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Genomic selection models based on integration of GWAS loci and epistatic interactions

CIMMYT Research Data & Software Repository Network Dataverse OAI Archive

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Title Genomic selection models based on integration of GWAS loci and epistatic interactions
 
Identifier https://hdl.handle.net/11529/10548366
 
Creator Sehgal, Deepmala
Rosyara, Umesh
Mondal, Suchismita
Singh, Ravi
Poland, Jesse
Dreisigacker, Susanne
 
Publisher CIMMYT Research Data & Software Repository Network
 
Description The potential to integrate consistent associations identified from GWAS as fixed variables in GP models to improve prediction accuracy for complex traits (for example, grain yield) has not been investigated comprehensively in wheat. Here, we untangled the genetic architecture of grain yield and yield stability by haplotypes-based GWAS and epistatic scan of the genome. We then integrated robust and stable associations (and interacting loci) as fixed effects in GP models to investigate the importance of these associations in improving prediction accuracies of the said traits. We concluded that the utility of GP incorporating GWAS results is noteworthy for GY when GWAS results identify significant and robust genomic regions.
 
Subject Agricultural Sciences
Agricultural research
Wheat
Triticum aestivum
Genomic selection
Haplotypes
GWAS
Grain yield
Plant height
Days to heading
Superiority index
International Bread Wheat Screen Nursery
International Wheat Improvement Network
 
Language English
 
Date 2020
 
Contributor Shrestha, Rosemary
CGIAR Research Program on Wheat (WHEAT)
Bill and Melinda Gates Foundation (BMGF)
Department for International Development (DFID)
United States Agency for International Development (USAID)
Global Wheat Program (GWP)
Kansas State University (KSU)
 
Type Experimental data
Genotypic data
Phenotypic data