Evaluation of Genetic Variation Contributing to Differences in Gene Expression between Populations

Abstract

Gene expression is a complex quantitative trait partially regulated by genetic variation in DNA sequence. Population differences in gene expression could contribute to some of the observed differences in susceptibility to common diseases and response to drug treatments. We characterized gene expression in the full set of HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry for 9156 transcript clusters (gene-level) evaluated with the Affymetrix GeneChip Human Exon 1.0 ST Array. Gene expression was found to differ significantly between these samples for 383 transcript clusters. Biological processes including ribosome biogenesis and antimicrobial humoral response were found to be enriched in these differential genes, suggesting their possible roles in contributing to the population differences at a higher level than that of mRNA expression and in response to environmental information. Genome-wide association studies for local or distant genetic variants that correlate with the differentially expressed genes enabled identification of significant associations with one or more single-nucleotide polymorphisms (SNPs), consistent with the hypothesis that genetic factors and not simply population identity or other characteristics (age of cell lines, length of culture, etc.) contribute to differences in gene expression in these samples. Our results provide a comprehensive view of the genes differentially expressed between populations and the enriched biological processes involved in these genes. We also provide an evaluation of the contributions of genetic variation and nongenetic factors to the population differences in gene expression.

Identification of genetic variants and gene expression relationships associated with pharmacogenes in humans

“…2). This finding is in agreement with previous findings that genetic polymorphisms may contribute to observed sample differences in gene expression [11,12,13].…”

Consistency of genome-wide associations across major ancestral groups

“…Typical reasons for this are population-speciWc mutations, diVerent LD patterns and recombination events, or even diVering selective pressures in the areas of origin or residence of these groups. Furthermore, individuals of European and African ancestry diVer signiWcantly in the expression of many genes which could contribute to some of the observed diVerences in susceptibility to common diseases (Spielman et al 2007;Zhang et al 2008). Finally, diVerences in riskallele frequencies may aVect the power to detect genomewide signiWcant associations across populations of varying ancestral origin (Moonesinghe et al 2008), and may also aVect the transferability of disease-risk prediction across major populations.…”

Towards unambiguous transcript mapping in the allotetraploid Brassica napusThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

“…There is now an opportunity to apply these types of analyses to nonstructured collections of diverse germplasm, combining the strength of association mapping with the sensitivity of transcript analysis to elucidate complex quantitative phenotypes. Such strategies are proving to be highly informative in studying the genetic architecture of transcript variation in humans (Zhang et al 2008).…”