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Development of a QTL-environment-based predictive model for node addition rate in common bean

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Title Development of a QTL-environment-based predictive model for node addition rate in common bean
 
Creator 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.
 
Subject phaseolus vulgaris
quantitative trait loci
genetic markers
environment factors
phenotypes
loci de rasgos cuantitativos
marcadores genéticos
factores ambientales
 
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.
 
Date 2017-05
2017-03-28T13:09:29Z
2017-03-28T13:09:29Z
 
Type Journal Article
 
Identifier 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.
https://hdl.handle.net/10568/80542
https://doi.org/10.1007/s00122-017-2871-y
 
Language en
 
Rights Copyrighted; all rights reserved
Open Access
 
Format 1065-1079
application/pdf
 
Publisher Springer Science and Business Media LLC
 
Source Theoretical and Applied Genetics