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ORIGINAL RESEARCH article

Front. Plant Sci.
Sec. Functional and Applied Plant Genomics
Volume 15 - 2024 | doi: 10.3389/fpls.2024.1494551
This article is part of the Research Topic Soybean Breeding for Abiotic Stress Tolerance: Towards Sustainable Agriculture View all 10 articles

Genome-Wide Association Analysis and Genomic Prediction of Salt Tolerance Trait in Soybean Germplasm

Provisionally accepted
Rongqing Xu Rongqing Xu 1Qing Yang Qing Yang 1*Zhi Liu Zhi Liu 1Xiaolei Shi Xiaolei Shi 1*Xintong Wu Xintong Wu 1*Yuehan Chen Yuehan Chen 1*Xinyu Du Xinyu Du 1*Qiqi Gao Qiqi Gao 1*Di He Di He 1*Ainong Shi Ainong Shi 2*Peijun Tao Peijun Tao 3*Long Yan Long Yan 1*
  • 1 Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
  • 2 University of Arkansas, Fayetteville, North Carolina, United States
  • 3 College of Agronomy, Hebei Agricultural University, Baoding, Hebei Province, China

The final, formatted version of the article will be published soon.

    Soybean is an important protein and oil crop, and improving yield has traditionally been a major breeding goal. However, salt stress is an important abiotic factor that can severely impair soybean yield by disrupting metabolic processes, inhibiting photosynthesis, and hindering plant growth, ultimately leading to a decrease in productivity. This study utilized phenotypic and genotypic data from 563 soybean germplasms sourced from over 20 countries. Employing four distinct models—we performed a genome-wide association study (GWAS) using four models, including MLM, MLMM, FarmCPU, and BLINK in GAPIT 3, we conducted a Genome-Wide Association Study (GWAS) to identify single nucleotide polymorphism (SNP) associated with salt tolerance in soybean. Subsequently, these identified SNP were further analyzed for candidate gene discovery. Using 34,181 SNPs for genomic prediction (GP) to assess prediction accuracy. Our study identified 10 SNPs significantly associated with salt tolerance, located on chromosomes 1, 2, 3, 7, and 16. And we identified 11 genes within a 5 kb window upstream and downstream of the QTLs on chromosomes 1, 3, and 16. Utilizing the GWAS-derived SNP marker sets for genomic prediction (GP) yielded r-values greater than 0.35, indicating a higher level of accuracy. This suggests that genomic selection for salt tolerance is feasible. The 10 identified SNP markers and candidate genes in this study provide a valuable reference for screening and developing salt-tolerant soybean germplasm resources.

    Keywords: Soybean, salt stress, Genome-Wide Association Study, Genomic prediction, germplasm

    Received: 11 Sep 2024; Accepted: 07 Oct 2024.

    Copyright: © 2024 Xu, Yang, Liu, Shi, Wu, Chen, Du, Gao, He, Shi, Tao and Yan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Qing Yang, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Xiaolei Shi, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Xintong Wu, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Yuehan Chen, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Xinyu Du, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Qiqi Gao, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Di He, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
    Ainong Shi, University of Arkansas, Fayetteville, 72701, North Carolina, United States
    Peijun Tao, College of Agronomy, Hebei Agricultural University, Baoding, 071001, Hebei Province, China
    Long Yan, Institute of Grain and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.