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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #310527

Research Project: Development and Application of Genetic, Genomic, and Bioinformatic Resources in Maize

Location: Plant, Soil and Nutrition Research

Title: Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches

Author
item LIPKA, ALEXANDER - Cornell University - New York
item LU, FEI - Cornell University - New York
item CHERNEY, JEROME - Cornell University - New York
item Buckler, Edward - Ed
item Casler, Michael
item COSTICH, DENISE - International Maize & Wheat Improvement Center (CIMMYT)

Submitted to: PLoS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/30/2014
Publication Date: 11/12/2014
Publication URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112227
Citation: Lipka, A.E., Lu, F., Cherney, J.H., Buckler IV, E.S., Casler, M.D., Costich, D.E. 2014. Accelerating the switchgrass (panicum virgatum L.) breeding cycle using genomic selection approaches. PLoS One. 9(11):e112227.

Interpretive Summary: Switchgrass is a great potential biofuel source, but since it has not been domesticated its growth habit is sub-optimal for biofuel production. However, standard breeding approaches take many years when applied to perennial crops like switchgrass. This research addresses whether DNA markers system could be used to accelerate the breeding of switchgrass using genomic selection. We evaluated numerous upland varieties for growth habit and biomass quality traits, and found that many of traits can be predicted reasonably with the aid genomic markers. This prediction accuracy suggests that genomic selection in combination with larger field breeding efforts and trait evaluation should be able to efficiently breed the more productive varieties of upland switchgrass.

Technical Abstract: Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield.