Wei, K. et al. Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582, 259–264 (2020).
Google Scholar
Cembrowski, M. S. & Menon, V. Continuous variation within cell types of the nervous system. Trends Neurosci. 41, 337–348 (2018).
Google Scholar
Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).
Google Scholar
Chun, S. et al. Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types. Nat. Genet. 49, 600–605 (2017).
Google Scholar
Umans, B. D., Battle, A. & Gilad, Y. Where are the disease-associated eQTLs? Trends Genet. 37, 109–124 (2021).
Google Scholar
Gutierrez-Arcelus, M. et al. Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci. Nat. Genet. 52, 247–253 (2020).
Google Scholar
Davenport, E. E. et al. Discovering in vivo cytokine–eQTL interactions from a lupus clinical trial. Genome Biol. 19, 168 (2018).
Google Scholar
Strober, B. J. et al. Dynamic genetic regulation of gene expression during cellular differentiation. Science 364, 1287–1290 (2019).
Google Scholar
Cuomo, A. S. E. et al. Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression. Nat. Commun. 11, 810 (2020).
Google Scholar
Zhernakova, D. V. et al. Identification of context-dependent expression quantitative trait loci in whole blood. Nat. Genet. 49, 139–145 (2017).
Google Scholar
Moore, R. et al. A linear mixed-model approach to study multivariate gene-environment interactions. Nat. Genet. 51, 180–186 (2019).
Google Scholar
Kim-Hellmuth, S. et al. Cell type-specific genetic regulation of gene expression across human tissues. Science 369, eaaz8528 (2020).
Google Scholar
Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2016).
Google Scholar
Trynka, G. et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat Genet. 45, 124–130 (2013).
Google Scholar
Farh, K. H. et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337–343 (2014).
Google Scholar
Wambre, E. et al. A phenotypically and functionally distinct human TH2 cell subpopulation is associated with allergic disorders. Sci. Transl. Med. 9, eaam9171 (2017).
Google Scholar
Arlehamn, C. L. et al. Transcriptional profile of tuberculosis antigen-specific T cells reveals novel multifunctional features. J. Immunol. 193, 2931–2940 (2014).
Google Scholar
Eizenberg-Magar, I. et al. Diverse continuum of CD4+ T-cell states is determined by hierarchical additive integration of cytokine signals. Proc. Natl Acad. Sci. USA 114, E6447–E6456 (2017).
Google Scholar
Annunziato, F., Cosmi, L., Liotta, F., Maggi, E. & Romagnini, S. Defining the human T helper 17 cell phenotype. Trends Immunol. 33, 505–512 (2012).
Google Scholar
Kiner, E. et al. Gut CD4+ T cell phenotypes are a continuum molded by microbes, not by TH archetypes. Nat. Immunol. 22, 216–228 (2021).
Google Scholar
van der Wijst, M. G. P. et al. Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs. Nat. Genet. 50, 493–497 (2018).
Google Scholar
Jerber, J. et al. Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation. Nat. Genet. 53, 304–312 (2021).
Google Scholar
Neavin, D. et al. Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells. Genome Biol. 22, 76 (2021).
Google Scholar
Randolph, H. E. et al. Genetic ancestry effects on the response to viral infection are pervasive but cell type specific. Science 374, 1127–1133 (2021).
Google Scholar
Nathan, A. et al. Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease. Nat. Immunol. 22, 781–793 (2021).
Google Scholar
Luo, Y. et al. Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians. Nat. Commun. 10, 3765 (2019).
Google Scholar
Chen, L. et al. Genetic drivers of epigenetic and transcriptional variation in human immune cells. Cell 167, 1398–1414 (2016).
Google Scholar
Kasela, S. et al. Pathogenic implications for autoimmune mechanisms derived by comparative eQTL analysis of CD4+ versus CD8+ T cells. PLoS Genet. 13, e1006643 (2017).
Google Scholar
GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).
Google Scholar
The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Google Scholar
Schmiedel, B. J. et al. Impact of genetic polymorphisms on human immune cell gene expression. Cell 175, 1701–1715 (2018).
Google Scholar
Rothenberg, E. V. & Taghon, T. Molecular genetics of T cell development. Annu. Rev. Immunol. 23, 601–649 (2005).
Google Scholar
Townes, F. W., Hicks, S. C., Aryee, M. J. & Irizarry, R. A. Feature selection and dimension reduction for single-cell RNA-seq based on a multinomial model. Genome Biol. 20, 295 (2019).
Google Scholar
Sarkar, A. & Stephens, M. Separating measurement and expression models clarifies confusion in single-cell RNA sequencing analysis. Nat. Genet. 53, 770–777 (2021).
Google Scholar
Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).
Google Scholar
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Google Scholar
Dobbyn, A. et al. Landscape of conditional eQTL in dorsolateral prefrontal cortex and co-localization with schizophrenia GWAS. Am. J. Hum. Genet. 102, 1169–1184 (2018).
Google Scholar
Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).
Google Scholar
Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376–381 (2014).
Google Scholar
Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).
Google Scholar
Laufer, V. A. et al. Genetic influences on susceptibility to rheumatoid arthritis in African-Americans. Hum. Mol. Genet. 28, 858–874 (2019).
Google Scholar
Liu, J. Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979–986 (2015).
Google Scholar
Stahl, E. A. et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat. Genet. 42, 508–514 (2010).
Google Scholar
Heintzman, N. D. et al. Histone modifications at human enhancers reflect global cell type-specific gene expression. Nature 459, 108–112 (2009).
Google Scholar
Hormozdiari, F., Kostem, E., Kang, E. Y., Pasaniuc, B. & Eskin, E. Identifying causal variants at loci with multiple signals of association. Genetics 198, 497–508 (2014).
Google Scholar
Amariuta, T. et al. IMPACT: genomic annotation of cell-state-specific regulatory elements inferred from the epigenome of bound transcription factors. Am. J. Hum. Genet. 104, 879–895 (2019).
Google Scholar
Zaitlen, N., Pasaniuc, B., Gur, T., Ziv, E. & Halperin, E. Leveraging genetic variability across populations for the identification of causal variants. Am. J. Hum. Genet. 86, 23–33 (2010).
Google Scholar
Calderon, D. et al. Landscape of stimulation-responsive chromatin across diverse human immune cells. Nat. Genet. 51, 1494–1505 (2019).
Google Scholar
Smillie, C. S. et al. Intra- and inter-cellular rewiring of the human colon during ulcerative colitis. Cell 178, 714–730 (2019).
Google Scholar
Reshef, Y. A. et al. Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics. Nat. Biotechnol. 40, 355–363 (2022).
Google Scholar
Burkhardt, D. B. et al. Quantifying the effect of experimental perturbations at single-cell resolution. Nat. Biotechnol. 39, 619–629 (2021).
Google Scholar
Ben-David, E. et al. Whole-organism eQTL mapping at cellular resolution with single-cell sequencing. eLife 10, e65857 (2021).
Google Scholar
Cuomo, A. S. E. et al. Optimizing expression quantitative trait locus mapping workflows for single-cell studies. Genome Biol. 22, 188 (2021).
Google Scholar
van der Wijst, M. et al. The single-cell eQTLGen consortium. eLife 9, e52155 (2020).
Google Scholar
Oelen, R. et al. Single-cell RNA-sequencing reveals widespread personalized, context-specific gene expression regulation in immune cells. Preprint at bioRxiv https://doi.org/10.1101/2021.06.04.447088 (2021).
Kotliar, D. et al. Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-seq. eLife 8, e43803 (2019).
Google Scholar