Systematic analysis of 1298 RNA-Seq samples and construction of a comprehensive soybean (Glycine max) expression atlas

Light recovery after maize harvesting promotes soybean flowering in a maize-soybean relay strip intercropping system

Moving from sole cropping to intercropping is a transformative change in agriculture, contributing to yield. Soybeans adapt to light conditions in intercropping by adjusting the onset of reproduction and the inflorescence architecture to optimize reproductive success. Maize-soybean strip intercropping (MS), maize-soybean relay strip intercropping (IS), and sole soybean (SS) systems are typical soybean planting systems with significant differences in light environments during growth periods. To elucidate the effect of changes in the light environment on soybean flowering processes and provide a theoretical basis for selecting suitable varieties in various planting systems to improve yields, field experiments combining planting systems (IS, MS, and SS) and soybean varieties (GQ8, GX7, ND25, and NN996) were conducted in 2021 and 2022. Results showed that growth recovery in the IS resulted in a balance in the expression of TERMINAL FLOWER 1 (TFL1) and FLOWERING LOCUS T (FT) in the meristematic tissues of soybeans, which promoted the formation of new branches or flowers. IS prolonged the flowering time (2-7 days) and increased the number of forming flowers compared with SS (93.0 and 169%) and MS (67.3 and 103.3%) at the later soybean flowering stage. The higher carbon and nitrogen content in the middle and bottom canopies of soybean contributed to decreased flower abscission by 26.7 and 30.2%, respectively, compared with SS. Canopy light environment recovery promoted branch and flower formation and transformation of flowers into pods with lower flower-pod abscission, which contributed to elevating soybean yields in late-maturing and multibranching varieties (ND25) in IS.

Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum

The gene expression landscape across different tissues and developmental stages reflects their biological functions and evolutionary patterns. Integrative and comprehensive analyses of all transcriptomic data in an organism are instrumental to obtaining a comprehensive picture of gene expression landscape. Such studies are still very limited in sorghum, which limits the discovery of the genetic basis underlying complex agricultural traits in sorghum. We characterized the genome-wide expression landscape for sorghum using 873 RNA-sequencing (RNA-seq) datasets representing 19 tissues. Our integrative analysis of these RNA-seq data provides the most comprehensive transcriptomic atlas for sorghum, which will be valuable for the sorghum research community for functional characterizations of sorghum genes. Based on the transcriptome atlas, we identified 595 housekeeping genes (HKGs) and 2080 tissue-specific expression genes (TEGs) for the 19 tissues. We identified different gene features between HKGs and TEGs, and we found that HKGs have experienced stronger selective constraints than TEGs. Furthermore, we built a transcriptome-wide co-expression network (TW-CEN) comprising 35 modules with each module enriched in specific Gene Ontology terms. High-connectivity genes in TW-CEN tend to express at high levels while undergoing intensive selective pressure. We also built global and seed-preferential co-expression networks of starch synthesis pathways, which indicated that photosynthesis and microtubule-based movement play important roles in starch synthesis. The global transcriptome atlas of sorghum generated by this study provides an important functional genomics resource for trait discovery and insight into starch synthesis regulation in sorghum.

StCoExpNet: a global co-expression network analysis facilitates identifying genes underlying agronomic traits in potatoes

KEY MESSAGE

We constructed a gene expression atlas and co-expression network for potatoes and identified several novel genes associated with various agronomic traits. This resource will accelerate potato genetics and genomics research. Potato (Solanum tuberosum L.) is the world's most crucial non-cereal food crop and ranks third in food production after wheat and rice. Despite the availability of several potato transcriptome datasets at public databases like NCBI SRA, an effort has yet to be put into developing a global transcriptome atlas and a co-expression network for potatoes. The objectives of our study were to construct a global expression atlas for potatoes using publicly available transcriptome datasets, identify housekeeping and tissue-specific genes, construct a global co-expression network and identify co-expression clusters, investigate the transcriptional complexity of genes involved in various essential biological processes related to agronomic traits, and provide a web server (StCoExpNet) to easily access the newly constructed expression atlas and co-expression network to investigate the expression and co-expression of genes of interest. In this study, we used data from 2299 publicly available potato transcriptome samples obtained from 15 different tissues to construct a global transcriptome atlas. We found that roughly 87% of the annotated genes exhibited detectable expression in at least one sample. Among these, we identified 281 genes with consistent and stable expression levels, indicating their role as housekeeping genes. Conversely, 308 genes exhibited marked tissue-specific expression patterns. We exemplarily linked some co-expression clusters to important agronomic traits of potatoes, such as self-incompatibility, anthocyanin biosynthesis, tuberization, and defense responses against multiple pathogens. The dataset compiled here constitutes a new resource (StCoExpNet), which can be accessed at https://stcoexpnet.julius-kuehn.de . This transcriptome atlas and the co-expression network will accelerate potato genetics and genomics research.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Regulation of seed traits in soybean

Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.

Global analysis of seed transcriptomes reveals a novel PLATZ regulator for seed size and weight control in soybean

Seed size and weight are important factors that influence soybean yield. Combining the weighted gene co-expression network analysis (WGCNA) of 45 soybean accessions and gene dynamic changes in seeds at seven developmental stages, we identified candidate genes that may control the seed size/weight. Among these, a PLATZ-type regulator overlapping with 10 seed weight QTLs was further investigated. This zinc-finger transcriptional regulator, named as GmPLATZ, is required for the promotion of seed size and weight in soybean. The GmPLATZ may exert its functions through direct binding to the promoters and activation of the expression of cyclin genes and GmGA20OX for cell proliferation. Overexpression of the GmGA20OX enhanced seed size/weight in soybean. We further found that the GmPLATZ binds to a 32-bp sequence containing a core palindromic element AATGCGCATT. Spacing of the flanking sequences beyond the core element facilitated GmPLATZ binding. An elite haplotype Hap3 was also identified to have higher promoter activity and correlated with higher gene expression and higher seed weight. Orthologues of the GmPLATZ from rice and Arabidopsis play similar roles in seeds. Our study reveals a novel module of GmPLATZ-GmGA20OX/cyclins in regulating seed size and weight and provides valuable targets for breeding of crops with desirable agronomic traits.

The Soybean Expression Atlas v2: A comprehensive database of over 5000 RNA-seq samples

Soybean is a crucial crop worldwide, used as a source of food, feed, and industrial products due to its high protein and oil content. Previously, the rapid accumulation of soybean RNA-seq data in public databases and the computational challenges of processing raw RNA-seq data motivated us to develop the Soybean Expression Atlas, a gene expression database of over a thousand RNA-seq samples. Over the past few years, our database has allowed researchers to explore the expression profiles of important gene families, discover genes associated with agronomic traits, and understand the transcriptional dynamics of cellular processes. Here, we present the Soybean Expression Atlas v2, an updated version of our database with a fourfold increase in the number of samples, featuring transcript- and gene-level transcript abundance matrices for 5481 publicly available RNA-seq samples. New features in our database include the availability of transcript-level abundance estimates and equivalence classes to explore differential transcript usage, abundance estimates in bias-corrected counts to increase the accuracy of differential gene expression analyses, a new web interface with improved data visualization and user experience, and a reproducible and scalable pipeline available as an R package. The Soybean Expression Atlas v2 is available at https://soyatlas.venanciogroup.uenf.br/, and it will accelerate soybean research, empowering researchers with high-quality and easily accessible gene expression data.

Genome-Wide Tissue-Specific Genes Identification for Novel Tissue-Specific Promoters Discovery in Soybean

Promoters play a crucial role in controlling the spatial and temporal expression of genes at transcriptional levels in the process of higher plant growth and development. The spatial, efficient, and correct regulation of exogenous genes expression, as desired, is the key point in plant genetic engineering research. Constitutive promoters widely used in plant genetic transformation are limited because, sometimes, they may cause potential negative effects. This issue can be solved, to a certain extent, by using tissue-specific promoters. Compared with constitutive promoters, a few tissue-specific promoters have been isolated and applied. In this study, based on the transcriptome data, a total of 288 tissue-specific genes were collected, expressed in seven tissues, including the leaves, stems, flowers, pods, seeds, roots, and nodules of soybean (Glycine max). KEGG pathway enrichment analysis was carried out, and 52 metabolites were annotated. A total of 12 tissue-specific genes were selected via the transcription expression level and validated through real-time quantitative PCR, of which 10 genes showed tissue-specific expression. The 3-kb 5' upstream regions of ten genes were obtained as putative promoters. Further analysis showed that all the 10 promoters contained many tissue-specific cis-elements. These results demonstrate that high-throughput transcriptional data can be used as effective tools, providing a guide for high-throughput novel tissue-specific promoter discovery.

Genome-wide identification of genes encoding SWI/SNF components in soybean and the functional characterization of GmLFR1 in drought-stressed plants

ATP-dependent SWI/SNF chromatin remodeling complexes (CRCs) are evolutionarily conserved multi-component machines that regulate transcription, replication, and genome stability in eukaryotes. SWI/SNF components play pivotal roles in development and various stress responses in plants. However, the compositions and biological functions of SWI/SNF complex subunits remain poorly understood in soybean. In this study, we used bioinformatics to identify 39 genes encoding SWI/SNF subunit distributed on the 19 chromosomes of soybean. The promoter regions of the genes were enriched with several cis-regulatory elements that are responsive to various hormones and stresses. Digital expression profiling and qRT-PCR revealed that most of the SWI/SNF subunit genes were expressed in multiple tissues of soybean and were sensitive to drought stress. Phenotypical, physiological, and molecular genetic analyses revealed that GmLFR1 (Leaf and Flower-Related1) plays a negative role in drought tolerance in soybean and Arabidopsis thaliana. Together, our findings characterize putative components of soybean SWI/SNF complex and indicate possible roles for GmLFR1 in plants under drought stress. This study offers a foundation for comprehensive analyses of soybean SWI/SNF subunit and provides mechanistic insight into the epigenetic regulation of drought tolerance in soybean.

Discovering and prioritizing candidate resistance genes against soybean pests by integrating GWAS and gene coexpression networks

Soybean is one of the most important legume crops worldwide. Soybean pests have a considerable impact on crop yield. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate resistance genes against the insects Aphis glycines and Spodoptera litura, and the nematode Heterodera glycines. We identified 171, 7, and 228 high-confidence candidate resistance genes against A. glycines, S. litura, and H. glycines, respectively. We found some overlap of candidate genes between insect species, but not between insects and H. glycines. Although 15% of the prioritized candidate genes encode proteins of unknown function, the vast majority of the candidates are related to plant immunity processes, such as transcriptional regulation, signaling, oxidative stress, recognition, and physical defense. Based on the number of resistance alleles, we selected the ten most promising accessions against each pest species in the soybean USDA germplasm. The most resistant accessions do not reach the maximum theoretical resistance potential, indicating that they might be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression networks we inferred in this work are available in a user-friendly web application (https://soypestgcn.venanciogroup.uenf.br/) and an R/Shiny package (https://github.com/almeidasilvaf/SoyPestGCN) that serve as a public resource to explore soybean-pest interactions at the transcriptional level.

Multi-omics assisted breeding for biotic stress resistance in soybean

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

Developmental dynamic transcriptome and systematic analysis reveal the major genes underlying isoflavone accumulation in soybean

INTRODUCTION

Soy isoflavone, a class of polyphenolic compounds exclusively occurred in legumes, is an important bioactive compound for both plants and human beings. The outline of isoflavones biosynthesis pathway has been drawn up basically in the previous research. However, research on the subject has been mostly restricted to investigate the static regulation of isoflavone content in soybean, rather than characterize its dynamic variation and modulation network in developing seeds.

METHODS

In this study, by using eight recombinant inbred lines (RIL), the contents of six isoflavone components in the different stages of developing soybean seeds were determined to characterize the dynamic variation of isoflavones, and the isoflavones accumulation pattern at physiological level was investigated. Meanwhile, we integrated and analyzed the whole genome expression profile of four lines and 42 meta-transcriptome data, based on the multiple algorithms.

RESULTS

This study: 1) obtained 4 molecular modules strongly correlated with isoflavone accumulation; 2) identified 28 novel major genes that could affect the accumulation of isoflavones in developing seeds free from the limitation of environments; 3) discussed the dynamic molecular patterns regulating isoflavones accumulation in developing seed; 4) expanded the isoflavone biosynthesis pathway.

DISCUSSION

The results not only promote the understandings on the biosynthesis and regulation of isoflavones at physiological and molecular level, but also facilitate to breed elite soybean cultivars with high isoflavone contents.

Flagellin and mannitol modulate callose biosynthesis and deposition in soybean seedlings

Callose is a polymer deposited on the cell wall and is necessary for plant growth and development. Callose is synthesized by genes from the glucan synthase-like family (GSL) and dynamically responds to various types of stress. Callose can inhibit pathogenic infection, in the case of biotic stresses, and maintain cell turgor and stiffen the plant cell wall in abiotic stresses. Here, we report the identification of 23 GSL genes (GmGSL) in the soybean genome. We performed phylogenetic analyses, gene structure prediction, duplication patterns, and expression profiles on several RNA-Seq libraries. Our analyses show that WGD/Segmental duplication contributed to expanding this gene family in soybean. Next, we analyzed the callose responses in soybean under abiotic and biotic stresses. The data show that callose is induced by both osmotic stress and flagellin 22 (flg22) and is related to the activity of β-1,3-glucanases. By using RT-qPCR, we evaluated the expression of GSL genes during the treatment of soybean roots with mannitol and flg22. The GmGSL23 gene was upregulated in seedlings treated with osmotic stress or flg22, showing the essential role of this gene in the soybean defense response to pathogenic organisms and osmotic stress. Our results provide an important understanding of the role of callose deposition and regulation of GSL genes in response to osmotic stress and flg22 infection in soybean seedlings.

GmMPK6 Positively Regulates Salt Tolerance through Induction of GmRbohI1 in Soybean

Salt stress is a critical environmental stress that impairs plant growth and development, especially in crop productivity; therefore, understanding the salt response in plants is the basis for their development of salt tolerance. Under salinity, soybean mitogen-activated protein kinase 6 (GmMPK6) is activated and positively regulates reactive oxygen species (ROS) generation. However, it is not yet elucidated how GmMPK6 regulates ROS generation and its role in salt tolerance. Here, we show that GmMPK6, solely activated in NaCl treatment, and gene expression of GmRbohI1 was not only reduced by MPK inhibitor SB202190 in NaCl treatment, but also increased in a GMKK1-expressing protoplast. Furthermore, SB202190 and the NADPH-oxidase inhibitor, diphenyleneiodonium chloride, increased susceptibility to salt stress. The expression of GmRD19A was induced by NaCl treatment, but this expression was compromised by SB202190. Consequently, we revealed that GmMPK6 induces ROS generation through the transcriptional regulation of GmRbohI1 and increases salt tolerance in soybean.

Genome-Wide Identification and Expression Analysis of the Ammonium Transporter Family Genes in Soybean

Ammonium transporters (AMTs) are responsible for ammonium absorption and utilization in plants. As a high-nitrogen-demand crop and a legume, soybean can also obtain ammonium from symbiotic root nodules in which nitrogen-fixing rhizobia convert atmospheric nitrogen (N₂) into ammonium. Although increasing evidence implicates vital roles of ammonium transport in soybean, no systematic analyses of AMTs in soybean (named GmAMTs) or functional analyses of GmAMTs are available. In this study, we aimed to identify all GmAMT family genes and gain a better understanding of the characteristics of GmAMT genes in soybean. Here, due to the improved genome assembly and annotation of soybean, we tried to generate a phylogenetic tree of 16 GmAMTs based on new information. Consistent with reported data, GmAMT family members can be divided into two subfamilies of GmAMT1 (6 genes) and GmAMT2 (10 genes). Interestingly, unlike Arabidopsis, which has only one AMT2, soybean has substantially increased the number of GmAMT2s, suggesting enhanced demand for ammonium transport. These genes were distributed on nine chromosomes, of which GmAMT1.3, GmAMT1.4, and GmAMT1.5 were three tandem repeat genes. The gene structures and conserved protein motifs of the GmAMT1 and GmAMT2 subfamilies were different. All the GmAMTs were membrane proteins with varying numbers of transmembrane domains ranging from 4 to 11. Promoter analysis found that these GmAMT genes have phytohormone-, circadian control-, and organ expression-related cis-elements in their promoters, and notably, there were nodulation-specific and nitrogen-responsive elements in the promoters of the GmAMT1 and GmAMT2 genes. Further expression data showed that these GmAMT family genes exhibited different spatiotemporal expression patterns across tissues and organs. In addition, GmAMT1.1, GmAMT1.2, GmAMT2.2, and GmAMT2.3 were responsive to nitrogen treatment, while GmAMT1.2, GmAMT1.3, GmAMT1.4, GmAMT1.5, GmAMT1.6, GmAMT2.1, GmAMT2.2, GmAMT2.3, GmAMT3.1, and GmAMT4.6 showed circadian rhythms in transcription. RT-qPCR validated the expression patterns of GmAMTs in response to different forms of nitrogen and exogenous ABA treatments. Gene expression analysis also confirmed that GmAMTs are regulated by key nodulation gene GmNINa, indicating a role of GmAMTs in symbiosis. Together, these data indicate that GmAMTs may differentially and/or redundantly regulate ammonium transport during plant development and in response to environmental factors. These findings provide a basis for future research on the functions of GmAMTs and the mechanisms through which GmAMTs regulate ammonium metabolism and nodulation in soybean.

Identification of QTN-by-environment interactions and their candidate genes for soybean seed oil-related traits using 3VmrMLM

INTRODUCTION

Although seed oil content and its fatty acid compositions in soybean were affected by environment, QTN-by-environment (QEIs) and gene-by-environment interactions (GEIs) were rarely reported in genome-wide association studies.

METHODS

The 3VmrMLM method was used to associate the trait phenotypes, measured in five to seven environments, of 286 soybean accessions with 106,013 SNPs for detecting QTNs and QEIs.

RESULTS

Seven oil metabolism genes (GmSACPD-A, GmSACPD-B, GmbZIP123, GmSWEET39, GmFATB1A, GmDGAT2D, and GmDGAT1B) around 598 QTNs and one oil metabolism gene GmFATB2B around 54 QEIs were verified in previous studies; 76 candidate genes and 66 candidate GEIs were predicted to be associated with these traits, in which 5 genes around QEIs were verified in other species to participate in oil metabolism, and had differential expression across environments. These genes were found to be related to soybean seed oil content in haplotype analysis. In addition, most candidate GEIs were co-expressed with drought response genes in co-expression network, and three KEGG pathways which respond to drought were enriched under drought stress rather than control condition; six candidate genes were hub genes in the co-expression networks under drought stress.

DISCUSSION

The above results indicated that GEIs, together with drought response genes in co-expression network, may respond to drought, and play important roles in regulating seed oil-related traits together with oil metabolism genes. These results provide important information for genetic basis, molecular mechanisms, and soybean breeding for seed oil-related traits.

Wildsoydb DataHub: a platform for accessing soybean multiomic datasets across multiple reference genomes

The Wildsoydb DataHub is an integrated interface for biologists and breeders to access soybean genomic resources easily, allowing them to fully utilize the results of genomic research.

A natural uORF variant confers phosphorus acquisition diversity in soybean

Phosphorus (P) is an essential element for all organisms. Because P fertilizers are a non-renewable resource and high fixation in soils, sustainable agriculture requires researchers to improve crop P acquisition efficiency. Here, we report a strong association signal at a locus of CPU1 (component of phosphorus uptake 1), from a genome-wide association study of P acquisition efficiency in a soybean core collection grown in the field. A SEC12-like gene, GmPHF1, is identified as the causal gene for CPU1. GmPHF1 facilitates the ER (endoplasmic reticulum) exit of the phosphate transporter, GmPT4, to the plasma membrane of root epidermal cells. A common SNP in an upstream open reading frame (uORF) of GmPHF1, which alters the abundance of GmPHF1 in a tissue-specific manner, contributes to P acquisition diversity in soybean. A natural genetic variation conditions diversity in soybean P acquisition, which can be used to develop P-efficient soybean genotypes.

Characterization of two constitutive promoters RPS28 and EIF1 for studying soybean growth, development, and symbiotic nodule development

Native promoters that can drive high and stable transgene expression are important tools for modifying plant traits. Although several such promoters have been reported in soybean (Glycine max), few of them function at multiple growth and development stages and during nodule development. Here, we report that the promoters of 40S RIBOSOMAL PROTEIN SMALL SUBUNIT S28 (RPS28) and EUKARYOTIC TRANSLATION INITIATION FACTOR 1 (EIF1) are ideal for high expression of transgene. Through bioinformatic analysis, we determined that RPS28 and EIF1 were highly expressed during soybean growth and development, nodule development, and various biotic and abiotic stresses. Fusion of both RPS28 and EIF1 promoters, with or without their first intron, with the reporter gene β-GLUCURONIDASE (uidA) in transgenic soybean, resulted in high GUS activity in seedlings, seeds, and nodules. Fluorimetric GUS assays showed that the RPS28 promoter and the EIF1 promoter yielded high expression, comparable to the soybean Ubiquitin (GmUbi) promoter. RPS28 and EIF1 promoters were also highly expressed in Arabidopsis thaliana and Nicotiana benthamiana. Our results indicate the potential of RPS28 and EIF1 promoters to facilitate future genetic engineering and breeding to improve the quality and yield of soybean, as well as in a wide variety of other plant species.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-022-00073-6.

Methyl-CpG binding proteins (MBD) family evolution and conservation in plants

DNA methylation is an epigenetic mechanism that acts on cytosine residues. The methyl-CpG-binding domain proteins (MBD) are involved in the recognition of methyl-cytosines by activating a signaling cascade that induces the formation of heterochromatin or euchromatin, thereby regulating gene expression. In this study, we analyzed the evolution and conservation of MBD proteins in plants. First, we performed a genome-wide identification and analysis of the MBD family in common bean and soybean, since they have experienced one and two whole-genome duplication events, respectively. We found one pair of MBD paralogs in soybean (GmMBD2) has subfunctionalized after their recent divergence, which was corroborated with their expression profile. Phylogenetic analysis revealed that classes of MBD proteins clustered with human MBD. Interestingly, the MBD9 may have emerged after the hexaploidization event in eudicots. We found that plants and humans share a great similarity in MBDs' binding affinity in the mCpG context. MBD2 and MBD4 from different plant species have the conserved four amino acid residues -Arg (R), Asp (D), Tyr (Y) and Arg (R)- reported to be responsible for MBD-binding in the mCpG. However, MBD8, MBD9, MBD10, and MBD11 underwent substitutions in these residues, suggesting the non-interaction in the mCpG context, but a heterochromatin association as MBD5 and MBD6 from human. This study represents the first genome-wide analysis of the MBD gene family in eurosids I - soybean and common bean. The data presented here contribute towards understanding the evolution of MBDs proteins in plants and their specific binding affinity on mCpG site.

Genome-Wide Analysis of DREB Genes Identifies a Novel Salt Tolerance Gene in Wild Soybean (Glycine soja)

Salt stress is a major factor limiting the growth and yield of soybean (Glycine max). Wild soybeans (Glycine soja) contain high allelic diversity and beneficial alleles that can be re-introduced into domesticated soybeans to improve adaption to the environment. However, very few beneficial alleles have been identified from wild soybean. Here, we demonstrate that wild soybean is more salt tolerant than cultivated soybean and examine dehydration responsive element-binding (DREB) family transcription factor genes to look for advantageous alleles that might improve drought tolerance in cultivated soybean. Our genome-wide analysis identified 103 DREB genes from the Glycine max genome. By combined RNA-sequencing and population genetics of wild, landrace, and cultivated soybean accessions, we show that the natural variation in DREB3a and DREB3b is related to differences in salt tolerance in soybean accessions. Interestingly, DREB3b, but not DREB3a, appears to have undergone artificial selection. Soybean plants carrying the wild soybean DREB3b allele (DREB3b^39Del ) are more salt tolerant than those containing the reference genome allele (DREB3b^Ref ). Together, our results suggest that the loss of the DREB3b^39Del allele through domestication of cultivated soybean may be associated with a reduction in salt tolerance. Our findings provide crucial information for improving salt tolerance in soybean through molecular breeding.

Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model

Plant tissues are distinguished by their gene expression patterns, which can help identify tissue-specific highly expressed genes and their differential functional modules. For this purpose, large-scale soybean transcriptome samples were collected and processed starting from raw sequencing reads in a uniform analysis pipeline. To address the gene expression heterogeneity in different tissues, we utilized an adversarial deconfounding autoencoder (AD-AE) model to map gene expressions into a latent space and adapted a standard unsupervised autoencoder (AE) model to help effectively extract meaningful biological signals from the noisy data. As a result, four groups of 1,743, 914, 2,107, and 1,451 genes were found highly expressed specifically in leaf, root, seed and nodule tissues, respectively. To obtain key transcription factors (TFs), hub genes and their functional modules in each tissue, we constructed tissue-specific gene regulatory networks (GRNs), and differential correlation networks by using corrected and compressed gene expression data. We validated our results from the literature and gene enrichment analysis, which confirmed many identified tissue-specific genes. Our study represents the largest gene expression analysis in soybean tissues to date. It provides valuable targets for tissue-specific research and helps uncover broader biological patterns. Code is publicly available with open source at https://github.com/LingtaoSu/SoyMeta.

Progress in soybean functional genomics over the past decade

Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

Pathogenesis-related protein 1 (PR-1) genes in soybean: Genome-wide identification, structural analysis and expression profiling under multiple biotic and abiotic stresses

Plant pathogenesis-related (PR) proteins are a large group of proteins, classified in 17 families, that are induced by pathological conditions. Here, we characterized the soybean PR-1 (GmPR-1) gene repertoire at the sequence, structural and expression levels. We found 24 GmPR-1 genes, clustered in two phylogenetic groups. GmPR-1 genes are under strong purifying selection, particularly those that emerged by tandem duplications. GmPR-1 promoter regions are abundant in cis-regulatory elements associated with major stress-related transcription factor families, namely WRKY, ERF, HD-Zip, C2H2, NAC, and GATA. We observed that 23 GmPR-1 genes are induced by stress conditions or exclusively expressed upon stress. We explored 1972 transcriptome samples, including 26 stress conditions, revealing that most GmPR-1 genes are differentially expressed in a plethora of biotic and abiotic stresses. Our findings highlight stress-responsive GmPR-1 genes with potential biotechnological applications, such as the development of transgenic lines with increased resistance to biotic and abiotic stresses.

Pathogenesis-related protein 1 (PR-1) genes in soybean: Genome-wide identification, structural analysis and expression profiling under multiple biotic and abiotic stresses

Plant pathogenesis-related (PR) proteins are a large group of proteins, classified in 17 families, that are induced by pathological conditions. Here, we characterized the soybean PR-1 (GmPR-1) gene repertoire at the sequence, structural and expression levels. We found 24 GmPR-1 genes, clustered in two phylogenetic groups. GmPR-1 genes are under strong purifying selection, particularly those that emerged by tandem duplications. GmPR-1 promoter regions are abundant in cis-regulatory elements associated with major stress-related transcription factor families, namely WRKY, ERF, HD-Zip, C2H2, NAC, and GATA. We observed that 23 GmPR-1 genes are induced by stress conditions or exclusively expressed upon stress. We explored 1972 transcriptome samples, including 26 stress conditions, revealing that most GmPR-1 genes are differentially expressed in a plethora of biotic and abiotic stresses. Our findings highlight stress-responsive GmPR-1 genes with potential biotechnological applications, such as the development of transgenic lines with increased resistance to biotic and abiotic stresses.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement

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Due to reduced diversity, it is essential to map domesticated and improved genes.

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13 known and 442 candidate genes were mined for seed size- and oil-related traits.

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All the genes were used to explain trait changes in domestication and improvement.

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56 domesticated and 15 improved genes may be valuable for future soybean breeding.

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This study provides useful gene resources for future breeding and biology research.

To address domestication and improvement studies of soybean seed size- and oil-related traits, a series of domesticated and improved regions, loci, and candidate genes were identified in 286 soybean accessions using domestication and improvement analyses, genome-wide association studies, quantitative trait locus (QTL) mapping and bulked segregant analyses in this study. As a result, 534 candidate domestication regions (CDRs) and 458 candidate improvement regions (CIRs) were identified in this study and integrated with those in five and three previous studies, respectively, to obtain 952 CDRs and 538 CIRs; 1469 loci for soybean seed size- and oil-related traits were identified in this study and integrated with those in Soybase to obtain 433 QTL clusters. The two results were intersected to obtain 245 domestication and 221 improvement loci for the above traits. Around these trait-related domestication and improvement loci, 7 domestication and 7 improvement genes were found to be truly associated with these traits, and 372 candidate domestication and 87 candidate improvement genes were identified using gene expression, SNP variants in genome, miRNA binding, KEGG pathway, DNA methylation, and haplotype analysis. These genes were used to explain the trait changes in domestication and improvement. As a result, the trait changes can be explained by their frequencies of elite haplotypes, base mutations in coding region, and three factors affecting their expression levels. In addition, 56 domestication and 15 improvement genes may be valuable for future soybean breeding. This study can provide useful gene resources for future soybean breeding and molecular biology research.

Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens

Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

The legume-specific transcription factor E1 controls leaf morphology in soybean

BACKGROUND

The leaf is a determinate organ essential for photosynthesis, whose size and shape determine plant architecture and strongly affect agronomic traits. In soybean, the molecular mechanism of leaf development is not well understood. The flowering repressor gene E1, which encodes a legume-specific B3-like protein, is known to be the gene with the largest influence on soybean flowering and maturity. However, knowledge of its potential other functions remains poor.

RESULTS

Here, we identified a novel function of E1 protein in leaf development. Unifoliolate leaves of E1-overexpression (E1-OE) lines were smaller and curlier than those of wild type DongNong 50 (DN50) and Williams 82 (W82). Transverse histological sections showed disorganized cells and significantly elevated palisade tissue number, spongy tissue number, and bulliform cell number in E1-OE lines. Our results indicate that E1 binds to the promoters of the leaf- development-related CINCINNATA (CIN)-like TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factor genes to negatively regulate their expression.

CONCLUSIONS

Our findings identify E1 as an important new factor in soybean leaf development.

Genome-Wide Identification of Soybean ABC Transporters Relate to Aluminum Toxicity

ATP-binding cassette (ABC) transporter proteins are a gene super-family in plants and play vital roles in growth, development, and response to abiotic and biotic stresses. The ABC transporters have been identified in crop plants such as rice and buckwheat, but little is known about them in soybean. Soybean is an important oil crop and is one of the five major crops in the world. In this study, 255 ABC genes that putatively encode ABC transporters were identified from soybean through bioinformatics and then categorized into eight subfamilies, including 7 ABCAs, 52 ABCBs, 48 ABCCs, 5 ABCDs, 1 ABCEs, 10 ABCFs, 111 ABCGs, and 21 ABCIs. Their phylogenetic relationships, gene structure, and gene expression profiles were characterized. Segmental duplication was the main reason for the expansion of the GmABC genes. Ka/Ks analysis suggested that intense purifying selection was accompanied by the evolution of GmABC genes. The genome-wide collinearity of soybean with other species showed that GmABCs were relatively conserved and that collinear ABCs between species may have originated from the same ancestor. Gene expression analysis of GmABCs revealed the distinct expression pattern in different tissues and diverse developmental stages. The candidate genes GmABCB23, GmABCB25, GmABCB48, GmABCB52, GmABCI1, GmABCI5, and GmABCI13 were responsive to Al toxicity. This work on the GmABC gene family provides useful information for future studies on ABC transporters in soybean and potential targets for the cultivation of new germplasm resources of aluminum-tolerant soybean.

A comprehensive RNA-Seq-based gene expression atlas of the summer squash (Cucurbita pepo) provides insights into fruit morphology and ripening mechanisms

BACKGROUND

Summer squash (Cucurbita pepo: Cucurbitaceae) are a popular horticultural crop for which there is insufficient genomic and transcriptomic information. Gene expression atlases are crucial for the identification of genes expressed in different tissues at various plant developmental stages. Here, we present the first comprehensive gene expression atlas for a summer squash cultivar, including transcripts obtained from seeds, shoots, leaf stem, young and developed leaves, male and female flowers, fruits of seven developmental stages, as well as primary and lateral roots.

RESULTS

In total, 27,868 genes and 2352 novel transcripts were annotated from these 16 tissues, with over 18,000 genes common to all tissue groups. Of these, 3812 were identified as housekeeping genes, half of which assigned to known gene ontologies. Flowers, seeds, and young fruits had the largest number of specific genes, whilst intermediate-age fruits the fewest. There also were genes that were differentially expressed in the various tissues, the male flower being the tissue with the most differentially expressed genes in pair-wise comparisons with the remaining tissues, and the leaf stem the least. The largest expression change during fruit development was early on, from female flower to fruit two days after pollination. A weighted correlation network analysis performed on the global gene expression dataset assigned 25,413 genes to 24 coexpression groups, and some of these groups exhibited strong tissue specificity.

CONCLUSIONS

These findings enrich our understanding about the transcriptomic events associated with summer squash development and ripening. This comprehensive gene expression atlas is expected not only to provide a global view of gene expression patterns in all major tissues in C. pepo but to also serve as a valuable resource for functional genomics and gene discovery in Cucurbitaceae.

Genome-Wide Analysis of the COBRA-Like Gene Family Supports Gene Expansion through Whole-Genome Duplication in Soybean (Glycine max)

The COBRA-like (COBL) gene family has been associated with the regulation of cell wall expansion and cellulose deposition. COBL mutants result in reduced levels and disorganized deposition of cellulose causing defects in the cell wall and inhibiting plant development. In this study, we report the identification of 24 COBL genes (GmCOBL) in the soybean genome. Phylogenetic analysis revealed that the COBL proteins are divided into two groups, which differ by about 170 amino acids in the N-terminal region. The GmCOBL genes were heterogeneously distributed in 14 of the 20 soybean chromosomes. This study showed that segmental duplication has contributed significantly to the expansion of the COBL family in soybean during all Glycine-specific whole-genome duplication events. The expression profile revealed that the expression of the paralogous genes is highly variable between organs and tissues of the plant. Only 20% of the paralogous gene pairs showed similar expression patterns. The high expression levels of some GmCOBLs suggest they are likely essential for regulating cell expansion during the whole soybean life cycle. Our comprehensive overview of the COBL gene family in soybean provides useful information for further understanding the evolution and diversification of COBL genes in soybean.

High-Resolution Transcriptome Atlas and Improved Genome Assembly of Common Buckwheat, Fagopyrum esculentum

Common buckwheat (Fagopyrum esculentum) is an important non-cereal grain crop and a prospective component of functional food. Despite this, the genomic resources for this species and for the whole family Polygonaceae, to which it belongs, are scarce. Here, we report the assembly of the buckwheat genome using long-read technology and a high-resolution expression atlas including 46 organs and developmental stages. We found that the buckwheat genome has an extremely high content of transposable elements, including several classes of recently (0.5-1 Mya) multiplied TEs ("transposon burst") and gradually accumulated TEs. The difference in TE content is a major factor contributing to the three-fold increase in the genome size of F. esculentum compared with its sister species F. tataricum. Moreover, we detected the differences in TE content between the wild ancestral subspecies F. esculentum ssp. ancestrale and buckwheat cultivars, suggesting that TE activity accompanied buckwheat domestication. Expression profiling allowed us to test a hypothesis about the genetic control of petaloidy of tepals in buckwheat. We showed that it is not mediated by B-class gene activity, in contrast to the prediction from the ABC model. Based on a survey of expression profiles and phylogenetic analysis, we identified the MYB family transcription factor gene tr_18111 as a potential candidate for the determination of conical cells in buckwheat petaloid tepals. The information on expression patterns has been integrated into the publicly available database TraVA: http://travadb.org/browse/Species=Fesc/. The improved genome assembly and transcriptomic resources will enable research on buckwheat, including practical applications.

Exploring the complexity of soybean (Glycine max) transcriptional regulation using global gene co-expression networks

MAIN CONCLUSION

We report a soybean gene co-expression network built with data from 1284 RNA-Seq experiments, which was used to identify important regulators, modules and to elucidate the fates of gene duplicates. Soybean (Glycine max (L.) Merr.) is one of the most important crops worldwide, constituting a major source of protein and edible oil. Gene co-expression networks (GCN) have been extensively used to study transcriptional regulation and evolution of genes and genomes. Here, we report a soybean GCN using 1284 publicly available RNA-Seq samples from 15 distinct tissues. We found modules that are differentially regulated in specific tissues, comprising processes such as photosynthesis, gluconeogenesis, lignin metabolism, and response to biotic stress. We identified transcription factors among intramodular hubs, which probably integrate different pathways and shape the transcriptional landscape in different conditions. The top hubs for each module tend to encode proteins with critical roles, such as succinate dehydrogenase and RNA polymerase subunits. Importantly, gene essentiality was strongly correlated with degree centrality and essential hubs were enriched in genes involved in nucleic acids metabolism and regulation of cell replication. Using a guilt-by-association approach, we predicted functions for 93 of 106 hubs without functional description in soybean. Most of the duplicated genes had different transcriptional profiles, supporting their functional divergence, although paralogs originating from whole-genome duplications (WGD) are more often preserved in the same module than those from other mechanisms. Together, our results highlight the importance of GCN analysis in unraveling key functional aspects of the soybean genome, in particular those associated with hub genes and WGD events.

MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information

The rapid assignment of genotypes to phenotypes has been a historically challenging process. The discovery of genes encoding biosynthetic pathway enzymes for defined plant specialized metabolites has been informed and accelerated by the detection of gene clusters. Unfortunately, biosynthetic pathway genes are commonly dispersed across chromosomes or reside in genes clusters that provide little predictive value. More reliably, transcript abundance of genes underlying biochemical pathways for plant specialized metabolites display significant coregulation. By rapidly identifying highly coexpressed transcripts, it is possible to efficiently narrow candidate genes encoding pathway enzymes and more easily predict both functions and functional associations. Mutual Rank (MR)-based coexpression analyses in plants accurately demonstrate functional associations for many specialized metabolic pathways; however, despite the clear predictive value of MR analyses, the application is uncommonly used to drive new pathway discoveries. Moreover, many coexpression databases aid in the prediction of both functional associations and gene functions, but lack customizability for refined hypothesis testing. To facilitate and speed flexible MR-based hypothesis testing, we developed MutRank, an R Shiny web-application for coexpression analyses. MutRank provides an intuitive graphical user interface with multiple customizable features that integrates user-provided data and supporting information suitable for personal computers. Tabular and graphical outputs facilitate the rapid analyses of both unbiased and user-defined coexpression results that accelerate gene function predictions. We highlight the recent utility of MR analyses for functional predictions and discoveries in defining two maize terpenoid antibiotic pathways. Beyond applications in biosynthetic pathway discovery, MutRank provides a simple, customizable and user-friendly interface to enable coexpression analyses relating to a breadth of plant biology inquiries. Data and code are available at GitHub: https://github.com/eporetsky/MutRank.