Genome‐wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

Author:

Njuguna Joyce N.1ORCID,Clark Lindsay V.2,Lipka Alexander E.1ORCID,Anzoua Kossonou G.3,Bagmet Larisa4,Chebukin Pavel5,Dwiyanti Maria S.3,Dzyubenko Elena4,Dzyubenko Nicolay4,Ghimire Bimal Kumar6,Jin Xiaoli7ORCID,Johnson Douglas A.8,Nagano Hironori3,Peng Junhua9,Petersen Karen Koefoed10,Sabitov Andrey4,Seong Eun Soo11,Yamada Toshihiko3ORCID,Yoo Ji Hye12,Yu Chang Yeon12,Zhao Hua13,Long Stephen P.1ORCID,Sacks Erik J.1

Affiliation:

1. Department of Crop Sciences University of Illinois, Urbana‐Champaign Urbana Illinois USA

2. Research Scientific Computing Seattle Children's Research Institute Seattle Washington USA

3. Field Science Center for Northern Biosphere Hokkaido University Sapporo Japan

4. Vavilov All‐Russian Institute of Plant Genetic Resources St. Petersburg Russian Federation

5. FSBSI “FSC of Agricultural Biotechnology of the Far East named after A.K. Chaiki” Ussuriisk Russian Federation

6. Department of Crop Science, College of Sanghuh Life Science Konkuk University Seoul Korea

7. Key Laboratory of Crop Germplasm Research of Zhejiang Province, Agronomy Department Zhejiang University Hangzhou China

8. USDA‐ARS Forage and Range Research Lab Utah State University Logan Utah USA

9. Spring Valley Agriscience Co. Ltd. Jinan Shandong China

10. Schroll Medical ApS Årslev Denmark

11. Division of Bioresource Sciences Kangwon National University Chuncheon Korea

12. Bioherb Research Institute Kangwon National University Chuncheon Korea

13. Key Laboratory of Horticultural Plant Biology of Ministry of Education Huazhong Agricultural University Wuhan People's Republic of China

Abstract

AbstractAccelerating 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 4 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.

Funder

Basic Energy Sciences

Biological and Environmental Research

Directorate for Biological Sciences

Publisher

Wiley

Subject

Waste Management and Disposal,Agronomy and Crop Science,Renewable Energy, Sustainability and the Environment,Forestry

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