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Genomic prediction across years in a maize doubled haploid breeding program to accelerate early-stage testcross testing.
Wang, Nan; Wang, Hui; Zhang, Ao; Liu, Yubo; Yu, Diansi; Hao, Zhuanfang; Ilut, Dan; Glaubitz, Jeffrey C; Gao, Yanxin; Jones, Elizabeth; Olsen, Michael; Li, Xinhai; San Vicente, Felix; Prasanna, Boddupalli M; Crossa, Jose; Pérez-Rodríguez, Paulino; Zhang, Xuecai.
Afiliação
  • Wang N; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Wang H; International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
  • Zhang A; International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
  • Liu Y; CIMMYT-China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai, China.
  • Yu D; Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China.
  • Hao Z; College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, Liaoning, China.
  • Ilut D; College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, Liaoning, China.
  • Glaubitz JC; International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
  • Gao Y; CIMMYT-China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai, China.
  • Jones E; Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China.
  • Olsen M; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Li X; Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA.
  • San Vicente F; Institute of Biotechnology, Cornell University, Ithaca, NY, USA.
  • Prasanna BM; Institute of Biotechnology, Cornell University, Ithaca, NY, USA.
  • Crossa J; Institute of Biotechnology, Cornell University, Ithaca, NY, USA.
  • Pérez-Rodríguez P; International Maize and Wheat Improvement Center (CIMMYT), P. O. Box 1041, Nairobi, Kenya.
  • Zhang X; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Theor Appl Genet ; 133(10): 2869-2879, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32607592
ABSTRACT
KEY MESSAGE Genomic selection with a multiple-year training population dataset could accelerate early-stage testcross testing by skipping the first-stage yield testing, which significantly saves the time and cost of early-stage testcross testing. With the development of doubled haploid (DH) technology, the main task for a maize breeder is to estimate the breeding values of thousands of DH lines annually. In early-stage testcross testing, genomic selection (GS) offers the opportunity of replacing expensive multiple-environment phenotyping and phenotypic selection with lower-cost genotyping and genomic estimated breeding value (GEBV)-based selection. In the present study, a total of 1528 maize DH lines, phenotyped in multiple-environment trials in three consecutive years and genotyped with a low-cost per-sample genotyping platform of rAmpSeq, were used to explore how to implement GS to accelerate early-stage testcross testing. Results showed that the average prediction accuracy estimated from the cross-validation schemes was above 0.60 across all the scenarios. The average prediction accuracies estimated from the independent validation schemes ranged from 0.23 to 0.32 across all the scenarios, when the one-year datasets were used as training population (TRN) to predict the other year data as testing population (TST). The average prediction accuracies increased to a range from 0.31 to 0.42 across all the scenarios, when the two-years datasets were used as TRN. The prediction accuracies increased to a range from 0.50 to 0.56, when the TRN consisted of two-years of breeding data and 50% of third year's data converted from TST to TRN. This information showed that GS with a multiple-year TRN set offers the opportunity to accelerate early-stage testcross testing by skipping the first-stage yield testing, which significantly saves the time and cost of early-stage testcross testing.

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico / Fatores de risco Idioma: Inglês Revista: Theor Appl Genet Ano de publicação: 2020 Tipo de documento: Artigo País de afiliação: China