The Role of eQTLs and sQTLs in Gene Expression and Disease

Expression quantitative trait loci (eQTLs) and splicing quantitative trait loci (sQTLs) play significant roles in the genetic regulation of gene expression and RNA splicing. Their analysis is crucial for understanding the genetic basis of complex traits and diseases.

eQTLs are genomic loci that influence gene expression levels. These can be local (cis-eQTLs) or distant (trans-eQTLs) relative to the gene they affect. They are identified by associating genetic variation, typically single nucleotide polymorphisms (SNPs), with variations in gene expression across individuals. sQTLs are similar to eQTLs, but they are associated with variations in RNA splicing, leading to different mRNA and protein products, which can have significant impacts on biological processes and disease states.

The importance of eQTLs and sQTLs in disease research is exemplified by a study that demonstrated their enrichment in associations with primary open-angle glaucoma (POAG) and intraocular pressure (IOP), suggesting their potential role in glaucoma pathogenesis. This study found that sQTLs might contribute more to POAG and IOP variation than eQTLs, highlighting the significance of both eQTLs and sQTLs in understanding complex traits and diseases​​.

Cell type or developmental stage specificity of eQTLs and sQTLs is also a crucial aspect. For example, eQTL mapping in fetal-like pancreatic progenitor cells provided insights into developmental stages and diabetes risk, demonstrating the dynamic nature of eQTLs in influencing different genes and biological processes across developmental stages and tissues​​.

sQTLs have been found to be significantly enriched in exonic regions, pointing to their role in alternative splicing mechanisms and their potential impact on disease susceptibility through effects on protein coding sequences​​.

In summary, understanding eQTLs and sQTLs is vital for unraveling the complex genetic regulation of gene expression and RNA splicing, with significant implications for human health and disease. This field continues to evolve with advances in genomic technologies and bioinformatics.

Reference:

Hamel, A. R., Yan, W., Rouhana, J. M., Monovarfeshani, A., Jiang, X., Mehta, P. A., ... & Segrè, A. V. (2022). Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma. medRxiv, 2022-05.
Nguyen, J. P., Arthur, T. D., Fujita, K., Salgado, B. M., Donovan, M. K., Matsui, H., ... & Frazer, K. A. (2023). eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk. Nature Communications, 14(1), 6928.
Takata, A., Matsumoto, N., & Kato, T. (2017). Genome-wide identification of splicing QTLs in the human brain and their enrichment among schizophrenia-associated loci. Nature communications, 8(1), 14519.