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Identification of genes for seed isoflavones based on bulk segregant analysis sequencing in soybean natural population

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Abstract

Key message

We identified four hub genes for isoflavone biosynthesis based on BSA-seq and WGCNA methods and validated that GmIE3-1 positively contribute to isoflavone accumulation in soybean.

Abstract

Soybean isoflavones are secondary metabolites of great interest owing to their beneficial impact on human health. Herein, we profiled the seed isoflavone content by HPLC in 1551 soybean accessions grown in two locations for two years and constructed two extreme pools with high (4065.1 µg g−1) and low (1427.23 µg g−1) isoflavone contents to identify candidate genes involved in isoflavone biosynthesis pathways using bulk segregant analysis sequencing (BSA-seq) approach. The results showed that the average sequencing depths were 50.3× and 65.7× in high and low pools, respectively. A total of 23,626 polymorphic SNPs and 5299 InDels were detected between both pools and 1492 genes with different variations were identified. Based on differential genes in BSA-seq and weighted gene co-expression network analysis (WGCNA), four hub genes, Glyma.06G290400 (designated as GmIE3-1), Glyma.01G239200, Glyma.01G241500, Glyma.13G256100 were identified, encoding E3 ubiquitin-protein ligase, arm repeat protein interacting with ABF2, zinc metallopeptidase EGY3, and dynamin-related protein 3A, respectively. The allelic variation in GmIE3-1 showed a significant influence on isoflavone accumulation. The virus-induced gene silencing (VIGS) and RNAi hairy root transformation of GmIE3-1 revealed partial suppression of this gene could cause a significant decrease (P < 0.0001) of total isoflavone content, suggesting GmIE3-1 is a positive regulator for isoflavones. The present study demonstrated that the BSA-seq approach combined with WGCNA, VIGS and hairy root transformation can efficiently identify isoflavone candidate genes in soybean natural population.

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Data availability

The high and low isoflavone pool resequencing data have been submitted to National Genomics Data Center, GEO, China (Accession Number: GVM000342).

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Acknowledgements

We thank Dr. Xianchun Xia, Institute of Crop Sciences, CAAS, for providing a critical review of this manuscript and valuable suggestions.

Funding

This research was funded by the National Natural Science Foundation of China (32272178, 32161143033, 31671716 and 32001574) and the Agricultural Science and Technology Innovation Program of CAAS (2060203–2).

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Author notes

  1. Muhammad Azam and Shengrui Zhang have contributed equally to this work.

Authors and Affiliations

  1. The National Engineering Research Center of Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China

    Muhammad Azam, Shengrui Zhang, Yuanyuan Huai, Ahmed M. Abdelghany, Abdulwahab S. Shaibu, Jie Qi, Yue Feng, Yitian Liu, Jing Li, Lijuan Qiu, Bin Li & Junming Sun

  2. Crop Science Department, Faculty of Agriculture, Damanhour University, Damanhour, 22516, Egypt

    Ahmed M. Abdelghany

  3. Department of Agronomy, Bayero University, Kano, Nigeria

    Abdulwahab S. Shaibu

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  1. Muhammad Azam
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Contributions

MA: Investigation, data curation, visualization, writing-original draft preparation, SZ: supervision, conceptualization, methodology, investigation, data curation, YH, AMA, ASS, JQ: resources, formal analysis, software, YF, YL, JL and LQ: resources, BL: project administration, conceptualization, writing–review and editing, JS: funding acquisition, supervision, conceptualization, visualization, writing–review and editing.

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Correspondence to Bin Li or Junming Sun.

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Azam, M., Zhang, S., Huai, Y. et al. Identification of genes for seed isoflavones based on bulk segregant analysis sequencing in soybean natural population. Theor Appl Genet 136, 13 (2023). https://doi.org/10.1007/s00122-023-04258-5

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