Dataset Information

Gene-expression variation within and among human populations.

ABSTRACT: Understanding patterns of gene-expression variation within and among human populations will provide important insights into the molecular basis of phenotypic diversity and the interpretation of patterns of expression variation in disease. However, little is known about how gene-expression variation is apportioned within and among human populations. Here, we characterize patterns of natural gene-expression variation in 16 individuals of European and African ancestry. We find extensive variation in gene-expression levels and estimate that approximately 83% of genes are differentially expressed among individuals and that approximately 17% of genes are differentially expressed among populations. By decomposing total gene-expression variation into within- versus among-population components, we find that most expression variation is due to variation among individuals rather than among populations, which parallels observations of extant patterns of human genetic variation. Finally, we performed allele-specific quantitative polymerase chain reaction to demonstrate that cis-regulatory variation in the lymphocyte adaptor protein (SH2B adapter protein 3) contributes to differential expression between European and African samples. These results provide the first insight into how human population structure manifests itself in gene-expression levels and will help guide the search for regulatory quantitative trait loci.

SUBMITTER: Storey JD

PROVIDER: S-EPMC1821107 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Gene-expression variation within and among human populations.

Storey John D JD Madeoy Jennifer J Strout Jeanna L JL Wurfel Mark M Ronald James J Akey Joshua M JM

American journal of human genetics 20070111 3

Understanding patterns of gene-expression variation within and among human populations will provide important insights into the molecular basis of phenotypic diversity and the interpretation of patterns of expression variation in disease. However, little is known about how gene-expression variation is apportioned within and among human populations. Here, we characterize patterns of natural gene-expression variation in 16 individuals of European and African ancestry. We find extensive variation i ...[more]

PMID: 17273971

Similar Datasets

Project description:Populations of beet cyst nematodes Heterodera schachtii vary in aggressiveness and virulence toward sugar beet varieties, but also in traits like host range, or decline rate in the field. Diversity of their essential pathogenicity gene vap1 is shaped by diversifying selection and gene flow. The authors developed a technique to study inter-population variation and intra-population diversity and dynamics of H. schachtii based on the gene vap1. Degenerate primers were designed to amplify, clone, and sequence this gene from diverse species and populations of cyst nematodes. This resulted in a high diversity of sequences for H. schachtii, and allowed to design non-degenerated primers to amplify a fragment suitable for sequence dependent separation of gene variants in denaturing gradient gel electrophoresis (DGGE). The developed primers span a highly variable intron and part of a slightly variable exon. A marker comprised of the 14 mostly detected gene variants was established for gel-to-gel comparisons. For individual juveniles up to six gene variants were resolved and substantial variation within and among cysts was observed. A fast and easy DNA extraction procedure for 20 pooled cysts was established, which provided DGGE patterns with high similarity among replicate samples from field populations. Permutation tests on pairwise similarities within and among populations showed significant differences among vap1 patterns of field populations of H. schachtii. Similarly, gene diversity as expressed by the Shannon index was statistically different among field populations. In conclusion, the DGGE technique is a fast and - compared to sequencing approaches - inexpensive tool to compare populations of H. schachtii and link observed biological characteristics to genetic pattern.Populations of beet cyst nematodes Heterodera schachtii vary in aggressiveness and virulence toward sugar beet varieties, but also in traits like host range, or decline rate in the field. Diversity of their essential pathogenicity gene vap1 is shaped by diversifying selection and gene flow. The authors developed a technique to study inter-population variation and intra-population diversity and dynamics of H. schachtii based on the gene vap1. Degenerate primers were designed to amplify, clone, and sequence this gene from diverse species and populations of cyst nematodes. This resulted in a high diversity of sequences for H. schachtii, and allowed to design non-degenerated primers to amplify a fragment suitable for sequence dependent separation of gene variants in denaturing gradient gel electrophoresis (DGGE). The developed primers span a highly variable intron and part of a slightly variable exon. A marker comprised of the 14 mostly detected gene variants was established for gel-to-gel comparisons. For individual juveniles up to six gene variants were resolved and substantial variation within and among cysts was observed. A fast and easy DNA extraction procedure for 20 pooled cysts was established, which provided DGGE patterns with high similarity among replicate samples from field populations. Permutation tests on pairwise similarities within and among populations showed significant differences among vap1 patterns of field populations of H. schachtii. Similarly, gene diversity as expressed by the Shannon index was statistically different among field populations. In conclusion, the DGGE technique is a fast and – compared to sequencing approaches – inexpensive tool to compare populations of H. schachtii and link observed biological characteristics to genetic pattern.

Dataset Information

Gene-expression variation within and among human populations.

Publications

Gene-expression variation within and among human populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets