Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations

Bibliographic Details
Main Author: Viana, José Marcelo Soriano
Publication Date: 2016
Other Authors: Piepho, Hans-Peter, Silva, Fabyano Fonseca e
Format: Article
Language: eng
Source: Scientia Agrícola (Online)
Download full: https://www.revistas.usp.br/sa/article/view/115565
Summary: To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL). This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies) and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction.
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spelling Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL). This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies) and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/11556510.1590/0103-9016-2014-0383Scientia Agricola; v. 73 n. 3 (2016); 243-251Scientia Agricola; Vol. 73 Núm. 3 (2016); 243-251Scientia Agricola; Vol. 73 No. 3 (2016); 243-2511678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/115565/113145Copyright (c) 2016 Scientia Agricolainfo:eu-repo/semantics/openAccessViana, José Marcelo SorianoPiepho, Hans-PeterSilva, Fabyano Fonseca e2016-05-20T18:42:52Zoai:revistas.usp.br:article/115565Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2016-05-20T18:42:52Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
title Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
spellingShingle Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
Viana, José Marcelo Soriano
title_short Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
title_full Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
title_fullStr Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
title_full_unstemmed Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
title_sort Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations
author Viana, José Marcelo Soriano
author_facet Viana, José Marcelo Soriano
Piepho, Hans-Peter
Silva, Fabyano Fonseca e
author_role author
author2 Piepho, Hans-Peter
Silva, Fabyano Fonseca e
author2_role author
author
dc.contributor.author.fl_str_mv Viana, José Marcelo Soriano
Piepho, Hans-Peter
Silva, Fabyano Fonseca e
description To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL). This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies) and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/115565
10.1590/0103-9016-2014-0383
url https://www.revistas.usp.br/sa/article/view/115565
identifier_str_mv 10.1590/0103-9016-2014-0383
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/115565/113145
dc.rights.driver.fl_str_mv Copyright (c) 2016 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 73 n. 3 (2016); 243-251
Scientia Agricola; Vol. 73 Núm. 3 (2016); 243-251
Scientia Agricola; Vol. 73 No. 3 (2016); 243-251
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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