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Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat.
Malik, Parveen; Kumar, Jitendra; Singh, Sahadev; Sharma, Shiveta; Meher, Prabina Kumar; Sharma, Mukesh Kumar; Roy, Joy Kumar; Sharma, Pradeep Kumar; Balyan, Harindra Singh; Gupta, Pushpendra Kumar; Sharma, Shailendra.
Afiliação
  • Malik P; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Kumar J; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Singh S; National Agri-Food Biotechnology Institute (NABI), Sector 81, Sahibzada Ajit Singh Nagar, 140306 Punjab India.
  • Sharma S; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Meher PK; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Sharma MK; Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India.
  • Roy JK; Department of Mathematics, Chaudhary Charan Singh University, Meerut 250004, India.
  • Sharma PK; National Agri-Food Biotechnology Institute (NABI), Sector 81, Sahibzada Ajit Singh Nagar, 140306 Punjab India.
  • Balyan HS; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Gupta PK; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
  • Sharma S; Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut 250004, India.
Mol Breed ; 41(7): 46, 2021 Jul.
Article em En | MEDLINE | ID: mdl-37309385
ABSTRACT
A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01240-1.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Índia

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Índia