Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

Deciphering Natural Allelic Variation in Switchgrass for Biomass Yield and Quality Using a Nested Association Mapping Populations

2012 Awardee

Investigators: Malay C. Saha, E. Charles Brummer, Shawn Kaeppler, Hem S. Bhandari

Institutions: Michael D. Casler, Ji He, Angela Ziebell, Robert Sykes

Non-Technical Summary: Our long-term goal is to understand the genetic basis of the key biofeedstock traits of biomass yield and composition in order to accelerate development of superior cultivars of switchgrass. Most of the target traits — biomass yield, cell wall composition, etc., — are complex, controlled by many genes and difficult to improve. Desired improvement for many of these traits can be obtained by using traditional breeding methodology augmented by marker-assisted breeding. The proposed research is focused to identify the genetic markers controlling important biomass traits. Pyramiding of desirable genes through the use of marker-assisted selection will help realize the gains needed for our renewable energy plan.

Objectives: The specific goals and expected outputs of the proposed research are: (a) Genetically-dissect components of plant architecture that are important to productivity of bioenergy grasses under annual or perennial production systems. Forward genetics in three populations that span the range of variation in eusorghums will provide baseline QTL data for components of plant architecture and related traits, also assessing inter-relationships with one another and perenniality. (b) Investigate levels and patterns of DNA sequence variation in positional and functional candidate genes for association with phenotypic variation in plant architecture and other traits. Phenotyping and resequencing of positional and/or functional candidate genes in a validated panel that broadly and deeply samples S. bicolor genetic diversity, will narrow the locations of QTLs, reveal haplotype diversity in trait-controlling regions, and perhaps even identify functional variants in some instances. (c) Enrich online resources for meta-analysis and deterministic utilization of variants in plant architecture. We will facilitate searches for positional candidate genes affecting plant architecture by supplementing a CMAP-based QTL resource being developed under current program funding for Miscanthus, with new QTLs as well as orthologs, paralogs or other homologs of major genes cited below (plus new additions and any inadvertent omissions) that qualitatively impact plant architecture. Further, we will facilitate integrative use of positional, diversity, and mutant information in discovery and utilization of genetic variation by using Gramene trait ontologies to interleave three well-characterized but to date isolated genetic resources as described below.

Approach: Ten highly diverse switchgrass genotypes were crossed to the reference parent AP13 and resulting hybrid families will be recombined to produce 10 separate intercrossed populations, each with 200 individuals. Thus, the NAM population consists of a total of 2,000 genotypes from 10 families. The population will be evaluated in replicated field trials at multiple environments. Phenotypic data on plant height, tillering ability, regrowth, flowering time, plant growth habit, leaf characteristics, biomass yield, lignin content, S/G ratio and sugar release will be determined. The population will be genotyped with SNP markers to detect QTL. Breeding populations developed in our program will be used to validate the marker effects. Validated markers cosegregated with key traits for biomass yield and composition will be used to initiate a marker-assisted and/or genomic selection program.

Project Contact
Name: Saha Malay
Phone: 580-224-6840
Fax: 580-224-6802
Email: [email protected]