The development and use of a molecular model for soybean maturity groups

Abstract

Background: Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3.

Results: We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada.

Conclusions: The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments.

Keywords: E genes; Glycine max; Maturity group; Soybean.

Fig. 1

Distribution of predicted E alleles and genotypes for Glycine max accessions from the USDA Soybean Germplasm Collection by country or region of origin. a The allele frequencies of predicted E1, E2, and E3 are shown for four geographical locations—North America, China, Japan and Korea, and Asia (16 Asian countries excluding China, Japan, and Korea are referred to as Asia with 90% of the soybean lines originating in Vietnam, Indonesia, India, and Nepal). Japan and Korea data were combined because their distributions of predicted E alleles were indistinguishable). The functional E1, E2, and E3 alleles are green, and e1-as and the nonfunctional alleles, e2 and e3-tr, are blue. b Eight predicted E genotype frequencies are grouped by geographic location

Fig. 2.

Classification of E genotype groups by MG based on ex-PVP and private-company soybean lines. Reading across each row, the frequency of the E genotype is shown as a percentage of the total number of lines with that E genotype compared to all lines examined within a MG. For example, for MG III, 83% of the 126 lines had the e1-as E2 E3 genotype while 10% had e1-as e2 E3, and 8% had e1-as E2 e3-tr. The E genotypes with the highest percentage in each MG are bolded and highlighted gray. The alleles e1-nl and e1-fs are combined as e1-n*. a The E genotypes for the ex-PVP lines are grouped into MG 0-IX. b The E genotypes from the private-company lines provided by Dow AgroSciences are arranged by RM. Two E genotype groups were excluded because they only occurred with about 10% frequency in RM 0.0–0.9 (e1-n* E2 e3-tr and e1-n* E2 E3).