Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level...

Area of Science:

• Genomics
• Transcriptomics
• Molecular Biology

Background:

• Identifying cis-acting regulatory variation is key to understanding complex traits and transcriptomic diversity.
• Expression quantitative trait loci (eQTL) analysis, particularly using allele-specific expression (ASE) from RNA sequencing (RNA-seq), enhances the detection of regulatory variation.

Purpose of the Study:

• To comprehensively evaluate cis-acting eQTLs in normal primary prostate tissue.
• To assess the benefit of integrating ASE data in eQTL analysis for improved reproducibility and functional context.

Main Methods:

• Analysis of RNA-seq gene expression and genome-wide high-density genotypes from 471 prostate tissue samples.
• Application of statistical models integrating ASE information for cis-eQTL detection.
• Utilizing phased genotype data to identify cis-acting co-regulation.

Main Results:

• Extensive cis-eQTLs were identified across the prostate transcriptome, with ~70% of expressed genes showing significant eQTLs (FDR 0.05).
• eQTLs were concentrated near transcription start/stop sites, with effects decreasing with distance.
• 233 SNPs were identified as strong eQTLs for multiple genes, and prostate cancer risk SNPs were enriched in prostate eQTLs.

Conclusions:

• Integrating ASE data in cis-eQTL analyses offers better reproducibility than using total expression alone.
• The study provides extensive functional context for thousands of SNPs in prostate tissue.
• These findings are valuable for future research into human prostate diseases.