Allele combinations of maturity genes E1-E4 affect adaptation of soybean to diverse geographic regions and farming systems in China

PLoS One. 2020 Jul 6;15(7):e0235397. doi: 10.1371/journal.pone.0235397. eCollection 2020.

Abstract

Appropriate flowering and maturity time are important for soybean production. Four maturity genes E1, E2, E3 and E4 have been molecularly identified and found to play major roles in the control of flowering and maturity of soybean. Here, to further investigate the effect of different allele combinations of E1-E4, we performed Kompetitive Allele Specific PCR (KASP) assays based on single nucleotide polymorphisms (SNPs) at these four E loci, and genotyped E1-E4 genes across 308 Chinese cultivars with a wide range of maturity groups. In total, twenty-one allele combinations for E1-E4 genes were identified across these Chinese cultivars. Various combinations of mutations at four E loci gave rise to the diversity of flowering and maturity time, which were associated with the adaptation of soybean cultivars to diverse geographic regions and farming systems. In particular, the cultivars with mutations at all four E loci reached flowering and maturity very early, and adapted to high-latitude cold regions. The allele combinations e1-as/e2-ns/e3-tr/E4, E1/e2-ns/E3/E4 and E1/E2/E3/E4 played important roles in the Northeast China, Huang-Huai-Hai (HHH) Rivers Valley and South China regions, respectively. Notably, E1 and E2, especially E2, affected flowering and maturity time of soybean significantly. Our study will be beneficial for germplasm evaluation, cultivar improvement and regionalization of cultivation in soybean production.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Physiological / genetics*
  • Alleles
  • China
  • Crop Production
  • Farms
  • Flowers / growth & development
  • Gene Expression Regulation, Plant*
  • Genes, Developmental*
  • Genes, Plant
  • Genetic Variation
  • Genotype
  • Geography
  • Glycine max / physiology*
  • Photoperiod
  • Quantitative Trait Loci*
  • Time Factors

Grants and funding

This work was supported by the National Key R&D Program of China (2017YFD0101400), the Chinese Academy of Agricultural Sciences (CAAS) Innovation Project and the China Agriculture Research System (CARS-04) awarded to T. Han.