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Publication | Open Access

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean

556

Citations

64

References

2017

Year

TLDR

Soybean is a major oil and protein crop whose growing demand drives the need for varieties with higher productivity, yet trait correlations and gene interactions complicate breeding. The study aims to elucidate the genetic networks that underlie phenotypic correlations in soybean. To do so, 809 accessions were phenotyped for 84 agronomic traits over two years at three locations. Genome‑wide association studies identified 245 loci, 95 of which interact, 14 oil‑synthesis genes act additively, 115 loci link 51 traits through linkage disequilibrium, and 23 loci—including known and novel ones—exhibit pleiotropy, offering insights for functional studies and breeding.

Abstract

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

References

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