Deep genome sequencing for diverse human populations from around the world
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina HiSeq 2000
ORGANISM(S): Homo Sapiens
SUBMITTER: HARVARD MEDICAL SCHOOL, DEPARTMENT OF GENETICS
PROVIDER: PRJEB9586 | EVA | 2015-06-30
REPOSITORIES: EVA
Similar Datasets
Project description:Background: Differences in levels of gene expression among individuals are an important source of phenotypic variation within populations. Recent microarray studies have revealed that expression variation is abundant in many species, including Drosophila melanogaster. However, previous expression surveys in this species generally focused on a small number of laboratory strains established from derived populations. Thus, these studies were not ideal for population genetic analyses. Results: We surveyed gene expression variation in adult males of 16 D. melanogaster strains from two natural populations, including an ancestral African population and a derived European population. Levels of expression polymorphism were nearly equal in the two populations, but a higher number of differences was detected when comparing strains between populations. Expression variation was greatest for genes associated with few molecular functions or biological processes, as well as those expressed predominantly in males. Our analysis also identified genes that differed in expression level between the European and African populations, which may be candidates for adaptive regulatory evolution. Genes involved in flight musculature and fatty acid metabolism were over-represented in the list of candidates. Conclusions: Overall, stabilizing selection appears to be the major force governing gene expression variation within populations. However, positive selection may be responsible for much of the between-population expression divergence. The nature of the genes identified to differ in expression between populations may reveal which traits were important for local adaptation to the European and African environments. Keywords: Natural variation
2008-01-21 | GSE8843 | GEO
Project description:Background: Differences in levels of gene expression among individuals are an important source of phenotypic variation within populations. Recent microarray studies have revealed that expression variation is abundant in many species, including Drosophila melanogaster. However, previous expression surveys in this species generally focused on a small number of laboratory strains established from derived populations. Thus, these studies were not ideal for population genetic analyses. Results: We surveyed gene expression variation in adult males of 16 D. melanogaster strains from two natural populations, including an ancestral African population and a derived European population. Levels of expression polymorphism were nearly equal in the two populations, but a higher number of differences was detected when comparing strains between populations. Expression variation was greatest for genes associated with few molecular functions or biological processes, as well as those expressed predominantly in males. Our analysis also identified genes that differed in expression level between the European and African populations, which may be candidates for adaptive regulatory evolution. Genes involved in flight musculature and fatty acid metabolism were over-represented in the list of candidates. Conclusions: Overall, stabilizing selection appears to be the major force governing gene expression variation within populations. However, positive selection may be responsible for much of the between-population expression divergence. The nature of the genes identified to differ in expression between populations may reveal which traits were important for local adaptation to the European and African environments. We used dual channel microarrays to compare genome-wide expression profiles in adult males from 16 inbred strains derived from two natural populations. In total 80 hybidizations were performed including dye-swaps. The hybridization scheme consisted of a balanced loop design, which allowed an unbiased comparison of relative expression levels within and between populations.
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Project description:One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increases the predictability of adaptive evolution.
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