P0747 Comparative Study of Switchgrass Cultivars Using RNA Sequencing Technology

A. Nandety , University of Wisconsin/ GLBRC, Madison, WI
Kevin L. Childs , Michigan State University, East Lansing, MI
C. Robin Buell , Michigan State University, East Lansing, MI
Shawn Kaeppler , University of Wisconsin, Dept. of Agronomy, Madison, WI
Michael Casler , USDA-ARS, Madison, WI
Switchgrass (Panicum virgatum L.) is a C4 perennial grass, identified as a promising bioenergy crop. Switchgrass exists in two ecotypes, upland and lowland, which are heterotic or genetically complementary to each other. The objectives of this study is to assess the potential of SNP markers as a breeding tool in development of hybrid switchgrass cultivars for higher biomass production and to identify candidate genes responsible for variation in lignification and flowering time. Higher ploidy levels (e.g. 2n = 8x = 72) and lack of complete sequence information have been a hindrance for developing genetic and genomic resources. High-throughput deep RNA sequencing technology (RNAseq), was used to facilitate the construction of transcriptome without a reference genome. Transcriptome assemblies of four upland and three lowland genotypes were constructed from mRNA collected from whole of the above-crown tissues. De novo assemblies were made with a sequencing depth of 90 million paired reads for each assembly (upland, lowland and upland-lowland combined). About 46,000 transcripts were annotated from a combined transcriptome of upland and lowland genotypes using maize as a search engine. A total of 286,221 high confidence SNPs have been identified over all the 7 genotypes of which 3028 are upland specific and 1530 are lowland specific. Relative expression levels will be quantified by fragments per kilobase transcript per million reads (FPKM) analysis, focusing largely on genes responsible for specific traits associated with biomass accumulation. Phylogenetic analysis will be carried out based on the SNP markers.