Key Themes 2025

Themes We Will Address in Year 2 of the Project

Ensure every team member (who is not a NARS breeder) has a direct collaboration with a NARS breeder (Outcome 1 & 2) 

The history of trait-oriented breeding and new genomic approaches in the public sector suggests that a lack of mutual understanding between breeders and researchers has previously limited effectiveness. Therefore we aim to have all trait scientists on the project directly collaborating with breeding programs within the context of core breeding activities (i.e not "side projects" for the breeding program). The trait technology and elite gene pool identification approaches we are deploying are designed to be directly relevant to near-term needs and decisions of NARS breeders, based on detailed knowledge of their breeding product profiles and breeding schemes. In this way, collaboration of researchers with NARS breeders will facilitate core breeding activities, and not distract breeders.

Implement and test new prebreeding strategies in the NARS-CGIAR networks (Outcome 1)

We have designed several new optimized prebreeding strategies (Elite gene pool identification, Flywheel Genomics, PCIL trait discovery) by extending well-established genetics/genome biology theory into this new context of pangenome technology and NARS-CGIAR networks.  We have demonstrated the plausibility of these approaches via retrospective analyses of breeding germplasm, and validated that they can increase genetic gain in silico using breeding simulations in AlphaSimR over a range of realistic assumptions. Now, however, in Year 2 of the project we will begin to implement and test the new methods. Importantly, we will test them rigorously using a priori hypotheses and predictions (Strong Inference), so each approach will only be scaled in the NARS-CGIAR network as their effectiveness is established and/or appropriate adjustments to the approaches are made.

Scale up the pangenome-enabled trait discovery approach (that succeeds or fails quickly) to many traits (Outcome 2)

The investment that BMGF and others have made in pangenome resources for sorghum can now be leveraged effectively for trait discovery using the pangenome-characterized introgression lines (PCILs) resource we have created under the BMGF Allele Mining project. With the dissemination of this resource across the GE team, we can now deploy it broadly for rapid trait discovery and testing, for many target traits and many target genes for each trait. In Year 2, we will focus on this deployment of PCIL for trait discovery on the GE target traits, which were defined and prioritized based on the ADCIN regional market segments. Importantly, because our pangenomic understanding of sorghum diversity extends into the breeding germplasm itself, when promising causative variants for target traits are identified, it will be relatively easy to deploy the trait-predictive marker in ongoing prebreeding and/or breeding activities within ADCIN.