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Genomic prediction in hybrid breeding: I. Optimizing the training set design.
Melchinger, Albrecht E; Fernando, Rohan; Stricker, Christian; Schön, Chris-Carolin; Auinger, Hans-Jürgen.
Afiliação
  • Melchinger AE; Plant Breeding, TUM School of Life Sciences, Technical University of Munich, 85354, Freising, Germany. albrechtmelchinger@gmail.com.
  • Fernando R; Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70599, Stuttgart, Germany. albrechtmelchinger@gmail.com.
  • Stricker C; Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
  • Schön CC; Plant Breeding, TUM School of Life Sciences, Technical University of Munich, 85354, Freising, Germany.
  • Auinger HJ; Plant Breeding, TUM School of Life Sciences, Technical University of Munich, 85354, Freising, Germany.
Theor Appl Genet ; 136(8): 176, 2023 Aug 02.
Article em En | MEDLINE | ID: mdl-37532821
ABSTRACT
KEY MESSAGE Training sets produced by maximizing the number of parent lines, each involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 and H2 hybrids. Genomic prediction holds great promise for hybrid breeding but optimum composition of the training set (TS) as determined by the number of parents (nTS) and crosses per parent (c) has received little attention. Our objective was to examine prediction accuracy ([Formula see text]) of GCA for lines used as parents of the TS (I1 lines) or not (I0 lines), and H0, H1 and H2 hybrids, comprising crosses of type I0 × I0, I1 × I0 and I1 × I1, respectively, as function of nTS and c. In the theory, we developed estimates for [Formula see text] of GBLUPs for hybrids (i)[Formula see text] based on the expected prediction accuracy, and (ii) [Formula see text] based on [Formula see text] of GBLUPs of GCA and SCA effects. In the simulation part, hybrid populations were generated using molecular data from two experimental maize data sets. Additive and dominance effects of QTL borrowed from literature were used to simulate six scenarios of traits differing in the proportion (τSCA = 1%, 6%, 22%) of SCA variance in σG2 and heritability (h2 = 0.4, 0.8). Values of [Formula see text] and [Formula see text] closely agreed with [Formula see text] for hybrids. For given size NTS = nTS × c of TS, [Formula see text] of H0 hybrids and GCA of I0 lines was highest for c = 1. Conversely, for GCA of I1 lines and H1 and H2 hybrids, c = 1 yielded lowest [Formula see text] with concordant results across all scenarios for both data sets. In view of these opposite trends, the optimum choice of c for maximizing selection response across all types of hybrids depends on the size and resources of the breeding program.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica / Melhoramento Vegetal Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Theor Appl Genet Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica / Melhoramento Vegetal Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Theor Appl Genet Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha
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