Genome-Wide Associations of Gene Expression Variation in Humans

Abstract

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12–13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

Population-level expression variability of mitochondrial DNA-encoded genes in humans

“…We resorted to identify transacting mitochondrial eQTLs (ie, the mtDNA expression-controlling SNPs located in autosomes). However, using the established method, 46 we detected no significant eQTL relationships between autosomal SNPs and mtDNA gene expression. Finally, we examined the existence of indirect links.…”

“…Associations between gene expression and genotype (eQTLs) have been established for many nuclear genes. 8,9,[43][44][45][46] We hypothesized that the expression variation of mtDNA genes may be associated with genotypes defined by autosomal SNPs, although the regulatory mechanisms through which these SNPs might affect mtDNA gene expression is not clear. Because all SNPs in mtDNA were of low frequency (MAFo10%), no cis-acting mitochondrial eQTLs (ie, the expression-controlling SNPs located in mtDNA) could be detected.…”

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

“…A great volume of transcriptional expressions that are regarded as quantitative traits can be analyzed using the transcriptional expression QTL (eQTL) mapping aproaches (Brem et al, 2002;Schadt et al, 2003;Morley et al, 2004;Stranger et al, 2005;Wang et al, 2006). Several methods for eQTL mapping also motivate the modeling scheme of multiple quantitative trait mapping.…”

SNPxGE2: a database for human 3-way SNP-expression associations

“…Recently, many studies have suggested that SNPs also have impacts on gene expression variations in human populations (6)(7)(8)(9). Stranger at al.…”

“…Stranger at al. (6) found that many regions within 1Mb of 374 expressed genes of interest had significant association of SNPs with expression variation. Stranger et al (7), performing association analyses of expression levels of 14,925 transcripts with SNPs and copy number variants (CNVs) using multiple linear regression, suggested that SNPs captured 83.6% of the total detected genetic variation in gene expression.…”