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Incorporating genome-wide association mapping results into genomic prediction models for grain yield and yield stability in CIMMYT spring bread wheat

Creator: Sehgal, D.
Creator: Rosyara, U.
Creator: Mondal, S.
Creator: Singh, R.P.
Creator: Poland, J.A.
Creator: Dreisigacker, S.
Year: 2020
URI: https://hdl.handle.net/10883/21102
Language: English
Publisher: Frontiers
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Type: Article
Place of Publication: Switzerland
Volume: 11
DOI: 10.3389/fpls.2020.00197
Keywords: Genotyping by Sequencing
Keywords: Genome-Wide Association Study
Keywords: Haplotypes
Keywords: Genomic Selection
Description: Untangling the genetic architecture of grain yield (GY) and yield stability is an important determining factor to optimize genomics-assisted selection strategies in wheat. We conducted in-depth investigation on the above using a large set of advanced bread wheat lines (4,302), which were genotyped with genotyping-by-sequencing markers and phenotyped under contrasting (irrigated and stress) environments. Haplotypes-based genome-wide-association study (GWAS) identified 58 associations with GY and 15 with superiority index Pi (measure of stability). Sixteen associations with GY were “environment-specific” with two on chromosomes 3B and 6B with the large effects and 8 associations were consistent across environments and trials. For Pi, 8 associations were from chromosomes 4B and 7B, indicating ‘hot spot’ regions for stability. Epistatic interactions contributed to an additional 5–9% variation on average. We further explored whether integrating consistent and robust associations identified in GWAS as fixed effects in prediction models improves prediction accuracy. For GY, the model accounting for the haplotype-based GWAS loci as fixed effects led to up to 9–10% increase in prediction accuracy, whereas for Pi this approach did not provide any advantage. This is the first report of integrating genetic architecture of GY and yield stability into prediction models in wheat.
Agrovoc: TRITICUM AESTIVUM
Agrovoc: GENOMES
Agrovoc: MARKER-ASSISTED SELECTION
Agrovoc: GENOMICS
Related Datasets: https://hdl.handle.net/11529/10548366
Related Datasets: https://figshare.com/collections/Incorporating_Genome-Wide_Association_Mapping_Results_Into_Genomic_Prediction_Models_for_Grain_Yield_and_Yield_Stability_in_CIMMYT_Spring_Bread_Wheat/4879911
ISSN: 1664-462X
Journal: Frontiers in Plant Science
Article number: 197


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  • Wheat
    Wheat - breeding, phytopathology, physiology, quality, biotech

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