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Junkui Ma

Shanxi Agricultural University

Publishes on Soybean genetics and cultivation, Legume Nitrogen Fixing Symbiosis, Nematode management and characterization studies. 8 papers and 106 citations.

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106Total Citations

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Natural allelic diversities of <i>GmPrx16</i> confer drought tolerance in soybean
Zhifang Zhang, Junkui Ma, Xia Yang et al.|Plant Biotechnology Journal|2023
Cited by 25Open Access

Drought has a serious impact on agricultural production, which can result in production losses ranging between 30% and 90%, depending on the crop species (Hussain et al., 2019; Lesk et al., 2016). Soybean [Glycine max (L.) Merr.] is an important crop that provides primary vegetable oil and protein as well as a supplement in livestock feed worldwide (Wilson, 2008). However, soybean is very sensitive to drought (Dong et al., 2019), and it has been revealed that from 1983 to 2009 approximately 67 Mha of harvested soybean areas experienced drought stress, resulting in a 7% total yield loss (Kim et al., 2019). To identify the genes and corresponding beneficial alleles conferring drought tolerance in soybean germplasms, we performed genome-wide association study (GWAS) using a panel of 585 soybean accessions, which had been genotyped in our previous work (Fang et al., 2017). The drought tolerance values of these 585 accessions were evaluated in the field in Shanxi Province, China (Figure S1, Table S1). GWAS identified one significant association locus on chromosome 16 ranging from 32 206 964 bp to 32 458 483 bp that covered 23 genes (Figure 1a, Table S2). Haplotype investigation showed that a C to G nonsynonymous SNP in Glyma.16G164400 (encoding a peroxidase, named as GmPrx16) was highly associated with the drought tolerance variation in soybean germplasm, suggesting that GmPrx16 might be the candidate gene in the association locus on chromosome 16 (Figure 1b). GmPrx16 was highly expressed in the root and mature leaf tissues (Figure S2a,b). Either dehydration stress treatment or withholding water treatment could induce the transcription of GmPrx16 (Figure S2c,d). A presence and absence variation (PAV) of a transposable element (TE) existed in the promoter region of GmPrx16, which was highly linked to the associated nonsynonymous SNP (Figure S2e). However, we determined that the PAV did not affect the expression of GmPrx16 in different accessions under normal and drought conditions (Figure S2f,g), indicating that the nonsynonymous SNP instead of the PAV was the causal polymorphism for the functional divergence of GmPrx16 in soybean. To validate the function of GmPrx16 in conferring drought tolerance in soybean, we performed overexpression (OE) and RNA interference (RNAi) on this gene in Dongnong No. 50 (DN50, an accession harbouring GmPrx16HapII) and obtained two independent transgenic lines for each construct (Figure S3a). Under well-watered condition, no obvious phenotypic differences were observed among DN50, OE lines and RNAi lines (Figure 1c, Figure S3b). When the 2-week-old seedling plants were subjected to drought treatment by withholding water for 12-day, the RNAi lines exhibited obvious drought-induced wilting compared with DN50 (Figure S3c); after withholding water for 14 days, the OE lines exhibited a higher drought-tolerant phenotype than DN50 (Figure 1d). Following a 14-day drought treatment, we rehydrated the plants and found that the survival rates of the OE lines were significantly higher than those of DN50, and the survival rates of the RNAi lines were significantly lower than those of DN50 (Figure 1e, Figure S3d). In consistent, malondialdehyde (MDA) content of DN50 was significantly higher than that of the OE lines, but lower than that of the RNAi lines (Figure 1f, Figure S3e). Interestingly, we also found that the GmPrx16 OE lines showed improved salt tolerance than DN50 (Figure S3f,g). These results demonstrated that GmPrx16 may play multiple roles besides drought tolerance in abiotic stress response. To test the functional divergence of GmPrx16HapI and GmPrx16HapII, we expressed the two GmPrx16 haplotypes in tobacco and observed that leaves expressing GmPrx16HapI exhibited higher peroxidase activity than that expressing GmPrx16HapII (Figure 1g). Furthermore, we compared the peroxidase activity of DN50 and the transgenic lines under drought conditions and found that the peroxidase activity in DN50 was significantly lower than that in the OE lines (Figure 1h) and higher than that in the RNAi lines (Figure 1i), consistent with the 3,3′-diaminobenzidine (DAB) staining assay (Figure S3h,i). To gain a better understanding how GmPrx16 conferred soybean drought tolerance, we performed RNA sequencing of GmPrx16 OE and RNAi lines with DN50 under drought conditions (Figure S4a,b). Gene ontology (GO) term enrichment analysis demonstrated GmPrx16 involved in multiple stress-responsive pathways (Figure S4c,d). It has been reported that peroxidases involve in lignin biosynthesis (Lee et al., 2007). Notably, pathways related to cell wall biosynthesis were also enriched (Figure S4c). We also found that the GmPrx16 OE lines had higher lignin content and the RNAi lines had lower lignin content than DN50 (Figure S4e). We randomly chose some reported and predicted genes participating in the above pathways and checking their expression levels using qRT-PCR (Figures S5 and S6). Consistent changing patterns to RNA-seq were obtained in the transgenic lines, suggesting a reliability of the RNA-seq data and also indicating that GmPrx16 influenced multiple pathways under drought stress. To determine the upstream regulator of GmPrx16, we screened a soybean root cDNA library through a one-hybrid assay (Y1H) and determined that two putative candidate regulators, Glyma.02G085900 (GmDRF1) and Glyma.07G171200 (GmDRF2), could specifically bind the promoter of GmPrx16 (Figure 1j). Transcriptional analysis showed that GmDRF1/2 were mainly expressed in leaves (Figure S7a) and either dehydration stress treatment or withholding water treatment could induce the transcription of GmDRF1/2 (Figure S7b,c). Transient transfection assays in Arabidopsis protoplasts and tobacco leaves indicated that GmDRF1/2 could significantly induce the expression of GmPrx16 (Figure 1k, Figure S7d). Therefore, we propose a model to illustrate the molecular mechanisms of GmPrx16 in modulating soybean drought tolerance (Figure 1l): GmDRF1/2 physically bind to the promoter of GmPrx16 and promote its expression, and drought stress induces the expression of GmDRF1/2, thereby influencing the accumulation of ROS and multiple stress response pathways. Taken together, we identified GmPrx16 as a key gene responsible for drought tolerance in soybean natural populations, providing insights into the development of drought-tolerant soybean cultivars by molecular design breeding. This work was supported by the National Key Research and Development Program of China (2021YFD1201101), the Taishan Scholars Program, the National Natural Science Foundation of China (32388201 and 32001501), Hainan Yazhou Bay Seed Laboratory Project (B21HJ0002 and B23YQ1501), Science and Technology Innovation Team of Soybean Modern Seed Industry in Hebei (21326313D), Support Plan for Innovation and Development of Key Industries in South Xinjiang (2022DB015), the Seed-Industrialized Development Program in Shandong Province (2021LZGC003) and Provincial Special Fund for Science and Technology Innovation and Development of Agricultural High-tech Industrial Demonstration Area of the Yellow River Delta of Shandong Province (2022SZX15). The authors declare no conflicts of interest. Z.T. designed the research; Z.Z., J.M., X.L., S.L., X.Y., Y.L., Z.L., S.L., Z.D., Z.W., X.Y., L.Y., and M.Z. performed the research; Z.Z., S.L., and Z.T. analysed the data; Z.Z., S.L., and Z.T. wrote the manuscript. All authors reviewed the manuscript. Figure S1 Frequency distribution histogram of drought tolerance value. Figure S2 GmPrx16 is the causal gene on the chromosome 16 association locus for drought tolerance in soybean. Figure S3 GmPrx16 confers drought and salt tolerance through regulating peroxidase activity in soybean. Figure S4 GmPrx16 affects multiple signaling pathways under drought condition in soybean. Figure S5 Expression levels of reported genes participating in drought tolerance in soybean in GmPrx16 transgenic lines and DN50 under drought condition. Figure S6 Expression levels of representative genes participating in the hormone signaling pathway and cell wall biosynthesis in DN50 and GmPrx16 transgenic lines under drought condition. Figure S7 GmDRF1 and GmDRF2 regulate GmPrx16 transcription. Table S1 Information for the natural population used in the GWAS. Table S2 Candidate genes list in the locus located on chomosome 16. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Soybean productivity can be enhanced by understanding rhizosphere microbiota: evidence from metagenomics analysis from diverse agroecosystems
Hong Ren, Huilong Hong, Bire Zha et al.|Microbiome|2025
Cited by 21Open Access

BACKGROUND: Microbial communities associated with roots play a crucial role in the growth and health of plants and are constantly influenced by plant development and alterations in the soil environment. Despite extensive rhizosphere microbiome research, studies examining multi-kingdom microbial variation across large-scale agricultural gradients remain limited. RESULTS: This study investigates the rhizosphere microbial communities associated with soybean across 13 diverse geographical locations in China. Using high-throughput shotgun metagenomic sequencing on the BGISEQ T7 platform with 10 GB per sample, we identified a total of 43,337 microbial species encompassing bacteria, archaea, fungi, and viruses. Our analysis revealed significant site-specific variations in microbial diversity and community composition, underscoring the influence of local environmental factors on microbial ecology. Principal coordinate analysis (PCoA) indicated distinct clustering patterns of microbial communities, reflecting the unique environmental conditions and agricultural practices of each location. Network analysis identified 556 hub microbial taxa significantly correlated with soybean yield traits, with bacteria showing the strongest associations. These key microorganisms were found to be involved in critical nutrient cycling pathways, particularly in carbon oxidation, nitrogen fixation, phosphorus solubilization, and sulfur metabolism. Our findings demonstrate the pivotal roles of specific microbial taxa in enhancing nutrient cycling, promoting plant health, and improving soybean yield, with significant positive correlations (r = 0.5, p = 0.039) between microbial diversity and seed yield. CONCLUSION: This study provides a comprehensive understanding of the diversity and functional potential of rhizosphere microbiota in enhancing soybean productivity. The findings underscore the importance of integrating microbial community dynamics into crop management strategies to optimize nutrient cycling, plant health, and yield. While this study identifies key microbial taxa with potential functional roles, future research should focus on isolating and validating these microorganisms for their bioremediation and biofertilization activities under field conditions. This will provide actionable insights for developing microbial-based agricultural interventions to improve crop resilience and sustainability. Video Abstract.

The GmSNAP11 Contributes to Resistance to Soybean Cyst Nematode Race 4 in Glycine max
Abdulwahab S. Shaibu, Shengrui Zhang, Junkui Ma et al.|Frontiers in Plant Science|2022
Cited by 18Open Access

Soybean cyst nematode (SCN) has devastating effects on soybean production, making it crucial to identify genes conferring SCN resistance. Here we employed next-generation sequencing-based bulked segregant analysis (BSA) to discover genomic regions, candidate genes, and diagnostic markers for resistance to SCN race 4 (SCN4) in soybean. Phenotypic analysis revealed highly significant differences among the reactions of 145 recombinant inbred lines (RILs) to SCN4. In combination with euclidean distance (ED) and Δsingle-nucleotide polymorphism (SNP)-index analyses, we identified a genomic region on Gm11 (designated as rhg1-paralog ) associated with SCN4 resistance. Overexpression and RNA interference analyzes of the two candidate genes identified in this region ( GmPLAC8 and GmSNAP11 ) revealed that only GmSNAP11 significantly contributes to SCN4 resistance. We developed a diagnostic marker for GmSNAP11 . Using this marker, together with previously developed markers for SCN-resistant loci, rhg1 and Rhg4 , we evaluated the relationship between genotypes and SCN4 resistance in 145 RILs and 30 soybean accessions. The results showed that all the SCN4-resistant lines harbored all the three loci, however, some lines harboring the three loci were still susceptible to SCN4. This suggests that these three loci are necessary for the resistance to SCN4, but they alone cannot confer full resistance. The GmSNAP11 and the diagnostic markers developed could be used in genomic-assisted breeding to develop soybean varieties with increased resistance to SCN4.

Global dissection of the recombination landscape in soybean using a high‐density <scp>600K SoySNP</scp> array
Xin Ma, Lei Fan, Zhifang Zhang et al.|Plant Biotechnology Journal|2022
Cited by 17Open Access

Summary Recombination is crucial for crop breeding because it can break linkage drag and generate novel allele combinations. However, the high‐resolution recombination landscape and its driving forces in soybean are largely unknown. Here, we constructed eight recombinant inbred line (RIL) populations and genotyped individual lines using the high‐density 600K SoySNP array, which yielded a high‐resolution recombination map with 5636 recombination sites at a resolution of 1.37 kb. The recombination rate was negatively correlated with transposable element density and GC content but positively correlated with gene density. Interestingly, we found that meiotic recombination was enriched at the promoters of active genes. Further investigations revealed that chromatin accessibility and active epigenetic modifications promoted recombination. Our findings provide important insights into the control of homologous recombination and thus will increase our ability to accelerate soybean breeding by manipulating meiotic recombination rate.

Identification of Quantitative Trait Locus and Candidate Genes for Drought Tolerance in a Soybean Recombinant Inbred Line Population
Wenqi Ouyang, Limiao Chen, Junkui Ma et al.|International Journal of Molecular Sciences|2022
Cited by 14Open Access

With global warming and regional decreases in precipitation, drought has become a problem worldwide. As the number of arid regions in the world is increasing, drought has become a major factor leading to significant crop yield reductions and food crises. Soybean is a crop that is relatively sensitive to drought. It is also a crop that requires more water during growth and development. The aim of this study was to identify the quantitative trait locus (QTL) that affects drought tolerance in soybean by using a recombinant inbred line (RIL) population from a cross between the drought-tolerant cultivar ‘Jindou21’ and the drought-sensitive cultivar ‘Zhongdou33’. Nine agronomic and physiological traits were identified under drought and well-watered conditions. Genetic maps were constructed with 923,420 polymorphic single nucleotide polymorphism (SNP) markers distributed on 20 chromosomes at an average genetic distance of 0.57 centimorgan (cM) between markers. A total of five QTLs with a logarithm of odds (LOD) value of 4.035–8.681 were identified on five chromosomes. Under well-watered conditions and drought-stress conditions, one QTL related to the main stem node number was located on chromosome 16, accounting for 17.177% of the phenotypic variation. Nine candidate genes for drought resistance were screened from this QTL, namely Glyma.16G036700, Glyma.16G036400, Glyma.16G036600, Glyma.16G036800, Glyma.13G312700, Glyma.13G312800, Glyma.16G042900, Glyma.16G043200, and Glyma.15G100700. These genes were annotated as NAC transport factor, GATA transport factor, and BTB/POZ-MATH proteins. This result can be used for molecular marker-assisted selection and provide a reference for breeding for drought tolerance in soybean.