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

大规模分析揭示了遗传变异对人类诱导性多能干细胞基因表达的影响

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作者: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

Abstract

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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