INVESTIGATOR: Yu, J., Tesso, T., Staggenborg, S., Wang, D., Bernardo, R., Wang, M., Pederson, G.
INSTITUTION: Kansas State University, University of Minnesota, USDA-ARS Plant Genetic Resources Conservation Unit
NON-TECHNICAL SUMMARY: Research in plant feedstock genomics is well positioned to contribute to bioenergy production by combining the merits of established plant breeding and germplasm improvement approaches with cutting-edge genomics strategies. Two essential components of accelerated biomass crop improvement are the understanding and exploitation of genetic diversity and of the genotype-phenotype relationship. Assessment of genetic diversity provides germplasm and information on an array of trait characteristics for systematic integration and exploitation. A robust genotype-phenotype relationship allows predictive approaches for efficient and cost-effective breeding, superior allele mining, and introgression on a gene/genomic region basis. The proposed research integrates several key genomics-assisted strategies into biomass sorghum research (i.e., selective phenotyping, genomic selection, and association mapping) and combines these genetic strategies with a high-throughput phenotyping method (i.e., near infrared spectroscopy for biomass composition) and traditional field-based phenotyping experiments.
OBJECTIVES: 1) genotypically characterize a diverse set of sorghum germplasm and selectively phenotype a representative set of germplasm for their biomass potential; 2) develop a standardized method for high-throughput and cost-effective phenotyping for sorghum biomass composition through near-infrared reflectance (NIR) spectroscopy; and 3) discover additional useful germplasm by genomewide prediction and useful genes by association mapping for biomass yield and composition.
APPROACH: We will genotype a collection of 1000 sorghum accessions with at least 50,000 SNP markers and identify a sample of 300 that captures the maximum amount of diversity in the collection. These 300 accessions will be evaluated in multi-environment experiments for biomass yield and compositional traits, the latter measured with new NIR calibrations we will develop. The best of the remaining 700 accessions will be identified by genomewide selection and evaluated in subsequent field experiments. We will also identify and evaluate accessions that carry haplotypes associated with biomass traits but with a low frequency in the sample of 300 and accessions carry novel haplotypes.
Name: Yu, J.