Abstract
Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene.
Highlights
In recent years, increasing attention has been given to the non-coding sequences of the human genome, highlighting the importance of common and rare genetic variants that influence disease etiology [1]
An immediate benefit is given for the evaluation of genome-wide association data as most of the genetic variants associated with complex traits are located in intronic or intergenic regions of the human genome [2,3]
Our study aimed to identify co-regulated genes and their organization in gene expression regulation clusters
Summary
In recent years, increasing attention has been given to the non-coding sequences of the human genome, highlighting the importance of common and rare genetic variants that influence disease etiology [1]. Genome editing allows direct modifications of gene expression regulation using either transcriptional activators [5,6] or repressors [7]. These advances are of paramount importance for gene therapy approaches to human disease [8]. A first study of Matharu et al (2019) [9] suggests that targeted activation of gene expression is suited to prevent clinical phenotypes attributed to haploinsufficiency. Such strategies, require a comprehensive understanding of the regulatory networks involved
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