Skip to main content
ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Dairy Forage Research » Research » Publications at this Location » Publication #324978

Title: Genetic polymorphisms of switchgrass revealed by exome capture sequence variation

Author
item EVANS, JOSEPH - Michigan State University
item Casler, Michael

Submitted to: Plant and Animal Genome
Publication Type: Abstract Only
Publication Acceptance Date: 11/15/2015
Publication Date: 1/8/2016
Citation: Evans, J., Casler, M.D. 2016. Genetic polymorphisms of switchgrass revealed by exome capture sequence variation [abstract]. Plant and Animal Genome XXIV. Paper No. W194.

Interpretive Summary:

Technical Abstract: Switchgrass (Panicum virgatum) is a perennial grass native to North and Central America that has been cultivated for forage and soil conservation, and recently as a biofuel production crop. Switchgrass and is divided into two ecotypes (lowland and upland) based on habitat, genome ploidy, and phenotype with upland accessions generally accumulating lower biomass than lowland accessions, yet capable of overwintering in low temperatures that cause stand failure in lowland switchgrass. Using an exome capture sequencing approach, we sequenced three population panels of switchgrass (Northern Association, Southern Association, Supplemental Southern Association), representing a total of 1169 individuals across 140 populations. We were able to identify ~1.9 million bi-allelic single nucleotide polymorphic (SNP) loci with coverage in all 1169 individuals. These loci were used to construct a genetic distance dendogram and identify population structure, revealing a total of 10 predicted switchgrass population groups, including a previously un-observed lowland central population group in the Louisiana region, a group in the central mid-west region, and a group in southern Florida. Structural variation was also present within the overall panel with 265,486 total copy number variants (CNVs), which when used in genetic distance estimations, were reflective of SNP-derived genetic relationships. Comparative analyses between upland and lowland populations revealed CNVs restricted to the two ecotypes, indicating a shared loss or duplication event. Additional analyses on genome variation between upland and lowland ecotypes is underway to link genes and alleles with phenotypes relevant to biofuel feedstock production.