A mega-analysis of expression quantitative trait loci in retinal tissue

Area of Science:

• Genomics
• Ophthalmology
• Molecular Biology

Background:

• Genome-wide association studies (GWAS) identify genomic regions associated with traits but often fail to pinpoint causative variants.
• Expression quantitative trait loci (eQTL) analysis in disease-relevant tissues is crucial for understanding disease mechanisms.
• Defining genetic regulation of gene expression in the retina is key to understanding eye diseases.

Purpose of the Study:

• To create the largest cis-eQTL dataset in healthy human retina.
• To identify genetic variants regulating gene expression in the retina.
• To correlate retinal eQTLs with genetic associations for complex eye diseases.

Main Methods:

• Collected genotype and RNA-Seq data from 311 healthy retinal samples.
• Applied rigorous quality control to genetic and expression data.
• Utilized FastQTL to identify cis-eQTL variants (eVariants) and their regulated genes (eGenes).
• Integrated GWAS data for twelve complex eye diseases/traits.

Main Results:

• Identified 403,151 significant eVariants regulating 3,007 eGenes (Q-Value < 0.05).
• Discovered 744 independent secondary eQTL signals and 96 potential regulatory clusters.
• Linked 80 eGenes to potential associations with complex eye diseases.
• Found 10 genes regulated by eVariants associated with multiple eye diseases, suggesting pleiotropic effects.

Conclusions:

• Generated a comprehensive catalogue of gene expression regulation in healthy retinal tissue.
• This resource facilitates the identification of genetic variants underlying eye diseases.
• The findings provide a foundation for exploring the mechanisms of various retinal disease etiologies and potential pleiotropic genetic effects.