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Data from: Identifying signatures of sexual selection using genomewide selection components analysis

Main Authors: Flanagan, Sarah P., Jones, Adam G.
Format: info dataset Journal
Terbitan: , 2016
Subjects:
simulation model
reproductive success
Online Access: https://zenodo.org/record/4997329
ctrlnum 4997329
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Flanagan, Sarah P.</creator><creator>Jones, Adam G.</creator><date>2016-02-25</date><description>Sexual selection must affect the genome for it to have an evolutionary impact, yet signatures of selection remain elusive. Here we use an individual-based model to investigate the utility of genome-wide selection components analysis, which compares allele frequencies of individuals at different life history stages within a single population to detect selection without requiring a priori knowledge of traits under selection. We modeled a diploid, sexually reproducing population and introduced strong mate choice on a quantitative trait to simulate sexual selection. Genome-wide allele frequencies in adults and offspring were compared using weighted FST values. The average number of outlier peaks (i.e., those with significantly large FST values) with a quantitative trait locus in close proximity ("real" peaks) represented correct diagnoses of loci under selection, whereas peaks above the FST significance threshold without a quantitative trait locus reflected spurious peaks. We found that, even with moderate sample sizes, signatures of strong sexual selection were detectable, but larger sample sizes improved detection rates. The model was better able to detect selection with more neutral markers, and when quantitative trait loci and neutral markers were distributed across multiple chromosomes. Although environmental variation decreased detection rates, the identification of real peaks nevertheless remained feasible. We also found that detection rates can be improved by sampling multiple populations experiencing similar selection regimes. In short, genome-wide selection components analysis is a challenging but feasible approach for the identification of regions of the genome under selection.</description><description>summary data from simulation modelThese data are the average percent of real loci and the average number of spurious loci detected given the various parameter combinations tested by the model.Flanagan_and_Jones_molecol_data.docx.xlsxmultiple populations comparisonThis data contains Fst values for loci in replicate populations with the same QTLs, which were: chrom 0: 702, 978; chrom 1: 516, 341; chrom 2: 878, 76; chrom 3: 46, 153.12May_same-qtls_Fsts.txtpopulationsHeader file for C++ simulation programlife_cycleC++ program file for simulation modelchi_squareHeader file containing functions to calculate chi-square p-values for C++ simulation model.rand_numsC++ header file containing functions to calculate and use random numbers for simulation model program. File is available in GitHub at https://github.com/spflanagan/gwsca_simulation_model/blob/master/simulation_model/simulation_model/rand_nums.hSimulation_DataAll summary data from the simulation model (the average number of real and spurious peaks for all parameter combinations).</description><identifier>https://zenodo.org/record/4997329</identifier><identifier>10.5061/dryad.5k84d</identifier><identifier>oai:zenodo.org:4997329</identifier><relation>doi:10.1002/ece3.1546</relation><relation>url:https://github.com/spflanagan/gwsca_simulation_model/blob/master/simulation_model/simulation_model/rand_nums.h</relation><relation>url:https://zenodo.org/communities/dryad</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/publicdomain/zero/1.0/legalcode</rights><subject>simulation model</subject><subject>reproductive success</subject><title>Data from: Identifying signatures of sexual selection using genomewide selection components analysis</title><type>Other:info:eu-repo/semantics/other</type><type>Other:dataset</type><recordID>4997329</recordID></dc>
format Other:info:eu-repo/semantics/other
Other
Other:dataset
Journal:Journal
Journal
author Flanagan, Sarah P.
Jones, Adam G.
title Data from: Identifying signatures of sexual selection using genomewide selection components analysis
publishDate 2016
topic simulation model
reproductive success
url https://zenodo.org/record/4997329
contents Sexual selection must affect the genome for it to have an evolutionary impact, yet signatures of selection remain elusive. Here we use an individual-based model to investigate the utility of genome-wide selection components analysis, which compares allele frequencies of individuals at different life history stages within a single population to detect selection without requiring a priori knowledge of traits under selection. We modeled a diploid, sexually reproducing population and introduced strong mate choice on a quantitative trait to simulate sexual selection. Genome-wide allele frequencies in adults and offspring were compared using weighted FST values. The average number of outlier peaks (i.e., those with significantly large FST values) with a quantitative trait locus in close proximity ("real" peaks) represented correct diagnoses of loci under selection, whereas peaks above the FST significance threshold without a quantitative trait locus reflected spurious peaks. We found that, even with moderate sample sizes, signatures of strong sexual selection were detectable, but larger sample sizes improved detection rates. The model was better able to detect selection with more neutral markers, and when quantitative trait loci and neutral markers were distributed across multiple chromosomes. Although environmental variation decreased detection rates, the identification of real peaks nevertheless remained feasible. We also found that detection rates can be improved by sampling multiple populations experiencing similar selection regimes. In short, genome-wide selection components analysis is a challenging but feasible approach for the identification of regions of the genome under selection.
summary data from simulation modelThese data are the average percent of real loci and the average number of spurious loci detected given the various parameter combinations tested by the model.Flanagan_and_Jones_molecol_data.docx.xlsxmultiple populations comparisonThis data contains Fst values for loci in replicate populations with the same QTLs, which were: chrom 0: 702, 978; chrom 1: 516, 341; chrom 2: 878, 76; chrom 3: 46, 153.12May_same-qtls_Fsts.txtpopulationsHeader file for C++ simulation programlife_cycleC++ program file for simulation modelchi_squareHeader file containing functions to calculate chi-square p-values for C++ simulation model.rand_numsC++ header file containing functions to calculate and use random numbers for simulation model program. File is available in GitHub at https://github.com/spflanagan/gwsca_simulation_model/blob/master/simulation_model/simulation_model/rand_nums.hSimulation_DataAll summary data from the simulation model (the average number of real and spurious peaks for all parameter combinations).
id IOS16997.4997329
institution ZAIN Publications
institution_id 7213
institution_type library:special
library
library Cognizance Journal of Multidisciplinary Studies
library_id 5267
collection Cognizance Journal of Multidisciplinary Studies
repository_id 16997
subject_area Multidisciplinary
city Stockholm
province INTERNASIONAL
shared_to_ipusnas_str 1
repoId IOS16997
first_indexed 2022-06-06T05:23:47Z
last_indexed 2022-06-06T05:23:47Z
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