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Genome-Wide Association Study of Haploid Male Fertility in Maize (Zea Mays L.)

Large-scale application of the doubled haploid (DH) technology by in vivo haploid induction has greatly improved the efficiency of maize breeding. While the haploid induction rate and the efficiency of identifying haploid plants have greatly improved in recent years, the low efficiency of doubling o...

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Detalles Bibliográficos
Autores principales: Ma, Hailin, Li, Guoliang, Würschum, Tobias, Zhang, Yao, Zheng, Debo, Yang, Xiaohong, Li, Jiansheng, Liu, Wenxin, Yan, Jianbing, Chen, Shaojiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057118/
https://www.ncbi.nlm.nih.gov/pubmed/30065732
http://dx.doi.org/10.3389/fpls.2018.00974
Descripción
Sumario:Large-scale application of the doubled haploid (DH) technology by in vivo haploid induction has greatly improved the efficiency of maize breeding. While the haploid induction rate and the efficiency of identifying haploid plants have greatly improved in recent years, the low efficiency of doubling of haploid plants has remained and currently presents the main limitation to maize DH line production. In this study, we aimed to assess the available genetic variation for haploid male fertility (HMF), i.e., the production of fertile pollen on haploid plants, and to investigate the underlying genetic architecture. To this end, a diversity panel of 481 maize inbred lines was crossed with “Mo17” and “Zheng58,” the F(1) hybrids subjected to haploid induction, and resulting haploid plants assessed for male fertility in two environments. Across both genetic backgrounds, we observed a large variation of HMF ranging from zero to ~60%, with a mean of 18%, and a heritability of 0.65. HMF was higher in the “Mo17” than in the “Zheng58” background and the correlation between both genetic backgrounds was 0.68. Genome-wide association mapping identified only few putative QTL that jointly explained 22.5% of the phenotypic variance. With the exception of one association explaining 11.77% of the phenotypic variance, all other putative QTL were of minor importance. A genome-wide prediction approach further corroborated the quantitative nature of HMF in maize. Analysis of the 14 significantly associated SNPs revealed several candidate genes. Collectively, our results illustrate the large variation of HMF that can be exploited for maize DH breeding. Owing to the apparent genetic complexity of this trait, this might best be achieved by rapid recurrent phenotypic selection coupled with marker-assisted selection for individual QTL.