Literature DB >> 27553082

Genetic architecture of male floral traits required for hybrid wheat breeding.

Philipp H G Boeven1, C Friedrich H Longin1, Willmar L Leiser1, Sonja Kollers2, Erhard Ebmeyer2, Tobias Würschum3.   

Abstract

KEY MESSAGE: This study revealed a complex genetic architecture of male floral traits in wheat, and Rht-D1 was identified as the only major QTL. Genome-wide prediction approaches but also phenotypic recurrent selection appear promising to increase outcrossing ability required for hybrid wheat seed production. Hybrid wheat breeding is a promising approach to increase grain yield and yield stability. However, the identification of lines with favorable male floral characteristics required for hybrid seed production currently poses a severe bottleneck for hybrid wheat breeding. This study therefore aimed to unravel the genetic architecture of floral traits and to assess the potential of genomic approaches to accelerate their improvement. To this end, we employed a panel of 209 diverse winter wheat lines assessed for male floral traits and genotyped with genome-wide markers as well as for Rht-B1 and Rht-D1. We found the highest proportion of explained genotypic variance for the Rht-D1 locus (11-24 %), for which the dwarfing allele Rht-D1b had a negative effect on anther extrusion, visual anther extrusion and pollen mass. The genome-wide scan detected only few QTL with small or medium effects, indicating a complex genetic architecture. Consequently, marker-assisted selection yielded only moderate prediction abilities (0.44-0.63), mainly relying on Rht-D1. Genomic selection based on weighted ridge-regression best linear unbiased prediction achieved higher prediction abilities of up to 0.70 for anther extrusion. In conclusion, recurrent phenotypic selection appears most cost-effective for the initial improvement of floral traits in wheat, while genome-wide prediction approaches may be worthwhile when complete marker profiles are already available in a hybrid wheat breeding program.

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Year:  2016        PMID: 27553082     DOI: 10.1007/s00122-016-2771-6

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  52 in total

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