Map to be re-estimated across different contexts. The implicit capture of non-stationary effects of alleles requires the G2P Such non-stationary effects of alleles are either ignored or assumed toīe implicitly captured by most gene-to-phenotype (G2P) maps used in genomic Interactions generate allele substitution effects that are non-stationary across differentĬontexts. Is that underlying non-additive genetic (GxG) and genotype-by-environment (G圎) Populations remains a challenge for plant breeding. Genomic prediction of complex traits across environments, breeding cycles, and Our findings suggest the promise of a whole-system approach to overcome challenges such as the negative correlation of grain yield and protein content to facilitating quantitative and objective breeding decisions in future crop breeding. Our method demonstrates an efficient way to identify genetically correlating traits and underlying pleiotropic genetic factors and provides an effective proxy for multi-trait selection within a whole-system framework that considers the joint genetic architecture of multiple interacting traits in crop breeding. Using ten traits and genome-wide SNP profiles from a worldwide barley panel and SEM analysis, we revealed a network of interacting traits, in which tiller number contributes positively to both grain yield and protein content we further identified common genetic factors affecting multiple traits in the network of interaction.
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Here, we test the framework of whole-system-based approach using structural equation modelling (SEM) to investigate how one trait affects others to guide the optimal selection of a combination of agronomically important traits.
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Future crop breeding needs to be based on practical yet accurate evaluation and effective selection of beneficial trait to retain genes with the best agronomic score for multiple traits. For example, grain yield and grain protein content correlate negatively with each other in cereal crops. Using genomic structural equation modelling, this research demonstrates an efficient way to identify genetically correlating traits and provides an effective proxy for multi-trait selection to consider the joint genetic architecture of multiple interacting traits in crop breeding.īreeding crop cultivars with optimal value across multiple traits has been a challenge, as traits may negatively correlate due to pleiotropy or genetic linkage.