Publication Date
3-11-2022
Journal
BMC Genomics
DOI
10.1186/s12864-022-08405-y
PMID
35272635
PMCID
PMC8915503
PubMedCentral® Posted Date
3-11-2022
PubMedCentral® Full Text Version
Post-Print
Published Open-Access
no
Keywords
Gene Expression Regulation, Lung, Polymorphism, Single Nucleotide, Quantitative Trait Loci, RNA Stability, Expression quantitative trait loci (eQTLs), RNA-Seq, mRNA stability, Stability QTLs (stQTLs)
Abstract
BACKGROUND: Expression quantitative trait loci (eQTLs) analyses have been widely used to identify genetic variants associated with gene expression levels to understand what molecular mechanisms underlie genetic traits. The resultant eQTLs might affect the expression of associated genes through transcriptional or post-transcriptional regulation. In this study, we attempt to distinguish these two types of regulation by identifying genetic variants associated with mRNA stability of genes (stQTLs).
RESULTS: Here, we presented a computational framework that takes advantage of recently developed methods to infer the mRNA stability of genes based on RNA-seq data and performed association analysis to identify stQTLs. Using the Genotype-Tissue Expression (GTEx) lung RNA-Seq data, we identified a total of 142,801 stQTLs for 3942 genes and 186,132 eQTLs for 4751 genes from 15,122,700 genetic variants for 13,476 genes on the autosomes, respectively. Interestingly, our results indicated that stQTLs were enriched in the CDS and 3'UTR regions, while eQTLs are enriched in the CDS, 3'UTR, 5'UTR, and upstream regions. We also found that stQTLs are more likely than eQTLs to overlap with RNA binding protein (RBP) and microRNA (miRNA) binding sites. Our analyses demonstrate that simultaneous identification of stQTLs and eQTLs can provide more mechanistic insight on the association between genetic variants and gene expression levels.
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