Year 1 Progress Update

Major Themes for Year 1 Progress Across the Project

Establishing a strong team culture, merging rigorous science with a product focus 

Since the Green Evolution project aims to catalyze a transformational change in the effectiveness NARS-CGIAR breeding partnerships, an essential first step has been developing a strong R&D culture that can stay focused on the delivery of products while using rigorous science to advance product development. We used several approaches to build this effective R&D culture in Year 1:

• Weekly meetings on Zoom, with four rotating formats, to align on shared goals and scientific foundation: "All-hands GE presentations", "Scientific Foundations for GE", "Design of GE Experiments", "Tracking GE Deliverables" 

• Intensive, semester-long training in goal-directed hypothesis-driven research in the Scientific Method course for all GE-affiliated students (CSU, KSU, and UNL) (Figure 1)

• Leadership & Management training (PIs) and Professional Development training (postdocs, students, technicians) from hfp consulting to facilitate communication, time management, and work effectiveness across the team (Figure 2)

Transfer and adoption of upstream prebreeding resources to Green Evolution for deployment and scaling across the network 

GE was designed as a bridge to deploy and up-scale resources developed in upstream prebreeding (Allele Mining) and genomics (Sorghum Genomics Toolkit) for trait discovery and prebreeding in NARS-CGIAR breeding networks ("connecting the dots"). We rapidly stood-up the GE R&D activities by leveraging several upstream resources:

• Pangenome data sets disseminated through the team and used to identify putative causative variant in reverse genetics trait discovery for multiple target traits (Figure 3)

• Pangenome characterized introgression line (PCIL) resources from Allele Mining have been shared with the GE team and used to design trait discovery experiments (Figure 4)

• To facilitate resource transfer, the sorghum Allele Mining team attended and presented the GE annual meeting in Ghana

Initial development and deployment of the panGenomeBreedr software package in NARS-CGIAR breeding activities

Development of the panGenomeBreedr (panGB) software has proceeded quickly under program integration lead, leveraging scripts developed by several team members (Figure 5; https://github.com/awkena/panGenomeBreedr). Moving forward, development and scaling of the panGenomeBreedr will be led by Dr. Kena and his team via the KNUST subcontract. In year 1, the following functionality was developed and deployed within the NARS-CGIAR breeding networks:

• Analysis and decision support tools to convert target variants identified from pangenome resources into markers on the Intertek KASP platform (Excellence In Breeding)

• Visualizing KASP marker genotyping results with decision support for rigorous hypothesis testing on genotypic discrimination ability (not available in any commercial software)

• Visualizing mid-density marker genotyping with decision support for foreground and background selection in marker-assisted introgression pipelines (Figure 6)

NARS R&D partnerships for prebreeding and trait technology development

The market segmentation, product advancement pipelines. Using these documentation and relationships as a starting point, the Green Evolution team is tasked with providing prebeeding resources and breeding technology to the networks. Therefore, Green Evolution budget included to-be-determined partnerships with NARS to co-develop and co-test the germplasm and trait technology that would be deployed via ADCIN. In year 1 we have:

• Established subaward with KNUST as an African hub for trait R&D and software development

• Established subaward and material transfer agreement with CSIR-SARI for trait testing and elite gene pool identification (Figure 7)

• Established agreement with EIAR for germplasm exchange in student projects (MTA and subaward in progress)

• Scale up the prebreeding and trait discovery partnership with ISRA and CIMMYT in Senegal (Figure 8)