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Trait variation and genetic diversity in a banana genomic selection training population

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency a...

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Autores principales: Nyine, Moses, Uwimana, Brigitte, Swennen, Rony, Batte, Michael, Brown, Allan, Christelová, Pavla, Hřibová, Eva, Lorenzen, Jim, Doležel, Jaroslav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460855/
https://www.ncbi.nlm.nih.gov/pubmed/28586365
http://dx.doi.org/10.1371/journal.pone.0178734
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author Nyine, Moses
Uwimana, Brigitte
Swennen, Rony
Batte, Michael
Brown, Allan
Christelová, Pavla
Hřibová, Eva
Lorenzen, Jim
Doležel, Jaroslav
author_facet Nyine, Moses
Uwimana, Brigitte
Swennen, Rony
Batte, Michael
Brown, Allan
Christelová, Pavla
Hřibová, Eva
Lorenzen, Jim
Doležel, Jaroslav
author_sort Nyine, Moses
collection PubMed
description Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.
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spelling pubmed-54608552017-06-15 Trait variation and genetic diversity in a banana genomic selection training population Nyine, Moses Uwimana, Brigitte Swennen, Rony Batte, Michael Brown, Allan Christelová, Pavla Hřibová, Eva Lorenzen, Jim Doležel, Jaroslav PLoS One Research Article Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents. Public Library of Science 2017-06-06 /pmc/articles/PMC5460855/ /pubmed/28586365 http://dx.doi.org/10.1371/journal.pone.0178734 Text en © 2017 Nyine et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nyine, Moses
Uwimana, Brigitte
Swennen, Rony
Batte, Michael
Brown, Allan
Christelová, Pavla
Hřibová, Eva
Lorenzen, Jim
Doležel, Jaroslav
Trait variation and genetic diversity in a banana genomic selection training population
title Trait variation and genetic diversity in a banana genomic selection training population
title_full Trait variation and genetic diversity in a banana genomic selection training population
title_fullStr Trait variation and genetic diversity in a banana genomic selection training population
title_full_unstemmed Trait variation and genetic diversity in a banana genomic selection training population
title_short Trait variation and genetic diversity in a banana genomic selection training population
title_sort trait variation and genetic diversity in a banana genomic selection training population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460855/
https://www.ncbi.nlm.nih.gov/pubmed/28586365
http://dx.doi.org/10.1371/journal.pone.0178734
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