GmGLU1 and GmRR4 contribute to iron deficiency tolerance in soybean.

Iron deficiency chlorosis (IDC) is a form of abiotic stress that negatively impacts soybean yield. In a previous study, we demonstrated that the historical IDC quantitative trait locus (QTL) on soybean chromosome Gm03 was composed of four distinct linkage blocks, each containing candidate genes for IDC tolerance. Here, we take advantage of virus-induced gene silencing (VIGS) to validate the function of three high-priority candidate genes, each corresponding to a different linkage block in the Gm03 IDC QTL. We built three single-gene constructs to target GmGLU1 (GLUTAMATE SYNTHASE 1, Glyma.03G128300), GmRR4 (RESPONSE REGULATOR 4, Glyma.03G130000), and GmbHLH38 (beta Helix Loop Helix 38, Glyma.03G130400 and Glyma.03G130600). Given the polygenic nature of the iron stress tolerance trait, we also silenced the genes in combination. We built two constructs targeting GmRR4+GmGLU1 and GmbHLH38+GmGLU1. All constructs were tested on the iron-efficient soybean genotype Clark grown in iron-sufficient conditions. We observed significant decreases in soil plant analysis development (SPAD) measurements using the GmGLU1 construct and both double constructs, with potential additive effects in the GmRR4+GmGLU1 construct. Whole genome expression analyses (RNA-seq) revealed a wide range of affected processes including known iron stress responses, defense and hormone signaling, photosynthesis, and cell wall structure. These findings highlight the importance of GmGLU1 in soybean iron stress responses and provide evidence that IDC is truly a polygenic trait, with multiple genes within the QTL contributing to IDC tolerance. Finally, we conducted BLAST analyses to demonstrate that the Gm03 IDC QTL is syntenic across a broad range of plant species.

Combining GWAS and comparative genomics to fine map candidate genes for days to flowering in mung bean.

BACKGROUND: Mung bean (Vigna radiata (L.) Wilczek), is an important pulse crop in the global south. Early flowering and maturation are advantageous traits for adaptation to northern and southern latitudes. This study investigates the genetic basis of the Days-to-Flowering trait (DTF) in mung bean, combining genome-wide association studies (GWAS) in mung bean and comparisons with orthologous genes involved with control of DTF responses in soybean (Glycine max (L) Merr) and Arabidopsis (Arabidopsis thaliana). RESULTS: The most significant associations for DTF were on mung bean chromosomes 1, 2, and 4. Only the SNPs on chromosomes 1 and 4 were heavily investigated using downstream analysis. The chromosome 1 DTF association is tightly linked with a cluster of locally duplicated FERONIA (FER) receptor-like protein kinase genes, and the SNP occurs within one of the FERONIA genes. In Arabidopsis, an orthologous FERONIA gene (AT3G51550), has been reported to regulate the expression of the FLOWERING LOCUS C (FLC). For the chromosome 4 DTF locus, the strongest candidates are Vradi04g00002773 and Vradi04g00002778, orthologous to the Arabidopsis PhyA and PIF3 genes, encoding phytochrome A (a photoreceptor protein sensitive to red to far-red light) and phytochrome-interacting factor 3, respectively. The soybean PhyA orthologs include the classical loci E3 and E4 (genes GmPhyA3, Glyma.19G224200, and GmPhyA2, Glyma.20G090000). The mung bean PhyA ortholog has been previously reported as a candidate for DTF in studies conducted in South Korea. CONCLUSION: The top two identified SNPs accounted for a significant proportion (~ 65%) of the phenotypic variability in mung bean DTF by the six significant SNPs (39.61%), with a broad-sense heritability of 0.93. The strong associations of DTF with genes that have orthologs with analogous functions in soybean and Arabidopsis provide strong circumstantial evidence that these genes are causal for this trait. The three reported loci and candidate genes provide useful targets for marker-assisted breeding in mung beans.

Virus induced gene silencing confirms oligogenic inheritance of brown stem rot resistance in soybean.

Brown Stem Rot (BSR), caused by the soil borne fungal pathogen Phialophora gregata, can reduce soybean yields by as much as 38%. Previous allelism studies identified three Resistant to brown stem Rot genes (Rbs1, Rbs2, and Rbs3), all mapping to large, overlapping regions on soybean chromosome 16. However, recent fine-mapping and genome wide association studies (GWAS) suggest Rbs1, Rbs2, and Rbs3 are alleles of a single Rbs locus. To address this conflict, we characterized the Rbs locus using the Williams82 reference genome (Wm82.a4.v1). We identified 120 Receptor-Like Proteins (RLPs), with hallmarks of disease resistance receptor-like proteins (RLPs), which formed five distinct clusters. We developed virus induced gene silencing (VIGS) constructs to target each of the clusters, hypothesizing that silencing the correct RLP cluster would result in a loss of resistance phenotype. The VIGS constructs were tested against P. gregata resistant genotypes L78-4094 (Rbs1), PI 437833 (Rbs2), or PI 437970 (Rbs3), infected with P. gregata or mock infected. No loss of resistance phenotype was observed. We then developed VIGS constructs targeting two RLP clusters with a single construct. Construct B1a/B2 silenced P. gregata resistance in L78-4094, confirming at least two genes confer Rbs1-mediated resistance to P. gregata. Failure of B1a/B2 to silence resistance in PI 437833 and PI 437970 suggests additional genes confer BSR resistance in these lines. To identify differentially expressed genes (DEGs) responding to silencing, we conducted RNA-seq of leaf, stem and root samples from B1a/B2 and empty vector control plants infected with P. gregata or mock infected. B1a/B2 silencing induced DEGs associated with cell wall biogenesis, lipid oxidation, the unfolded protein response and iron homeostasis and repressed numerous DEGs involved in defense and defense signaling. These findings will improve integration of Rbs resistance into elite germplasm and provide novel insights into fungal disease resistance.

Coupling VIGS with Short- and Long-Term Stress Exposure to Understand the Fiskeby III Iron Deficiency Stress Response.

Yield loss due to abiotic stress is an increasing problem in agriculture. Soybean is a major crop for the upper Midwestern United States and calcareous soils exacerbate iron deficiency for growers, resulting in substantial yield losses. Fiskeby III is a soybean variety uniquely resistant to a variety of abiotic stresses, including iron deficiency. Previous studies identified a MATE transporter (Glyma.05G001700) associated with iron stress tolerance in Fiskeby III. To understand the function of this gene in the Fiskeby III response to iron deficiency, we coupled its silencing using virus-induced gene silencing with RNAseq analyses at two timepoints. Analyses of these data confirm a role for the MATE transporter in Fiskeby III iron stress responses. Further, they reveal that Fiskeby III induces transcriptional reprogramming within 24 h of iron deficiency stress, confirming that like other soybean varieties, Fiskeby III is able to quickly respond to stress. However, Fiskeby III utilizes novel genes and pathways in its iron deficiency response. Identifying and characterizing these genes and pathways in Fiskeby III provides novel targets for improving abiotic stress tolerance in elite soybean lines.

Comparing Early Transcriptomic Responses of 18 Soybean (Glycine max) Genotypes to Iron Stress.

Iron deficiency chlorosis (IDC) is an abiotic stress that negatively affects soybean (Glycine max [L.] Merr.) production. Much of our knowledge of IDC stress responses is derived from model plant species. Gene expression, quantitative trait loci (QTL) mapping, and genome-wide association studies (GWAS) performed in soybean suggest that stress response differences exist between model and crop species. Our current understanding of the molecular response to IDC in soybeans is largely derived from gene expression studies using near-isogenic lines differing in iron efficiency. To improve iron efficiency in soybeans and other crops, we need to expand gene expression studies to include the diversity present in germplasm collections. Therefore, we collected 216 purified RNA samples (18 genotypes, two tissue types [leaves and roots], two iron treatments [sufficient and deficient], three replicates) and used RNA sequencing to examine the expression differences of 18 diverse soybean genotypes in response to iron deficiency. We found a rapid response to iron deficiency across genotypes, most responding within 60 min of stress. There was little evidence of an overlap of specific differentially expressed genes, and comparisons of gene ontology terms and transcription factor families suggest the utilization of different pathways in the stress response. These initial findings suggest an untapped genetic potential within the soybean germplasm collection that could be used for the continued improvement of iron efficiency in soybean.

Mining Fiskeby III and Mandarin (Ottawa) Expression Profiles to Understand Iron Stress Tolerant Responses in Soybean.

The soybean (Glycine max L. merr) genotype Fiskeby III is highly resistant to a multitude of abiotic stresses, including iron deficiency, incurring only mild yield loss during stress conditions. Conversely, Mandarin (Ottawa) is highly susceptible to disease and suffers severe phenotypic damage and yield loss when exposed to abiotic stresses such as iron deficiency, a major challenge to soybean production in the northern Midwestern United States. Using RNA-seq, we characterize the transcriptional response to iron deficiency in both Fiskeby III and Mandarin (Ottawa) to better understand abiotic stress tolerance. Previous work by our group identified a quantitative trait locus (QTL) on chromosome 5 associated with Fiskeby III iron efficiency, indicating Fiskeby III utilizes iron deficiency stress mechanisms not previously characterized in soybean. We targeted 10 of the potential candidate genes in the Williams 82 genome sequence associated with the QTL using virus-induced gene silencing. Coupling virus-induced gene silencing with RNA-seq, we identified a single high priority candidate gene with a significant impact on iron deficiency response pathways. Characterization of the Fiskeby III responses to iron stress and the genes underlying the chromosome 5 QTL provides novel targets for improved abiotic stress tolerance in soybean.

Gene Expression Responses to Sequential Nutrient Deficiency Stresses in Soybean.

Throughout the growing season, crops experience a multitude of short periods of various abiotic stresses. These stress events have long-term impacts on plant performance and yield. It is imperative to improve our understanding of the genes and biological processes underlying plant stress tolerance to mitigate end of season yield loss. The majority of studies examining transcriptional changes induced by stress focus on single stress events. Few studies have been performed in model or crop species to examine transcriptional responses of plants exposed to repeated or sequential stress exposure, which better reflect field conditions. In this study, we examine the transcriptional profile of soybean plants exposed to iron deficiency stress followed by phosphate deficiency stress (-Fe-Pi). Comparing this response to previous studies, we identified a core suite of genes conserved across all repeated stress exposures (-Fe-Pi, -Fe-Fe, -Pi-Pi). Additionally, we determined transcriptional response to sequential stress exposure (-Fe-Pi) involves genes usually associated with reproduction, not stress responses. These findings highlight the plasticity of the plant transcriptome and the complexity of unraveling stress response pathways.

Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters.

We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.

Examining Short-Term Responses to a Long-Term Problem: RNA-Seq Analyses of Iron Deficiency Chlorosis Tolerant Soybean.

Iron deficiency chlorosis (IDC) is a global crop production problem, significantly impacting yield. However, most IDC studies have focused on model species, not agronomically important crops. Soybean is the second largest crop grown in the United States, yet the calcareous soils across most of the upper U.S. Midwest limit soybean growth and profitability. To understand early soybean iron stress responses, we conducted whole genome expression analyses (RNA-sequencing) of leaf and root tissue from the iron efficient soybean (Glycine max) cultivar Clark, at 30, 60 and 120 min after transfer to iron stress conditions. We identified over 10,000 differentially expressed genes (DEGs), with the number of DEGs increasing over time in leaves, but decreasing over time in roots. To investigate these responses, we clustered our expression data across time to identify suites of genes, their biological functions, and the transcription factors (TFs) that regulate their expression. These analyses reveal the hallmarks of the soybean iron stress response (iron uptake and homeostasis, defense, and DNA replication and methylation) can be detected within 30 min. Furthermore, they suggest root to shoot signaling initiates early iron stress responses representing a novel paradigm for crop stress adaptations.

Deconstructing the genetic architecture of iron deficiency chlorosis in soybean using genome-wide approaches.

BACKGROUND: Iron (Fe) is an essential micronutrient for plant growth and development. Iron deficiency chlorosis (IDC), caused by calcareous soils or high soil pH, can limit iron availability, negatively affecting soybean (Glycine max) yield. This study leverages genome-wide association study (GWAS) and a genome-wide epistatic study (GWES) with previous gene expression studies to identify regions of the soybean genome important in iron deficiency tolerance. RESULTS: A GWAS and a GWES were performed using 460 diverse soybean PI lines from 27 countries, in field and hydroponic iron stress conditions, using more than 36,000 single nucleotide polymorphism (SNP) markers. Combining this approach with available RNA-sequencing data identified significant markers, genomic regions, and novel genes associated with or responding to iron deficiency. Sixty-nine genomic regions associated with IDC tolerance were identified across 19 chromosomes via the GWAS, including the major-effect quantitative trait locus (QTL) on chromosome Gm03. Cluster analysis of significant SNPs in this region deconstructed this historically prominent QTL into four distinct linkage blocks, enabling the identification of multiple candidate genes for iron chlorosis tolerance. The complementary GWES identified SNPs in this region interacting with nine other genomic regions, providing the first evidence of epistatic interactions impacting iron deficiency tolerance. CONCLUSIONS: This study demonstrates that integrating cutting edge genome wide association (GWA), genome wide epistasis (GWE), and gene expression studies is a powerful strategy to identify novel iron tolerance QTL and candidate loci from diverse germplasm. Crops, unlike model species, have undergone selection for thousands of years, constraining and/or enhancing stress responses. Leveraging genomics-enabled approaches to study these adaptations is essential for future crop improvement.

Dynamic gene expression changes in response to micronutrient, macronutrient, and multiple stress exposures in soybean.

Preserving crop yield is critical for US soybean production and the global economy. Crop species have been selected for increased yield for thousands of years with individual lines selected for improved performance in unique environments, constraints not experienced by model species such as Arabidopsis. This selection likely resulted in novel stress adaptations, unique to crop species. Given that iron deficiency is a perennial problem in the soybean growing regions of the USA and phosphate deficiency looms as a limitation to global agricultural production, nutrient stress studies in crop species are critically important. In this study, we directly compared whole-genome expression responses of leaves and roots to iron (Fe) and phosphate (Pi) deficiency, representing a micronutrient and macronutrient, respectively. Conducting experiments side by side, we observed soybean responds to both nutrient deficiencies within 24 h. While soybean responds largely to -Fe deficiency, it responds strongly to Pi resupply. Though the timing of the responses was different, both nutrient stress signals used the same molecular pathways. Our study is the first to demonstrate the speed and diversity of the soybean stress response to multiple nutrient deficiencies. We also designed the study to examine gene expression changes in response to multiple stress events. We identified 865 and 3375 genes that either altered their direction of expression after a second stress exposure or were only differentially expressed after a second stress event. Understanding the molecular underpinnings of these responses in crop species could have major implications for improving stress tolerance and preserving yield.

Comprehensive mapping of abiotic stress inputs into the soybean circadian clock.

The plant circadian clock evolved to increase fitness by synchronizing physiological processes with environmental oscillations. Crop fitness was artificially selected through domestication and breeding, and the circadian clock was identified by both natural and artificial selections as a key to improved fitness. Despite progress in Arabidopsis, our understanding of the crop circadian clock is still limited, impeding its rational improvement for enhanced fitness. To unveil the interactions between the crop circadian clock and various environmental cues, we comprehensively mapped abiotic stress inputs to the soybean circadian clock using a 2-module discovery pipeline. Using the "molecular timetable" method, we computationally surveyed publicly available abiotic stress-related soybean transcriptomes to identify stresses that have strong impacts on the global rhythm. These findings were then experimentally confirmed using a multiplexed RNA sequencing technology. Specific clock components modulated by each stress were further identified. This comprehensive mapping uncovered inputs to the plant circadian clock such as alkaline stress. Moreover, short-term iron deficiency targeted different clock components in soybean and Arabidopsis and thus had opposite effects on the clocks of these 2 species. Comparing soybean varieties with different iron uptake efficiencies suggests that phase modulation might be a mechanism to alleviate iron deficiency symptoms in soybean. These unique responses in soybean demonstrate the need to directly study crop circadian clocks. Our discovery pipeline may serve as a broadly applicable tool to facilitate these explorations.

Using RNA-seq to characterize responses to 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor herbicide resistance in waterhemp (Amaranthus tuberculatus).

BACKGROUND: Waterhemp (Amaranthus tuberculatus (Moq.) J.D. Sauer) is a problem weed commonly found in the Midwestern United States that can cause crippling yield losses for both maize (Zea mays L.) and soybean (Glycine max L. Merr). In 2011, 4-hydroxyphenylpyruvate-dioxygenase (HPPD, EC 1.13.11.27) inhibitor herbicide resistance was first reported in two waterhemp populations. Since the discovery of HPPD-herbicide resistance, studies have identified the mechanism of resistance and described the inheritance of the herbicide resistance. However, no studies have examined genome-wide gene expression changes in response to herbicide treatment in herbicide resistant and susceptible waterhemp. RESULTS: We conducted RNA-sequencing (RNA-seq) analyses of two waterhemp populations (HPPD-herbicide resistant and susceptible), from herbicide-treated and mock-treated leaf samples at three, six, twelve, and twenty-four hours after treatment (HAT). We performed a de novo transcriptome assembly using all sample sequences. Following assessments of our assembly, individual samples were mapped to the de novo transcriptome allowing us to identify transcripts specific to a genotype, herbicide treatment, or time point. Our results indicate that the response of HPPD-herbicide resistant and susceptible waterhemp genotypes to HPPD-inhibiting herbicide is rapid, established as soon as 3 hours after herbicide treatment. Further, there was little overlap in gene expression between resistant and susceptible genotypes, highlighting dynamic differences in response to herbicide treatment. In addition, we used stringent analytical methods to identify candidate single nucleotide polymorphisms (SNPs) that distinguish the resistant and susceptible genotypes. CONCLUSIONS: The waterhemp transcriptome, herbicide-responsive genes, and SNPs generated in this study provide valuable tools for future studies by numerous plant science communities. This collection of resources is essential to study and understand herbicide effects on gene expression in resistant and susceptible weeds. Understanding how herbicides impact gene expression could allow us to develop novel approaches for future herbicide development. Additionally, an increased understanding of the prolific traits intrinsic in weed success could lead to crop improvement.

Leveraging RNA-Seq to Characterize Resistance to Brown Stem Rot and the Rbs3 Locus in Soybean.

Brown stem rot, caused by the fungus Phialophora gregata, reduces soybean yield by up to 38%. Although three dominant resistance loci have been identified (Rbs1 to Rbs3), the gene networks responsible for pathogen recognition and defense remain unknown. Further, identification and characterization of resistant and susceptible germplasm remains difficult. We conducted RNA-Seq of infected and mock-infected leaf, stem, and root tissues of a resistant (PI 437970, Rbs3) and susceptible (Corsoy 79) genotype. Combining historical mapping data with genotype expression differences allowed us to identify a cluster of receptor-like proteins that are candidates for the Rbs3 resistance gene. Reads mapping to the Rbs3 locus were used to identify potential novel single-nucleotide polymorphisms within candidate genes that could improve phenotyping and breeding efficiency. Comparing responses to infection revealed little overlap in differential gene expression between genotypes or tissues. Gene networks associated with defense, DNA replication, and iron homeostasis are hallmarks of resistance to P. gregata. This novel research demonstrates the utility of combining contrasting genotypes, gene expression, and classical genetic studies to characterize complex disease resistance loci.

Fast neutron-induced structural rearrangements at a soybean NAP1 locus result in gnarled trichomes.

KEY MESSAGE: Three adjacent and distinct sequence rearrangements were identified at a NAP1 locus in a soybean mutant. Genetic dissection and validation revealed the function of this gene in soybean trichome development. A soybean (Glycine max (L.) Merr.) gnarled trichome mutant, exhibiting stunted trichomes compared to wild-type, was identified in a fast neutron mutant population. Genetic mapping using whole genome sequencing-based bulked segregant analysis identified a 26.6 megabase interval on chromosome 20 that co-segregated with the phenotype. Comparative genomic hybridization analysis of the mutant indicated that the chromosome 20 interval included a small structural variant within the coding region of a soybean ortholog (Glyma.20G019300) of Arabidopsis Nck-Associated Protein 1 (NAP1), a regulator of actin nucleation during trichome morphogenesis. Sequence analysis of the candidate allele revealed multiple rearrangements within the coding region, including two deletions (approximately 1-2 kb each), a translocation, and an inversion. Further analyses revealed that the mutant allele perfectly co-segregated with the phenotype, and a wild-type soybean NAP1 transgene functionally complemented an Arabidopsis nap1 mutant. In addition, mapping and exon sequencing of NAP1 in a spontaneous soybean gnarled trichome mutant (T31) identified a frame shift mutation resulting in a truncation of the coding region. These data indicate that the soybean NAP1 gene is essential for proper trichome development and show the utility of the soybean fast neutron population for forward genetic approaches for identifying genes.

Virus-Induced Gene Silencing and Transient Gene Expression in Soybean (Glycine max) Using Bean Pod Mottle Virus Infectious Clones.

Virus-induced gene silencing (VIGS) is a powerful and rapid approach for determining the functions of plant genes. The basis of VIGS is that a viral genome is engineered so that it can carry fragments of plant genes, typically in the 200 to 300 base pair size range. The recombinant viruses are used to infect experimental plants, and wherever the virus invades, the target gene or genes will be silenced. VIGS is thus transient, and in the span of a few weeks, it is possible to design VIGS constructs and then generate loss-of-function phenotypes through RNA silencing of the target genes. In soybean (Glycine max), the Bean pod mottle virus (BPMV) has been engineered to be valuable tool for silencing genes with diverse functions and also for over-expression of foreign genes. This protocol describes a method for designing BPMV constructs and using them to silence or transiently express genes in soybean. © 2016 by John Wiley & Sons, Inc.

Transgene silencing of sucrose synthase in alfalfa (Medicago sativa L.) stem vascular tissue suggests a role for invertase in cell wall cellulose synthesis.

BACKGROUND: Alfalfa (Medicago sativa L.) is a widely adapted perennial forage crop that has high biomass production potential. Enhanced cellulose content in alfalfa stems would increase the value of the crop as a bioenergy feedstock. We examined if increased expression of sucrose synthase (SUS; EC 2.4.1.13) would increase cellulose in stem cell walls. RESULTS: Alfalfa plants were transformed with a truncated alfalfa phosphoenolpyruvate carboxylase gene promoter (PEPC7-P4) fused to an alfalfa nodule-enhanced SUS cDNA (MsSUS1) or the ß-glucuronidase (GUS) gene. Strong GUS expression was detected in xylem and phloem indicating that the PEPC7-P4 promoter was active in stem vascular tissue. In contrast to expectations, MsSUS1 transcript accumulation was reduced 75-90 % in alfalfa plants containing the PEPC7-P4::MsSUS1 transgene compared to controls. Enzyme assays indicated that SUS activity in stems of selected down-regulated transformants was reduced by greater than 95 % compared to the controls. Although SUS activity was detected in xylem and phloem of control plants by in situ enzyme assays, plants with the PEPC7-P4::MsSUS1 transgene lacked detectable SUS activity in post-elongation stem (PES) internodes and had very low SUS activity in elongating stem (ES) internodes. Loss of SUS protein in PES internodes of down-regulated lines was confirmed by immunoblots. Down-regulation of SUS expression and activity in stem tissue resulted in no obvious phenotype or significant change in cell wall sugar composition. However, alkaline/neutral (A/N) invertase activity increased in SUS down-regulated lines and high levels of acid invertase activity were observed. In situ enzyme assays of stem tissue showed localization of neutral invertase in vascular tissues of ES and PES internodes. CONCLUSIONS: These results suggest that invertases play a primary role in providing glucose for cellulose biosynthesis or compensate for the loss of SUS1 activity in stem vascular tissue.

The Medicago sativa gene index 1.2: a web-accessible gene expression atlas for investigating expression differences between Medicago sativa subspecies.

BACKGROUND: Alfalfa (Medicago sativa L.) is the primary forage legume crop species in the United States and plays essential economic and ecological roles in agricultural systems across the country. Modern alfalfa is the result of hybridization between tetraploid M. sativa ssp. sativa and M. sativa ssp. falcata. Due to its large and complex genome, there are few genomic resources available for alfalfa improvement. RESULTS: A de novo transcriptome assembly from two alfalfa subspecies, M. sativa ssp. sativa (B47) and M. sativa ssp. falcata (F56) was developed using Illumina RNA-seq technology. Transcripts from roots, nitrogen-fixing root nodules, leaves, flowers, elongating stem internodes, and post-elongation stem internodes were assembled into the Medicago sativa Gene Index 1.2 (MSGI 1.2) representing 112,626 unique transcript sequences. Nodule-specific and transcripts involved in cell wall biosynthesis were identified. Statistical analyses identified 20,447 transcripts differentially expressed between the two subspecies. Pair-wise comparisons of each tissue combination identified 58,932 sequences differentially expressed in B47 and 69,143 sequences differentially expressed in F56. Comparing transcript abundance in floral tissues of B47 and F56 identified expression differences in sequences involved in anthocyanin and carotenoid synthesis, which determine flower pigmentation. Single nucleotide polymorphisms (SNPs) unique to each M. sativa subspecies (110,241) were identified. CONCLUSIONS: The Medicago sativa Gene Index 1.2 increases the expressed sequence data available for alfalfa by ninefold and can be expanded as additional experiments are performed. The MSGI 1.2 transcriptome sequences, annotations, expression profiles, and SNPs were assembled into the Alfalfa Gene Index and Expression Database (AGED) at http://plantgrn.noble.org/AGED/ , a publicly available genomic resource for alfalfa improvement and legume research.

An RNA-Seq based gene expression atlas of the common bean.

BACKGROUND: Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. RESULTS: Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. CONCLUSIONS: These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.

Legume genomics: understanding biology through DNA and RNA sequencing.

BACKGROUND: The legume family (Leguminosae) consists of approx. 17 000 species. A few of these species, including, but not limited to, Phaseolus vulgaris, Cicer arietinum and Cajanus cajan, are important dietary components, providing protein for approx. 300 million people worldwide. Additional species, including soybean (Glycine max) and alfalfa (Medicago sativa), are important crops utilized mainly in animal feed. In addition, legumes are important contributors to biological nitrogen, forming symbiotic relationships with rhizobia to fix atmospheric N2 and providing up to 30 % of available nitrogen for the next season of crops. The application of high-throughput genomic technologies including genome sequencing projects, genome re-sequencing (DNA-seq) and transcriptome sequencing (RNA-seq) by the legume research community has provided major insights into genome evolution, genomic architecture and domestication. SCOPE AND CONCLUSIONS: This review presents an overview of the current state of legume genomics and explores the role that next-generation sequencing technologies play in advancing legume genomics. The adoption of next-generation sequencing and implementation of associated bioinformatic tools has allowed researchers to turn each species of interest into their own model organism. To illustrate the power of next-generation sequencing, an in-depth overview of the transcriptomes of both soybean and white lupin (Lupinus albus) is provided. The soybean transcriptome focuses on analysing seed development in two near-isogenic lines, examining the role of transporters, oil biosynthesis and nitrogen utilization. The white lupin transcriptome analysis examines how phosphate deficiency alters gene expression patterns, inducing the formation of cluster roots. Such studies illustrate the power of next-generation sequencing and bioinformatic analyses in elucidating the gene networks underlying biological processes.