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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Dairy Forage Research » Research » Publications at this Location » Publication #292052
Title: Understanding genome diversity in switchgrass through an exome capture sequencing approach

Author
item JEONGWOON, KIM - Michigan State University
item EVANS, JOSEPH - Michigan State University
item RICHMOND, TODD - Roche Nimblegen, Inc
item JEDDOLEH, JEFF - Roche Nimblegen, Inc
item CHILDS, KEVIN - Michigan State University
item KAEPLER, SHAWN - University Of Wisconsin
item Casler, Michael
item BUELL, C. ROBIN - Michigan State University

Submitted to: American Society of Plant Biologists Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 3/15/2013
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Switchgrass (Panicum virgatum) is a native North American perennial grass that is a target species for biofuel feedstock production. Switchgrass can be differentiated into ecotypes, upland and lowland, that are distinguished based on phenotype and adaptation to distinct habitats. Switchgrass is largely self-incompatible with a highly heterozygous and complex genome that consists of two highly homologous subgenomes. To facilitate breeding of improved switchgrass cultivars for biofuel feedstock production, we undertook a reduced representation approach and developed a probe set for exome capture and sequencing of the switchgrass exome. Switchgrass transcript sequences derived from Sanger sequencing of Expressed Sequence Tags were combined with a de novo assembly of publicly available Roche 454 transcript sequences. Exome capture probes were designed by Nimblegen to represent 50 Mb of the switchgrass transcriptome. Probe design assessed by mapping the probe sequences to the reference genome generated from AP13, a tetraploid lowland accession, revealed that nearly 75% of the capture probes aligned to unique genes. Exome capture of lowland and upland ecotypes followed by Illumina sequencing yielded robust coverage of the switchgrass predicted gene models, as well as ample single nucleotide polymorphisms across accessions. These results will enable genome-based breeding efforts and improve our understanding of genomic diversity within switchgrass.