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Geoffrey P. Morris

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Open access Aug 2026

Identifying marker-trait associations for wheat stem sawfly resistance

Two novel WSS resistance loci were identified on chromosomes 2B and 5A. Characterization of WSS resistance loci will improve breeders’ ability to select to reduce yield loss due to WSS. Wheat stem sawfly (WSS) is a native grass feeding pest of winter wheat (Triticum aestivum L) which is difficult to control since most of its life cycle occurs within the stem of wheat plants. The only well-characterized genetic resistance to WSS is the solid stem locus (Sst1) on chromosome 3B, which exhibits environmental variability. It is critical to identify novel forms of genetic resistance outside of Sst1 to improve the overall resistance of wheat to WSS. In this study, genome-wide association studies (GWAS) were performed on lines in the Colorado State University wheat breeding program grown between 2014 and 2025 field seasons for three traits of interest: heading date (HD), WSS damage in the form of stem cutting (CUT), and stem solidity (SOLID). Significant marker trait associations (MTA) were identified on chromosomes 2B, 2D, 3A, 3B, 5A, and 5D for CUT and 2A, 3B, 4B, and 6A for SOLID. Significant MTA from these GWAS were used to identify beneficial allelic combinations (AC) for WSS resistance. The stem cutting ACs which had the lowest damage estimates were those in which lines possessed the resistant haplotype at every locus assessed (CUT = 2.35, error = 0.21, N = 56). Lines that had all resistant alleles in the stem solidity ACs showed the same superior estimate (SOLID = 14.7, error = 0.78, N = 22). The positive effects of the identified small-effect MTA on CUT and SOLID indicated the importance of including these loci when breeding for WSS resistance.

Mikayla Hammers, Z. Winn, Brian R. Rice et al. · 0 citations
Open access Aug 2026

Flywheel Genomics: Simultaneous trait discovery and genetic gain in plant breeding

Genomic mapping has yielded extensive catalogs of quantitative trait loci underlying agronomic traits, yet translating these discoveries into breeding gains remains inefficient. Here, we introduce Flywheel Genomics, a framework that integrates trait discovery directly within rapid cycling breeding populations. Using empirical data from a smallholder-oriented sorghum breeding program, we demonstrate that recurrent intermating and selection maintain genetic diversity, effective population size, and recombination while reducing confounding from plant height and maturity. Within this population, we resolve loci underlying simple adaptive and complex environmentally responsive traits and generate large segregating populations for mapping and near-isogenic lines for locus validation. We further demonstrate applicability in a public wheat breeding program, where known agronomic loci were readily detected. Simulations show that rapid cycling better preserves the population genetic properties required for Flywheel Genomics than conventional pure line development. By integrating discovery with improvement, Flywheel Genomics reframes breeding programs as engines of both crop improvement and genetic insight.

Brian R. Rice, Ebenezer Ogoe, Jean Rigaud Charles et al. · 0 citations

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