Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/109136
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Type: Journal article
Title: Increased genomic prediction accuracy in wheat breeding using a large Australian panel
Author: Taylor, J.D.
Norman, A.
Tanaka, E.
Telfer, P.
Edwards, J.
Martinant, J.P.
Kuchel, H.
Citation: Theoretical and Applied Genetics: international journal of plant breeding research, 2017; 130(12):2543-2555
Publisher: Springer Verlag
Issue Date: 2017
ISSN: 0040-5752
1432-2242
Statement of
Responsibility: 
Adam Norman, Julian Taylor, Emi Tanaka, Paul Telfer, James Edwards, Jean‑Pierre Martinant, Haydn Kuchel
Abstract: In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom AxiomTM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.
Keywords: Triticum
Linear Models
Chromosome Mapping
Genomics
Genotype
Linkage Disequilibrium
Phenotype
Polymorphism, Single Nucleotide
Quantitative Trait Loci
Models, Genetic
Australia
Plant Breeding
Rights: © The Author(s) 2017. This article is an open access publication. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
DOI: 10.1007/s00122-017-2975-4
Grant ID: ARC
Published version: https://link.springer.com/article/10.1007/s00122-017-2975-4
Appears in Collections:Agriculture, Food and Wine publications
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