Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human...

Area of Science:

• Genomics
• Genetics
• Molecular Biology

Background:

• Genetic association studies link phenotypes to genomic regions but struggle to identify causal variants.
• Whole-genome sequencing (WGS) offers comprehensive variant data but is costly for large Genome-Wide Association Studies (GWAS).
• Expression quantitative trait loci (eQTL) mapping connects genetic variants to gene expression levels.

Purpose of the Study:

• To develop and validate a method for identifying likely causal single nucleotide polymorphisms (SNPs) using WGS and eQTL data.
• To assess the proportion of causal variants located in open-chromatin regions.
• To identify high-confidence causal variants and evaluate their enrichment in GWAS associations for complex traits.

Main Methods:

• Performed eQTL mapping using WGS and RNA-sequencing data.
• Conducted simulations to derive properties of causal variants.
• Developed a novel method to identify likely causal SNPs based on WGS and eQTL data.
• Estimated the location of causal variants within open-chromatin regions.
• Identified high-confidence causal variants and assessed their enrichment in GWAS associations.

Main Results:

• Lead eQTL variants identified using WGS were more likely to be causal.
• Estimated 25-70% of causal variants reside in open-chromatin regions, varying by tissue and experiment.
• Identified a set of high-confidence causal variants.
• These causal variants showed greater enrichment in GWAS associations compared to other eQTLs.
• Discovered 65 associations between high-confidence causal variants and GWAS traits, with functional validation for some complex traits.

Conclusions:

• WGS combined with eQTL analysis provides a powerful approach to identify causal variants for complex traits.
• The developed method enhances the discovery of functionally relevant SNPs from genetic association studies.
• This research advances the understanding of the genetic architecture underlying complex diseases and traits.