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Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids.
Li, Lanzhi; Zheng, Xingfei; Wang, Jiabo; Zhang, Xueli; He, Xiaogang; Xiong, Liwen; Song, Shufeng; Su, Jing; Diao, Ying; Yuan, Zheming; Zhang, Zhiwu; Hu, Zhongli.
Afiliação
  • Li L; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Zheng X; Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crop Institute, Hubei Academy of Agricultural Sciences, 430064, Wuhan, Hubei, China.
  • Wang J; State Key Laboratory of Hybrid Rice, College of Life Science, Wuhan University, 430072, Wuhan, Hubei, China.
  • Zhang X; Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization of Ministry of Education and Sichuan province, Southwest Minzu University, 610041, Chengdu, Sichuan, China.
  • He X; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Xiong L; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Song S; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Su J; State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center, Hunan Academy of Agricultural Sciences, 410125, Changsha, Hunan, China.
  • Diao Y; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Yuan Z; School of Life Science and Technology, Wuhan Polytechnic University, 430023, Wuhan, Hubei, China.
  • Zhang Z; Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
  • Hu Z; Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USA. Zhiwu.Zhang@WSU.edu.
Nat Commun ; 14(1): 3930, 2023 07 04.
Article em En | MEDLINE | ID: mdl-37402793
ABSTRACT
Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oryza Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oryza Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article