Genome-Wide Identification of Expression Quantitative Trait Loci (eQTLs) in Human Heart

In recent years genome-wide association studies (GWAS) have uncovered numerous chromosomal loci associated with various electrocardiographic traits and cardiac arrhythmia predisposition. A considerable fraction of these loci lie within inter-genic regions. The underlying trait-associated variants likely reside in regulatory regions and exert their effect by modulating gene expression. Hence, the key to unraveling the molecular mechanisms underlying these cardiac traits is to interrogate variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis. In this study we conducted an eQTL analysis of human heart. For a total of 129 left ventricular samples that were collected from non-diseased human donor hearts, genome-wide transcript abundance and genotyping was determined using microarrays. Each of the 18,402 transcripts and 897,683 SNP genotypes that remained after pre-processing and stringent quality control were tested for eQTL effects. We identified 771 eQTLs, regulating 429 unique transcripts. Overlaying these eQTLs with cardiac GWAS loci identified novel candidates for studies aimed at elucidating the functional and transcriptional impact of these loci. Thus, this work provides for the first time a comprehensive eQTL map of human heart: a powerful and unique resource that enables systems genetics approaches for the study of cardiac traits.

近年来，全基因组关联研究（Genome-Wide Association Studies, GWAS）已发现大量与各类心电图特征及心律失常易感性相关的染色体位点。其中相当一部分位点位于基因间区。这些与性状相关的潜在变异大概率位于调控区域，并通过调控基因表达发挥作用。因此，阐明这些心脏性状背后分子机制的关键，是通过表达数量性状位点（expression quantitative trait locus, eQTL）分析，探究变异与转录本丰度差异之间的关联。本研究针对人类心脏开展了eQTL分析。本研究共纳入129份来自非病变人类供体心脏的左心室样本，通过微阵列技术测定了全基因组范围内的转录本丰度与基因型。经预处理与严格质量控制后留存的18402条转录本及897683个单核苷酸多态性（Single Nucleotide Polymorphism, SNP）基因型，均被用于eQTL效应检验。本研究共鉴定出771个eQTL，调控429个独特的转录本。将这些eQTL与心脏GWAS位点进行整合分析后，我们找到了一批新的候选研究靶点，可用于阐释这些位点的功能与转录调控效应。综上，本研究首次构建了人类心脏的全基因组eQTL图谱：这一兼具实用性与独特性的宝贵资源，可为心脏性状的系统遗传学研究提供强力支持。