Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn

Detalhes bibliográficos
Autor(a) principal: Veiga,Adriano Delly
Data de Publicação: 2012
Outros Autores: Pinho,Renzo Garcia Von, Resende,Luciane Vilela, Pinho,Édila Vilela de Resende Von, Balestre,Márcio, Pereira,Laís Andrade
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência e Agrotecnologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542012000100004
Resumo: The main objectives of hybrid development programs include incorporating genetic resistance to diseases and increasing grain yield. Identification of Quantitative Trait Loci (QTL) through the statistical analysis of molecular markers allows efficient selection of resistant and productive hybrids. The objective of this research was to identify QTL associated with resistance to gray leaf spot and for grain yield in the germplasm of tropical corn. We used two strains with different degrees of reaction to the disease; the genotypes are owned by GENESEEDS Ltda, their F1 hybrid and the F2 population. The plants were evaluated for gray leaf spot resistance, for grain yield and were genotyped with 94 microsatellite markers. Association of the markers with the QTL was performed by single marker analysis using linear regression and maximum likelihood analysis. It was observed that the additive effect was predominant for genetic control of resistance to gray leaf spot, and the dominant effect in that of grain yield. The most promising markers to be used in studies of assisted selection are: umc2082 in bins 4.03 and umc1117 in bins 4.04 for resistance to gray leaf spot; for grain yield umc1042 in bins 2.07 and umc1058 in bins 4.11.
id UFLA-2_9b26ae3c5b7d04007151f3b172567bfe
oai_identifier_str oai:scielo:S1413-70542012000100004
network_acronym_str UFLA-2
network_name_str Ciência e Agrotecnologia (Online)
repository_id_str
spelling Quantitative trait loci associated with resistance to gray leaf spot and grain yield in cornMaximum likelihoodmicrosatellitesregressionThe main objectives of hybrid development programs include incorporating genetic resistance to diseases and increasing grain yield. Identification of Quantitative Trait Loci (QTL) through the statistical analysis of molecular markers allows efficient selection of resistant and productive hybrids. The objective of this research was to identify QTL associated with resistance to gray leaf spot and for grain yield in the germplasm of tropical corn. We used two strains with different degrees of reaction to the disease; the genotypes are owned by GENESEEDS Ltda, their F1 hybrid and the F2 population. The plants were evaluated for gray leaf spot resistance, for grain yield and were genotyped with 94 microsatellite markers. Association of the markers with the QTL was performed by single marker analysis using linear regression and maximum likelihood analysis. It was observed that the additive effect was predominant for genetic control of resistance to gray leaf spot, and the dominant effect in that of grain yield. The most promising markers to be used in studies of assisted selection are: umc2082 in bins 4.03 and umc1117 in bins 4.04 for resistance to gray leaf spot; for grain yield umc1042 in bins 2.07 and umc1058 in bins 4.11.Editora da UFLA2012-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542012000100004Ciência e Agrotecnologia v.36 n.1 2012reponame:Ciência e Agrotecnologia (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLA10.1590/S1413-70542012000100004info:eu-repo/semantics/openAccessVeiga,Adriano DellyPinho,Renzo Garcia VonResende,Luciane VilelaPinho,Édila Vilela de Resende VonBalestre,MárcioPereira,Laís Andradeeng2012-04-17T00:00:00Zoai:scielo:S1413-70542012000100004Revistahttp://www.scielo.br/cagroPUBhttps://old.scielo.br/oai/scielo-oai.php||renpaiva@dbi.ufla.br|| editora@editora.ufla.br1981-18291413-7054opendoar:2012-04-17T00:00Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
title Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
spellingShingle Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
Veiga,Adriano Delly
Maximum likelihood
microsatellites
regression
title_short Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
title_full Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
title_fullStr Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
title_full_unstemmed Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
title_sort Quantitative trait loci associated with resistance to gray leaf spot and grain yield in corn
author Veiga,Adriano Delly
author_facet Veiga,Adriano Delly
Pinho,Renzo Garcia Von
Resende,Luciane Vilela
Pinho,Édila Vilela de Resende Von
Balestre,Márcio
Pereira,Laís Andrade
author_role author
author2 Pinho,Renzo Garcia Von
Resende,Luciane Vilela
Pinho,Édila Vilela de Resende Von
Balestre,Márcio
Pereira,Laís Andrade
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Veiga,Adriano Delly
Pinho,Renzo Garcia Von
Resende,Luciane Vilela
Pinho,Édila Vilela de Resende Von
Balestre,Márcio
Pereira,Laís Andrade
dc.subject.por.fl_str_mv Maximum likelihood
microsatellites
regression
topic Maximum likelihood
microsatellites
regression
description The main objectives of hybrid development programs include incorporating genetic resistance to diseases and increasing grain yield. Identification of Quantitative Trait Loci (QTL) through the statistical analysis of molecular markers allows efficient selection of resistant and productive hybrids. The objective of this research was to identify QTL associated with resistance to gray leaf spot and for grain yield in the germplasm of tropical corn. We used two strains with different degrees of reaction to the disease; the genotypes are owned by GENESEEDS Ltda, their F1 hybrid and the F2 population. The plants were evaluated for gray leaf spot resistance, for grain yield and were genotyped with 94 microsatellite markers. Association of the markers with the QTL was performed by single marker analysis using linear regression and maximum likelihood analysis. It was observed that the additive effect was predominant for genetic control of resistance to gray leaf spot, and the dominant effect in that of grain yield. The most promising markers to be used in studies of assisted selection are: umc2082 in bins 4.03 and umc1117 in bins 4.04 for resistance to gray leaf spot; for grain yield umc1042 in bins 2.07 and umc1058 in bins 4.11.
publishDate 2012
dc.date.none.fl_str_mv 2012-02-01
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=S1413-70542012000100004
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542012000100004
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1413-70542012000100004
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 Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv Ciência e Agrotecnologia v.36 n.1 2012
reponame:Ciência e Agrotecnologia (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Ciência e Agrotecnologia (Online)
collection Ciência e Agrotecnologia (Online)
repository.name.fl_str_mv Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv ||renpaiva@dbi.ufla.br|| editora@editora.ufla.br
_version_ 1750226493963763712