Bigger data reveal the second, third and fourth switches controlling a gene
We now take for granted the idea that a genome-wide association study, or GWAS, can help identify genetic variants associated with complex traits. Such studies have identified loci associated with everything from breast cancer to heart disease to diabetes.
A recent study published in Science has revealed that a lot of data is essential to understand the switches controlling gene expression and splicing. Traditionally, genome-wide association studies (GWAS) have identified genetic variants associated with complex traits, but they do not directly link these variants to the genes involved.
To truly understand the connection between genetic variants and disease or complex traits, researchers need to understand how gene expression and splicing are controlled. This requires extensive data, as demonstrated by a new study led by Peter Orchard, Ph.D., and Steve Parker, Ph.D., of the University of Michigan. The team used Trans-Omics for Precision Medicine (TOPMed) data, which includes RNA sequencing samples from various tissues, to map tens of thousands of expression and splicing quantitative trait loci (eQTL and sQTL) signals with high resolution.
The findings show that the more samples included in the study, the more e/sQTL signals are detected. Most genes have multiple independent control switches, with the second, third, and fourth switches being harder to detect in smaller studies. The connections between GWAS signals and specific genes are often made through these secondary switches, which have larger effects and are more likely to be linked to specific diseases.
The study emphasizes the importance of collecting tissue samples beyond whole blood to uncover these critical loci, as many non-European ancestry populations are still underrepresented in data sets.
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