Comprehensively Evaluating cis-Regulatory Variation in the Human Prostate Transcriptome by Using Gene-Level Allele-Specific Expression

Nicholas Larson, Shannon McDonnell, Amy J. French, Zach Fogarty, John Cheville, Sumit Middha, Shaun Riska, Saurabh Baheti, Asha A. Nair, Liang Wang, Daniel J Schaid, Stephen N Thibodeau

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.

Original languageEnglish (US)
JournalAmerican Journal of Human Genetics
DOIs
StateAccepted/In press - Dec 30 2014

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Quantitative Trait Loci
Transcriptome
Prostate
Alleles
RNA Sequence Analysis
Single Nucleotide Polymorphism
Genes
Genotype
Transcription Initiation Site
Statistical Models
Prostatic Neoplasms
Genome
Gene Expression

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Comprehensively Evaluating cis-Regulatory Variation in the Human Prostate Transcriptome by Using Gene-Level Allele-Specific Expression. / Larson, Nicholas; McDonnell, Shannon; French, Amy J.; Fogarty, Zach; Cheville, John; Middha, Sumit; Riska, Shaun; Baheti, Saurabh; Nair, Asha A.; Wang, Liang; Schaid, Daniel J; Thibodeau, Stephen N.

In: American Journal of Human Genetics, 30.12.2014.

Research output: Contribution to journalArticle

Larson, Nicholas ; McDonnell, Shannon ; French, Amy J. ; Fogarty, Zach ; Cheville, John ; Middha, Sumit ; Riska, Shaun ; Baheti, Saurabh ; Nair, Asha A. ; Wang, Liang ; Schaid, Daniel J ; Thibodeau, Stephen N. / Comprehensively Evaluating cis-Regulatory Variation in the Human Prostate Transcriptome by Using Gene-Level Allele-Specific Expression. In: American Journal of Human Genetics. 2014.
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