Identifying the contributions of physiological component traits to yield selection by reverse genomic haplotype prediction (Subproject 4)

• Applicant: Dr. Eva Herzog
• Subject Area: Plant Breeding and Plant Pathology
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 518914346

Wheat is one of the most important staple food crops and high grain yields are essential for global food security. Breeding raised yields continuously over the past century, however yield potential is increasingly suppressed by challenges associated with climate change and regulatory restrictions on crop inputs. A better understanding of the interplay between genetics and physiological and metabolic processes underlying source-sink activities is vital to optimise adaptive responses that limit yield potential and to account for genotype*environment*management (G*E*M) interactions. In a previous collaboration, a large panel of elite European winter wheat cultivars was extensively phenotyped in a G*E*M context. Findings from this project suggest that selection over decades resulted in an accumulation of chromosome segments with favourable effects on source- and sink-related key component traits of yield, such as water and nutrient use efficiency, biomass, radiation interception efficiency and green canopy duration. However, these putative physiological advantages did not always result in increased grain yield. This suggests that an efficient recombination of source and sink traits as component traits of yield has great potential to enhance genetic gain in a wide range of environmental and management scenarios. The aim of this subproject 4 in the package proposal “Wheat source-sink relationships and limitations (WheatSouSi)” is to dissect source-sink contributions to yield and yield stability into their most important components which were retrospectively reponsible for long-term breeding progress. We will implement the deep physiological datasets from subprojects 1-3 in a quantitative genetic meta-analysis of retrospective breeding progress. We will apply the reverse genomic selection statistic G ̂ on the basis of genome-wide multi-allelic haplotype block effects on source- and sink-related component traits of yield to measure and compare the response to selection for all traits measured under different environments and constraints in the sub-projects. We will also develop a corresponding reverse genomic selection index for yield stability which implements statistics for environmental parametrisation. This index will be applied on the multi-dimensional datasets generated by the subprojects to elucidate the respective contributions of different “trait-by-environmental constraint” interactions to long-term breeding progress for yield stability. The key component traits of yield and yield stability identified in subproject 4 will ultimately serve as a basis for the design and implementation of a new quantitative phenomic-genomic selection model to advance the theoretical framework into a practical breeding and agronomy context in project phase II. The newly developed analytical tools and selection strategies will also be validated in a new panel of advanced elite genotypes which represent a further 10 years of breeding progress.

• DFG Programme: Research Grants
• Co-Investigator: Professor Dr. Matthias Frisch