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Impact of the Interaction between 3′-UTR SNPs and microRNA on the Expression of Human Xenobiotic Metabolism Enzyme and Transporter Genes

Overview of attention for article published in Frontiers in Genetics, January 2012
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Title
Impact of the Interaction between 3′-UTR SNPs and microRNA on the Expression of Human Xenobiotic Metabolism Enzyme and Transporter Genes
Published in
Frontiers in Genetics, January 2012
DOI 10.3389/fgene.2012.00248
Pubmed ID
Authors

Rongrong Wei, Fan Yang, Thomas J. Urban, Lang Li, Naga Chalasani, David A. Flockhart, Wanqing Liu

Abstract

Genetic variation in the expression of human xenobiotic metabolism enzymes and transporters (XMETs) leads to inter-individual variability in metabolism of therapeutic agents as well as differed susceptibility to various diseases. Recent expression quantitative traits loci (eQTL) mapping in a few human cells/tissues have identified a number of single nucleotide polymorphisms (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 (miRs) in gene transcription regulation, we hypothesize that those eQTLs or their proxies in strong linkage disequilibrium (LD) altering miR targeting are likely causative SNPs affecting gene expression. The aim of this study is to identify eQTLs potentially regulating major XMETs via interference with miR 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 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 (r(2) ≥ 0.8) with these eQTLs using the 1,000 Genome SNP data. Among these 8,177 SNPs, 27 are located in the 3'-UTR of 14 genes. Using two algorithms predicting miR-SNP interaction, we found that almost all these SNPs (26 out of 27) were predicted to create, abolish, or change the target site for miRs in both algorithms. Many of these miRs 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 24%
Student > Doctoral Student 7 15%
Researcher 6 13%
Student > Master 5 11%
Student > Bachelor 4 9%
Other 9 20%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 46%
Medicine and Dentistry 6 13%
Biochemistry, Genetics and Molecular Biology 6 13%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Neuroscience 2 4%
Other 3 7%
Unknown 5 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 November 2012.
All research outputs
#20,174,175
of 22,687,320 outputs
Outputs from Frontiers in Genetics
#8,519
of 11,752 outputs
Outputs of similar age
#221,211
of 244,123 outputs
Outputs of similar age from Frontiers in Genetics
#195
of 255 outputs
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So far Altmetric has tracked 11,752 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 255 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.