1. Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs
- Author
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Lude Franke, Monique G. P. van der Wijst, Morris A. Swertz, Patrick Deelen, Dylan H. de Vries, Harm Brugge, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), and Stem Cell Aging Leukemia and Lymphoma (SALL)
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0301 basic medicine ,Quantitative Trait Loci ,Gene regulatory network ,Genome-wide association study ,Computational biology ,Quantitative trait locus ,Biology ,eQTL ,GENOTYPE IMPUTATION ,Article ,PANEL ,03 medical and health sciences ,Genetic variation ,scRNA-seq ,DRIVERS ,Genetics ,Humans ,co-expression QTL ,Gene Regulatory Networks ,single-cell RNA-sequencing ,Genetic association ,GENE-EXPRESSION ,ASSOCIATIONS ,REGULATORS ,Regulation of gene expression ,Sequence Analysis, RNA ,Genetic Variation ,Epistasis, Genetic ,Gene expression profiling ,030104 developmental biology ,IMMUNE CELLS ,Expression quantitative trait loci ,Leukocytes, Mononuclear ,Single-Cell Analysis ,Transcriptome ,gene regulation ,Genome-Wide Association Study - Abstract
Genome-wide association studies have identified thousands of genetic variants that are associated with disease 1 . Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large 2 and celltype-specific3-5. To identify these celltype-specific eQTLs using an unbiased approach, we used single-cell RNA sequencing to generate expression profiles of ~25,000 peripheral blood mononuclear cells from 45 donors. We identified previously reported cis-eQTLs, but also identified new celltype-specific cis-eQTLs. Finally, we generated personalized co-expression networks and identified genetic variants that significantly alter co-expression relationships (which we termed 'co-expression QTLs'). Single-cell eQTL analysis thus allows for the identification of genetic variants that impact regulatory networks.
- Published
- 2018
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