Mapping determinants of human gene expression by regional and genome-wide association

Top Cited Papers
Publisher Website
Google Scholar
Abstract
Even when two humans have the same genes, the levels at which those genes are expressed can contribute greatly to variation between individuals. Based on HapMap Project data, Cheung et al. use genetic association to map the parts of each gene that control levels of expression. The data also provide a detailed comparison of the techniques of genetic linkage and association, both of which are used to look for genetic determinants of human disease. To study the genetic basis of natural variation in gene expression, we previously carried out genome-wide linkage analysis and mapped the determinants of ∼1,000 expression phenotypes1. In the present study, we carried out association analysis with dense sets of single-nucleotide polymorphism (SNP) markers from the International HapMap Project2. For 374 phenotypes, the association study was performed with markers only from regions with strong linkage evidence; these regions all mapped close to the expressed gene. For a subset of 27 phenotypes, analysis of genome-wide association was performed with >770,000 markers. The association analysis with markers under the linkage peaks confirmed the linkage results and narrowed the candidate regulatory regions for many phenotypes with strong linkage evidence. The genome-wide association analysis yielded highly significant results that point to the same locations as the genome scans for about 50% of the phenotypes. For one candidate determinant, we carried out functional analyses and confirmed the variation in cis-acting regulatory activity. Our findings suggest that association studies with dense SNP maps will identify susceptibility loci or other determinants for some complex traits or diseases.