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Impacts of dominance effects on genomic prediction of sorghum hybrid performance.

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  • معلومة اضافية
    • المصدر:
      Publisher: Japanese Society of Breeding Country of Publication: Japan NLM ID: 9888571 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1344-7610 (Print) Linking ISSN: 13447610 NLM ISO Abbreviation: Breed Sci Subsets: PubMed not MEDLINE
    • بيانات النشر:
      Original Publication: [Tokyo] : Japanese Society of Breeding, 1999-
    • نبذة مختصرة :
      Non-additive (dominance and epistasis) effects have remarkable influences on hybrid performance, e.g., via heterosis. Nevertheless, only additive effects are often considered in genomic predictions (GP). In this study, we demonstrated the importance of dominance effects in the prediction of hybrid performance in bioenergy sorghum [ Sorghum bicolor (L.) Moench]. The dataset contained more than 400 hybrids between 200 inbred lines and two testers. The hybrids exhibited considerable heterosis in culm length and fresh weight, and the degree of heterosis was consistent with the genetic distance from the corresponding tester. The degree of heterosis was further different among subpopulations. Conversely, Brix exhibited limited heterosis. Regarding GP, we examined three statistical models and four training dataset types. In most of the dataset types, genomic best linear unbiased prediction (GBLUP) with additive effects had lower prediction accuracy than GBLUP with additive and dominance effects (GBLUP-AD) and Gaussian kernel regression (GK). The superiority of GBLUP-AD and GK depended on the level of dominance variance, which was high for culm length and fresh weight, and low for Brix. Considering subpopulations, the influence of dominance was more complex. Our findings highlight the importance of considering dominance effects in GP models for sorghum hybrid breeding.
      (Copyright © 2020 by JAPANESE SOCIETY OF BREEDING.)
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    • Contributed Indexing:
      Keywords: F1 hybrid; biofuel-related traits; dominance; genomic best linear unbiased prediction (GBLUP); genomic selection; sorghum
    • الموضوع:
      Date Created: 20210219 Latest Revision: 20210220
    • الموضوع:
      20221213
    • الرقم المعرف:
      PMC7878944
    • الرقم المعرف:
      10.1270/jsbbs.20042
    • الرقم المعرف:
      33603557