Genome-Wide Association and Genomic Prediction for Yield and Component Traits of Miscanthus sacchariflorus

 

CABBI Theme: Feedstock Production

Keywords: Biomass Analytics, Genomics

 

Citation

Njuguna J.N., Lipka, A; Anzoua K.G., Bagmet L., Chebukin P., Dwiyanti M.S., Dzyubenko E., Dzyubenko N., Ghimire B.K., Jin X., Johnson D.A., Nagano H., Peng J., Petersen K.K., Sabitov A., Seong E.S., Yamada T., Yoo J.H., Yu C.Y., Zhao H., Long S.P.Sacks E.J. Sept. 8, 2023. “Genome-Wide Association and Genomic Prediction for Yield and Component Traits of Miscanthus sacchariflorus.” Global Change Biology Bioenergy. DOI: 10.1111/gcbb.13097.

 

Bar plot showing the gene regions of the 835 significant single-nucleotide polymorphisms (SNPs) (light grey) identified compared to gene regions of all 268,109 SNPs (dark grey) used in the genome wide association study of 16 yield-related traits of Miscanthus sacchariflorus. Genome wide association analysis was performed on 590 accessions using 268,109 SNP markers.

Overview

Accelerating biomass improvement is a major goal of miscanthus breeding. The development and implementation of genomic-enabled breeding tools, like marker-assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of miscanthus breeding. The present study conducted genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across four years in one subtropical and three temperate locations and genotyped with 268,109 single-nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield-component traits in M. sacchariflorus that may facilitate marker-assisted breeding for biomass yield. Genomic prediction accuracy for the yield-related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population-improvement of M. sacchariflorus.

 

Data

Download (21.2 MB) includes: 

  • Culm data
  • Dry biomass yield
  • Gene summary