Rare and Common Regulatory Variation in Population-Scale Sequenced Human Genomes

摘要

Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function. Author Summary The recent availability of almost fully sequenced human genomes by the 1000 genomes project allows the direct study of genetic variants that influence levels of gene expression in the cell. In this study, we explore the effect of rare and common variants on levels of gene expression. We show that the availability of a more comprehensive list of variants brings us closer to the likely causal variants, and we discuss their genomic and evolutionary properties. We also demonstrate the effects of variants that change splicing patterns or length of the protein product, the putative joint impacts of variants that affect gene expression, and those that affect protein structure. Finally, we show the impact of rare regulatory variants that cannot be detected by the conventional methodologies of association and require the interrogation of full genome sequencing and full transcriptome sequencing. These approaches bring us closer to the implementation of these data and methodologies to a direct clinical application.