Significant association signals from genome-wide association studies (GWAS) point to genomic regions of interest. However, for most loci the causative genetic variant remains undefined. Determining expression quantitative trait loci (eQTL) in a disease relevant tissue is an excellent approach to zoom in on disease- or trait-associated association signals and hitherto on relevant disease mechanisms. To this end, we explored regulation of gene expression in healthy retina (n = 311) and generated the largest cis-eQTL data set available to date. Genotype- and RNA-Seq data underwent rigorous quality control protocols before FastQTL was applied to assess the influence of genetic markers on local (cis) gene expression. Our analysis identified 403,151 significant eQTL variants (eVariants) that regulate 3,007 genes (eGenes) (Q-Value < 0.05). A conditional analysis revealed 744 independent secondary eQTL signals for 598 of the 3,007 eGenes. Interestingly, 99,165 (24.71%) of all unique eVariants regulate the expression of more than one eGene. Filtering the dataset for eVariants regulating three or more eGenes revealed 96 potential regulatory clusters. Of these, 31 harbour 130 genes which are partially regulated by the same genetic signal. To correlate eQTL and association signals, GWAS data from twelve complex eye diseases or traits were included and resulted in identification of 80 eGenes with potential association. Remarkably, expression of 10 genes is regulated by eVariants associated with multiple eye diseases or traits. In conclusion, we generated a unique catalogue of gene expression regulation in healthy retinal tissue and applied this resource to identify potentially pleiotropic effects in highly prevalent human eye diseases. Our study provides an excellent basis to further explore mechanisms of various retinal disease etiologies.

来自全基因组关联研究（GWAS）的重要关联信号指向感兴趣的基因组区域。但是，对于大多数基因座，致病性遗传变异仍未确定。确定疾病相关组织中的表达定量性状基因位点（eQTL）是放大与疾病或性状相关的关联信号以及迄今为止有关疾病机制的一种极好的方法。为此，我们探索了健康视网膜（n = 311）中基因表达的调控并产生了迄今为止最大的顺式-eQTL数据集。在应用FastQTL评估遗传标记对局部（顺式）基因表达的影响之前，对基因型和RNA-Seq数据进行了严格的质量控制。我们的分析确定了403,151个重要的eQTL变体（eVariant），它们可调节3,007个基因（eGenes）（Q值<0.05）。条件分析揭示了3,007个eGene中的598个的744个独立次级eQTL信号。有趣的是，所有独特eVariant中的99,165（24.71％）个调节一个以上eGene的表达。筛选用于调节三个或更多eGene的eVariant的数据集，发现96个潜在的调节簇。在这些基因中，有31个包含130个基因，这些基因部分受同一遗传信号的调控。为了关联eQTL和关联信号，包括了来自十二种复杂眼病或性状的GWAS数据，并鉴定了具有潜在关联的80个eGene。值得注意的是，10种基因的表达受与多种眼部疾病或性状相关的eVariant的调节。结论，我们在健康的视网膜组织中生成了独特的基因表达调控目录，并利用此资源来识别高度流行的人眼疾病的潜在多效性作用。我们的研究为进一步探讨各种视网膜疾病病因的机制提供了极好的基础。