Bioinformatics Identification and Expression Analysis of Acetyl-CoA Carboxylase Reveal Its Role in Isoflavone Accumulation during Soybean Seed Development.

Isoflavones belong to the class of flavonoid compounds, which are important secondary metabolites that play a crucial role in plant development and defense. Acetyl-CoA carboxylase (ACCase) is a biotin-dependent enzyme that catalyzes the conversion of Acetyl-CoA into Malonyl-CoA in plants. It is a key enzyme in fatty acid synthesis and also catalyzes the production of various secondary metabolites. However, information on the ACC gene family in the soybean (Glycine max L. Merr.) genome and the specific members involved in isoflavone biosynthesis is still lacking. In this study, we identified 20 ACC family genes (GmACCs) from the soybean genome and further characterized their evolutionary relationships and expression patterns. Phylogenetic analysis showed that the GmACCs could be divided into five groups, and the gene structures within the same groups were highly conserved, indicating that they had similar functions. The GmACCs were randomly distributed across 12 chromosomes, and collinearity analysis suggested that many GmACCs originated from tandem and segmental duplications, with these genes being under purifying selection. In addition, gene expression pattern analysis indicated that there was functional divergence among GmACCs in different tissues. The GmACCs reached their peak expression levels during the early or middle stages of seed development. Based on the transcriptome and isoflavone content data, a weighted gene co-expression network was constructed, and three candidate genes (Glyma.06G105900, Glyma.13G363500, and Glyma.13G057400) that may positively regulate isoflavone content were identified. These results provide valuable information for the further functional characterization and application of GmACCs in isoflavone biosynthesis in soybean.

Joint GWAS and WGCNA Identify Genes Regulating the Isoflavone Content in Soybean Seeds.

Isoflavone is a secondary metabolite of the soybean phenylpropyl biosynthesis pathway with physiological activity and is beneficial to human health. In this study, the isoflavone content of 205 soybean germplasm resources from 3 locations in 2020 showed wide phenotypic variation. A joint genome-wide association study (GWAS) and weighted gene coexpression network analysis (WGCNA) identified 33 single-nucleotide polymorphisms and 11 key genes associated with soybean isoflavone content. Gene ontology enrichment analysis, gene coexpression, and haplotype analysis revealed natural variations in the Glyma.12G109800 (GmOMT7) gene and promoter region, with Hap1 being the elite haplotype. Transient overexpression and knockout of GmOMT7 increased and decreased the isoflavone content, respectively, in hairy roots. The combination of GWAS and WGCNA effectively revealed the genetic basis of soybean isoflavone and identified potential genes affecting isoflavone synthesis and accumulation in soybean, providing a valuable basis for the functional study of soybean isoflavone.

QTL Detection of Salt Tolerance at Soybean Seedling Stage Based on Genome-Wide Association Analysis and Linkage Analysis.

The utilization of saline land is a global challenge, and cultivating salt-tolerant soybean varieties is beneficial for improving the efficiency of saline land utilization. Exploring the genetic basis of salt-tolerant soybean varieties and developing salt-tolerant molecular markers can effectively promote the process of soybean salt-tolerant breeding. In the study, the membership function method was used to evaluate seven traits related to salt tolerance and comprehensive salt tolerance at the soybean seedling stage; genome-wide association analysis (GWAS) was performed in a natural population containing 200 soybean materials; and linkage analysis was performed in 112 recombinant inbred lines (RIL) population to detect quantitative trait loci (QTLs) of salt tolerance. In the GWAS, 147 SNPs were mapped, explaining 5.28-17.16% of phenotypic variation. In the linkage analysis, 10 QTLs were identified, which could explain 6.9-16.16% of phenotypic variation. And it was found that there were two co-located regions between the natural population and the RIL population, containing seven candidate genes of salt tolerance in soybean. In addition, one colocalization interval was found to contain qZJS-15-1, rs47665107, and rs4793412, all of which could explain more than 10% of phenotypic variation rates, making it suitable for molecular marker development. The physical positions of rs47665107 and rs47934112 were included in qZJS-15-1. Therefore, a KASP marker was designed and developed using Chr. 15:47907445, which was closely linked to the qZJS-15-1. This marker could accurately and clearly cluster the materials of salt-tolerant genotypes in the heterozygous population tested. The QTLs and KASP markers found in the study provide a theoretical and technical basis for accelerating the salt-tolerant breeding of soybean.

GWAS and WGCNA Analysis Uncover Candidate Genes Associated with Oil Content in Soybean.

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

Integrating Genome-Wide Association Study, Transcriptome and Metabolome Reveal Novel QTL and Candidate Genes That Control Protein Content in Soybean.

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.

Multi-omics analysis reveals novel loci and a candidate regulatory gene of unsaturated fatty acids in soybean (Glycine max (L.) Merr).

BACKGROUND: Soybean is a major oil crop; the nutritional components of soybean oil are mainly controlled by unsaturated fatty acids (FA). Unsaturated FAs mainly include oleic acid (OA, 18:1), linoleic acid (LLA, 18:2), and linolenic acid (LNA, 18:3). The genetic architecture of unsaturated FAs in soybean seeds has not been fully elucidated, although many independent studies have been conducted. A 3 V multi-locus random single nucleotide polymorphism (SNP)-effect mixed linear model (3VmrMLM) was established to identify quantitative trait loci (QTLs) and QTL-by-environment interactions (QEIs) for complex traits. RESULTS: In this study, 194 soybean accessions with 36,981 SNPs were calculated using the 3VmrMLM model. As a result, 94 quantitative trait nucleotides (QTNs) and 19 QEIs were detected using single-environment (QTN) and multi-environment (QEI) methods. Three significant QEIs, namely rs4633292, rs39216169, and rs14264702, overlapped with a significant single-environment QTN. CONCLUSIONS: For QTNs and QEIs, further haplotype analysis of candidate genes revealed that the Glyma.03G040400 and Glyma.17G236700 genes were beneficial haplotypes that may be associated with unsaturated FAs. This result provides ideas for the identification of soybean lipid-related genes and provides insights for breeding high oil soybean varieties in the future.

GmPLP1 negatively regulates soybean resistance to high light stress by modulating photosynthetic capacity and reactive oxygen species accumulation in a blue light-dependent manner.

High light stress is an important factor limiting crop yield. Light receptors play an important role in the response to high light stress, but their mechanisms are still poorly understood. Here, we found that the abundance of GmPLP1, a positive blue light receptor protein, was significantly inhibited by high light stress and mainly responded to high blue light. GmPLP1 RNA-interference soybean lines exhibited higher light energy utilization ability and less light damage and reactive oxygen species (ROS) accumulation in leaves under high light stress, while the phenotype of GmPLP1:GmPLP1-Flag overexpression soybean showed the opposite characteristics. Then, we identified a protein-protein interaction between GmPLP1 and GmVTC2, and the intensity of this interaction was primarily affected by sensing the intensity of blue light. More importantly, overexpression of GmVTC2b improved soybean tolerance to high light stress by enhancing the ROS scavenging capability through increasing the biosynthesis of ascorbic acid. This regulation was significantly enhanced after interfering with a GmPLP1-interference fragment in GmVTC2b-ox soybean leaves, but was weakened when GmPLP1 was transiently overexpressed. These findings demonstrate that GmPLP1 regulates the photosynthetic capacity and ROS accumulation of soybean to adapt to changes in light intensity by sensing blue light. In summary, this study discovered a new mechanism through which GmPLP1 participates in high light stress in soybean, which has great significance for improving soybean yield and the adaptability of soybean to high light.

Genome-wide identification and analysis of glyceraldehyde-3-phosphate dehydrogenase family reveals the role of GmGAPDH14 to improve salt tolerance in soybean (Glycine max L.).

Introduction: Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an essential key enzyme in the glycolytic pathway and plays an important role in stress responses. Although GAPDH family genes have been found in different plant species, the determination of their gene family analysis and their functional roles in soybean are still unknown. Methods: In this study, gene sequence and expression data were obtained using online tools, and systematic evolution, expression profile analysis, and qRT-PCR analysis were conducted. Results and Discussion: Here a total of 16 GmGAPDH genes were identified on nine chromosomes, which were classified into three clusters. Additionally, all GmGAPDH genes harbor two highly conserved domains, including Gp_dh_N (PF00044) and Gp_dh_C (PF02800). The qRTPCR analysis also showed that most GmGAPDH genes significantly responded to multiple abiotic stresses, including NaHCO3, polyethylene glycol, cold, and salt. Among them, GmGAPDH14 was extraordinarily induced by salt stress. The GmGAPDH14 gene was cloned and overexpressed through soybean hair roots. The overexpressed transgenic soybean plants of the GmGAPDH14 gene have also shown better growth than that of control plants. Moreover, the overexpressed transgenic plants of GmGAPDH14 gene had higher activities of superoxide dismutase but lower malonaldehyde (MDA) content than those of control plants under salt stress. Meanwhile, a total of four haplotypes were found for the GmGAPDH14 gene, and haplotypes 2, 3, and 4 were beneficial for the tolerance of soybean to salt stress. These results suggest that the GmGAPDH14 gene might be involved in the process of soybean tolerance to salt stress. The results of this study will be valuable in understanding the role of GAPDH genes in the abiotic stress response of soybean.

Identification of QTL, QTL-by-environment interactions, and their candidate genes for resistance HG Type 0 and HG Type 1.2.3.5.7 in soybean using 3VmrMLM.

Introduction: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is an important disease affecting soybean yield in the world. Potential SCN-related QTLs and QTL-by-environment interactions (QEIs) have been used in SCN-resistant breeding. Methods: In this study, a compressed variance component mixed model, 3VmrMLM, in genome-wide association studies was used to detect QTLs and QEIs for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7 in 156 different soybean cultivars materials. Results and discussion: The results showed that 53 QTLs were detected in single environment analysis; 36 QTLs and 9 QEIs were detected in multi-environment analysis. Based on the statistical screening of the obtained QTLs, we obtained 10 novel QTLs and one QEI which were different from the previous studies. Based on previous studies, we identified 101 known genes around the significant/suggested QTLs and QEIs. Furthermore, used the transcriptome data of SCN-resistant (Dongnong L-10) and SCN-susceptible (Suinong 14) cultivars, 10 candidate genes related to SCN resistance were identified and verified by Quantitative real time polymerase chain reaction (qRT-PCR) analysis. Haplotype difference analysis showed that Glyma.03G005600 was associated with SCN HG Type 0 and HG Type 1.2.3.5.7 resistance and had a haplotype beneficial to multi-SCN-race resistance. These results provide a new idea for accelerating SCN disease resistance breeding.

Genome-wide association analysis of resistance to frogeye leaf spot China race 7 in soybean based on high-throughput sequencing.

KEY MESSAGE: FLS is a disease that causes severe yield reduction in soybean. In this study, four genes (Glyma.16G176800, Glyma.16G177300, Glyma.16G177400 and Glyma.16G182300) were tentatively confirmed to play an important role in the resistance of soybean to FLS race 7. Frogeye leaf spot (FLS) causes severe yield loss in soybean and has been found in several countries worldwide. Therefore, it is necessary to select and utilize FLS-resistant varieties for the management of FLS. In the present study, 335 representative soybean materials were assessed for partial resistance to FLS race 7. Quantitative trait nucleotide (QTN) and FLS race 7 candidate genes were identified using genome-wide association analysis (GWAS) based on a site-specific amplified fragment sequencing (SLAF-seq) approach. A total of 23,156 single-nucleotide polymorphisms (SNPs) were used to evaluate the level of linkage disequilibrium with a minor allele frequency ≥ 5 and deletion data < 3%. These SNPs covered about 947.01 MBP, nearly 86.09% of the entire soybean genome. In addition, a compressed mixed linear model was utilized to identify association signals for partial resistance to FLS race 7. A total of 15 QTNs associated with resistance were found to be novel for FLS race 7 resistance. A total of 217 candidate genes located in the 200-kb genomic region of these peak SNPs were identified. Based on gene association analysis, qRT-PCR, haplotype analysis and virus-induced gene silencing (VIGS) systems were used to further verify candidate genes Glyma.16G176800, Glyma.16G177300, Glyma.16G177400 and Glyma.16G182300. This indicates that these four candidate genes may participate in FLS race 7 resistance responses.

Combined analysis of the metabolome and transcriptome provides insight into seed oil accumulation in soybean.

BACKGROUND: Soybean (Glycine max (L.) Merr) is an important source of human food, animal feed, and bio-energy. Although the genetic network of lipid metabolism is clear in Arabidopsis, the understanding of lipid metabolism in soybean is limited. RESULTS: In this study, 30 soybean varieties were subjected to transcriptome and metabolome analysis. In total, 98 lipid-related metabolites were identified, including glycerophospholipid, alpha-linolenic acid, linoleic acid, glycolysis, pyruvate, and the sphingolipid pathway. Of these, glycerophospholipid pathway metabolites accounted for the majority of total lipids. Combining the transcriptomic and metabolomic analyses, we found that 33 lipid-related metabolites and 83 lipid-related genes, 14 lipid-related metabolites and 17 lipid-related genes, and 12 lipid-related metabolites and 25 lipid-related genes were significantly correlated in FHO (five high-oil varieties) vs. FLO (five low-oil varieties), THO (10 high-oil varieties) vs. TLO (10 low-oil varieties), and HO (15 high-oil varieties) vs. LO (15 low-oil varieties), respectively. CONCLUSIONS: The GmGAPDH and GmGPAT genes were significantly correlated with lipid metabolism genes, and the result revealed the regulatory relationship between glycolysis and oil synthesis. These results improve our understanding of the regulatory mechanism of soybean seed oil improvement.

Genome-wide signatures of the geographic expansion and breeding of soybean.

Soybean is a leguminous crop that provides oil and protein. Exploring the genomic signatures of soybean evolution is crucial for breeding varieties with improved adaptability to environmental extremes. We analyzed the genome sequences of 2,214 soybeans and proposed a soybean evolutionary route, i.e., the expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from southern China and its domestication in central China, followed by the expansion and local breeding selection of its landraces (G. max (L.) Merr.). We observed that the genetic introgression in soybean landraces was mostly derived from sympatric rather than allopatric wild populations during the geographic expansion. Soybean expansion and breeding were accompanied by the positive selection of flowering time genes, including GmSPA3c. Our study sheds light on the evolutionary history of soybean and provides valuable genetic resources for its future breeding.

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM.

Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

Genome-wide association studies reveal novel QTLs, QTL-by-environment interactions and their candidate genes for tocopherol content in soybean seed.

Genome-wide association studies (GWAS) is an efficient method to detect quantitative trait locus (QTL), and has dissected many complex traits in soybean [Glycine max (L.) Merr.]. Although these results have undoubtedly played a far-reaching role in the study of soybean biology, environmental interactions for complex traits in traditional GWAS models are frequently overlooked. Recently, a new GWAS model, 3VmrMLM, was established to identify QTLs and QTL-by-environment interactions (QEIs) for complex traits. In this study, the GLM, MLM, CMLM, FarmCPU, BLINK, and 3VmrMLM models were used to identify QTLs and QEIs for tocopherol (Toc) content in soybean seed, including δ-Tocotrienol (δ-Toc) content, γ-Tocotrienol (γ-Toc) content, α-Tocopherol (α-Toc) content, and total Tocopherol (T-Toc) content. As a result, 101 QTLs were detected by the above methods in single-environment analysis, and 57 QTLs and 13 QEIs were detected by 3VmrMLM in multi-environment analysis. Among these QTLs, some QTLs (Group I) were repeatedly detected three times or by at least two models, and some QTLs (Group II) were repeatedly detected only by 3VmrMLM. In the two Groups, 3VmrMLM was able to correctly detect all known QTLs in group I, while good results were achieved in Group II, for example, 8 novel QTLs were detected in Group II. In addition, comparative genomic analysis revealed that the proportion of Glyma_max specific genes near QEIs was higher, in other words, these QEIs nearby genes are more susceptible to environmental influences. Finally, around the 8 novel QTLs, 11 important candidate genes were identified using haplotype, and validated by RNA-Seq data and qRT-PCR analysis. In summary, we used phenotypic data of Toc content in soybean, and tested the accuracy and reliability of 3VmrMLM, and then revealed novel QTLs, QEIs and candidate genes for these traits. Hence, the 3VmrMLM model has broad prospects and potential for analyzing the genetic structure of complex quantitative traits in soybean.

Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean (Glycine max L.) via Association and Expression Analysis.

Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.

Genome-Wide Association Analysis and Gene Mining of Resistance to China Race 1 of Frogeye Leaf Spot in Soybean.

Soybean frogeye leaf spot (FLS) is a worldwide fungal disease. Its higher occurrence frequency and wider distribution range always led to severe yield losses of soybean, therefore, breeding new cultivars with FLS resistance has been an important breeding goal for soybean breeders. In this study, an association panel of 183 representative soybean accessions was used to evaluate their resistance to FLS race 1, and to identify quantitative trait nucleotides (QTNs) and candidate genes based on genome-wide association study (GWAS) and high-throughput single-nucleotide polymorphisms (SNPs). A total of 23,156 high-quality SNPs were developed using the specific locus-amplified fragment sequencing (SLAF-seq) approach. Finally, 13 novel association signals associated with FLS race 1 resistance were identified by the compressed mixed linear model (CMLM). In addition, 119 candidate genes were found within the 200-kb flanking genomic region of these 13 peak SNPs. Based on the gene-based association analysis, haplotype analysis, expression pattern analysis, and virus-induced gene silencing (VIGS) systems, four genes (Glyma.05G121100, Glyma.17G228300, Glyma.19G006900, and Glyma.19G008700) were preliminarily proved to play an important role in the soybean resistance to FLS race 1.

A Nuclear Factor Y-B Transcription Factor, GmNFYB17, Regulates Resistance to Drought Stress in Soybean.

Soybean is sensitive to drought stress, and increasing tolerance to drought stresses is an important target for improving the performance of soybean in the field. The genetic mechanisms underlying soybean's drought tolerance remain largely unknown. Via a genome-wide association study (GWAS) combined with linkage analysis, we identified 11 single-nucleotide polymorphisms (SNPs) and 22 quantitative trait locus (QTLs) that are significantly associated with soybean drought tolerance. One of these loci, namely qGI10-1, was co-located by GWAS and linkage mapping. The two intervals of qGI10-1 were differentiated between wild and cultivated soybean. A nuclear factor Y transcription factor, GmNFYB17, was located in one of the differentiated regions of qGI10-1 and thus selected as a candidate gene for further analyses. The analysis of 29 homologous genes of GmNFYB17 in soybean showed that most of the genes from this family were involved in drought stress. The over-expression of GmNFYB17 in soybean enhanced drought resistance and yield accumulation. The transgenic plants grew better than control under limited water conditions and showed a lower degree of leaf damage and MDA content but higher RWC, SOD activity and proline content compared with control. Moreover, the transgenic plants showed a fast-growing root system, especially regarding a higher root-top ratio and more branching roots and lateral roots. The better agronomic traits of yield were also found in GmNFYB17 transgenic plants. Thus, the GmNFYB17 gene was proven to positively regulate drought stress resistance and modulate root growth in soybean. These results provide important insights into the molecular mechanisms underlying drought tolerance in soybean.

Fine-Mapping and Functional Analyses of a Candidate Gene Controlling Isoflavone Content in Soybeans Seed.

Isoflavones, one of the most important secondary metabolites produced by soybeans (Glycine max (L.) Merr.), are important for a variety of biological processes, and are beneficial for human health. To identify genetic loci underlying soybean isoflavone content, a mapping population containing 119 F5:18 recombinant inbred lines, derived by crossing soybean cultivar "Zhongdou27" with "Dongong8004," was used. We identified 15 QTLs associated with isoflavone contents. A novel loci, qISO19-1, was mapped onto soybean chromosome 19 and was fine-mapped to a 62.8 kb region using a BC2F2 population. We considered GmMT1 as a candidate gene for the qISO19-1 locus due to the significant positive correlation recovered between its expression level and isoflavone content in the seeds of 43 soybean germplasms. Overexpression of GmMT1 in Arabidopsis and soybean cultivars increased isoflavone contents. Transgenic soybeans overexpressing GmMT1 also exhibited improved resistance to pathogenic infection, while transgenic Arabidopsis resisted salt and drought stress.

GmLecRlk, a Lectin Receptor-like Protein Kinase, Contributes to Salt Stress Tolerance by Regulating Salt-Responsive Genes in Soybean.

Soybean [Glycine max (L.) Merr.] is an important oil crop that provides valuable resources for human consumption, animal feed, and biofuel. Through the transcriptome analysis in our previous study, GmLecRlk (Glyma.07G005700) was identified as a salt-responsive candidate gene in soybean. In this study, qRT-PCR analysis showed that the GmLecRlk gene expression level was significantly induced by salt stress and highly expressed in soybean roots. The pCAMBIA3300-GmLecRlk construct was generated and introduced into the soybean genome by Agrobacterium rhizogenes. Compared with the wild type (WT), GmLecRlk overexpressing (GmLecRlk-ox) soybean lines had significantly enhanced fresh weight, proline (Pro) content, and catalase (CAT) activity, and reduced malondialdehyde (MDA) and H2O2 content under salt stress. These results show that GmLecRlk gene enhanced ROS scavenging ability in response to salt stress in soybean. Meanwhile, we demonstrated that GmLecRlk gene also conferred soybean salt tolerance when it was overexpressed alone in soybean hairy root. Furthermore, the combination of RNA-seq and qRT-PCR analysis was used to determine that GmLecRlk improves the salt tolerance of soybean by upregulating GmERF3, GmbHLH30, and GmDREB2 and downregulating GmGH3.6, GmPUB8, and GmLAMP1. Our research reveals a new mechanism of salt resistance in soybean, which exposes a novel avenue for the cultivation of salt-resistant varieties.

Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1.

Introduction: The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance. Methods: Here, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules. Results and Discussion: A total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars ('Dongnong L-204') and SCN-susceptible cultivars ('Heinong 37') increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the 'turquoise module' were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN.