Development of a QTL-environment-based predictive model for node addition rate in common bean
To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day− 1) on the main stem of the common bean (Phaseolus...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Springer
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/80542 |
| _version_ | 1855531580192194560 |
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| author | Zhang, Li Gezan, Salvador A. Vallejos, C. Eduardo Jones, James W. Boote, Kenneth J. Clavijo Michelangeli, José A. Bhakta, Mehul S. Osorno, Juan M. Rao, Idupulapati M. Beebe, Stephen E. Roman Paoli, Elvin O. González, Abiezer Beaver, James S. Ricaurte Oyola, José Jaumer Colbert, Raphael Correll, Melanie J. |
| author_browse | Beaver, James S. Beebe, Stephen E. Bhakta, Mehul S. Boote, Kenneth J. Clavijo Michelangeli, José A. Colbert, Raphael Correll, Melanie J. Gezan, Salvador A. González, Abiezer Jones, James W. Osorno, Juan M. Rao, Idupulapati M. Ricaurte Oyola, José Jaumer Roman Paoli, Elvin O. Vallejos, C. Eduardo Zhang, Li |
| author_facet | Zhang, Li Gezan, Salvador A. Vallejos, C. Eduardo Jones, James W. Boote, Kenneth J. Clavijo Michelangeli, José A. Bhakta, Mehul S. Osorno, Juan M. Rao, Idupulapati M. Beebe, Stephen E. Roman Paoli, Elvin O. González, Abiezer Beaver, James S. Ricaurte Oyola, José Jaumer Colbert, Raphael Correll, Melanie J. |
| author_sort | Zhang, Li |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day− 1) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50–90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions. |
| format | Journal Article |
| id | CGSpace80542 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace805422025-11-12T05:57:13Z Development of a QTL-environment-based predictive model for node addition rate in common bean Zhang, Li Gezan, Salvador A. Vallejos, C. Eduardo Jones, James W. Boote, Kenneth J. Clavijo Michelangeli, José A. Bhakta, Mehul S. Osorno, Juan M. Rao, Idupulapati M. Beebe, Stephen E. Roman Paoli, Elvin O. González, Abiezer Beaver, James S. Ricaurte Oyola, José Jaumer Colbert, Raphael Correll, Melanie J. phaseolus vulgaris quantitative trait loci genetic markers environment factors phenotypes loci de rasgos cuantitativos marcadores genéticos factores ambientales To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day− 1) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50–90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions. 2017-05 2017-03-28T13:09:29Z 2017-03-28T13:09:29Z Journal Article https://hdl.handle.net/10568/80542 en Open Access application/pdf Springer Zhang, Li; Gezan, Salvador A.; Vallejos, C. Eduardo; Jones, James W.; Boote, Kenneth J.; Clavijo-Michelangeli, Jose A.; Bhakta, Mehul; Osorno, Juan M.; Rao, Idupulapati; Beebe, Stephen; Roman-Paoli, Elvin; Gonzalez, Abiezer; Beaver, James; Ricaurte, Jaumer; Colbert, Raphael; Correll, Melanie J.. 2017. Development of a QTL-environment-based predictive model for node addition rate in common bean. Theoretical and Applied Genetics . 130(5): 1065-1079. |
| spellingShingle | phaseolus vulgaris quantitative trait loci genetic markers environment factors phenotypes loci de rasgos cuantitativos marcadores genéticos factores ambientales Zhang, Li Gezan, Salvador A. Vallejos, C. Eduardo Jones, James W. Boote, Kenneth J. Clavijo Michelangeli, José A. Bhakta, Mehul S. Osorno, Juan M. Rao, Idupulapati M. Beebe, Stephen E. Roman Paoli, Elvin O. González, Abiezer Beaver, James S. Ricaurte Oyola, José Jaumer Colbert, Raphael Correll, Melanie J. Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title | Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title_full | Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title_fullStr | Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title_full_unstemmed | Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title_short | Development of a QTL-environment-based predictive model for node addition rate in common bean |
| title_sort | development of a qtl environment based predictive model for node addition rate in common bean |
| topic | phaseolus vulgaris quantitative trait loci genetic markers environment factors phenotypes loci de rasgos cuantitativos marcadores genéticos factores ambientales |
| url | https://hdl.handle.net/10568/80542 |
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