Genomic insights into the NPGS intermediate wheatgrass germplasm collection
Publication: Crop Science Volume 63 Issue 3
The Land Institute’s Lee DeHaan (Lead Scientist, Kernza) and Sajal Sthapit (Postdoctoral Researcher, Kernza) worked with research collaborators to release this publication detailing the value of the USDA’s National Plant Germplasm System (NPGS), which assists breeding efforts for genetic diversity and agronomic traits like forage and grain characteristics in intermediate wheatgrass, the perennial plant from which Kernza® grain is produced.
The National Plant Germplasm System (NPGS) is a vital resource for genetic diversity, yet utilization of this resource requires a thorough understanding of the germplasm and genetic diversity. Intermediate wheatgrass (IWG, Thinopyrum intermedium) is a perennial grass species that has been improved for forage production through breeding utilizing the NPGS collection and has also been targeted for domestication as a perennial grain crop. To better characterize the IWG collection, we combined previously published forage data with new agronomic and genomic data. A total of 331 NPGS accessions were genomically profiled with genotyping-by-sequencing (GBS) and a genome-wide association study (GWAS) was used to evaluate trait architecture. Along with the GWAS, in silico bulk samples were profiled by recoding GBS data to conduct association mapping through allele counting with extreme-phenotype (XP)-GWAS. Genomic analysis revealed two subpopulations, which were defined as European and Asian groups, and are differentiated around the Black Sea region. Phenotypic observations for forage and agronomic traits differed between the two groups (p < 0.05), even though greater than 70% of the genetic variance was partitioned within individual accessions. Finally, XP-GWAS revealed 303 marker–trait associations for five agronomic and four forage traits. These results suggest that genetic diversity within the NPGS collection should lead to genetic gains for both forage and grain breeding as well as opportunities for breeding programs to enhance genetic diversity. More broadly, the methods we applied could be applicable to low-resourced species, leveraging existing, and new data, to strengthen genetic characterization and breeding efficiency.