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Fradgley, N. S.

Publications and source records attributed to Fradgley, N. S..

3 recordsLinked to original sources

OzWheat: a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research.

For over a century, Australian wheat breeders have successfully adapted wheat to a broad range of climatic conditions and crop management practices. The OzWheat genome-to-phenome (G2P) platform was established to capture this breeding history and explore traits, genes, and their interactions with the environment to enable ongoing research and deliver targets for wheat improvement. A panel of 285 cultivars and landraces were chosen through knowledge of breeding pedigrees to represent both global diversity and the historic flow of genetic variation over more than 100 years of selective breeding in Australia. Genetic characterisation of the panel included identification of genome-wide sequence variants and gene expression profiling across environments. Important traits for adaptation (flowering time and plant height) were assayed in controlled environments and at multiple field sites and years, with genome-wide association analyses (GWAS) using linear mixed models detecting both known and novel loci. Here, we report establishment of the OzWheat G2P platform as a powerful tool to integrate wheat genomes and phenomes and demonstrate its use to identify candidate genes and understand gene by environment interactions. This provides the wheat research and breeding community a new resource to support future cultivar development.

genomics↗

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture in long-term genetic gains in wheat

Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand selection within a breeding context, and how it might be optimised, we analysed genotypic and phenotypic data from a diverse, 16-founder wheat multi-parent advanced generation inter-cross (MAGIC) population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90% of traits, improving grain yield prediction accuracy by 3-52%. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10-36%. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimised long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, which involved optimisation of antagonistic trait relationships. We found multi-trait selection indices could be used to optimise undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model, accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes and provide insights into mechanisms for continued genetic gain in a limited genepool and optimisation of multiple traits for crop improvement.

genetics↗

Limited haplotype diversity underlies polygenic trait architecture across 70 years of wheat breeding

BackgroundBreeding has helped improve bread wheat yield significantly over the last century. Understanding the potential for future crop improvement depends on relating segregating genetic variation to agronomic traits. ResultsWe bred NIAB Diverse MAGIC population, comprising over 500 recombinant inbred lines, descended from sixteen bread wheat varieties released between 1935-2004. We sequenced the founders exomes and promotors by capture. Despite being highly representative of North-West European wheat and capturing 73% of global polymorphism, we found 89% of genes contained no more than three haplotypes. We sequenced each line with 0.3x coverage whole-genome sequencing, and imputed 1.1M high-quality SNPs that were over 99% concordant with array genotypes. Imputation accuracy remained high at coverage as low as 0.076x, with or without the use of founder genomes as reference panels. We created a genotype-phenotype map for 47 traits over two years. We found 136 genome-wide significant associations, concentrated at 42 genetic loci with large and often pleiotropic effects. Outside of these loci most traits are polygenic, as revealed by multi-locus shrinkage modelling. ConclusionsHistorically, wheat breeding has reshuffled a limited palette of haplotypes; continued improvement will require selection at dozens of loci of diminishing effect, as most of the major loci we mapped are known. Breeding to optimise one trait generates correlated trait changes, exemplified by the negative trade-off between yield and protein content, unless selection and recombination can break critical unfavourable trait-trait associations. Finally, low coverage whole genome sequencing of bread wheat populations is an economical and accurate genotyping strategy.

genomics↗