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Circadian clocks are a great evolutionary innovation and provide competitive advantage during the day/night cycle and under changing environmental conditions. The circadian clock mediates expression of a large proportion of genes in plants, achieving a harmonious relationship between energy metabolism, photosynthesis, and biotic and abiotic stress responses. Here it is shown that multiple paralogues of clock genes are present in soybean (Glycine max) and mediate flooding and drought responses. Differential expression of many clock and SUB1 genes was found under flooding and drought conditions. Furthermore, natural variation in the amplitude and phase shifts in PRR7 and TOC1 genes was also discovered under drought and flooding conditions, respectively. PRR3 exhibited flooding- and drought-specific splicing patterns and may work in concert with PRR7 and TOC1 to achieve energy homeostasis under flooding and drought conditions. Higher expression of TOC1 also coincides with elevated levels of abscisic acid (ABA) and variation in glucose levels in the morning and afternoon, indicating that this response to abiotic stress is mediated by ABA, endogenous sugar levels, and the circadian clock to fine-tune photosynthesis and energy utilization under stress conditions. It is proposed that the presence of multiple clock gene paralogues with variation in DNA sequence, phase, and period could be used to screen exotic germplasm to find sources for drought and flooding tolerance. Furthermore, fine tuning of multiple clock gene paralogues (via a genetic engineering approach) should also facilitate the development of flooding- and drought-tolerant soybean varieties.

Highlight Lipochitooligosaccharide (LCOs) are important molecules for plant-microbe symbiosis but can also serve as plant growth regulators. This study shows that LCO addition induces the expression of genes involved in root growth promotion in C4 grasses., Although lipo-chitooligosaccharides (LCOs) are important signal molecules for plant-symbiont interactions, a number of reports suggest that LCOs can directly impact plant growth and development, separate from any role in plant symbioses. In order to investigate this more closely, maize and Setaria seedlings were treated with LCO and their growth was evaluated. The data indicate that LCO treatment significantly enhanced root growth. RNA-seq transcriptomic analysis of LCO-treated maize roots identified a number of genes whose expression was significantly affected by the treatment. Among these genes, some LCO-up-regulated genes are likely involved in root growth promotion. Interestingly, some stress-related genes were down-regulated after LCO treatment, which might indicate reallocation of resources from defense responses to plant growth. The promoter activity of several LCO-up-regulated genes using a β-glucuronidase reporter system was further analysed. The results showed that the promoters were activated by LCO treatment. The data indicate that LCO can directly impact maize root growth and gene expression.

The OLIGOPEPTIDE TRANSPORTER 3 (OPT3) has recently been identified as a component of the systemic network mediating iron (Fe) deficiency responses in Arabidopsis. Reduced expression of OPT3 induces an over accumulation of Fe in roots and leaves, due in part by an elevated expression of the IRON-REGULATED TRANSPORTER 1 (IRT1). Here we show however, that opt3 leaves display a transcriptional program consistent with an Fe overload, suggesting that Fe excess is properly sensed in opt3 leaves and that the OPT3-mediated shoot-to-root signaling is critical to prevent a systemic Fe overload. We also took advantage of the tissue-specific localization of OPT3, together with other Fe-responsive genes, to determine the timing and location of early transcriptional events during Fe limitation and re-supply. Our results show that the leaf vasculature responds more rapidly than roots to both Fe deprivation and re-supply, suggesting that the leaf vasculature is within the first tissues that sense and respond to changes in Fe availability. Our data highlight the importance of the leaf vasculature in Fe homeostasis by sensing changes in apoplastic levels of Fe coming tough the xylem and relaying back this information to roots via the phloem to regulate Fe uptake at the root level.

Nuclear factor-Y (NF-Y), a heterotrimeric transcription factor, is composed of NF-YA, NF-YB and NF-YC proteins. In plants, there are usually more than 10 genes for each family and their members have been identified to be key regulators in many developmental and physiological processes controlling gametogenesis, embryogenesis, nodule development, seed development, abscisic acid (ABA) signaling, flowering time, primary root elongation, blue light responses, endoplasmic reticulum (ER) stress response and drought tolerance. Taking the advantages of the recent soybean genome draft and information on functional characterizations of nuclear factor Y (NF-Y) transcription factor family in plants, we identified 21 GmNF-YA, 32 GmNF-YB, and 15 GmNF-YC genes in the soybean (Glycine max) genome. Phylogenetic analyses show that soybean’s proteins share strong homology to Arabidopsis and many of them are closely related to functionally characterized NF-Y in plants. Expression analysis in various tissues of flower, leaf, root, seeds of different developmental stages, root hairs under rhizobium inoculation, and drought-treated roots and leaves revealed that certain groups of soybean NF-Y are likely involved in specific developmental and stress responses. This study provides extensive evaluation of the soybean NF-Y family and is particularly useful for further functional characterization of GmNF-Y proteins in seed development, nodulation and drought adaptation of soybean. Electronic supplementary material The online version of this article (doi:10.1007/s00438-014-0978-2) contains supplementary material, which is available to authorized users.

Microbe-associated molecular pattern (MAMP)-triggered immunity (MTI) is an important component of the plant innate immunity response to invading pathogens. Although several MTI responses can be measured in different plant species, their magnitude is probably plant species specific and even cultivar specific. In this study, a genome-wide transcriptome analysis of two soybean parental lines and two progeny lines treated for 30 min with the MAMPs flg22 and chitin was carried out. This analysis revealed a clear variation in gene expression, under both untreated and flg22+chitin-treated conditions. In addition, genes with potential additive and non-additive effects were identified in the two progeny lines, with several of these genes having a potential function in the control of innate immunity. The data presented herein represent the basis for further functional analysis that can lead to a better understanding of the soybean innate immunity response.

A transcriptomic analysis of bacteroids isolated from soybean plants inoculated with B. japonicum USDA 110, relative to cells cultured in HM-arabinose medium was performed and the results combined with two other transcriptomic analyses to form a reiterated pool of transcripts that define genes expressed during symbiotic nitrogen fixation. The majority of annotated genes represented in the reiterated transcript pool with increased expression had already been identified by prior experimentation demonstrating the validity of the reiterated transcript approach. The majority of all reiterated transcripts with increased expression in bacteroids were hypothetical genes suggesting many symbiotic processes have yet to be identified. Genes for carbon metabolism, amino acid metabolism, energy metabolism and transport genes were represented by only a few reiterated transcripts suggesting these annotated processes do not participate in symbiosis, are masked by experimental conditions, or are fulfilled by hypothetical/unknown genes. Bioinformatic analysis revealed a statistically significant bias of the AG content of the reiterated transcripts with increased expression. A DNA motif identified in the reiterated transcripts with decreased expression was found preceding malate dehydrogenase (bll0456) and demonstrated to perform a role in expression of the gene.

Background: Idiopathic nephrotic syndrome (INS) is a common childhood renal disease characterized by a remitting and relapsing course, associated with different histopathological subtypes. The true incidence of various histopathological subtypes of NS remains under estimated owing to the diversity in indication criteria for performing renal biopsies in pediatric population.Methods: This was a cross-sectional observational study in children with nephrotic syndrome at a tertiary health care centre. Total 22 children, with nephrotic syndrome, who underwent renal biopsy procedure during a period of one year, were enrolled for the study. Indications of renal biopsy were noted, and the histopathology reports were studied in detail.Results: In this study group, the most common indication for renal biopsy was “Atypical age (> 8years) of diagnosis in 45.5% (10/22) patients, followed by 22.7% (5/22) in “Children presenting with hypertension and hematuria”.The most common histopathological finding in these children was mesangial proliferative glomerulonephritis in 45.5% (10/22) patients followed by IgA nephropathy with mesangial proliferation in 22.72% (5/22) and minimal change disease in only 13.6% (3/22).Conclusions: This study highlights the occurrence of non-MCD as the common cause of INS in the children and denotes the significance of performing renal biopsies in children with INS for better prognostication.

Cytosine DNA methylation is one avenue for passing information through cell divisions. Here, we present epigenomic analyses of soybean recombinant inbred lines (RILs) and their parents. Identification of differentially methylated regions (DMRs) revealed that DMRs mostly cosegregated with the genotype from which they were derived, but examples of the uncoupling of genotype and epigenotype were identified. Linkage mapping of methylation states assessed from whole-genome bisulfite sequencing of 83 RILs uncovered widespread evidence for local methylQTL. This epigenomics approach provides a comprehensive study of the patterns and heritability of methylation variants in a complex genetic population over multiple generations, paving the way for understanding how methylation variants contribute to phenotypic variation.

Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for bridging the gap between soybean translational genomics and molecular breeding. It provides information for six entities including genes/proteins, microRNAs (miRNAs)/small interfering RNAs (sRNA), metabolites, single nucleotide polymorphisms (SNPs), and plant introduction lines and traits. It has a user-friendly web interface publicly available at http://soykb.org , which integrates and presents data in an intuitive manner to the soybean researchers, breeders, and consumers. It incorporates several informatics and analytical tools for integrating and merging various multi-omics datasets.

Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for bridging the gap between soybean translational genomics and molecular breeding. It provides information for six entities including genes/proteins, microRNAs (miRNAs)/small interfering RNAs (sRNA), metabolites, single nucleotide polymorphisms (SNPs), and plant introduction lines and traits. It has a user-friendly web interface publicly available at http://soykb.org , which integrates and presents data in an intuitive manner to the soybean researchers, breeders, and consumers. It incorporates several informatics and analytical tools for integrating and merging various multi-omics datasets.

Background With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed “PGen”, an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way. Results We have developed both a Linux version in GitHub (https://github.com/pegasus-isi/PGen-GenomicVariations-Workflow) and a web-based implementation of the PGen workflow integrated within the Soybean Knowledge Base (SoyKB), (http://soykb.org/Pegasus/index.php). Using PGen, we identified 10,218,140 single-nucleotide polymorphisms (SNPs) and 1,398,982 indels from analysis of 106 soybean lines sequenced at 15X coverage. 297,245 non-synonymous SNPs and 3330 copy number variation (CNV) regions were identified from this analysis. SNPs identified using PGen from additional soybean resequencing projects adding to 500+ soybean germplasm lines in total have been integrated. These SNPs are being utilized for trait improvement using genotype to phenotype prediction approaches developed in-house. In order to browse and access NGS data easily, we have also developed an NGS resequencing data browser (http://soykb.org/NGS_Resequence/NGS_index.php) within SoyKB to provide easy access to SNP and downstream analysis results for soybean researchers. Conclusion PGen workflow has been optimized for the most efficient analysis of soybean data using thorough testing and validation. This research serves as an example of best practices for development of genomics data analysis workflows by integrating remote HPC resources and efficient data management with ease of use for biological users. PGen workflow can also be easily customized for analysis of data in other species. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1227-y) contains supplementary material, which is available to authorized users.

Plants tolerate water deficits by regulating gene networks controlling cellular and physiological traits to modify growth and development. Transcription factor (TF)-directed regulation of transcription within these gene networks is key to eliciting appropriate responses. In this study, reverse transcription quantitative PCR (RT-qPCR) was used to examine the abundance of 618 transcripts from 536 TF genes in individual root and shoot tissues of maize seedlings grown in vermiculite under well-watered (water potential of -0.02 MPa) and water-deficit conditions (water potentials of -0.3 and -1.6 MPa). A linear mixed model identified 433 TF transcripts representing 392 genes that differed significantly in abundance in at least one treatment, including TFs that intersect growth and development and environmental stress responses. TFs were extensively differentially regulated across stressed maize seedling tissues. Hierarchical clustering revealed TFs with stress-induced increased abundance in primary root tips that likely regulate root growth responses to water deficits, possibly as part of abscisic acid and/or auxin-dependent signaling pathways. Ten of these TFs were selected for validation in nodal root tips of drought-stressed field-grown plants (late V1 to early V2 stage). Changes in abundance of these TF transcripts under a field drought were similar to those observed in the seedling system.

Chromatin modifications, such as cytosine methylation of DNA, play a significant role in mediating gene expression in plants, which affects growth, development, and cell differentiation. As root hairs are single-cell extensions of the root epidermis and the primary organs for water uptake and nutrients, we sought to use root hairs as a single-cell model system to measure the impact of environmental stress. We measured changes in cytosine DNA methylation in single-cell root hairs as compared with multicellular stripped roots, as well as in response to heat stress. Differentially methylated regions (DMRs) in each methylation context showed very distinct methylation patterns between cell types and in response to heat stress. Intriguingly, at normal temperature, root hairs were more hypermethylated than were stripped roots. However, in response to heat stress, both root hairs and stripped roots showed hypomethylation in each context, especially in the CHH context. Moreover, expression analysis of mRNA from similar tissues and treatments identified some associations between DMRs, genes and transposons. Taken together, the data indicate that changes in DNA methylation are directly or indirectly associated with expression of genes and transposons within the context of either specific tissues/cells or stress (heat).

Heat stress is likely to be a key factor in the negative impact of climate change on crop production. Heat stress significantly influences the functions of roots, which provide support, water and nutrients to other plant organs. Likewise, roots play an important role in the establishment of symbiotic associations with different microorganisms. Despite the physiological relevance of roots, few studies have examined their response to heat stress. In this study, we performed genome-wide transcriptomic and proteomic analyses on isolated root hairs, which are a single, epidermal cell type, and compared their response to stripped roots. On average, we identified 1,849 and 3,091 genes differentially regulated in root hairs and stripped roots, respectively, in response to heat stress. Our gene regulatory module analysis identified ten key modules that might control the majority of the transcriptional response to heat stress. We also conducted proteomic analysis on membrane fractions isolated from root hairs and compared these responses to stripped roots. These experiments identified a variety of proteins whose expression changed within 3 hours of application of heat stress. Most of these proteins were predicted to play a significant role in thermo-tolerance, as well as in chromatin remodeling and post-transcriptional regulation. The data presented represent an in-depth analysis of the heat stress response of a single cell type in soybean.

Previous systems analyses in plants have focused on a single developmental stage or time point, although it is often important to additionally consider time-index changes. During seed development a cascade of events occurs within a relatively brief time scale. We have collected protein and transcript expression data from five sequential stages of Arabidopsis (Arabidopsis thaliana) seed development encompassing the period of reserve polymer accumulation. Protein expression profiling employed two-dimensional gel electrophoresis coupled with tandem mass spectrometry, while transcript profiling used oligonucleotide microarrays. Analyses in biological triplicate yielded robust expression information for 523 proteins and 22,746 genes across the five developmental stages, and established 319 protein/transcript pairs for subsequent pattern analysis. General linear modeling was used to evaluate the protein/transcript expression patterns. Overall, application of this statistical assessment technique showed concurrence for a slight majority (56%) of expression pairs. Many specific examples of discordant protein/transcript expression patterns were detected, suggesting that this approach will be useful in revealing examples of posttranscriptional regulation.

The protozoan parasite Leishmania donovani, a causative agent of visceral leishmaniasis, has evolved several strategies to interfere with the immune system and establish persistent infections that are potentially lethal. In this article, we discuss two mechanisms of immune evasion adopted by the parasite: the induction of immune suppressive IL-10 responses and the generation of poor and functionally impaired CD8(+) T-cell responses.

Nodulation is the result of a symbiosis between legumes and rhizobial bacteria in soil. This symbiosis is mutually beneficial, with the bacteria providing a source of nitrogen to the host while the plant supplies carbon to the symbiont. Nodule development is a complex process that is tightly regulated in the host plant cell through networks of gene expression. In order to examine this regulation in detail, a library of quantitative reverse transcription-polymerase chain reaction primer sets was developed for a large number of soybean (Glycine max) putative regulatory genes available in the current expressed sequence tag collection. This library contained primers specific to soybean transcription factor genes as well as genes involved in chromatin modification and translational regulation. Using this library, we analyzed the expression of this gene set during nodule development. A large number of genes were found to be differentially expressed, especially at the later stages of nodule development when active nitrogen fixation was occurring. Expression of these putative regulatory genes was also analyzed in response to the addition of nitrate as a nitrogen source. This comparative analysis identified genes that may be specifically involved in nitrogen assimilation, metabolism, and the maintenance of active nodules. To address this possibility, the expression of one such candidate was studied in more detail by expressing in soybean roots promoter β-glucuronidase and green fluorescent protein fusions. This gene, named Control of Nodule Development (CND), encoded a Myb transcription factor gene. When the CND gene was silenced, nodulation was reduced. These results, associated with a strong expression of the CND gene in the vascular tissues, suggest a role for CND in controlling soybean nodulation.

All eukaryotic organisms have a diversity of transcription factor (TF) gene families, encoding key proteins regulating gene expression. TF families are strongly conserved across eukaryotic organisms, especially plants. The specific function of each of these TF genes is of interest due to their role

Embryo-specific overexpression of biotin carboxyl carrier protein 2 (BCCP2) inhibited plastid acetyl-coenzyme A carboxylase (ACCase), resulting in altered oil, protein, and carbohydrate composition in mature Arabidopsis (Arabidopsis thaliana) seed. To characterize gene and protein regulatory consequences of this mutation, global microarray, two-dimensional difference gel electrophoresis, iTRAQ, and quantitative immunoblotting were performed in parallel. These analyses revealed that (1) transgenic overexpression of BCCP2 did not affect the expression of three other ACCase subunits; (2) four subunits to plastid pyruvate dehydrogenase complex were 25% to 70% down-regulated at protein but not transcript levels; (3) key glycolysis and de novo fatty acid/lipid synthesis enzymes were induced; (4) multiple storage proteins, but not cognate transcripts, were up-regulated; and (5) the biotin synthesis pathway was up-regulated at both transcript and protein levels. Biotin production appears closely matched to endogenous BCCP levels, since overexpression of BCCP2 produced mostly apo-BCCP2 and the resulting ACCase-compromised, low-oil phenotype. Differential expression of glycolysis, plastid pyruvate dehydrogenase complex, fatty acid, and lipid synthesis activities indicate multiple, complex regulatory responses including feedback as well as futile “feed-forward” elicitation in the case of fatty acid and lipid biosynthetic enzymes. Induction of storage proteins reveals that oil and protein synthesis share carbon intermediate(s) and that reducing malonyl-coenzyme A flow into fatty acids diverts carbon into amino acid and protein synthesis.

Interleukin-21 (IL-21) is a recently identified γ-chain receptor cytokine family member that promotes B-cell apoptosis as well as activation of innate immune system. Based on this, we hypothesized that IL-21 might enhance the apoptosis induced by fludarabine and rituximab and also play a role in augmenting immune-mediated clearance of the chronic lymphocytic leukemia (CLL) cells. Our studies demonstrate that the majority of CLL patients have surface IL-21 receptor-α, and its expression correlates with apoptosis, tyrosine phosphorylation of STAT1, and up-regulation of the proapoptotic BH3 domain protein BIM. IL-21–induced BIM up-regulation is critical for apoptosis because inhibition of BIM expression using small interfering RNA prevented IL-21–induced apoptosis. IL-21 treatment of CLL cells but not normal T cells with fludarabine or rituximab additively enhanced the direct cytotoxic effect of these therapies. In addition to its proapoptotic effect, IL-21 promoted STAT1 and STAT5 phosphorylation in natural killer cells with concurrent enhanced antibody-dependent cellular cytotoxicity against rituximab-coated CLL cells in vitro. These data provide justification for combination studies of IL-21 with fludarabine and rituximab in CLL and suggest that BIM up-regulation might serve as relevant pharmacodynamic end point to measure biologic effect of this cytokine in vivo.

Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Background Soybean [Glycine max (L.) Merrill] is one of the most important legumes cultivated worldwide, and Brazil is one of the main producers of this crop. Since the sequencing of its reference genome, interest in structural and allelic variations of cultivated and wild soybean germplasm has grown. To investigate the genetics of the Brazilian soybean germplasm, we selected soybean cultivars based on the year of commercialization, geographical region and maturity group and resequenced their genomes. Results We resequenced the genomes of 28 Brazilian soybean cultivars with an average genome coverage of 14.8X. A total of 5,835,185 single nucleotide polymorphisms (SNPs) and 1,329,844 InDels were identified across the 20 soybean chromosomes, with 541,762 SNPs, 98,922 InDels and 1,093 CNVs that were exclusive to the 28 Brazilian cultivars. In addition, 668 allelic variations of 327 genes were shared among all of the Brazilian cultivars, including genes related to DNA-dependent transcription-elongation, photosynthesis, ATP synthesis-coupled electron transport, cellular respiration, and precursors of metabolite generation and energy. A very homogeneous structure was also observed for the Brazilian soybean germplasm, and we observed 41 regions putatively influenced by positive selection. Finally, we detected 3,880 regions with copy-number variations (CNVs) that could help to explain the divergence among the accessions evaluated. Conclusions The large number of allelic and structural variations identified in this study can be used in marker-assisted selection programs to detect unique SNPs for cultivar fingerprinting. The results presented here suggest that despite the diversification of modern Brazilian cultivars, the soybean germplasm remains very narrow because of the large number of genome regions that exhibit low diversity. These results emphasize the need to introduce new alleles to increase the genetic diversity of the Brazilian germplasm. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2431-x) contains supplementary material, which is available to authorized users.

Background Soybean is a major crop that provides an important source of protein and oil to humans and animals, but its production can be dramatically decreased by the occurrence of drought stress. Soybeans can survive drought stress if there is a robust and deep root system at the early vegetative growth stage. However, little is known about the genome-wide molecular mechanisms contributing to soybean root system architecture. This study was performed to gain knowledge on transcriptome changes and related molecular mechanisms contributing to soybean root development under water limited conditions. Results The soybean Williams 82 genotype was subjected to very mild stress (VMS), mild stress (MS) and severe stress (SS) conditions, as well as recovery from the severe stress after re-watering (SR). In total, 6,609 genes in the roots showed differential expression patterns in response to different water-deficit stress levels. Genes involved in hormone (Auxin/Ethylene), carbohydrate, and cell wall-related metabolism (XTH/lipid/flavonoids/lignin) pathways were differentially regulated in the soybean root system. Several transcription factors (TFs) regulating root growth and responses under varying water-deficit conditions were identified and the expression patterns of six TFs were found to be common across the stress levels. Further analysis on the whole plant level led to the finding of tissue-specific or water-deficit levels specific regulation of transcription factors. Analysis of the over-represented motif of different gene groups revealed several new cis-elements associated with different levels of water deficit. The expression patterns of 18 genes were confirmed byquantitative reverse transcription polymerase chain reaction method and demonstrated the accuracy and effectiveness of RNA-Seq. Conclusions The primary root specific transcriptome in soybean can enable a better understanding of the root response to water deficit conditions. The genes detected in root tissues that were associated with key hormones, carbohydrates, and cell wall-related metabolism could play a vital role in achieving drought tolerance and could be promising candidates for future functional characterization. TFs involved in the soybean root and at the whole plant level could be used for future network analysis between TFs and cis-elements. All of these findings will be helpful in elucidating the molecular mechanisms associated with water stress responses in soybean roots. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2378-y) contains supplementary material, which is available to authorized users.

Summary of the most relevant results from the Gene Ontology (GO) enrichment analysis. (DOCX 117 kb)

Number of non-synonymous InDels identified in important regions of the Brazilian soybean cultivars. All: SNP present in all Brazilian cultivars compared to reference genome; Disruptive + Inframe Del: one codon is changed and one or more codons are deleted; Disruptive + Inframe Ins: one codon is changed and one or many codons are inserted; Inframe Del: one or many codons are deleted; Inframe Ins: one or many codons are inserted; Frame var: insertion or deletion causes a frame shift; Exon loss: a deletion removes the whole exon; Start lost: Variant causes start codon to be mutated into a non-start codon; Stop G.: Variant causes a STOP codon; Stop L.: Variant causes stop codon to be mutated into a non-stop codon; Splice Site A.: The variant hits a splice acceptor site; Splice Site D.: The variant hits a Splice donor site. (DOCX 131 kb)

Sequencing information for the Brazilian soybean lines (DOCX 95 kb)

PGen workflow user guide. This is a PGen user guide file for Linux users. In this file, users will be guided regarding applying for computational resources access and starting PGen workflows using provided sample datasets. Users can prepare their own datasets and run the PGen workflow with their own configurations. (DOCX 27 kb)

Number of SNPs associated to important regions on Brazilian soybean cultivars. All: SNP present in all Brazilian cultivars compared to reference genome; Non-syn cds: non-synonymous SNP inside coding region, Start G.: A variant in 5'UTR region produces a three base sequence that can be a START codon; Start L.: Variant causes start codon to be mutated into a non-start codon; Stop G.: Variant causes a STOP codon; Stop L.: Variant causes stop codon to be mutated into a non-stop codon; Splice Site A.: The variant hits a splice acceptor site; Splice Site D.: The variant hits a Splice donor site. (DOCX 109 kb)

High correlation between RNA-Seq data (X axis) and qRT-PCR data (y axis) using the log2 values for different stress levels. (PPTX 38 kb)

Variant rate details of the Brazilian soybean accessions. (DOCX 54 kb)

Basic description of all Brazilian soybean accessions used in this study. RMG: relative maturity group; Det/Ind: growing development plant; Ind: Indeterminate growing; Det: Determinate growing habit. (DOCX 79 kb)

Our current understanding of plant functional genomics derives primarily from measurements of gene, protein and/or metabolite levels averaged over the whole plant or multicellular tissues. These approaches risk diluting the response of specific cells that might respond strongly to the treatment but whose signal is diluted by the larger proportion of non-responding cells. For example, if a gene is expressed at a low level, does this mean that it is indeed lowly expressed or is it highly expressed, but only in a few cells? In order to avoid these issues, we adopted the soybean root hair cell, derived from a single, differentiated root epidermal cell, as a single-cell model for functional genomics. Root hair cells are intrinsically interesting since they are major conduits for root water and nutrient uptake and are also the preferred site of infection by nitrogen-fixing rhizobium bacteria. Although a variety of other approaches have been used to study single plant cells or single cell types, the root hair system is perhaps unique in allowing application of the full repertoire of functional genomic and biochemical approaches. In this mini review, we summarize our published work and place this within the broader context of root biology, with a significant focus on understanding the initial events in the soybean-rhizobium interaction.

Drought stress causes significant yield losses in major oil seed crops, such as soybean [Glycine max (L.) Merr]. Few soybean lines have been identified as canopy-wilting tolerant; however, the molecular mechanism conferring tolerance is not fully understood. To understand the biological process, a whole genome transcriptome analysis was performed for leaf tissues of two contrasting soybean lines: drought-susceptible (DS) Pana and drought-tolerant (DT) PI 567690. A pairwise comparison of the DS and DT lines under drought and control conditions detected 1914 and 670 genes with a greater than two-fold change in expression under drought conditions. Pairwise treatment comparison and gene enrichment analysis on the DT line showed the down-regulation of genes associated with protein binding, hydrolase activity, carbohydrate/lipid metabolism, xyloglucan endo-transglycosylases associated with cell-wall, apoplast, and chlorophyll a/b binding proteins. On the other hand, genes that were associated with the biotic stress response, ion binding and transport, the oxido-reductive process and electron carrier activity were up-regulated. Gene enrichment analysis detected UDP glucuronosyl transferase activity-encoding genes to be differentially expressed in PI 567690 under drought stress conditions. We found valuable SNPs variation in aquaporin genes of the DT line that are conserved in known slower canopy-wilting lines, this should facilitate marker-assisted selection in soybeans with improved drought tolerance.

Phagocytosis of IgG-coated particles via FcgammaR is accompanied by the generation of superoxide and inflammatory cytokines, which can cause collateral tissue damage in the absence of regulation. Molecular mechanisms regulating these phagocytosis-associated events are not known. SHIP is an inositol phosphatase that downregulates PI3K-mediated activation events. Here, we have examined the role of SHIP in FcgammaR-induced production of superoxide and inflammatory cytokines. We report that primary SHIP-deficient bone marrow macrophages produce elevated levels of superoxide upon FcgammaR clustering. Analysis of the molecular mechanism revealed that SHIP regulates upstream Rac-GTP binding, an obligatory event for superoxide production. Likewise, SHIP-deficient macrophages displayed enhanced IL-1beta and IL-6 production in response to FcgammaR clustering. Interestingly, whereas IL-6 production required activation of both PI3K and Ras/Erk pathways, IL-1beta production was dependent only on Ras/Erk activation, suggesting that SHIP may also regulate the Ras/Erk pathway in macrophages. Consistently, SHIP-deficient macrophages displayed enhanced activation of Erk upon FcgammaR clustering. Inhibition of Ras/Erk or PI3K suppressed the enhanced production of IL-6 in SHIP-deficient macrophages. In contrast, inhibition of Ras/Erk, but not PI3K, suppressed IL-1beta production in these cells. Together, these data demonstrate that SHIP regulates phagocytosis-associated events through the inhibition of PI3K and Ras/Erk pathways.

Background Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most devastating pathogen of soybean. Many gene expression profiling studies have been conducted to investigate the responses of soybean to the infection by this pathogen using primarily the first-generation soybean genome array that covered approximately 37,500 soybean transcripts. However, no study has been reported yet using the second-generation Affymetrix soybean whole-genome transcript array (Soybean WT array) that represents approximately 66,000 predicted soybean transcripts. Results In the present work, the gene expression profiles of two soybean plant introductions (PIs) PI 437654 and PI 567516C (both resistant to multiple SCN HG Types) and cultivar Magellan (susceptible to SCN) were compared in the presence or absence of the SCN inoculum at 3 and 8 days post-inoculation using the Soybean WT array. Data analysis revealed that the two resistant soybean lines showed distinctive gene expression profiles from each other and from Magellan not only in response to the SCN inoculation, but also in the absence of SCN. Overall, 1,413 genes and many pathways were revealed to be differentially regulated. Among them, 297 genes were constitutively regulated in the two resistant lines (compared with Magellan) and 1,146 genes were responsive to the SCN inoculation in the three lines, with 30 genes regulated both constitutively and by SCN. In addition to the findings similar to those in the published work, many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in the present study. GC-rich elements (e.g., GCATGC) were found over-represented in the promoter regions of certain groups of genes. These have not been observed before, and could be new defense-responsive regulatory elements. Conclusions Different soybean lines showed different gene expression profiles in the presence and absence of the SCN inoculum. Both inducible and constitutive gene expression may contribute to resistance to multiple SCN HG Types in the resistant soybean PI lines. Ethylene, protein degradation, and phenylpropanoid pathways, as well as many other pathways reported previously, may play important roles in mediating the soybean-SCN interactions. The revealed genes, pathways, and promoter elements can be further explored to regulate or engineer soybean for resistance to SCN. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1316-8) contains supplementary material, which is available to authorized users.

Background Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja. Results Wild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean. Conclusion Rare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1334-6) contains supplementary material, which is available to authorized users.

Integration of TF ORFeome information into Soykb. On the TF-ORFeome data page in SoyKB (A), clicking a gene of interest will lead to its gene card page (B), where the relevant genomic information (C) and multi-omics expression datasets (D, E) can be browsed.

Odds Table of Epistasis Model 1. Table S2 Odds Table of Epistasis Model 2. Table S3. Odds Table of Epistasis Model 3. Table S4. Odds Table of Epistasis Model 4. Table S5. P(I|Data) in Dependency Model 5 Partition. Table S6. P(I|Data) in Dependency Model 6 Partition. Table S7. P(I|Data) in Dependency Model 7 Partition. Table S8. P(I|Data) in Dependency Model 8 Partition. Figure S1: Statistic power of Model 1 with sample size 2000. Figure S2: Statistic power of Model 1 with sample size 4000. Figure S3: Statistic power of Model 2 with sample size 2000. Figure S4: Statistic power of Model 2 with sample size 4000. Figure S5: Statistic power of Model 3 with sample size 2000. Figure S6: Statistic power of Model 3 with sample size 4000. Figure S7: Statistic power of Model 4 with sample size 5000. Figure S8: Statistic power of Model 4 with sample size 10,000. (DOCX 62 kb)

Background SWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported. Results In the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6. Conclusion Present investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research community and can be extremely valuable for understanding sink unloading and enhancing carbohydrate delivery to developing seeds for improving yield. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1730-y) contains supplementary material, which is available to authorized users.

Three soybean [Glycine max (L) Merr.] small RNA libraries were generated and sequenced using the Illumina platform to examine the role of miRNAs during soybean nodulation. The small RNA libraries were derived from root hairs inoculated with Bradyrhizobium japonicum (In_RH) or mock-inoculated with water (Un_RH), as well as from the comparable inoculated stripped root samples (i.e. inoculated roots with the root hairs removed). Sequencing of these libraries identified a total of 114 miRNAs, including 22 novel miRNAs. A comparison of miRNA abundance among the 114 miRNAs identified 66 miRNAs that were differentially expressed between root hairs and stripped roots, and 48 miRNAs that were differentially regulated in infected root hairs in response to B. japonicum when compared to uninfected root hairs (P ≤ 0.05). A parallel analysis of RNA ends (PARE) library was constructed and sequenced to reveal a total of 405 soybean miRNA targets, with most predicted to encode transcription factors or proteins involved in protein modification, protein degradation and hormone pathways. The roles of gma-miR4416 and gma-miR2606b during nodulation were further analysed. Ectopic expression of these two miRNAs in soybean roots resulted in significant changes in nodule numbers. miRNA target information suggested that gma-miR2606b regulates a Mannosyl-oligosaccharide 1, 2-alpha-mannosidase gene, while gma-miR4416 regulates the expression of a rhizobium-induced peroxidase 1 (RIP1)-like peroxidase gene, GmRIP1, during nodulation.

Background Whole genome sequencing provides the most comprehensive collection of an organism’s genetic information. The availability of complete genome sequences is expected to dramatically deliver a high impact on biology. However, to achieve this impact in the area of crop improvement, significant efforts are still required on functional genomics, including the areas of gene annotation, cloning, expression profiling, and functional validation. Results Here we report our efforts in generating the first transcription factor (TF) open reading frame (ORF)eome resource associated with drought resistance in soybean (Glycine max), a major oil/protein crop grown worldwide. This study provides a highly annotated soybean TF-ORFeome associated with drought resistance. It contains information from experimentally verified protein-coding sequences (CDS), expression profiling under several abiotic stresses (drought, salinity, dehydration and ABA), and computationally predicted protein subcellular localization and cis-regulatory elements (CREs) analysis. All the information is available to plant researchers through a freely accessible and user-friendly database, Soybean Knowledge Base (SoyKB). Conclusions The soybean TF-ORFeome provides a valuable public resource for functional genomics studies, especially in the area of plant abiotic stresses. It will accelerate findings in the areas of abiotic stresses and lead to the generation of crops with enhanced resistance to multiple stresses. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1743-6) contains supplementary material, which is available to authorized users.

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.

Background Glycine max is an economically important crop and many different varieties of soybean exist around the world. The first draft sequences and gene models of G. max (domesticated soybean) as well as G. soja (wild soybean), both became available in 2010. This opened the door for comprehensive comparative genomics studies between the two varieties. Results We have further analysed the sequences and identified the 425 genes that are unique to G. max and unavailable in G. soja. We further studied the genes with significant number of non-synonymous SNPs in their upstream regions. 12 genes involved in seed development, 3 in oil and 6 in protein concentration are unique to G. max. A significant number of unique genes are seen to overlap with the QTL regions of the three traits including seed, oil and protein. We have also developed a graphical chromosome visualizer as part of the Soybean Knowledge Base (SoyKB) tools for molecular breeding, which was used in the analysis and visualization of overlapping QTL regions for multiple traits with the deletions and SNPs in G. soja. Conclusions The comparisons between genome sequences of G. max and G. soja show significant differences between the genomic compositions of the two. The differences also highlight the phenotypic differences between the two in terms of seed development, oil and protein traits. These significant results have been integrated into the SoyKB resource and are publicly available for users to browse at http://soykb.org/GSoja.

Background Current experimental evidence indicates that functionally related genes show coordinated expression in order to perform their cellular functions. In this way, the cell transcriptional machinery can respond optimally to internal or external stimuli. This provides a research opportunity to identify and study co-expressed gene modules whose transcription is controlled by shared gene regulatory networks. Results We developed and integrated a set of computational methods of differential gene expression analysis, gene clustering, gene network inference, gene function prediction, and DNA motif identification to automatically identify differentially co-expressed gene modules, reconstruct their regulatory networks, and validate their correctness. We tested the methods using microarray data derived from soybean cells grown under various stress conditions. Our methods were able to identify 42 coherent gene modules within which average gene expression correlation coefficients are greater than 0.8 and reconstruct their putative regulatory networks. A total of 32 modules and their regulatory networks were further validated by the coherence of predicted gene functions and the consistency of putative transcription factor binding motifs. Approximately half of the 32 modules were partially supported by the literature, which demonstrates that the bioinformatic methods used can help elucidate the molecular responses of soybean cells upon various environmental stresses. Conclusions The bioinformatics methods and genome-wide data sources for gene expression, clustering, regulation, and function analysis were integrated seamlessly into one modular protocol to systematically analyze and infer modules and networks from only differential expression genes in soybean cells grown under stress conditions. Our approach appears to effectively reduce the complexity of the problem, and is sufficiently robust and accurate to generate a rather complete and detailed view of putative soybean gene transcription logic potentially underlying the responses to the various environmental challenges. The same automated method can also be applied to reconstruct differentially co-expressed gene modules and their regulatory networks from gene expression data of any other transcriptome.

Background Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean translational genomics. SoyKB is designed to handle the management and integration of soybean genomics, transcriptomics, proteomics and metabolomics data along with annotation of gene function and biological pathway. It contains information on four entities, namely genes, microRNAs, metabolites and single nucleotide polymorphisms (SNPs). Methods SoyKB has many useful tools such as Affymetrix probe ID search, gene family search, multiple gene/metabolite search supporting co-expression analysis, and protein 3D structure viewer as well as download and upload capacity for experimental data and annotations. It has four tiers of registration, which control different levels of access to public and private data. It allows users of certain levels to share their expertise by adding comments to the data. It has a user-friendly web interface together with genome browser and pathway viewer, which display data in an intuitive manner to the soybean researchers, producers and consumers. Conclusions SoyKB addresses the increasing need of the soybean research community to have a one-stop-shop functional and translational omics web resource for information retrieval and analysis in a user-friendly way. SoyKB can be publicly accessed at http://soykb.org/.