Lipka Alexander E, Lu Fei, Cherney Jerome H, Buckler Edward S, Casler Michael D, Costich Denise E
Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America.
Department of Crop and Soil Sciences, Cornell University, Ithaca, New York, United States of America.
PLoS One. 2014 Nov 12;9(11):e112227. doi: 10.1371/journal.pone.0112227. eCollection 2014.
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.
柳枝稷（Panicum virgatum L.）是一种多年生草本植物，正作为生物燃料原料进行培育。阻碍该物种育种工作的最重要因素之一是需要准确测量每公顷的生物量产量。对近似生物量产量的易于测量的性状进行基因组选择有可能显著加快育种周期。柳枝稷基因组和表型资源的最新进展现在使得评估此类性状基因组选择的潜力成为可能。我们利用这些资源研究了三种广泛使用的基因组选择模型预测主要由适应北方的旱地种质组成的关联群体中形态和生物量质量性状表型值的能力。大多数性状都获得了较高的预测准确性，其中直立性具有最高的十倍交叉验证预测准确性（0.52）。此外，形态性状的预测准确性通常高于生物量质量性状。然而，我们的结果表明，目前可用于柳枝稷的基因组和表型资源质量足够高，基因组选择能够显著影响生物量产量的育种工作。
