A new decade and new data at SoyBase, the USDA-ARS soybean genetics and genomics database.

SoyBase, a USDA genetic and genomics database, holds professionally curated soybean genetic and genomic data, which is integrated and made accessible to researchers and breeders. The site holds several reference genome assemblies, as well as genetic maps, thousands of mapped traits, expression and epigenetic data, pedigree information, and extensive variant and genotyping data sets. SoyBase displays include genetic, genomic, and epigenetic maps of the soybean genome. Gene expression data is presented in the genome viewer as heat maps and pictorial and tabular displays in gene report pages. Millions of sequence variants have been added, representing variations across various collections of cultivars. This variant data is explorable using new interactive tools to visualize the distribution of those variants across the genome, between selected accessions. SoyBase holds several reference-quality soybean genome assemblies, accessible via various query tools and browsers, including a new visualization system for exploring the soybean pan-genome. SoyBase also serves as a nexus of announcements pertinent to the greater soybean research community. The database also includes a soybean-specific anatomic and biochemical trait ontology. The database can be accessed at https://soybase.org.

Genome-Wide Identification, Characterization, and Expression Analysis of SPIRAL1 Family Genes in Legume Species.

The SPIRAL1 (SPR1) gene family encodes microtubule-associated proteins that are essential for the anisotropic growth of plant cells and abiotic stress resistance. Currently, little is known about the characteristics and roles of the gene family outside of Arabidopsis thaliana. This study intended to investigate the SPR1 gene family in legumes. In contrast to that of A. thaliana, the gene family has undergone shrinking in the model legume species Medicago truncatula and Glycine max. While the orthologues of SPR1 were lost, very few SPR1-Like (SP1L) genes were identified given the genome size of the two species. Specifically, the M. truncatula and G. max genomes only harbor two MtSP1L and eight GmSP1L genes, respectively. Multiple sequence alignment showed that all these members contain conserved N- and C-terminal regions. Phylogenetic analysis clustered the legume SP1L proteins into three clades. The SP1L genes showed similar exon-intron organizations and similar architectures in their conserved motifs. Many essential cis-elements are present in the promoter regions of the MtSP1L and GmSP1L genes associated with growth and development, plant hormones, light, and stress. The expression analysis revealed that clade 1 and clade 2 SP1L genes have relatively high expression in all tested tissues in Medicago and soybean, suggesting their function in plant growth and development. MtSP1L-2, as well as clade 1 and clade 2 GmSP1L genes, display a light-dependent expression pattern. The SP1L genes in clade 2 (MtSP1L-2, GmSP1L-3, and GmSP1L-4) were significantly induced by sodium chloride treatment, suggesting a potential role in the salt-stress response. Our research provides essential information for the functional studies of SP1L genes in legume species in the future.

Minc00344 and Mj-NULG1a effectors interact with GmHub10 protein to promote the soybean parasitism by Meloidogyne incognita and M. javanica.

Several economically important crops are susceptible to root-knot nematode (RKNs). Meloidogyne incognita and M. javanica are the two most reported species from the RKN complex, causing damage to several crops worldwide. The successful outcome of the Meloidogyne-plant interaction is associated with molecular factors secreted by the nematode to suppress the plant's immune response and promote nematode parasitism. In contrast, several plant factors are associated with defense against nematode infection. In this study, we identified and characterized the specific interaction of Minc00344 and Mj-NULG1a effectors with soybean GmHub10 (Glyma.19G008200) protein in vitro and in vivo. An Arabidopsis thaliana T-DNA mutant of AtHub10 (AT3G27960, an orthologous gene of GmHub10) showed higher susceptibility to M. incognita. Thus, since soybean and A. thaliana Hub10 proteins are involved in pollen tube growth and indirect activation of the defense response, our data suggest that effector-Hub10 interactions could be associated with an increase in plant susceptibility. These findings indicate the potential of these effector proteins to develop new biotechnological tools based on RNA interference and the overexpression of engineered Hub10 proteins for the efficient management of RKN in crops.

Chromosomal features revealed by comparison of genetic maps of Glycine max and Glycine soja.

Recombination is a crucial component of evolution and breeding. New combinations of variation on chromosomes are shaped by recombination. Recombination is also involved in chromosomal rearrangements. However, recombination rates vary tremendously among chromosome segments. Genome-wide genetic maps are one of the best tools to study variation of recombination. Here, we describe high density genetic maps of Glycine max and Glycine soja constructed from four segregating populations. The maps were used to identify chromosomal rearrangements and find the highly predictable pattern of cross-overs on the broad scale in soybean. Markers on these genetic maps were used to evaluate assembly quality of the current soybean reference genome sequence. We find a strong inversion candidate larger than 3 Mb based on patterns of cross-overs. We also identify quantitative trait loci (QTL) that control number of cross-overs. This study provides fundamental insights relevant to practical strategy for breeding programs and for pan-genome researches.

Genome-Wide Identification and Characterization of TALE Superfamily Genes in Soybean (Glycine max L.).

The three-amino-acid-loop-extension (TALE) superfamily genes broadly existed in plants, which played important roles in plant growth, development and abiotic stress responses. In this study, we identified 68 Glycine max TALE (GmTALE) superfamily members. Phylogenetic analysis divided the GmTALE superfamily into the BEL1-like (BLH/BELL homeodomain) and the KNOX (KNOTTED-like homeodomain) subfamilies. Moreover, the KNOX subfamily could be further categorized into three clades (KNOX Class I, KNOX Class II and KNOX Class III). The GmTALE genes showed similarities in the gene structures in the same subfamily or clade, whose coding proteins exhibited analogous motif and conserved domain compositions. Besides, synteny analyses and evolutionary constraint evaluations of the TALE members among soybean and different species provided more clues for GmTALE superfamily evolution. The cis-element analyses in gene promoter regions and relevant gene expression profiling revealed different regulating roles of GmTALE genes during soybean plant development, saline and dehydration stresses. Genome-wide characterization, evolution, and expression profile analyses of GmTALE genes can pave the way for future gene functional research and facilitate their roles for applications in genetic improvement on soybean in saline and dehydration stresses.

Comparison of the seed nutritional composition between conventional varieties and transgenic soybean overexpressing Physaria FAD3-1.

BACKGROUND: PfFAD3 transgenic soybean expressing omega-3 fatty acid desaturase 3 of Physaria produces increased level of α-linolenic acid in seed. Composition data of non-transgenic conventional varieties is important in the safety assessment of the genetically-modified (GM) crops in the context of the natural variation. RESULTS: The natural variation was characterized in seed composition of 13 Korean soybean varieties grown in three locations in South Korea for 2 years. Univariate analysis of combined data showed significant differences by variety and cultivation environment for proximates, minerals, anti-nutrients, and fatty acids. Percent variability analysis demonstrated that genotype, environment and the interaction of environment with genotype contributed to soybean seed compositions. Principal component analysis and orthogonal projections to latent structure discriminant analysis indicated that significant variance in compositions was attributable to location and cultivation year. The composition of three PfFAD3 soybean lines for proximates, minerals, anti-nutrients, and fatty acids was compared to a non-transgenic commercial comparator (Kwangankong, KA), and three non-transgenic commercial varieties grown at two sites in South Korea. Only linoleic and linolenic acids significantly differed in PfFAD3-1 lines compared to KA, which were expected changes by the introduction of the PfFAD3-1 trait in KA. CONCLUSION: Genotype, environment, and the interaction of environment with genotype contributed to compositional variability in soybean. PfFAD3-1 soybean is equivalent to the conventional varieties with respect to these components. © 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Location of Helicoverpa zea (Lepidoptera: Noctuidae) larvae on different plant parts of determinate and indeterminate soybean.

Helicoverpa zea (Boddie) is a damaging pest of many crops including soybean, Glycine max (L.), especially in the southern United States. Previous studies have concluded that oviposition and development of H. zea larvae mirror the phenology of soybean, with oviposition occurring during full bloom, younger larvae developing on blooms and leaves, intermediate aged larvae developing on varying tissue types, and older larvae developing on flowers and pods. In a field trial, we investigated the presence of natural infestations of H. zea larvae by instar in determinate and indeterminate soybean varieties. In complementary experiments, we artificially infested H. zea and allowed them to oviposit on plants within replicated cages (one with a determinate variety and two with an indeterminate variety). Plants were sampled weekly during the time larvae were present. In the natural infestation experiment, most larvae were found on blooms during R3 and were early to middle instars; by R4, most larvae were found on leaves and were middle to late instars. In contrast, in the cage study, most larvae were found on leaves regardless of soybean growth stage or larval stage. Determinate and indeterminate growth habit did not impact larval preference for different soybean tissue types. Our studies suggest H. zea larvae prefer specific tissue types, but also provide evidence that experimental design can influence the results. Finally, our finding of larval preference for leaves contrasts with findings from previous studies.

Genomic, molecular evolution, and expression analysis of NOX genes in soybean (Glycine max).

Reactive oxygen species (ROS) are versatile signaling molecules in sensing stresses and play critical roles in signaling and development. Plasma membrane NADPH oxidases (NOXs) are key producers of ROS, and play important roles in the regulation of plant-pathogen interactions. Here, we performed a comprehensive analysis of the NOX gene family in the soybean genome (Glycine max) and 17 NOX (GmNOX) genes were identified. Structural analysis revealed that the GmNOX proteins in soybean were as conserved as those in other plants. 8 duplicated gene pairs were formed by a Glycine-specific whole-genome duplication (WGD) event approximately 13 million years ago (Mya). The Ka/Ks ratios of GmNOX genes ranged from 0.04 to 0.28, suggesting that the GmNOX family had undergone purifying selection in soybean. Gene expression patterns showed different expression of these duplicate genes, suggesting that the GmNOXs were retained by substantial subfunctionalization during the soybean evolutionary processes. Subsequently, the expression of GmNOXs in response to drought and phytohormones were characterized via qPCR. Importantly, four GmNOXs showed strong expression in nodules, pointing to their probable involvement in nodulation. Thus, our results shed light on the evolutionary history of this family in soybean and contribute to the functional characterization of GmNOX genes in soybean.

Mineral Composition of Traditional Non-GMO Soybean Cultivars in relation to Nitrogen Fertilization.

Soybean is widely used as food. Genetic factors, as well as agrotechnical procedures, affect the yield and quality of soybeans. The subject of our research was the synchronization between soil N supply (from both mineralization and fertilization) and crop N demand. The aim of the research was to determine the effect of the cultivar and nitrogen application on the seed yield and mineral content in soybeans. Two non-GMO soybean cultivars (Amandine and Merlin) and four mineral nitrogen fertilizers ((A) N 0, control; (B) N 30:0, 30 kg N ha-1 before sowing; (C) N 0:30, 30 kg N ha-1 at BBCH 73-75; (D) N 30:30, 30 kg N ha-1 before sowing and 30 kg N ha-1 at BBCH 73-75) were tested. The highest soybean yield was obtained following nitrogen application at a rate of 60 kg ha-1. The genetic factor was found to significantly influence the content of some macronutrients (P, K, and Mg) and micronutrients (Cu, Mn, and Fe). In general, the Merlin cultivar had better macronutrient parameters except nitrogen, while Amandine had a higher content of Cu and Fe. Nitrogen fertilization decreased the content of P, K, and Zn in the soybeans but significantly increased the content of Ca, Mg, Cu, and Mn.

Soybean-VCF2Genomes: a database to identify the closest accession in soybean germplasm collection.

BACKGROUND: The development of next generation sequencer (NGS) and the analytical methods allowed the researchers to profile their samples more precisely and easier than before. Especially for agriculture, the certification of the genomic background of their plant materials would be important for the reliability of seed market and stable yield as well as for quarantine procedure. However, the analysis of NGS data is still difficult for non-computational researchers or breeders to verify their samples because majority of current softwares for NGS analysis require users to access unfamiliar Linux environment. MAIN BODY: Here, we developed a web-application, "Soybean-VCF2Genomes", http://pgl.gnu.ac.kr/soy_vcf2genome/ to map single sample variant call format (VCF) file against known soybean germplasm collection for identification of the closest soybean accession. Based on principal component analysis (PCA), we simplified genotype matrix for lowering computational burden while maintaining accurate clustering. With our web-application, users can simply upload single sample VCF file created by more than 10x resequencing strategy to find the closest samples along with linkage dendrogram of the reference genotype matrix. CONCLUSION: The information of the closest soybean cultivar will allow breeders to estimate relative germplasmic position of their query sample to determine soybean breeding strategies. Moreover, our VCF2Genomes scheme can be extended to other plant species where the whole genome sequences of core collection are publicly available.

Quantifying Variation in Soybean Due to Flood Using a Low-Cost 3D Imaging System.

Flood has an important effect on plant growth by affecting their physiologic and biochemical properties. Soybean is one of the main cultivated crops in the world and the United States is one of the largest soybean producers. However, soybean plant is sensitive to flood stress that may cause slow growth, low yield, small crop production and result in significant economic loss. Therefore, it is critical to develop soybean cultivars that are tolerant to flood. One of the current bottlenecks in developing new crop cultivars is slow and inaccurate plant phenotyping that limits the genetic gain. This study aimed to develop a low-cost 3D imaging system to quantify the variation in the growth and biomass of soybean due to flood at its early growth stages. Two cultivars of soybeans, i.e. flood tolerant and flood sensitive, were planted in plant pots in a controlled greenhouse. A low-cost 3D imaging system was developed to take measurements of plant architecture including plant height, plant canopy width, petiole length, and petiole angle. It was found that the measurement error of the 3D imaging system was 5.8% in length and 5.0% in angle, which was sufficiently accurate and useful in plant phenotyping. Collected data were used to monitor the development of soybean after flood treatment. Dry biomass of soybean plant was measured at the end of the vegetative stage (two months after emergence). Results show that four groups had a significant difference in plant height, plant canopy width, petiole length, and petiole angle. Flood stress at early stages of soybean accelerated the growth of the flood-resistant plants in height and the petiole angle, however, restrained the development in plant canopy width and the petiole length of flood-sensitive plants. The dry biomass of flood-sensitive plants was near two to three times lower than that of resistant plants at the end of the vegetative stage. The results indicate that the developed low-cost 3D imaging system has the potential for accurate measurements in plant architecture and dry biomass that may be used to improve the accuracy of plant phenotyping.

Genetic Mapping and Molecular Characterization of a Broad-spectrum Phytophthora sojae Resistance Gene in Chinese Soybean.

Phytophthora root rot (PRR) causes serious annual soybean yield losses worldwide. The most effective method to prevent PRR involves growing cultivars that possess genes conferring resistance to Phytophthora sojae (Rps). In this study, QTL-sequencing combined with genetic mapping was used to identify RpsX in soybean cultivar Xiu94-11 resistance to all P. sojae isolates tested, exhibiting broad-spectrum PRR resistance. Subsequent analysis revealed RpsX was located in the 242-kb genomic region spanning the RpsQ locus. However, a phylogenetic investigation indicated Xiu94-11 carrying RpsX is distantly related to the cultivars containing RpsQ, implying RpsX and RpsQ have different origins. An examination of candidate genes revealed RpsX and RpsQ share common nonsynonymous SNP and a 144-bp insertion in the Glyma.03g027200 sequence encoding a leucine-rich repeat (LRR) region. Glyma.03g027200 was considered to be the likely candidate gene of RpsQ and RpsX. Sequence analyses confirmed that the 144-bp insertion caused by an unequal exchange resulted in two additional LRR-encoding fragments in the candidate gene. A marker developed based on the 144-bp insertion was used to analyze the genetic population and germplasm, and proved to be useful for identifying the RpsX and RpsQ alleles. This study implies that the number of LRR units in the LRR domain may be important for PRR resistance in soybean.

Overexpression of GmCAMTA12 Enhanced Drought Tolerance in Arabidopsis and Soybean.

Fifteen transcription factors in the CAMTA (calmodulin binding transcription activator) family of soybean were reported to differentially regulate in multiple stresses; however, their functional analyses had not yet been attempted. To characterize their role in stresses, we first comprehensively analyzed the GmCAMTA family in silico and thereafter determined their expression pattern under drought. The bioinformatics analysis revealed multiple stress-related cis-regulatory elements including ABRE, SARE, G-box and W-box, 10 unique miRNA (microRNA) targets in GmCAMTA transcripts and 48 proteins in GmCAMTAs' interaction network. We then cloned the 2769 bp CDS (coding sequence) of GmCAMTA12 in an expression vector and overexpressed in soybean and Arabidopsis through Agrobacterium-mediated transformation. The T3 (Transgenic generation 3) stably transformed homozygous lines of Arabidopsis exhibited enhanced tolerance to drought in soil as well as on MS (Murashige and Skoog) media containing mannitol. In their drought assay, the average survival rate of transgenic Arabidopsis lines OE5 and OE12 (Overexpression Line 5 and Line 12) was 83.66% and 87.87%, respectively, which was ~30% higher than that of wild type. In addition, the germination and root length assays as well as physiological indexes such as proline and malondialdehyde contents, catalase activity and leakage of electrolytes affirmed the better performance of OE lines. Similarly, GmCAMTA12 overexpression in soybean promoted drought-efficient hairy roots in OE chimeric plants as compare to that of VC (Vector control). In parallel, the improved growth performance of OE in Hoagland-PEG (polyethylene glycol) and on MS-mannitol was revealed by their phenotypic, physiological and molecular measures. Furthermore, with the overexpression of GmCAMTA12, the downstream genes including AtAnnexin5, AtCaMHSP, At2G433110 and AtWRKY14 were upregulated in Arabidopsis. Likewise, in soybean hairy roots, GmELO, GmNAB and GmPLA1-IId were significantly upregulated as a result of GmCAMTA12 overexpression and majority of these upregulated genes in both plants possess CAMTA binding CGCG/CGTG motif in their promoters. Taken together, we report that GmCAMTA12 plays substantial role in tolerance of soybean against drought stress and could prove to be a novel candidate for engineering soybean and other plants against drought stress. Some research gaps were also identified for future studies to extend our comprehension of Ca-CaM-CAMTA-mediated stress regulatory mechanisms.

A Rapid and Highly Efficient Method for the Identification of Soybean Seed Varieties: Hyperspectral Images Combined with Transfer Learning.

Convolutional neural network (CNN) can be used to quickly identify crop seed varieties. 1200 seeds of ten soybean varieties were selected, hyperspectral images of both the front and the back of the seeds were collected, and the reflectance of soybean was derived from the hyperspectral images. A total of 9600 images were obtained after data augmentation, and the images were divided into a training set, validation set, and test set with a 3:1:1 ratio. Pretrained models (AlexNet, ResNet18, Xception, InceptionV3, DenseNet201, and NASNetLarge) after fine-tuning were used for transfer training. The optimal CNN model for soybean seed variety identification was selected. Furthermore, the traditional machine learning models for soybean seed variety identification were established by using reflectance as input. The results show that the six models all achieved 91% accuracy in the validation set and achieved accuracy values of 90.6%, 94.5%, 95.4%, 95.6%, 96.8%, and 97.2%, respectively, in the test set. This method is better than the identification of soybean seed varieties based on hyperspectral reflectance. The experimental results support a novel method for identifying soybean seeds rapidly and accurately, and this method also provides a good reference for the identification of other crop seeds.

Gene-based SNP identification and validation in soybean using next-generation transcriptome sequencing.

Gene-based molecular markers are increasingly used in crop breeding programs for marker-assisted selection. However, identification of genetic variants associated with important agronomic traits has remained a difficult task in soybean. RNA-Seq provides an efficient way, other than assessing global expression variations of coding genes, to discover gene-based SNPs at the whole genome level. In this study, RNA isolated from four soybean accessions each with three replications was subjected to high-throughput sequencing and a range of 44.2-65.9 million paired-end reads were generated for each library. A total of 75,209 SNPs were identified among different genotypes after combination of replications, 89.1% of which were located in expressed regions and 27.0% resulted in amino acid changes. GO enrichment analysis revealed that most significant enriched genes with nonsynonymous SNPs were involved in ribonucleotide binding or catalytic activity. Of 22 SNPs subjected to PCR amplification and Sanger sequencing, all of them were validated. To test the utility of identified SNPs, these validated SNPs were also assessed by genotyping a relative large population with 393 wild and cultivated soybean accessions. These SNPs identified by RNA-Seq provide a useful resource for genetic and genomic studies of soybean. Moreover, the collection of nonsynonymous SNPs annotated with their predicted functional effects also provides a valuable asset for further discovery of genes, identification of gene variants, and development of functional markers.

Variable Mesophyll Conductance among Soybean Cultivars Sets a Tradeoff between Photosynthesis and Water-Use-Efficiency.

Photosynthetic efficiency is a critical determinant of crop yield potential, although it remains below the theoretical optimum in modern crop varieties. Enhancing mesophyll conductance (i.e. the rate of carbon dioxide diffusion from substomatal cavities to the sites of carboxylation) may increase photosynthetic and water use efficiencies. To improve water use efficiency, mesophyll conductance should be increased without concomitantly increasing stomatal conductance. Here, we partition the variance in mesophyll conductance to within- and among-cultivar components across soybean (Glycine max) grown under both controlled and field conditions and examine the covariation of mesophyll conductance with photosynthetic rate, stomatal conductance, water use efficiency, and leaf mass per area. We demonstrate that mesophyll conductance varies more than 2-fold and that 38% of this variation is due to cultivar identity. As expected, mesophyll conductance is positively correlated with photosynthetic rates. However, a strong positive correlation between mesophyll and stomatal conductance among cultivars apparently impedes positive scaling between mesophyll conductance and water use efficiency in soybean. Contrary to expectations, photosynthetic rates and mesophyll conductance both increased with increasing leaf mass per area. The presence of genetic variation for mesophyll conductance suggests that there is potential to increase photosynthesis and mesophyll conductance by selecting for greater leaf mass per area. Increasing water use efficiency, though, is unlikely unless there is simultaneous stabilizing selection on stomatal conductance.

Variability of CP4 EPSPS expression in genetically engineered soybean (Glycine max L. Merrill).

The expression of the CP4 EPSPS protein in genetically engineered (GE) soybean confers tolerance to the Roundup® family of agricultural herbicides. This study evaluated the variability of CP4 EPSPS expression using an enzyme-linked immunosorbent assay in soybean tissues collected across diverse germplasm and 74 different environments in Argentina, Brazil and the USA. Evaluated material included single and combined (stacked) trait products with other GE traits in entries with cp4 epsps gene at one or two loci. The highest level of CP4 EPSPS was observed in leaf tissues, intermediate in forage and seed, and lowest in root tissues. Varieties with two loci had approximately twice the level of CP4 EPSPS expression compared to one locus entries. Variable and non-directional level of CP4 EPSPS was observed with other factors like genetic background, trait stacking, growing region or season. The maximum and average CP4 EPSPS expression levels in seed provided large margins of exposure (MOE of approximately 4000 and 11,000, respectively), mitigating concerns over exposure to this protein in food and feed from soybean varieties tolerant to Roundup® herbicides.

Mechanisms of Soybean Roots' Tolerances to Salinity Revealed by Proteomic and Phosphoproteomic Comparisons Between Two Cultivars.

Understanding molecular mechanisms underlying plant salinity tolerance provides valuable knowledgebase for effective crop improvement through genetic engineering. Current proteomic technologies, which support reliable and high-throughput analyses, have been broadly used for exploring sophisticated molecular networks in plants. In the current study, we compared phosphoproteomic and proteomic changes in roots of different soybean seedlings of a salt-tolerant cultivar (Wenfeng07) and a salt-sensitive cultivar (Union85140) induced by salt stress. The root samples of Wenfeng07 and Union85140 at three-trifoliate stage were collected at 0 h, 0.5 h, 1 h, 4 h, 12 h, 24 h, and 48 h after been treated with 150 mm NaCl. LC-MS/MS based phosphoproteomic analysis of these samples identified a total of 2692 phosphoproteins and 5509 phosphorylation sites. Of these, 2344 phosphoproteins containing 3744 phosphorylation sites were quantitatively analyzed. Our results showed that 1163 phosphorylation sites were differentially phosphorylated in the two compared cultivars. Among them, 10 MYB/MYB transcription factor like proteins were identified with fluctuating phosphorylation modifications at different time points, indicating that their crucial roles in regulating flavonol accumulation might be mediated by phosphorylated modifications. In addition, the protein expression profiles of these two cultivars were compared using LC MS/MS based shotgun proteomic analysis, and expression pattern of all the 89 differentially expressed proteins were independently confirmed by qRT-PCR. Interestingly, the enzymes involved in chalcone metabolic pathway exhibited positive correlations with salt tolerance. We confirmed the functional relevance of chalcone synthase, chalcone isomerase, and cytochrome P450 monooxygenase genes using soybean composites and Arabidopsis thaliana mutants, and found that their salt tolerance were positively regulated by chalcone synthase, but was negatively regulated by chalcone isomerase and cytochrome P450 monooxygenase. A novel salt tolerance pathway involving chalcone metabolism, mostly mediated by phosphorylated MYB transcription factors, was proposed based on our findings. (The mass spectrometry raw data are available via ProteomeXchange with identifier PXD002856).

Ascospore Inoculum Density and Characterization of Components of Partial Resistance to Sclerotinia sclerotiorum in Soybean.

Germplasm screening programs have primarily relied on inoculation with mycelia to determine the resistance reaction of soybean genotypes to Sclerotinia sclerotiorum. However, under field conditions, ascospores are the primary source of inoculum. Therefore, the objective of this study was to determine which components most accurately differentiate the resistance reaction of soybean genotypes inoculated with ascospores of S. sclerotiorum. Ascospores were produced in the laboratory and all of the experiments were carried out under controlled conditions with inoculations at flowering stage. Initially, inoculum densities of 1 × 104, 1 × 105 and 1 × 106 ascospores ml-1 were compared on six soybean genotypes with known resistance reactions. Disease symptoms developed on all genotypes and at all inoculum densities. The highest ascospore concentration increased infection efficiency but it was not correlated with an increase in lesion length. Components of resistance were then measured on a set of 17 cultivars with known resistance reactions at 1 × 105 ascospores ml-1. Resistance reactions could be differentiated based on the level of infection efficiency and lesion length on the main stem. Although inoculation with ascospores presents some limitations such as the time required for inoculum production as well as the time and space required for plant growth, it has the potential to be used to complement other methods for the characterization of resistance of soybean genotypes.

Genomic organization, phylogenetic comparison, and expression profiles of the SPL family genes and their regulation in soybean.

SQUAMOSA Promoter-Binding Protein-Like (SPL) genes form a major family of plant-specific transcription factors and play an important role in plant growth and development. In this study, we report the identification of 41 SPL genes (GmSPLs) in the soybean genome. Phylogenetic analysis revealed that these genes were divided into five groups (groups 1-5). Further, exon/intron structure and motif composition revealed that the GmSPL genes are conserved within their same group. The N-terminal zinc finger 1 (Zn1) of the SBP domain was a CCCH (Cys3His1) and the C terminus zinc finger 2 (Zn2) was a CCHC (Cys2HisCys) type. The 41 GmSPL genes were distributed unevenly on 17 of the 20 chromosomes, with tandem and segmental duplication events. We found that segmental duplication has made an important contribution to soybean SPL gene family expansion. The Ka/Ks ratios revealed that the duplicated GmSPL genes evolved under the effect of purifying selection. In addition, 17 of the 41 GmSPLs were found as targets of miR156; these might be involved in their posttranscriptional regulation through miR156. Importantly, RLM-RACE analysis confirmed the GmmiR156-mediated cleavage of GmSPL2a transcript in 2-4 mm stage of soybean seed. Alternative splicing events in 9 GmSPLs were detected which produces transcripts and proteins of different lengths that may modulate protein signaling, binding, localization, stability, and other properties. Expression analysis of the soybean SPL genes in various tissues and different developmental stages of seed suggested distinct spatiotemporal patterns. Differences in the expression patterns of miR156-targeted and miR156-non-targeted soybean SPL genes suggest that miR156 plays key functions in soybean development. Our results provide an important foundation for further uncovering the crucial roles of GmSPLs in the development of soybean and other biological processes.