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

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 trai...

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Main Authors: Alexander E Lipka, Fei Lu, Jerome H Cherney, Edward S Buckler, Michael D Casler, Denise E Costich
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0112227
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spelling doaj-60b2050215bd4c9c91fdf3a4b77b58932021-03-04T08:47:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01911e11222710.1371/journal.pone.0112227Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.Alexander E LipkaFei LuJerome H CherneyEdward S BucklerMichael D CaslerDenise E CostichSwitchgrass (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.https://doi.org/10.1371/journal.pone.0112227
collection DOAJ
language English
format Article
sources DOAJ
author Alexander E Lipka
Fei Lu
Jerome H Cherney
Edward S Buckler
Michael D Casler
Denise E Costich
spellingShingle Alexander E Lipka
Fei Lu
Jerome H Cherney
Edward S Buckler
Michael D Casler
Denise E Costich
Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
PLoS ONE
author_facet Alexander E Lipka
Fei Lu
Jerome H Cherney
Edward S Buckler
Michael D Casler
Denise E Costich
author_sort Alexander E Lipka
title Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
title_short Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
title_full Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
title_fullStr Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
title_full_unstemmed Accelerating the switchgrass (Panicum virgatum L.) breeding cycle using genomic selection approaches.
title_sort accelerating the switchgrass (panicum virgatum l.) breeding cycle using genomic selection approaches.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0112227
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