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

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    Journal Article (817.9Kb)
    Authors
    Nyine, M.
    Uwimana, B.
    Swennen, Rony L.
    Batte, M.
    Brown, A.
    Christelova, P.
    Hribova, E.
    Lorenzen, J.H.
    Doležel, Jaroslav
    Date Issued
    2017-06
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    ISI journal
    Accessibility
    Open Access
    Usage rights
    CC-BY-4.0
    Metadata
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    Citation
    Nyine, M., Uwimana, B., Swennen, R., Batte, M., Brown, A., Christelová, P. ... & Doležel, J. (2017). Trait variation and genetic diversity in a banana genomic selection training population. PLoS One, 12(6), e0178734. 1-23.
    Permanent link to cite or share this item: https://hdl.handle.net/10568/82760
    DOI: https://doi.org/10.1371/journal.pone.0178734
    Abstract/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.
    Notes
    Open Access Journal
    Other CGIAR Affiliations
    Roots, Tubers and Bananas
    AGROVOC Keywords
    genetic variation; genomic selection; east african highland banana; traits variation
    Subjects
    BANANA; FOOD SECURITY; PLANT GENETIC RESOURCES
    Countries
    Uganda
    Regions
    Africa; Eastern Africa
    Organizations Affiliated to the Authors
    Palacky University; International Institute of Tropical Agriculture; Czech Academy of Sciences
    Investors/sponsors
    Bill & Melinda Gates Foundation
    Collections
    • Bioversity Journal Articles [1060]
    • Effective Genetic Resources Conservation and Use [446]
    • IITA Journal Articles [4999]
    • RTB Journal Articles [1344]

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