A., Prosperini, E., Ghisletti, S., & Natoli, G. (2013) · Cell · doi:10.1016/j.cell.2012.12.018 · Cited by 867 · see citing works
Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression
Fairfax, B. P., Humburg, P., Makino, S., Naranbhai, V., Wong, D., Lau, E., Jostins, L., Plant, K., Andrews, R., McGee, C., et al. (2014) · Science · doi:10.1126/science.1246949 · Cited by 764 · see citing works
CrossMap: a versatile tool for coordinate conversion between genome assemblies
Zhao, H., Sun, Z., Wang, J., Huang, H., Kocher, J., & Wang, L. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt730 · Cited by 718 · see citing works
DNase I sensitivity QTLs are a major determinant of human expression variation
Degner, J. F., Pai, A. A., Piqué-Regi, R., Veyrieras, J., Gaffney, D. J., Pickrell, J. K., Leon, S. D., Michelini, K., Lewellen, N., Crawford, G. E., et al. (2012) · Nature · doi:10.1038/nature10808 · Cited by 633 · see citing works
Self-citationRemoving technical variability in RNA-seq data using conditional quantile normalization
Hansen, K. D., Irizarry, R. A., & WU, Z. (2012) · Biostatistics · doi:10.1093/biostatistics/kxr054 · Cited by 607 · see citing works
Common genetic variation drives molecular heterogeneity in human iPSCs
Kilpinen, H., Goncalves, A., Leha, A., Afzal, V., Alasoo, K., Ashford, S., Bala, S., Bensaddek, D., Casale, F. P., Culley, O. J., et al. (2017) · Nature · doi:10.1038/nature22403 · Cited by 586 · see citing works
Self-citationRamirez-Carrozzi, V. R., Braas, D., Bhatt, D. M., Cheng, C. S., Hong, C., Doty, K. R., Black, J. C., Hoffmann, A., Carey, M., & Smale, S. T. (2009) · Cell · doi:10.1016/j.cell.2009.04.020 · Cited by 581 · see citing works
Fast and efficient QTL mapper for thousands of molecular phenotypes
Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T., & Delaneau, O. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv722 · Cited by 571 · see citing works
Master Transcription Factors Determine Cell-Type-Specific Responses to TGF-β Signaling
Mullen, A. C., Orlando, D. A., Newman, J. J., Lovén, J., Kumar, R., Bilodeau, S., Reddy, J., Guenther, M. G., DeKoter, R. P., & Young, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.08.050 · Cited by 563 · see citing works
Enhancer loops appear stable during development and are associated with paused polymerase
Ghavi-Helm, Y., Klein, F. A., Pakozdi, T., Ciglar, L., Noordermeer, D., Huber, W., & Furlong, E. E. M. (2014) · Nature · doi:10.1038/nature13417 · Cited by 536 · see citing works
Pique-Regi, R., Degner, J. F., Pai, A. A., Gaffney, D. J., Gilad, Y., & Pritchard, J. K. (2011) · Genome Research · doi:10.1101/gr.112623.110 · Cited by 521 · see citing works
Self-citationGenetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens
Nédélec, Y., Sanz, J., Baharian, G., Szpiech, Z. A., Pacis, A., Dumaine, A., Grenier, J.-C., Freiman, A., Sams, A. J., Hebert, S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.025 · Cited by 512 · see citing works
Jun, G., Flickinger, M., Hetrick, K. N., Romm, J. M., Doheny, K. F., Abecasis, G. R., Boehnke, M., & Kang, H. M. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.09.004 · Cited by 484 · see citing works
Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells
Lee, M. N., Ye, C., Villani, A.-C., Raj, T., Li, W., Eisenhaure, T. M., Imboywa, S. H., Chipendo, P. I., Ran, F. A., Slowikowski, K., et al. (2014) · Science · doi:10.1126/science.1246980 · Cited by 441 · see citing works
Sherwood, R. I., Hashimoto, T., O'Donnell, C. W., Lewis, S., Barkal, A. A., van Hoff, J. P., Karun, V., Jaakkola, T., & Gifford, D. K. (2014) · Nature Biotechnology · doi:10.1038/nbt.2798 · Cited by 416 · see citing works
Tools and best practices for data processing in allelic expression analysis.
Castel, S. E., Levy-Moonshine, A., Mohammadi, P., Banks, E., & Lappalainen, T. (2015) · Genome Biology · doi:10.1186/s13059-015-0762-6 · Cited by 375 · see citing works
TFBSTools: an R/bioconductor package for transcription factor binding site analysis
Tan, G., & Lenhard, B. (2016) · Bioinform. · doi:10.1093/bioinformatics/btw024 · Cited by 370 · see citing works
Qiao, Y., Giannopoulou, E. G., Chan, C. H., Park, S.-H., Gong, S., Chen, J., Hu, X., Elemento, O., & Ivashkiv, L. B. (2013) · Immunity · doi:10.1016/j.immuni.2013.08.009 · Cited by 330 · 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
Trompouki, E., Bowman, T. V., Lawton, L. N., Fan, Z. P., Wu, D.-C., DiBiase, A., Martin, C., Cech, J. N., Sessa, A. K., LeBlanc, J., et al. (2011) · Cell · doi:10.1016/j.cell.2011.09.044 · Cited by 303 · see citing works
Effect of natural genetic variation on enhancer selection and function
Heinz, S., Romanoski, C. E., Benner, C., Allison, K. A., Kaikkonen, M. U., Orozco, L. D., & Glass, C. K. (2013) · Nature · doi:10.1038/nature12615 · Cited by 298 · see citing works
Hierarchy within the mammary STAT5-driven Wap super-enhancer
Shin, H. Y., Willi, M., Yoo, K. H., Zeng, X., Wang, C., Metser, G., & Hennighausen, L. (2016) · Nature Genetics · doi:10.1038/ng.3606 · Cited by 282 · see citing works
Wang, A., Yue, F., Li, Y., Xie, R., Harper, T. C., Patel, N. A., Muth, K., Palmer, J., Qiu, Y., Wang, J., et al. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.02.013 · Cited by 263 · see citing works
Fine-mapping cellular QTLs with RASQUAL and ATAC-seq
Kumasaka, N., Knights, A. J., & Gaffney, D. J. (2015) · Nature Genetics · doi:10.1038/ng.3467 · Cited by 259 · see citing works
Self-citationChun, S., Casparino, A., Patsopoulos, N. A., Croteau-Chonka, D. C., Raby, B. A., De Jager, P. L., Sunyaev, S. R., & Cotsapas, C. (2017) · Nature Genetics · doi:10.1038/ng.3795 · Cited by 259 · see citing works
Barreiro, L. B., Tailleux, L., Pai, A. A., Gicquel, B., Marioni, J. C., & Gilad, Y. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115761109 · Cited by 235 · 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
Kim-Hellmuth, S., Bechheim, M., Pütz, B., Mohammadi, P., Nédélec, Y., Giangreco, N., Becker, J., Kaiser, V. B., Fricker, N., Beier, E., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00366-1 · Cited by 196 · see citing works
Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi
Li, Y., Oosting, M., Deelen, P., Ricaño-Ponce, I., Smeekens, S. P., Jaeger, M., Matzaraki, V., Swertz, M. A., Xavier, R. J., Franke, L., et al. (2016) · Nature Medicine · doi:10.1038/nm.4139 · Cited by 189 · see citing works
Pioneer factors: directing transcriptional regulators within the chromatin environment
Magnani, L., Eeckhoute, J., & Lupien, M. (2011) · Trends in Genetics · doi:10.1016/j.tig.2011.07.002 · Cited by 161 · see citing works
Conditional eQTL analysis reveals allelic heterogeneity of gene expression
Jansen, R., Hottenga, J.-J., Nivard, M. G., Abdellaoui, A., Laport, B., de Geus, E. J., Wright, F. A., Penninx, B. W. J. H., & Boomsma, D. I. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx043 · Cited by 141 · see citing works
Guo, H., Fortune, M. D., Burren, O. S., Schofield, E. C., Todd, J. A., & Wallace, C. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv077 · Cited by 139 · see citing works
Davis, J. R., Frésard, L., Knowles, D. A., Pala, M., Bustamante, C. D., Battle, A. J., & Montgomery, S. B. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.021 · Cited by 138 · see citing works
Impact of regulatory variation across human iPSCs and differentiated cellsPreprint
Banovich, N. E., Li, Y., Raj, A., Ward, M. C., Greenside, P., Calderon, D., Tung, P., Burnett, J. E., Myrthil, M., Thomas, S. M., et al. (2017) · Genome Research · doi:10.1101/gr.224436.117 · Cited by 129 · see citing works
Pai, A. A., Cain, C. E., Mizrahi-Man, O., Leon, S. D., Lewellen, N., Veyrieras, J., Degner, J. F., Gaffney, D. J., Pickrell, J. K., Stephens, M., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1003000 · Cited by 108 · see citing works
Self-citationAlasoo, K., Martinez, F. O., Hale, C., Gordon, S., Powrie, F., Dougan, G., Mukhopadhyay, S., & Gaffney, D. J. (2015) · Scientific Reports · doi:10.1038/srep12524 · Cited by 103 · see citing works
Self-citationJin, F., Li, Y., Ren, B., & Natarajan, R. D. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017214108 · Cited by 83 · see citing works
Characterizing the genetic basis of innate immune response in TLR4-activated human monocytes
Kim-Hellmuth, S., Becker, J., Bechheim, M., Kaiser, V. B., Noursadeghi, M., Fricker, N., Beier, E., Klaschik, S., Boor, P., Hess, T., et al. (2014) · Nature Communications · doi:10.1038/ncomms6236 · Cited by 74 · see citing works
Host Genetic Variation Influences Gene Expression Response to Rhinovirus Infection
Çalışkan, M., Baker, S. W., Gilad, Y., & Ober, C. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005111 · Cited by 70 · see citing works
Bojcsuk, D., Nagy, G., & Bálint, B. L. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1283 · Cited by 67 · see citing works
A Distal Locus Element Mediates IFN-γ Priming of Lipopolysaccharide-Stimulated TNF Gene Expression
Chow, N. A., Jasenosky, L. D., & Goldfeld, A. E. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.11.011 · Cited by 26 · see citing works
Kim-Hellmuth, S., Bechheim, M., Pütz, B., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/116376 · Cited by 25 · see citing works
Impact of regulatory variation across human iPSCs and differentiated cellsPreprint
Banovich, N. E., Li, Y., Raj, A., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/091660 · Cited by 20 · see citing works
Alasoo, K., Martínez, F. O., Hale, C., et al. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/014209 · Cited by 10 · see citing works
Self-citationGenetic determinants of chromatin accessibility in T cell activation across humansPreprint
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. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/090241 · Cited by 7 · see citing works
Kaur Alasoo [Aut, C. (2017) · NCI BioConductor · doi:10.18129/b9.bioc.wiggleplotr · Cited by 6 · see citing works
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- [64]Li H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM arXiv [q-bio.GN] 2013
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Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017) · Cell · doi:10.1016/j.cell.2017.05.038 · Cited by 2,851 · see citing works
New insights into the genetic etiology of Alzheimer’s disease and related dementias
Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01024-z · Cited by 2,498 · see citing works
Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Holland, D., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00921-z · Cited by 1,011 · see citing works
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Eizirik, D. L., Pasquali, L., & Cnop, M. (2020) · Nature Reviews Endocrinology · doi:10.1038/s41574-020-0355-7 · Cited by 854 · see citing works
Cano-Gamez, E., & Trynka, G. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00424 · Cited by 608 · see citing works
Schwartzentruber, J., Cooper, S., Liu, J. Z., Barrio-Hernandez, I., Bello, E., Kumasaka, N., Young, A. M. H., Franklin, R. J. M., Johnson, T., Estrada, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00776-w · Cited by 532 · see citing works
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A compendium of uniformly processed human gene expression and splicing quantitative trait loci
Kerimov, N., Hayhurst, J. D., Peikova, K., Manning, J. R., Walter, P., Kolberg, L., Samoviča, M., Sakthivel, M. P., Kuzmin, I., Trevanion, S. J., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00924-w · Cited by 440 · see citing works
Self-citationEliciting priors and relaxing the single causal variant assumption in colocalisation analyses
Wallace, C. (2020) · PLOS Genetics · doi:10.1371/journal.pgen.1008720 · Cited by 441 · see citing works
Tximeta: Reference sequence checksums for provenance identification in RNA-seq
Love, M. I., Soneson, C., Hickey, P. F., Johnson, L. K., Pierce‐Ward, N. T., Shepherd, L. A., Morgan, M. T., & Patro, R. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007664 · Cited by 360 · see citing works
Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases
Ota, M., Nagafuchi, Y., Hatano, H., Ishigaki, K., Terao, C. C., Takeshima, Y., Yanaoka, H., Kobayashi, S., Okubo, M., Shirai, H., et al. (2021) · Cell · doi:10.1016/j.cell.2021.03.056 · Cited by 322 · see citing works
Cuomo, A. S. E., Seaton, D. D., McCarthy, D. J., Martinez, I., Bonder, M. J., Garcia-Bernardo, J., Amatya, S., Madrigal, P., Isaacson, A., Buettner, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14457-z · Cited by 331 · see citing works
Self-citationDream: powerful differential expression analysis for repeated measures designs
Hoffman, G. E., & Roussos, P. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btaa687 · Cited by 319 · see citing works
Genetic Architectures of Childhood- and Adult-Onset Asthma Are Partly Distinct
Ferreira, M. A. R., Mathur, R., Vonk, J. M., Szwajda, A., Brumpton, B. M., Granell, R., Brew, B. K., Ullemar, V., Lu, Y., Jiang, Y., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.02.022 · Cited by 305 · see citing works
Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation
Jerber, J., Seaton, D. D., Cuomo, A. S. E., Kumasaka, N., Haldane, J., Steer, J., Patel, M. J., Pearce, D., Andersson, M. H. L., Bonder, M. J., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00801-6 · Cited by 288 · see citing works
Self-citationSey, N. Y. A., Hu, B., Mah, W., Fauni, H., McAfee, J. C., Rajarajan, P., Brennand, K. J., Akbarian, S., & Won, H. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0603-0 · Cited by 297 · see citing works
Where Are the Disease-Associated eQTLs?
Umans, B. D., Battle, A., & Gilad, Y. (2021) · Trends in Genetics · doi:10.1016/j.tig.2020.08.009 · Cited by 296 · see citing works
Landscape of stimulation-responsive chromatin across diverse human immune cells
Calderon, D., Nguyen, M. L. T., Mezger, A., Kathiria, A. S., Müller, F., Nguyen, V. Q., Lescano, N., Wu, B., Trombetta, J. J., Ribado, J. V., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0505-9 · Cited by 282 · see citing works
Human iPSC banking: barriers and opportunities
Huang, C., Liu, C.-L., Ting, C.-Y., Chiu, Y.-T., Cheng, Y., Nicholson, M. W., & Hsieh, P. C. H. (2019) · Journal of Biomedical Science · doi:10.1186/s12929-019-0578-x · Cited by 216 · see citing works
A Map of Transcriptional Heterogeneity and Regulatory Variation in Human Microglia
Young, A. M. H., Kumasaka, N., Calvert, F., Hammond, T. R., Knights, A., Panousis, N., Park, J. S., Schwartzentruber, J., Liu, J., Kundu, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00875-2 · Cited by 213 · see citing works
Self-citationDiscovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens
Morris, J. A., Caragine, C., Daniloski, Z., Domingo, J., Barry, T., Lu, L., Davis, K., Ziosi, M., Glinos, D. A., Hao, S., et al. (2023) · Science · doi:10.1126/science.adh7699 · Cited by 208 · see citing works
Immune disease risk variants regulate gene expression dynamics during CD4+ T cell activation
Soskic, B., Cano-Gamez, E., Smyth, D. J., Ambridge, K., Ke, Z., Matte, J. C., Bossini‐Castillo, L., Kaplanis, J., Ramirez-Navarro, L., Lorenc, A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01066-3 · Cited by 189 · see citing works
Human Immunology through the Lens of Evolutionary Genetics
Quintana‐Murci, L. (2019) · Cell · doi:10.1016/j.cell.2019.02.033 · Cited by 171 · see citing works
Genetics of the human microglia regulome refines Alzheimer’s disease risk loci
Kosoy, R., Fullard, J. F., Zeng, B., Bendl, J., Dong, P., Rahman, S., Kleopoulos, S. P., Shao, Z., Girdhar, K., Humphrey, J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01149-1 · Cited by 168 · see citing works
High-Diversity Mouse Populations for Complex Traits
Saul, M. C., Philip, V. M., Reinholdt, L. G., & Chesler, E. J. (2019) · Trends in Genetics · doi:10.1016/j.tig.2019.04.003 · Cited by 165 · see citing works
Ramos-Rodríguez, M., Raurell‐Vila, H., Colli, M. L., Alvelos, M. I., Subirana-Granés, M., Juan‐Mateu, J., Norris, R., Turatsinze, J., Nakayasu, E. S., Webb‐Robertson, B., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0524-6 · Cited by 155 · see citing works
A disease-associated gene desert directs macrophage inflammation through ETS2
Stankey, C., Bourges, C., Haag, L., Turner-Stokes, T., Piedade, A., Palmer-Jones, C., Papa, I., dos Santos, M. S., Zhang, Q., Cameron, A., et al. (2024) · Nature · doi:10.1038/s41586-024-07501-1 · Cited by 136 · see citing works
Budu‐Aggrey, A., Kilanowski, A., Sobczyk, M., Shringarpure, S., Mitchell, R. E., Reis, K., Reigo, A., Mägi, R., Nelis, M., Tanaka, N., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41180-2 · Cited by 135 · see citing works
Chromatin activity at GWAS loci identifies T cell states driving complex immune diseases
Soskic, B., Cano-Gamez, E., Smyth, D. J., Rowan, W. C., Nakić, N., Esparza-Gordillo, J., Bossini‐Castillo, L., Tough, D. F., Larminie, C. G. C., Bronson, P. G., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0493-9 · Cited by 128 · see citing works
A practical view of fine-mapping and gene prioritization in the post-genome-wide association era
Broekema, R., Bakker, O. B., & Jonkers, I. H. (2020) · Open Biology · doi:10.1098/rsob.190221 · Cited by 127 · see citing works
Donovan, M. K. R., D’Antonio‐Chronowska, A., D’Antonio, M., & Frazer, K. A. (2020) · Nature Communications · doi:10.1038/s41467-020-14561-0 · Cited by 123 · see citing works
Bovijn, J., Krebs, K., Chen, C.-Y., Boxall, R., Censin, J. C., Ferreira, T., Pulit, S. L., Glastonbury, C. A., Laber, S., Millwood, I. Y., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6570 · Cited by 119 · see citing works
Knowles, D. A., Burrows, C. K., Blischak, J., Patterson, K. M., Serie, D., Norton, N., Ober, C., Pritchard, J. K., & Gilad, Y. (2018) · eLife · doi:10.7554/elife.33480 · Cited by 116 · see citing works
Magusali, N., Graham, A. C., Piers, T. M., Panichnantakul, P., Yaman, U., Shoai, M., Reynolds, R. H., Botia, J. A., Brookes, K. J., Guetta-Baranes, T., et al. (2021) · Brain · doi:10.1093/brain/awab337 · Cited by 111 · see citing works
“OAS1 is expressed by multiple cell types in the myeloid lineage including monocytes, macrophages, and microglia, as well as natural killer cell lymphocytes.(33,81,82,94)”
BackgroundGenetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk
Salih, D. A., Bayram, S., Guelfi, S., Reynolds, R. H., Shoai, M., Ryten, M., Brenton, J. W., Zhang, D., Matarin, M., Botia, J. A., et al. (2019) · Brain Communications · doi:10.1093/braincomms/fcz022 · Cited by 110 · see citing works
Nonparametric expression analysis using inferential replicate counts
Zhu, A., Srivastava, A., Ibrahim, J. G., Patro, R., & Love, M. I. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz622 · Cited by 110 · see citing works
Genetic and molecular architecture of complex traits
Lappalainen, T., Li, Y., Ramachandran, S., & Gusev, A. (2024) · Cell · doi:10.1016/j.cell.2024.01.023 · Cited by 108 · see citing works
Liang, D., Elwell, A. L., Aygün, N., Krupa, O., Wolter, J. M., Kyere, F. A., Lafferty, M. J., Cheek, K. E., Courtney, K. P., Yusupova, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00858-w · Cited by 83 · see citing works
Molecular quantitative trait loci
Aguet, F., Alasoo, K., Li, Y. I., Battle, A., Im, H. K., Montgomery, S. B., & Lappalainen, T. (2023) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00188-6 · Cited by 98 · see citing works
Self-citationQuantification, Dynamic Visualization, and Validation of Bias in ATAC-Seq Data with ataqv
Orchard, P., Kyono, Y., Hensley, J., Kitzman, J. O., & Parker, S. C. J. (2020) · Cell Systems · doi:10.1016/j.cels.2020.02.009 · Cited by 94 · see citing works
Decoding the genetic and epigenetic basis of asthma
Stikker, B., Hendriks, R. W., & Stadhouders, R. (2023) · Allergy · doi:10.1111/all.15666 · Cited by 95 · see citing works
Genetics of Anthracycline Cardiomyopathy in Cancer Survivors
Bhatia, S. (2020) · JACC CardioOncology · doi:10.1016/j.jaccao.2020.09.006 · Cited by 88 · see citing works
Epigenetic reprogramming of immune cells in injury, repair, and resolution
Placek, K., Schultze, J. L., & Aschenbrenner, A. C. (2019) · Journal of Clinical Investigation · doi:10.1172/jci124619 · Cited by 83 · see citing works
Snyder‐Mackler, N., Sanz, J., Kohn, J. N., Voyles, T., Piqué-Regi, R., Wilson, M. E., Barreiro, L. B., & Tung, J. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1811758115 · Cited by 79 · see citing works
Global discovery of lupus genetic risk variant allelic enhancer activity
Lu, X., Chen, X., Forney, C. R., Donmez, O. A., Miller, D., Parameswaran, S., Hong, T., Huang, Y., Pujato, M. A., Cazares, T. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21854-5 · Cited by 74 · see citing works
Evolutionary and functional impact of common polymorphic inversions in the human genome
Giner-Delgado, C., Villatoro, S., Lerga-Jaso, J., Gayà‐Vidal, M., Oliva, M., Castellano, D., Pantano, L., Bitarello, B. D., Izquierdo, D., Noguera, I., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12173-x · Cited by 74 · see citing works
Bonder, M. J., Smail, C., Gloudemans, M. J., Frésard, L., Jakubosky, D. A., D’Antonio, M., Li, X., Ferraro, N. M., Carcamo‐Orive, I., Mirauta, B. A., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00800-7 · Cited by 68 · see citing works
Interpreting non-coding disease-associated human variants using single-cell epigenomics
Gaulton, K. J., Preißl, S., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00598-6 · Cited by 79 · see citing works
The impact of cell type and context-dependent regulatory variants on human immune traits
Mu, Z., Wei, W., Fair, B. J., Miao, J., Zhu, P., & Li, Y. (2021) · Genome biology · doi:10.1186/s13059-021-02334-x · Cited by 67 · see citing works
Yang, J., McGovern, A., Martin, P., Duffus, K., Ge, X. J., Zarrineh, P., Morris, A. P., Adamson, A. D., Fraser, P., Rattray, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18180-7 · Cited by 71 · see citing works
Approaches and advances in the genetic causes of autoimmune disease and their implications
Inshaw, J. R. J., Cutler, A. J., Burren, O. S., Stefana, M. I., & Todd, J. A. (2018) · Nature Immunology · doi:10.1038/s41590-018-0129-8 · Cited by 70 · see citing works
Findley, A. S., Monziani, A., Richards, A. L., Rhodes, K., Ward, M. C., Kalita, C. A., Alazizi, A., Pazokitoroudi, A., Sankararaman, S., Wen, X., et al. (2021) · eLife · doi:10.7554/elife.67077 · Cited by 66 · see citing works
Baca, S. C., Singler, C., Zacharia, S., Seo, J.-H., Morova, T., Hach, F., Ding, Y., Schwarz, T., Huang, C.-C. F., Anderson, J. R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01168-y · Cited by 30 · see citing works
Type 2 Diabetes–Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets
Khetan, S., Kursawe, R., Youn, A., Lawlor, N. T., Jillette, A., Márquez, E. J., Ucar, D., & Stitzel, M. L. (2018) · Diabetes · doi:10.2337/db18-0393 · Cited by 61 · see citing works
Genetic effects on promoter usage are highly context-specific and contribute to complex traits
Alasoo, K., Rodrigues, J., Danesh, J., Freitag, D. F., Paul, D. S., & Gaffney, D. J. (2019) · eLife · doi:10.7554/elife.41673 · Cited by 63 · see citing works
Self-citationTissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles
Sakaue, S., Weinand, K., Isaac, S., Dey, K. K., Jagadeesh, K. A., Kanai, M., Watts, G. F. M., Zhu, Z., Accelerating Medicines Partnership® RA/SLE Program and Network, Albrecht, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01682-1 · Cited by 60 · see citing works
GRaNIE and GRaNPA: inference and evaluation of enhancer‐mediated gene regulatory networks
Kamal, A., Arnold, C., Claringbould, A., Moussa, R., Servaas, N. H., Kholmatov, M. M., Daga, N., Nogina, D., Müller‐Dott, S., Reyes‐Palomares, A., et al. (2023) · Molecular Systems Biology · doi:10.15252/msb.202311627 · Cited by 63 · see citing works
Genotype × environment interactions in gene regulation and complex traits
Boye, C., Nirmalan, S., Ranjbaran, A., & Luca, F. (2024) · Nature Genetics · doi:10.1038/s41588-024-01776-w · Cited by 65 · see citing works
Genetic effects on liver chromatin accessibility identify disease regulatory variants.
Currin, K. W., Erdos, M., Narisu, N., Rai, V., Vadlamudi, S., Perrin, H. J., Idol, J. R., Yan, T.-F., Albanus, R. D., Broadaway, K. A., et al. (2021) · American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.05.001 · Cited by 55 · see citing works
Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver
Çalışkan, M., Manduchi, E., Rao, H. S., Segert, J. A., Beltrame, M. H., Trizzino, M., Park, Y., Baker, S. W., Chesi, A., Johnson, M. E., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.05.010 · Cited by 57 · see citing works
Kerimov, N., Tambets, R., Hayhurst, J. D., Rahu, I., Kolberg, P., Raudvere, U., Kuzmin, I., Chowdhary, A., Vija, A., Teras, H., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010932 · Cited by 60 · see citing works
Self-citationBrain-trait-associated variants impact cell-type-specific gene regulation during neurogenesis
Aygün, N., Elwell, A. L., Liang, D., Lafferty, M. J., Cheek, K. E., Courtney, K. P., Mory, J. T., Hadden-Ford, E., Krupa, O., de la Torre-Ubieta, L., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.07.011 · Cited by 54 · see citing works
Immune disease variants modulate gene expression in regulatory CD4+ T cells
Bossini‐Castillo, L., Glinos, D. A., Kunowska, N., Golda, G., Lamikanra, A., Spitzer, M., Soskic, B., Cano-Gamez, E., Smyth, D. J., Cattermole, C., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100117 · Cited by 58 · see citing works
Self-citationCuomo, A. S. E., Seaton, D. D., McCarthy, D. J., Martinez, I., Bonder, M. J., Garcia‐Bernardo, J., Amatya, S., Madrigal, P., Isaacson, A., Buettner, F., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/630996 · Cited by 57 · see citing works
Self-citationWard, M. C., Banovich, N. E., Sarkar, A., Stephens, M., & Gilad, Y. (2021) · eLife · doi:10.7554/elife.57345 · Cited by 50 · see citing works
ideal: an R/Bioconductor package for interactive differential expression analysis
Marini, F., Linke, J., & Binder, H. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03819-5 · Cited by 55 · see citing works
Keele, G. R., Quach, B. C., Israel, J. W., Chappell, G. A., Lewis, L., Safi, A., Simon, J. M., Cotney, P. A., Crawford, G. E., Valdar, W. S. J., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008537 · Cited by 47 · see citing works
Naive Pluripotent Stem Cells Exhibit Phenotypic Variability that Is Driven by Genetic Variation
Ortmann, D., Brown, S. E., Czechanski, A., Aydin, S. C., Muraro, D., Huang, Y., Tomaz, R. A., Osnato, A., Canu, G., Wesley, B. T., et al. (2020) · Cell stem cell · doi:10.1016/j.stem.2020.07.019 · Cited by 53 · see citing works
Lynall, M.-E., Soskic, B., Hayhurst, J. D., Schwartzentruber, J., Levey, D. F., Pathak, G. A., Polimanti, R. A., Gelernter, J. E., Stein, M. B., Trynka, G., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33885-7 · Cited by 50 · see citing works
Skelly, D. A., Czechanski, A., Byers, C., Aydin, S. C., Spruce, C. A., Olivier, C., Choi, K., Gatti, D. M., Raghupathy, N., Keele, G. R., et al. (2020) · Cell stem cell · doi:10.1016/j.stem.2020.07.005 · Cited by 53 · see citing works
Benaglio, P., Newsome, J. M., Han, J. Y., Chiou, J., Aylward, A., Corban, S., Miller, M., Okino, M.-L., Kaur, J., Preißl, S., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010759 · Cited by 51 · see citing works
GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data
Marini, F., Ludt, A., Linke, J., & Strauch, K. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04461-5 · Cited by 45 · see citing works
Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
McAfee, J. C., Lee, S., Lee, J., Bell, J., Krupa, O., Davis, J. E., Insigne, K. D., Bond, M. L., Zhao, N., Boyle, A. P., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100404 · Cited by 49 · see citing works
Transcription factor regulation of eQTL activity across individuals and tissues
Flynn, E. D., Tsu, A. L., Kasela, S., Kim-Hellmuth, S., Aguet, F., Ardlie, K., Bussemaker, H. J., Mohammadi, P., & Lappalainen, T. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1009719 · Cited by 47 · see citing works
Mapping interindividual dynamics of innate immune response at single-cell resolution
Kumasaka, N., Rostom, R., Huang, N., Polański, K., Meyer, K. B., Patel, S. R., Boyd, R., Gomez, C., Barnett, S. N., Panousis, N. I., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01421-y · Cited by 46 · see citing works
Massively parallel functional dissection of schizophrenia-associated noncoding genetic variants
Rummel, C. K., Gagliardi, M., Ahmad, R., Herholt, A., Jiménez-Barrón, L. T., Murek, V., Weigert, L., Hausruckinger, A., Maidl, S., Hauger, B., et al. (2023) · Cell · doi:10.1016/j.cell.2023.09.015 · Cited by 48 · see citing works
D’Antonio, M., Nguyen, J., Arthur, T. D., Matsui, H., D’Antonio‐Chronowska, A., Frazer, K. A., Neale, B. M., Daly, M. J., Ganna, A., Stevens, C. R., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110020 · Cited by 44 · see citing works
Aracena, K. A., Lin, Y., Luo, K., Pacis, A., Gona, S., Mu, Z., Yotova, V., Sindeaux, R., Pramatarova, A., Simon, M.-M., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01668-z · Cited by 42 · see citing works
Largest GWAS (N=1,126,563) of Alzheimer’s Disease Implicates Microglia and Immune CellsPreprint
Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., Martinsen, A. E., et al. (2020) · medRxiv · doi:10.1101/2020.11.20.20235275 · Cited by 42 · see citing works
Single-cell analysis of cis-regulatory elements
Marand, A. P., & Schmitz, R. J. (2021) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2021.102094 · Cited by 41 · see citing works
Chromatin accessibility associates with protein-RNA correlation in human cancer
Sanghi, A., Gruber, J. J., Metwally, A. A., Jiang, L., Reynolds, W. D., Sunwoo, J. B., Orloff, L. A., Chang, H. Y., Kasowski, M. M., & Snyder, M. P. (2021) · Nature Communications · doi:10.1038/s41467-021-25872-1 · Cited by 41 · see citing works
Arthur, T. D., Nguyen, J., Henson, B. A., D’Antonio‐Chronowska, A., Jaureguy, J., Silva, N., Arias, A. D., Benaglio, P., Berggren, W. T., Borja, V., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100775 · Cited by 39 · see citing works
A generally conserved response to hypoxia in iPSC-derived cardiomyocytes from humans and chimpanzees
Ward, M. C., & Gilad, Y. (2019) · eLife · doi:10.7554/elife.42374 · Cited by 38 · see citing works
Huang, Q. Q., Tang, H. H. F., Teo, S. M., Mok, D., Ritchie, S. C., Nath, A. P., Brożyńska, M., Salim, A., Bakshi, A., Holt, B. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17477-x · Cited by 38 · see citing works
Zhou, T., Zhu, X., Ye, Z., Wang, Y., Yao, C., Xu, N., Zhou, M., Ma, J., Qin, Y., Shen, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29514-y · Cited by 36 · see citing works
Stikker, B., Stik, G., van Ouwerkerk, A. F., Trap, L., Spicuglia, S., Hendriks, R. W., & Stadhouders, R. (2022) · Genome biology · doi:10.1186/s13059-022-02669-z · Cited by 36 · see citing works
Zhang, P., Amarasinghe, H. E., Whalley, J. P., Tay, C., Fang, H., Migliorini, G., Brown, A., Allcock, A., Scozzafava, G., Rath, P., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02702-1 · Cited by 35 · see citing works
Selvarajan, I., Toropainen, A., Garske, K. M., Rodríguez, M. L., Ko, A., Miao, Z., Kamińska, D., Õunap, K., Örd, T., Ravindran, A., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.02.006 · Cited by 34 · see citing works
Beyond GWAS: from simple associations to functional insights
Ishigaki, K. (2021) · Seminars in Immunopathology · doi:10.1007/s00281-021-00894-5 · Cited by 34 · see citing works
The major genetic risk factor for severe COVID-19 is associated with protection against HIV
Zeberg, H. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2116435119 · Cited by 34 · see citing works
Fang, H., Chen, L., & Knight, J. C. (2019) · The Lancet Rheumatology · doi:10.1016/s2665-9913(19)30134-1 · Cited by 31 · see citing works
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- Authors
- HIPSCI Consortium, Alasoo, K., Rodrigues, J., Mukhopadhyay, S., Knights, A. J., Mann, A. L., Kundu, K., Hale, C., Dougan, G., & Gaffney, D. J.
- Affiliations
- Wellcome Sanger Institute (GB)
- University of Cambridge (GB)
- Corresponding author
- Alasoo, Kaur
- Gaffney, Daniel J.
- ORCID
- Venue
- Nature Genetics
- Published
- 2018-01-29
- Volume
- 50
- Issue
- 3
- Pages
- 424-431
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6548559
- OpenAlex
- W2785443776
- Cited by
- 338
- References
- 74
- Citations by year
- 2026: 37 · 2025: 45 · 2024: 50 · 2023: 45 · 2022: 35 · 2021: 48 · 2020: 36 · 2019: 33 · 2018: 7 · 2017: 2
- FWCI
- 11.29
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Research Portal (King's College London) (submittedVersion)
- Apollo
- Funders
- Life Technologies Corporation
- Wellcome Trust (WT099754, 098503, WT 098051, 098051)
- LifeArc
- Eesti Teadusagentuur
- Medical Research Council (MC_PC_12026)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- chromatin accessibility, expression quantitative trait loci, macrophages, interferon-gamma, Salmonella, immune response, regulatory variants, PU.1, NF-κB, STAT2, transcription factor binding, quantitative trait loci
- MeSH terms
- Cells, Cultured, Chromatin, Enhancer Elements, Genetic, Female, Humans, Immunity, Cellular, Macrophages, Male, Protein Binding, Salmonella Infections, Salmonella typhimurium, Transcription Factors, Gene Expression, Quantitative Trait Loci
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