Predicting performance of soybean populations using genetic distances estimated with RAPD markers
Autor(a) principal: | |
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Data de Publicação: | 2003 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Genetics and Molecular Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572003000300020 |
Resumo: | In order to verify whether genetic distance (GD) is associated with population mean (PM), genetic variance (GV) and the proportion of superior progenies generated by each cross in advanced generations of selfing (PS), the genetic distances between eight soybean lines (five adapted and three non-adapted) were estimated using 213 polymorphic RAPD markers. The genetic distances were partitioned according to Griffing's Model I Method 4 for diallel analysis, i.e., GDij = GD+ GGDi+ GGDj + SGDij. Phenotypic data were recorded for seed yield and plant height for 25 out of 28 populations of a diallel set derived from the eight soybean lines and evaluated from F2:8 to F2:11 generations. No significant correlation for seed yield was detected between GD and GV, while negative correlations were detected between GD and PM and between GD and PS (r = -0.74** and -0.75**, respectively). Similar results were observed for the correlation between GGDi + GGDj and PM and between GGDi + GGDj and PS (r = -0.78** and -0.80**, respectively). No significant correlation was detected for plant height. The magnitudes of the correlations for seed yield were high enough to allow predictions of the potential of the populations based on RAPD markers. |
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Genetics and Molecular Biology |
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Predicting performance of soybean populations using genetic distances estimated with RAPD markerssoybeangenetic distancemolecular markersRAPDpredictionIn order to verify whether genetic distance (GD) is associated with population mean (PM), genetic variance (GV) and the proportion of superior progenies generated by each cross in advanced generations of selfing (PS), the genetic distances between eight soybean lines (five adapted and three non-adapted) were estimated using 213 polymorphic RAPD markers. The genetic distances were partitioned according to Griffing's Model I Method 4 for diallel analysis, i.e., GDij = GD+ GGDi+ GGDj + SGDij. Phenotypic data were recorded for seed yield and plant height for 25 out of 28 populations of a diallel set derived from the eight soybean lines and evaluated from F2:8 to F2:11 generations. No significant correlation for seed yield was detected between GD and GV, while negative correlations were detected between GD and PM and between GD and PS (r = -0.74** and -0.75**, respectively). Similar results were observed for the correlation between GGDi + GGDj and PM and between GGDi + GGDj and PS (r = -0.78** and -0.80**, respectively). No significant correlation was detected for plant height. The magnitudes of the correlations for seed yield were high enough to allow predictions of the potential of the populations based on RAPD markers.Sociedade Brasileira de Genética2003-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572003000300020Genetics and Molecular Biology v.26 n.3 2003reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572003000300020info:eu-repo/semantics/openAccessBarroso,Paulo Augusto ViannaGeraldi,Isaias OlívioVieira,Maria Lúcia CarneiroPulcinelli,Carlos EduardoVencovsky,RolandDias,Carlos Tadeu dos Santoseng2003-10-02T00:00:00Zoai:scielo:S1415-47572003000300020Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2003-10-02T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false |
dc.title.none.fl_str_mv |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
title |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
spellingShingle |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers Barroso,Paulo Augusto Vianna soybean genetic distance molecular markers RAPD prediction |
title_short |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
title_full |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
title_fullStr |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
title_full_unstemmed |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
title_sort |
Predicting performance of soybean populations using genetic distances estimated with RAPD markers |
author |
Barroso,Paulo Augusto Vianna |
author_facet |
Barroso,Paulo Augusto Vianna Geraldi,Isaias Olívio Vieira,Maria Lúcia Carneiro Pulcinelli,Carlos Eduardo Vencovsky,Roland Dias,Carlos Tadeu dos Santos |
author_role |
author |
author2 |
Geraldi,Isaias Olívio Vieira,Maria Lúcia Carneiro Pulcinelli,Carlos Eduardo Vencovsky,Roland Dias,Carlos Tadeu dos Santos |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Barroso,Paulo Augusto Vianna Geraldi,Isaias Olívio Vieira,Maria Lúcia Carneiro Pulcinelli,Carlos Eduardo Vencovsky,Roland Dias,Carlos Tadeu dos Santos |
dc.subject.por.fl_str_mv |
soybean genetic distance molecular markers RAPD prediction |
topic |
soybean genetic distance molecular markers RAPD prediction |
description |
In order to verify whether genetic distance (GD) is associated with population mean (PM), genetic variance (GV) and the proportion of superior progenies generated by each cross in advanced generations of selfing (PS), the genetic distances between eight soybean lines (five adapted and three non-adapted) were estimated using 213 polymorphic RAPD markers. The genetic distances were partitioned according to Griffing's Model I Method 4 for diallel analysis, i.e., GDij = GD+ GGDi+ GGDj + SGDij. Phenotypic data were recorded for seed yield and plant height for 25 out of 28 populations of a diallel set derived from the eight soybean lines and evaluated from F2:8 to F2:11 generations. No significant correlation for seed yield was detected between GD and GV, while negative correlations were detected between GD and PM and between GD and PS (r = -0.74** and -0.75**, respectively). Similar results were observed for the correlation between GGDi + GGDj and PM and between GGDi + GGDj and PS (r = -0.78** and -0.80**, respectively). No significant correlation was detected for plant height. The magnitudes of the correlations for seed yield were high enough to allow predictions of the potential of the populations based on RAPD markers. |
publishDate |
2003 |
dc.date.none.fl_str_mv |
2003-01-01 |
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=S1415-47572003000300020 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572003000300020 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1415-47572003000300020 |
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 |
Sociedade Brasileira de Genética |
publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
dc.source.none.fl_str_mv |
Genetics and Molecular Biology v.26 n.3 2003 reponame:Genetics and Molecular Biology instname:Sociedade Brasileira de Genética (SBG) instacron:SBG |
instname_str |
Sociedade Brasileira de Genética (SBG) |
instacron_str |
SBG |
institution |
SBG |
reponame_str |
Genetics and Molecular Biology |
collection |
Genetics and Molecular Biology |
repository.name.fl_str_mv |
Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG) |
repository.mail.fl_str_mv |
||editor@gmb.org.br |
_version_ |
1752122378667687936 |