Identification of hub genes regulating isoflavone accumulation in soybean seeds via GWAS and WGCNA approaches - Azam, Muhammad; Zhang, Shengrui; Li, Jing; Ahsan, Muhammad; Agyenim-Boateng, Kwadwo Gyapong; Qi, Jie; Feng, Yue; Liu, Yitian; Li, Bin; Qiu, Lijuan; Sun, Junming (Frontiers in Plant Science, 2023)
Isoflavones are the secondary metabolites synthesized by the phenylpropanoid biosynthesis pathway in soybean that benefits human and plant health. In this study, we have profiled seed isoflavone content by HPLC in 1551 soybean accessions grown in Beijing and Hainan for two consecutive years (2017 and 2018) and in Anhui for one year (2017). A broad range of phenotypic variations was observed for individual and total isoflavone (TIF) content. The TIF content ranged from 677.25 to 5823.29 µg g-1 in the soybean natural population. Using a genome-wide association study (GWAS) based on 6,149,599 single nucleotide polymorphisms (SNPs), we identified 11,704 SNPs significantly associated with isoflavone contents; 75% of them were located within previously reported QTL regions for isoflavone. Two significant regions on chromosomes 5 and 11 were associated with TIF and malonylglycitin across more than 3 environments. Furthermore, The WGCNA identified eight key modules: black, blue, brown, green, magenta, pink, purple, and turquoise. Of the eight co-expressed modules, brown (r = 0.68***), magenta (r = 0.64***), and green (r = 0.51**) showed a significant positive association with TIF, as well as with individual isoflavone contents. By combining the gene significance, functional annotation, and enrichment analysis information, four hub genes Glyma.11G108100, Glyma.11G107100, Glyma.11G106900, and Glyma.11G109100 encoding, basic-leucine zipper (bZIP) transcription factor, MYB4 transcription factor, early responsive to dehydration, and PLATZ transcription factor respectively were identified in brown and green modules. The allelic variation in Glyma.11G108100 significantly influenced individual and TIF accumulation. The present study demonstrated that the GWAS approach, combined with WGCNA, could efficiently identify isoflavone candidate genes in the natural soybean population.