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

Monique G P van der WijstHarm BruggeDylan H de VriesPatrick DeelenMorris A Swertznull nullnull nullLude H Franke
Published in: Nature genetics (2018)
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.
Keyphrases
  • single cell
  • poor prognosis
  • rna seq
  • binding protein
  • genome wide
  • high throughput
  • genome wide association
  • dna methylation
  • high resolution
  • gene expression
  • mass spectrometry
  • copy number