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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 #313115
Title: Detecting genetic associations with phenology in switchgrass using exome-capture

Author
item Grabowski, Paul
item Casler, Michael

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 12/1/2014
Publication Date: 1/10/2015
Citation: Grabowski, P.P., Casler, M.D. 2015. Detecting genetic associations with phenology in switchgrass using exome-capture [abstract]. Plant and Animal Genome Conference. Paper No. W565.

Interpretive Summary:

Technical Abstract: Switchgrass is an emerging bioenergy feedstock, and improving biomass yield is critical for developing switchgrass into an economically sustainable bioenergy crop. Phenology has a major effect on biomass yield. For example, flowering too early forgoes potential productivity at the end of the growing season, whereas flowering too late increases susceptibility to winter mortality, decreasing productivity in subsequent years. Thus, understanding the genetic basis of phenological control is important for developing resources for improving biomass yield in switchgrass. However, switchgrass is polyploid and has a large and complex genome, which has hindered attempts to identify genes that control phenotypes. To address this, exome-capture libraries were developed for switchgrass, enabling targeted analysis of genic regions of the switchgrass genome. Here, we present our progress using exome-capture data to, via association mapping, identify genes that control flowering time in switchgrass. Genotypes for more than 500 switchgrass individuals were generated using the switchgrass Roche-NimbleGen exome-capture probe set. These individuals originate from more than 60 natural populations and cultivars from across the northern portion of the natural switchgrass distribution in North America. These samples are part of an association panel that was phenotyped in Ithaca, New York for three growing seasons. Using the exome-capture-based genotypes and flowering phenotypes, we identify associations of flowering time with variants in and near switchgrass genes, implicating their role in controlling flowering time in switchgrass. These results help characterize the genetic control of flowering time in switchgrass and will aid the development of resources to improve biomass yield in switchgrass.