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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61389030%3A_____%2F17%3A00476567" target="_blank" >RIV/61389030:_____/17:00476567 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1371/journal.pone.0178734" target="_blank" >http://dx.doi.org/10.1371/journal.pone.0178734</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0178734" target="_blank" >10.1371/journal.pone.0178734</a>

Result language

angličtina

Original language name

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

Original language 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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10611 - Plant sciences, botany

Project

<a href="/en/project/LO1204" target="_blank" >LO1204: Sustainable development of research in the Centre of the Region Haná</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

PLoS ONE

ISSN

1932-6203

e-ISSN

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Volume of the periodical

12

Issue of the periodical within the volume

6

Country of publishing house

US - UNITED STATES

Number of pages

23

Pages from-to

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UT code for WoS article

000402875700025

EID of the result in the Scopus database

2-s2.0-85020300549