Literature DB >> 25192659

Genome-wide detection of allelic gene expression in hepatocellular carcinoma cells using a human exome SNP chip.

Yon Mi Park1, Hyun Sub Cheong2, Jong-Keuk Lee3.   

Abstract

Allelic variations in gene expression influence many biological responses and cause phenotypic variations in humans. In this study, Illumina Human Exome BeadChips containing more than 240,000 single nucleotide polymorphisms (SNPs) were used to identify changes in allelic gene expression in hepatocellular carcinoma cells following lipopolysaccharide (LPS) stimulation. We found 17 monoallelically expressed genes, 58 allelic imbalanced genes, and 7 genes showing allele substitution. In addition, we also detected 33 differentially expressed genes following LPS treatment in vitro using these human exome SNP chips. However, alterations in allelic gene expression following LPS treatment were detected in only three genes (MLXIPL, TNC, and MX2), which were observed in one cell line sample only, indicating that changes in allelic gene expression following LPS stimulation of liver cells are rare events. Among a total of 75 genes showing allelic expression in hepatocellular carcinoma cells, either monoallelic or imbalanced, 43 genes (57.33%) had expression quantitative trait loci (eQTL) data, indicating that high-density exome SNP chips are useful and reliable for studying allelic gene expression. Furthermore, most genes showing allelic expression were regulated by cis-acting mechanisms and were also significantly associated with several human diseases. Overall, our study provides a better understanding of allele-specific gene expression in hepatocellular carcinoma cells with and without LPS stimulation and potential clues for the cause of human disease due to alterations in allelic gene expression.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Allele substitution; Allelic gene expression; Allelic imbalance; Hepatocellular carcinoma cells; Monoallelic expression; Single nucleotide polymorphism (SNP)

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Year:  2014        PMID: 25192659     DOI: 10.1016/j.gene.2014.09.001

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


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