|Ersoz, Elhan -|
|Wright, Mark -|
|Pangilinan, Jasmyn -|
|Sheehan, Moira -|
Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 31, 2012
Publication Date: September 25, 2012
Repository URL: http://DOI: 10.1371/journal.pone.0044112
Citation: Ersoz, E.S., Wright, M.H., Pangilinan, J.L., Sheehan, M.J., Tobias, C.M., Casler, M.D., Buckler IV, E.S., Costich, D. 2012. SNP discovery with EST and NextGen sequencing in switchgrass (panicum virgatum L.). PLoS One. 7(9):e44112. Interpretive Summary: The genetic tools for biofuel feedstock crop improvement of species such as switchgrass (Panicum virgatum L.), are still in the early stages of development. In this study, we developed genetic markers from thirteen diverse switchgrass cultivars, representing the major ecotypes (upland and lowland), as well as the predominant ploidy types (tetraploid and octoploid). The markers discovered in this study will contribute to our understanding of the genetic diversity of switchgrass and greatly enhance breeding efforts that target the improvement of key biofuel traits and the development of new switchgrass cultivars.
Technical Abstract: Although yield trials for switchgrass (Panicum virgatum L.), a potentially high value biofuel feedstock crop , are currently underway throughout North America, the genetic tools for crop improvement in this species are still in the early stages of development. The identification of high-density molecular markers, such as single nucleotide polymorphisms (SNPs), that are amenable to high-throughput genotyping approaches, is the first step in a quantitative genetics study of this model biofuels crop species. From thirteen diverse switchgrass cultivars, representing both upland and lowland ecotypes, as well as tetraploid and octoploid genomes, we generated and sequenced expressed sequence tag (EST) libraries. This was followed by reduced genomic library preparation and massively parallel sequencing of the same samples using the Illumina- GA technology platform. EST libraries were used to generate unigene clusters and establish a gene-space reference sequence, thus providing a framework for the short sequence reads to be assembled. SNPs were identified utilizing these scaffolds. We used a custom software program for alignment and SNP detection and identified over 149,000 SNPs across the 13 short-read sequencing libraries (SRSLs). An additional ~25K SNPs were also identified from the entire EST collection available for the species. This sequencing effort generated data that are suitable for marker development and for the estimation of population genetic parameters, such as nucleotide diversity and linkage disequilibrium. Based on these data, we assess the feasibility of association mapping applications in switchgrass. Overall, the SNP markers discovered in this study will help facilitate quantitative genetics experiments and greatly enhance breeding efforts that target the improvement of key biofuel traits and the development of new switchgrass cultivars.