Impact of the interaction between 3’-UTR SNPs and microRNA on the expression of human xenobiotic metabolism enzyme and transporter (XMETs) genes

Frontiers in Genetics

Thomas J. Urban¹  Naga eChalasani²  Wanqing eLiu²  Lang eLi²  David A Flockhart²  Fan eYang³  Rongrong eWei³ 

[1] Duke University;Indiana University;Purdue University;

关键词: Pharmacogenetics;    eQTL;    microRNA;    xenobiotic metabolism enzyme;    3’-UTR;    xenobiotic metabolism enzyme and transporter;   

DOI  :  10.3389/fgene.2012.00248

来源: DOAJ

【 摘 要 】

Genetic variation in the expression of human XMETs leads to inter-individual variability in metabolism of therapeutic agents as well as differed susceptibility to various diseases. Recent eQTL (expression quantitative traits loci) mapping in a few human cells/tissues have identified a number of SNPs significantly associated with mRNA expression of many XMET genes. These eQTLs are therefore important candidate markers for pharmacogenetic studies. However, questions remain about whether these SNPs are causative and in what mechanism these SNPs may function. Given the important role of microRNAs in gene transcription regulation, we hypothesize that those eQTLs or their proxies in strong linkage disequilibrium (LD) altering microRNA targeting are likely causative SNPs affecting gene expression. The aim of this study is to identify eQTLs potentially regulating major XMETs via interference with microRNA targeting. To this end, we performed a genome-wide screening for eQTLs for 409 genes encoding major drug metabolism enzymes transporters and transcription factors, in publically available eQTL datasets generated from the HapMap lymphoblastoid cell lines (LCLs) and human liver and brain tissue. As a result, 308 eQTLs significantly (p<10-5) associated with mRNA expression of 101 genes were identified. We further identified 7,869 SNPs in strong LD (r2≥0.8) with these eQTLs using the 1000 Genome SNP data. Among these 8,177 SNPs, 27 are located in the 3’-UTR of 14 genes. Using two algorithms predicting microRNA-SNP interaction, we found that almost all these SNPs (26 out of 27) were predicted to create, abolish or change the target site for microRNAs in both algorithms. Many of these microRNAs were also expressed in the same tissue that the eQTL were identified. Our study provides a strong rationale for continued investigation for the functions of these eQTLs in pharmacogenetic settings.

【 授权许可】

Unknown