Abstract
Several recent studies have reported that expression quantitative trait loci (eQTLs) may affect gene expression in a cell-dependent manner. In the current study, a genome-wide eQTL analysis was performed in whole blood samples collected from 76 Japanese subjects. RNA microarray analysis was performed for 3 independent sample groups that were genotyped in a genome-wide scan. The correlations between the genotypes of 534,404 autosomal single nucleotide polymorphisms (SNPs) and the expression levels of 30,465 probes were examined for each sample group. The SNP-probe pairs with combined correlation coefficients of all 3 sample groups corresponding to P<3.1×10−12 (i.e., Bonferroni-corrected P<0.05) were considered significant. SNP-probe pairs with a high likelihood of cross-hybridization and SNP-in-probe effects were excluded to avoid false positive results. We identified 102 cis-acting and 5 trans-acting eQTL regions. The cis-eQTL regions were widely distributed both upstream and downstream of the gene, as well as within the gene. The eQTL SNPs identified were examined for their influence on the expression levels in lymphoblastoid cell lines by using a public database. The results showed that genetic variants affecting expression levels in whole blood may have different effects on gene expression in lymphoblastoid cell lines. Further studies are required to clarify how SNPs function in affecting the expression levels in whole blood as well as in other tissues.
Highlights
Advances in high-throughput genotyping and gene expression platforms have enabled genome-wide analysis of gene expression quantitative trait loci, allowing investigation of both cis and trans effects
Investigation of combined Chinese and Japanese (CHB+JPT) panels from the 1000 Genomes Pilot 1 single nucleotide polymorphisms (SNPs) data set and the HapMap release 22 data set showed a greater number of SNPs in high linkage disequilibrium (LD) (r2.0.8) with the eQTL SNPs identified in the current study
Since the high intermarker correlations cause difficulties in determining which SNP is responsible for the regulation of gene expression, we defined the eQTL region of a gene as the genomic range in which the SNPs in LD (r2.0.8) with the eQTL SNPs of the gene are located
Summary
Advances in high-throughput genotyping and gene expression platforms have enabled genome-wide analysis of gene expression quantitative trait loci (eQTLs), allowing investigation of both cis and trans effects. Developed web tools such as SNPexp [7] and Genevar [8] have enabled analysis of the correlation between SNP genotypes in HapMap genotype data and genome-wide expression levels in lymphoblastoid cell lines Development of such tools in other cell types is anticipated, as a substantial fraction of eQTLs are cell type-specific [9,10,11,12]. The large number of gene expression traits and genomic loci requires enormous calculations, raising issues of computer efficiency and statistical power Another challenge is the varying genetic backgrounds in study populations, which may be one of the causes of the poor reproducibility observed across studies. Genome-wide eQTL data for Asian population is scarce [15]
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