Genetics of Fe, Zn, β-carotene, GPC and yield traits in bread wheat (Triticum aestivum L.) using multi-locus and multi-traits GWAS
Kumar, J.
Genetics of Fe, Zn, β-carotene, GPC and yield traits in bread wheat (Triticum aestivum L.) using multi-locus and multi-traits GWAS - Netherlands : Springer, 2018.
Peer review
The present study was conducted to study the genetic architecture of grain micronutrients (Zn, Fe and ?-carotene contents), grain protein content and four yield traits in a spring wheat reference set comprising 246 genotypes. Phenotypic data on these traits recorded at two locations and the genotyping data for 17,937 SNP markers (obtained through outsourcing) were used for genome wide association study, which gave following results after Bonferroni correction using four methods: (1) single locus single trait analysis gave 136 marker-trait associations; (2) multi-locus mixed model gave 587 MTAs; (3) multi-trait mixed model gave 28 MTAs and (4) matrix-variate linear mixed model gave 33 MTAs. As many as 73 epistatic interactions were also detected. Keeping all the results in mind, nine most important MTAs were selected for biofortification. These markers were associated with three traits (GPC, GFeC and GYPP). These MTAs can be used in wheat improvement programs either using marker-assisted recurrent selection or pseudo-backcrossing method. © 2018, Springer Nature B.V.
Text in English
https://doi.org/10.1007/s10681-018-2284-2
Triticum aestivum
Soft wheat
Iron
Zinc
Carotenes
Genetics of Fe, Zn, β-carotene, GPC and yield traits in bread wheat (Triticum aestivum L.) using multi-locus and multi-traits GWAS - Netherlands : Springer, 2018.
Peer review
The present study was conducted to study the genetic architecture of grain micronutrients (Zn, Fe and ?-carotene contents), grain protein content and four yield traits in a spring wheat reference set comprising 246 genotypes. Phenotypic data on these traits recorded at two locations and the genotyping data for 17,937 SNP markers (obtained through outsourcing) were used for genome wide association study, which gave following results after Bonferroni correction using four methods: (1) single locus single trait analysis gave 136 marker-trait associations; (2) multi-locus mixed model gave 587 MTAs; (3) multi-trait mixed model gave 28 MTAs and (4) matrix-variate linear mixed model gave 33 MTAs. As many as 73 epistatic interactions were also detected. Keeping all the results in mind, nine most important MTAs were selected for biofortification. These markers were associated with three traits (GPC, GFeC and GYPP). These MTAs can be used in wheat improvement programs either using marker-assisted recurrent selection or pseudo-backcrossing method. © 2018, Springer Nature B.V.
Text in English
https://doi.org/10.1007/s10681-018-2284-2
Triticum aestivum
Soft wheat
Iron
Zinc
Carotenes