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Transgressive Potential Prediction and Optimal Cross Design of Seed Protein Content in the Northeast China Soybean Population Based on Full Exploration of the QTL-Allele System.
Feng, Weidan; Fu, Lianshun; Fu, Mengmeng; Sang, Ziqian; Wang, Yanping; Wang, Lei; Ren, Haixiang; Du, Weiguang; Hao, Xiaoshuai; Sun, Lei; Zhang, Jiaoping; Wang, Wubin; Xing, Guangnan; He, Jianbo; Gai, Junyi.
Afiliação
  • Feng W; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • Fu L; State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
  • Fu M; Tieling Academy of Agricultural Sciences, Tieling, China.
  • Sang Z; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • Wang Y; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • Wang L; Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China.
  • Ren H; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • Du W; State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
  • Hao X; Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China.
  • Sun L; Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China.
  • Zhang J; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • Wang W; State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
  • Xing G; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
  • He J; State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
  • Gai J; Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China.
Front Plant Sci ; 13: 896549, 2022.
Article em En | MEDLINE | ID: mdl-35903228
Northeast China is a major soybean production region in China. A representative sample of the Northeast China soybean germplasm population (NECSGP) composed of 361 accessions was evaluated for their seed protein content (SPC) in Tieling, Northeast China. This SPC varied greatly, with a mean SPC of 40.77%, ranging from 36.60 to 46.07%, but it was lower than that of the Chinese soybean landrace population (43.10%, ranging from 37.51 to 50.46%). The SPC increased slightly from 40.32-40.97% in the old maturity groups (MG, MGIII + II + I) to 40.93-41.58% in the new MGs (MG0 + 00 + 000). The restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNP linkage-disequilibrium block (SNPLDB) markers identified 73 SPC quantitative trait loci (QTLs) with 273 alleles, explaining 71.70% of the phenotypic variation, wherein 28 QTLs were new ones. The evolutionary changes of QTL-allele structures from old MGs to new MGs were analyzed, and 97.79% of the alleles in new MGs were inherited from the old MGs and 2.21% were new. The small amount of new positive allele emergence and possible recombination between alleles might explain the slight SPC increase in the new MGs. The prediction of recombination potentials in the SPC of all the possible crosses indicated that the mean of SPC overall crosses was 43.29% (+2.52%) and the maximum was 50.00% (+9.23%) in the SPC, and the maximum transgressive potential was 3.93%, suggesting that SPC breeding potentials do exist in the NECSGP. A total of 120 candidate genes were annotated and functionally classified into 13 categories, indicating that SPC is a complex trait conferred by a gene network.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article