Analysis of microsatellite variation in Drosophila melanogaster with population-scale genome sequencing.

TitleAnalysis of microsatellite variation in Drosophila melanogaster with population-scale genome sequencing.
Publication TypeJournal Article
Year of Publication2012
AuthorsFondon, JW, Martin, A, Richards, S, Gibbs, RA, Mittelman, D
JournalPLoS One
Date Published2012
KeywordsAnimals, Drosophila melanogaster, Genetic Variation, Genetics, Population, Genome, Genotype, Microsatellite Repeats, Mutation

Genome sequencing technologies promise to revolutionize our understanding of genetics, evolution, and disease by making it feasible to survey a broad spectrum of sequence variation on a population scale. However, this potential can only be realized to the extent that methods for extracting and interpreting distinct forms of variation can be established. The error profiles and read length limitations of early versions of next-generation sequencing technologies rendered them ineffective for some sequence variant types, particularly microsatellites and other tandem repeats, and fostered the general misconception that such variants are inherently inaccessible to these platforms. At the same time, tandem repeats have emerged as important sources of functional variation. Tandem repeats are often located in and around genes, and frequent mutations in their lengths exert quantitative effects on gene function and phenotype, rapidly degrading linkage disequilibrium between markers and traits. Sensitive identification of these variants in large-scale next-gen sequencing efforts will enable more comprehensive association studies capable of revealing previously invisible associations. We present a population-scale analysis of microsatellite repeats using whole-genome data from 158 inbred isolates from the Drosophila Genetics Reference Panel, a collection of over 200 extensively phenotypically characterized isolates from a single natural population, to uncover processes underlying repeat mutation and to enable associations with behavioral, morphological, and life-history traits. Analysis of repeat variation from next-generation sequence data will also enhance studies of genome stability and neurodegenerative diseases.

Alternate JournalPLoS One
PubMed ID22427938
PubMed Central IDPMC3299726
Grant ListU54 HG003273 / HG / NHGRI NIH HHS / United States
HG003273 / HG / NHGRI NIH HHS / United States

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