Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Parallel selection mapping using artificially selected mice reveals body weight control loci (SNP)

ABSTRACT: Understanding how polygenic traits evolve and respond to selection is a major unsolved problem, because challenges exist for identifying genes underlying a complex trait and understanding how multi-locus selection operates in the genome. Here we used artificial selection experiments to study polygenic response to selection. Inbred strains from seven independent long-term selection experiments in mice for extreme bodyweight (“High” lines weigh 77-42g vs. 40-16g in “Controls” lines), were genotyped at 527,572 SNPs to identify genetic variants controlling bodyweight. We identified 67 high-resolution parallel selected regions (PSRs) where multiple High lines share variants rarely found among the Controls. By comparing allele frequencies in one selection experiment against its unselected control, we found classical selective sweep signatures centered on the PSRs. Multiple lines of evidence support two G protein-coupled receptors GPR133 and Prlhr, as positional candidate genes controlling bodyweight. Artificial selection may mimic natural selection in the wild: compared to control loci, we detected reduced heterozygosity in PSRs in wild populations of unusually large mice on islands. Many PSRs overlap loci associated with human height variation, possibly through evolutionary conservation of functional pathways. Our data suggest that parallel selection on complex traits may evoke parallel responses at many genes involved in diverse but relevant pathways. These samples were used to test the enrichment of certain gene functional categories. Genomic DNA SNP comparison between artificially selected high lines (BEH, DAHi, DUH, MUH, EDH, RAHi, Du6/G154 and Du6i/G80) and unselected control lines.

ORGANISM(S): Mus musculus

SUBMITTER: Yingguang Frank Chan

PROVIDER: E-GEOD-36409 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Understanding how polygenic traits evolve and respond to selection is a major unsolved problem, because challenges exist for identifying genes underlying a complex trait and understanding how multi-locus selection operates in the genome. Here we used artificial selection experiments to study polygenic response to selection. Inbred strains from seven independent long-term selection experiments in mice for extreme bodyweight (M-bM-^@M-^\HighM-bM-^@M-^] lines weigh 77-42g vs. 40-16g in M-bM-^@M-^\ControlsM-bM-^@M-^] lines), were genotyped at 527,572 SNPs to identify genetic variants controlling bodyweight. We identified 67 high-resolution parallel selected regions (PSRs) where multiple High lines share variants rarely found among the Controls. By comparing allele frequencies in one selection experiment against its unselected control, we found classical selective sweep signatures centered on the PSRs. Multiple lines of evidence support two G protein-coupled receptors GPR133 and Prlhr, as positional candidate genes controlling bodyweight. Artificial selection may mimic natural selection in the wild: compared to control loci, we detected reduced heterozygosity in PSRs in wild populations of unusually large mice on islands. Many PSRs overlap loci associated with human height variation, possibly through evolutionary conservation of functional pathways. Our data suggest that parallel selection on complex traits may evoke parallel responses at many genes involved in diverse but relevant pathways. These samples were used to test the enrichment of certain gene functional categories. Mouse tissue samples (muscle and liver) were collected from 44 and 45 days old males from each of the nine out of thirteen lines (5 High lines: BEHi, DUHi, EDHi, MUHi, ROHi and 4 Control lines: BELi, EDLi, MULi and ROLi; n=23 total) at the University of Edinburgh. Frozen tissue samples were stored at -80M-BM-:C until use. Tissues were dissociated using TissueLyser II with steel beads (both Qiagen) following manufacturersM-bM-^@M-^Y instructions. mRNA was extracted and purified using TRIzol Reagent and the PureLink RNA Mini Kit (Life Technologies GmbH, Darmstadt, Germany). cDNA was synthesized using Maxima First Strand cDNA synthesis kit (Thermo Fisher Scientific, St. Leon-Rot, Germany). Muscle and liver cDNA samples were hybridized on a Mouse GE 4x44k Microarray (Agilent Technologies, Inc., Waldbronn, Germany) according to manufacturerM-bM-^@M-^Ys recommendations. Three technical replicate each was done on pooled cDNA samples from each mouse line.

Project description:Alcoholism is a complex disorder determined by interactions between genetic and environmental risk factors. Drosophila represents a powerful model system to dissect the genetic architecture of alcohol sensitivity, as large numbers of flies can readily be reared in defined genetic backgrounds and under controlled environmental conditions. Furthermore, flies exposed to ethanol undergo physiological and behavioral changes that resemble human alcohol intoxication, including loss of postural control, sedation, and development of tolerance. We performed artificial selection for alcohol sensitivity for 25 generations and created duplicate selection lines that are either highly sensitive or resistant to ethanol exposure along with unselected control lines. We used whole genome expression analysis to identify 1,678 probe sets with different expression levels between the divergent lines, pooled across replicates, at a false discovery rate of q < 0.001. We assessed to what extent genes with altered transcriptional regulation might be causally associated with ethanol sensitivity by measuring alcohol sensitivity of 37 co-isogenic P-element insertional mutations in 35 candidate genes, and found that 32 of these mutants differed in sensitivity to ethanol exposure from their co-isogenic controls. Furthermore, 23 of these novel genes have human orthologues. Combining whole genome expression profiling with selection for genetically divergent lines is an effective approach for identifying candidate genes that affect complex traits, such as alcohol sensitivity. Because of evolutionary conservation of function, it is likely that human orthologues of genes affecting alcohol sensitivity in Drosophila may contribute to alcohol-associated phenotypes in humans. Experiment Overall Design: Starting with flies from Raleigh natural population (see material and methods) we performed artificial selection for alcohol sensitivity for 35 generation. In each generations we scored 60 males and females, separately, from each line (resistant, sensitive, and control)using inebriometer, and the 20 highest-scoring flies from the resistant lines and the 20 lowest-scoring flies from the sensitive lines were selected as parents for the next generation. Control line flies were scored each generation and 20 random flies were used as parents. Experiment Overall Design: At generation 25, two replicates of 15 three-five day old virgin males and females were collected from each selection line. Total RNA was extracted from the 24 samples . Biotinylated cRNA probes were hybridized to high density oligonucleotide microarrays (Affymetrix, Inc. Drosophila GeneChip 2.0) and visualized with a streptavidin-phycoerythrin conjugate, as described in the Affymetrix GeneChip Expression Analysis Technical Manual (2000), using internal references for quantification. The quantitative estimate of expression of each probe set is the Signal (Sig) metric, as described in the Affymetrix Microarray Suite, Version 5.0.

Dataset Information

Parallel selection mapping using artificially selected mice reveals body weight control loci (SNP)

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets