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

Detalhes bibliográficos
Autor(a) principal: Viana,José Marcelo Soriano
Data de Publicação: 2016
Outros Autores: Piepho,Hans-Peter, Silva,Fabyano Fonseca e
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300243
Resumo: ABSTRACT 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 populationsgenome-wide selectionadditive value predictionprediction accuracyABSTRACT 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.Escola Superior de Agricultura "Luiz de Queiroz"2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300243Scientia Agricola v.73 n.3 2016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/0103-9016-2014-0383info:eu-repo/semantics/openAccessViana,José Marcelo SorianoPiepho,Hans-PeterSilva,Fabyano Fonseca eeng2016-05-16T00:00:00Zoai:scielo:S0103-90162016000300243Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2016-05-16T00:00Scientia 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
genome-wide selection
additive value prediction
prediction accuracy
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
dc.subject.por.fl_str_mv genome-wide selection
additive value prediction
prediction accuracy
topic genome-wide selection
additive value prediction
prediction accuracy
description ABSTRACT 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
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300243
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300243
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-9016-2014-0383
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.73 n.3 2016
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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