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Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

ABSTRACT: Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models.

SUBMITTER: Atanur SS

PROVIDER: S-EPMC3732391 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

Atanur Santosh S SS Diaz Ana Garcia AG Maratou Klio K Sarkis Allison A Rotival Maxime M Game Laurence L Tschannen Michael R MR Kaisaki Pamela J PJ Otto Georg W GW Ma Man Chun John MC Keane Thomas M TM Hummel Oliver O Saar Kathrin K Chen Wei W Guryev Victor V Gopalakrishnan Kathirvel K Garrett Michael R MR Joe Bina B Citterio Lorena L Bianchi Giuseppe G McBride Martin M Dominiczak Anna A Adams David J DJ Serikawa Tadao T Flicek Paul P Cuppen Edwin E Hubner Norbert N Petretto Enrico E Gauguier Dominique D Kwitek Anne A Jacob Howard H Aitman Timothy J TJ

Cell 20130725 3

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analy ...[more]

PMID: 23890820

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Project description:BACKGROUND: An increasing number of aquaculture species are subjected to artificial selection in systematic breeding programs. Rapid improvements of important commercial traits are reported, but little is known about the effects of the strong directional selection applied, on gene level variation. Large numbers of genetic markers are becoming available, making it feasible to detect and estimate these effects. Here a simulation tool was developed in order to explore the power by which single genetic loci subjected to uni-directional selection in parallel breeding populations may be detected. FINDINGS: Two simulation models were pursued: 1) screening for loci displaying higher genetic differentiation than expected (high-FST outliers), from neutral evolution between a pool of domesticated populations and a pool of wild populations; 2) screening for loci displaying lower genetic differentiation (low-FST outliers) between domesticated strains than expected from neutral evolution. The premise for both approaches was that the isolated domesticated strains are subjected to the same breeding goals. The power to detect outlier loci was calculated under the following parameter values: number of populations, effective population size per population, number of generations since onset of selection, initial FST, and the selection coefficient acting on the locus. Among the parameters investigated, selection coefficient, the number of generation since onset of selection, and number of populations, had the largest impact on power. The power to detect loci subjected to directional in breeding programmes was high when applying the between farmed and wild population approach, and low for the between farmed populations approach. CONCLUSIONS: A simulation tool was developed for estimating the power to detect artificial selection acting directly on single loci. The simulation tool should be applicable to most species subject to domestication, as long as a reasonable high accuracy in input parameters such as effective population size, number of generations since the initiation of selection, and initial differentiation (FST) can be obtained. Identification of genetic loci under artificial selection would be highly valuable, since such loci could be used to monitor maintenance of genetic variation in the breeding populations and monitoring possible genetic changes in wild populations from genetic interaction between escapees and their wild counterpart.

Dataset Information

Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

Publications

Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

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