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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Soybean Genomics & Improvement Laboratory » Research » Publications at this Location » Publication #338129

Title: Genome-wide footprints of grain yield stability and environmental interactions in a multi-parental soybean population

item XAVIER, ALENCAR - Purdue University
item JARQUIN, DIEGO - University Of Nebraska
item HOWARD, REKA - University Of Nebraska
item RAMASUBRAMANIAN, VISHNU - Iowa State University
item SPECHT, JAMES - University Of Nebraska
item GRAEF, GEORGE - University Of Nebraska
item BEAVIS, WILLIAM - Iowa State University
item DIERS, BRIAN - University Of Illinois
item Song, Qijian
item CREGAN, PERRY - Retired ARS Employee
item Nelson, Randall
item Mian, Rouf
item SHANNON, J - University Of Missouri
item MCHALE, LEAH - The Ohio State University
item WANG, DECHUN - Michigan State University
item SCHAPAUGH, WILLIAM - Michigan State University
item LORENZ, AARON - University Of Wisconsin
item ZU, SHIZHONG - University Of California
item MUIR, WILLIAM - University Of California
item RAINEY, KATY - University Of California

Submitted to: G3, Genes/Genomes/Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/21/2017
Publication Date: 12/7/2017
Citation: Xavier, A., Jarquin, D., Howard, R., Ramasubramanian, V., Specht, J.E., Graef, G.L., Beavis, W.D., Diers, B.W., Song, Q., Cregan, P., Nelson, R.L., Mian, R.M., Shannon, J.G., Mchale, L., Wang, D., Schapaugh, W., Lorenz, A.J., Zu, S., Muir, W.M., Rainey, K.M. 2017. Genome-wide footprints of grain yield stability and environmental interactions in a multi-parental soybean population. G3, Genes/Genomes/Genetics. 8(2):519-529.

Interpretive Summary: One of the main objectives of plant breeders is to develop sustainable improved varieties for a wide set of environmental conditions. Usually, this objective is challenged by ever changing environmental variables. The changes affect performance of genes, and this complicates the breeder’s task of selecting the best parents for breeding. In this study, two standard analyses were used to investigate connections between genetics and environment based on the yield of the progeny from 40 soybean families. We identified six chromosomal DNA regions linked to genetics associated with environmental factors, and we also found that one of these chromosomal regions was associated with yield stability. This study provides insight into genomic assisted breeding for stable yield of soybean. Breeders at universities, private institutions and government agencies can use this information to develop soybeans with yield improvements.

Technical Abstract: Genetic improvement towards optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions might help breeders to develop sustainable varieties. 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 induced by the genotype by environmental interaction is an important step in improving selection procedures in soybean breeding programs. Our goal is to dissect the genetic basis of soybean grain yield responsiveness to environmental factors using a large soybean nested association population. For that, genome-wide association studies were conducted upon performance stability based on the Finlay-Wilkinson index and higher order interactions through multiplicative interaction models. Genomic footprints were investigated by analysis and meta-analysis through the multi-parent model of Wei and Xu (2016). Results indicate that specific genomic regions are associated with stability, and multiplicative interactions are present between environment and genetic background. Six genomic regions were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding for stable agronomic performance of soybean and opportunities to exploit genomic regions that are responsive for interactions with environments and subpopulations.