MPB_2025v16n1

Molecular Plant Breeding 2025, Vol.16, No.1, 63-72 http://genbreedpublisher.com/index.php/mpb 66 ABA-independent pathways also contribute to drought tolerance in soybean. For example, the comparative transcriptome analysis of drought-tolerant and sensitive soybean genotypes revealed that numerous differentially expressed genes (DEGs) are involved in signal transduction pathways such as calcium signaling and MAPK signaling, which are independent of ABA (Xuan et al., 2022). The GmHdz4 transcription factor, edited via CRISPR/Cas9, enhances drought tolerance through mechanisms that include antioxidant enzyme activity and osmolyte accumulation, which are not directly linked to ABA signaling (Zhong et al., 2022). 3.3 Genomic and proteomic approaches Genomic approaches such as genome-wide association studies (GWAS) have identified several loci associated with drought tolerance in soybean. For instance, a study identified 26 SNPs related to drought tolerance during the germination stage, leading to the identification of 41 candidate genes (Figure 2) (Zhao et al., 2020). Another study identified 11 SNPs and 22 QTLs significantly associated with drought tolerance, with the GmNFYB17 gene being a key candidate for further analysis (Sun et al., 2022). Additionally, RNA-seq analysis of wild soybean genotypes under drought stress identified thousands of DEGs involved in various stress responses, providing a comprehensive understanding of the genetic mechanisms underlying drought tolerance (Aleem et al., 2020). Proteomic approaches have also been employed to identify proteins associated with drought tolerance. For example, a study identified 163 metabolites and 3 000 genes that are strongly regulated during water stress, including transcription factors and signaling components that are potential targets for improving drought responses (Tripathi et al., 2016). Proteomic profiling of soybean seedlings under drought stress revealed key pathways and proteins involved in stress responses, such as those related to cell wall remodeling and stress-related proteins (Xuan et al., 2022.) Figure 2 Genetic structure and relatedness of the 410 soybean accessions (Adopted from Zhao et al., 2020) Image caption: (A) Neighbor--joining tree constructed using SNP data, foreign soybean germplasm expressed as green; soybean accessions from north are shown in red; those from the Huanghuaihai valley region are shown in blue; and those from the south valley region are shown in orange. (B) Principal component analysis for the entire panel of soybean accessions; (C) PCA eigenvalue performed by GAPIT using the pruned set of 200K SNP. As presented, the total variance explained by each principal component (PC) decreased from PC1 to PC4 and, after PC4, the variance explained by each further PC remained low and stable; (D) Clustering for PCA = 4 for the entire panel of soybean accessions. Each individual is represented by a vertical bar, as well as partitioned into colored segments, with the length of each segment representing the proportion of the individual's genome from groups when PCA = 4 (Adopted from Zhao et al., 2020)

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