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

Publication date: 6 April 2017
Source:Cell Stem Cell, Volume 20, Issue 4
Author(s): Christopher DeBoever, He Li, David Jakubosky, Paola Benaglio, Joaquin Reyna, Katrina M. Olson, Hui Huang, William Biggs, Efren Sandoval, Matteo D'Antonio, Kristen Jepsen, Hiroko Matsui, Angelo Arias, Bing Ren, Naoki Nariai, Erin N. Smith, Agnieszka D'Antonio-Chronowska, Emma K. Farley, Kelly A. Frazer
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.

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Teaser

Working as part of the NextGen consortium, DeBoever et al. use whole-genome and RNA sequencing to map expression quantitative trait loci in a set of 215 human induced pluripotent stem cell lines. These genotype-expression associations provide a foundation for understanding the genetic regulation of gene expression in pluripotent cells.


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