Large-Scale Profiling Reveals the Influence of Genetic Variation on Gene Expression in Human Induced Pluripotent Stem Cells

Cell Stem Cell. 2017 Apr 6;20(4):533-546.e7. doi: 10.1016/j.stem.2017.03.009.


In this study, we used whole-genome sequencing and gene expression profiling of 215 human induced pluripotent stem cell (iPSC) lines from different donors to identify genetic variants associated with RNA expression for 5,746 genes. We were able to predict causal variants for these expression quantitative trait loci (eQTLs) that disrupt transcription factor binding and validated a subset of them experimentally. We also identified copy-number variant (CNV) eQTLs, including some that appear to affect gene expression by altering the copy number of intergenic regulatory regions. In addition, we were able to identify effects on gene expression of rare genic CNVs and regulatory single-nucleotide variants and found that reactivation of gene expression on the X chromosome depends on gene chromosomal position. Our work highlights the value of iPSCs for genetic association analyses and provides a unique resource for investigating the genetic regulation of gene expression in pluripotent cells.

Keywords: eQTL; expression quantitative trait loci; gene expression; regulation of gene expression; stem cell gene expression; stem cell genetics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites / genetics
  • Cellular Reprogramming / genetics
  • Chromosomes, Human, X / genetics
  • DNA Copy Number Variations / genetics
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation*
  • Genetic Heterogeneity
  • Genetic Variation*
  • Humans
  • Induced Pluripotent Stem Cells / metabolism*
  • Molecular Sequence Annotation
  • Quantitative Trait Loci / genetics
  • Regulatory Sequences, Nucleic Acid / genetics
  • Transcription Factors / metabolism


  • Transcription Factors