Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population

Authors

Alencar Xavier, Purdue UniversityFollow
Diego Jarquin, University of Nebraska-LincolnFollow
Reka Howard, University of Nebraska-LincolnFollow
Vishnu Ramasubramanian, Iowa State UniversityFollow
James E. Specht, University of Nebraska-LincolnFollow
George L. Graef, University of Nebraska-LincolnFollow
William D. Beavis, Iowa State UniversityFollow
Brian W. Diers, University of Illinois at Urbana-ChampaignFollow
Qijian Song, USDA-ARSFollow
Perry B. Cregan, USDA-ARSFollow
Randall L. Nelson, USDA-ARSFollow
Rouf Mian, North Carolina State UniversityFollow
J. Grover Shannon, University of MissouriFollow
Leah K. McHale, Ohio State UniversityFollow
Dechun Wang, Michigan State UniversityFollow
William Schapaugh, Kansas State UniversityFollow
Aaron J. Lorenz, University of MinnesotaFollow
Shizhong Xu, University of California, RiversideFollow
William M. Muir, Purdue UniversityFollow
Katy M. Rainey, Purdue UniversityFollow

Date of this Version

2-2018

Citation

Genes, Genomes, Genetics (February 2018) Volume 8, pp. 519 - 529.

Abstract

Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations.