Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs

Lifelines Cohort Study, BIOS Consortium

Research output: Contribution to journalArticleAcademicpeer-review

73 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)493-497
Number of pages5
JournalNature Genetics
Volume50
Issue number4
DOIs
Publication statusPublished - 2-Apr-2018

Keywords

  • scRNA-seq
  • eQTL
  • co-expression QTL
  • single-cell RNA-sequencing
  • gene regulation
  • DRIVERS
  • PANEL
  • GENE-EXPRESSION
  • GENOTYPE IMPUTATION
  • IMMUNE CELLS
  • ASSOCIATIONS
  • REGULATORS

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