Genetic architecture and genomic predictive ability of apple quantitative traits across environments
Visualitza/Obre
Autor/a
Jung, Michaela
Keller, Beat
Roth, Morgane
Aranzana, Maria José
Auwerkerken, Annemarie
Guerra, Walter
Al-Rifaï, Mehdi
Lewandowski, Mariusz
Sanin, Nadia
Rymenants, Marijn
Didelot, Frédérique
Dujak, Christian
Knauf, Andrea
Laurens, François
Studer, Bruno
Muranty, Hélène
Patocchi, Andrea
Data de publicació
2022-02-19ISSN
2052-7276
Resum
Implementation of genomic tools is desirable to increase the efficiency of apple breeding. Recently, the multi-environment apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic predictive ability, and studying genotype by environment interactions (G × E). So far, only two phenological traits were investigated using the apple REFPOP, although the population may be valuable when dissecting genetic architecture and reporting predictive abilities for additional key traits in apple breeding. Here we show contrasting genetic architecture and genomic predictive abilities for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic predictive abilities of 0.18–0.88 were estimated using main-effect univariate, main-effect multivariate, multi-environment univariate, and multi-environment multivariate models.
The G × E accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of traitenvironment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.
Tipus de document
Article
Versió del document
Versió publicada
Llengua
Anglès
Matèries (CDU)
633 - Cultius i produccions
Pàgines
22
Publicat per
Oxford University Press
Publicat a
Horticulture Research
Citació
Jung, Michaela, Beat Keller, Morgane Roth, Maria José Aranzana, Annemarie Auwerkerken, Walter Guerra, and Mehdi Al-Rifaï et al. 2022. "Genetic Architecture And Genomic Predictive Ability Of Apple Quantitative Traits Across Environments". Horticulture Research 9. doi:10.1093/hr/uhac028.
Número de l'acord de la subvenció
MINECO/Programa Estatal de fomento de la investigación científica y técnica de excelencia/SEV-2015-0533/ES/ /
MICINN/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/CEX2019-000902-S/ES/ /
EC/H2020/817970/EU/INnovations in plant VarIety Testing in Europe to foster the introduction of new varieties better adapted to varying biotic and abiotic conditions and to more sustainable crop management practices/INVITE
Programa
Genòmica i Biotecnologia
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