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Significance The effects of diverse environmental factors on the crop circadian clock have not been systemically studied. We devised a reliable and cost-effective discovery pipeline and demonstrated its feasibility by mapping the abiotic stress “inputome” of the soybean clock. We found that the interfaces between the soybean clock and abiotic stress signals were quite different from those in Arabidopsis. Furthermore, alkaline stress was identified as a circadian clock modulator. These findings highlight the complexity of the soybean clock, which cannot be simply extrapolated from knowledge obtained from Arabidopsis. Our discovery pipeline thus offers a broadly applicable and affordable tool for similar large-scale circadian clock studies in diverse species since it does not rely on transgenic circadian reporters or expensive imaging systems., 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.

Nutrient deficiencies limit growth and yield in many different crop species. The calcareous soils in the upper Midwestern United States favor the development of iron deficiency chlorosis (IDC) in soybean (Glycine max L. Merr.). Even minor symptoms result in end of season yield loss. To identify molecular pathways and networks underlying tolerance to iron deficiency stress in soybean, we leveraged two near isogenic lines (Clark and Isoclark) that differ in their tolerance to iron stress. Clark and Isoclark were grown in hydroponics in one of three treatments: iron sufficient media for ten days, iron deficient media for ten days, or iron sufficient media for eight days followed by transfer to iron deficient media for two days. Following phenotyping, plant tissues were harvested for RNA-seq analysis. To facilitate analyses, we clustered differentially expressed genes across genotypes and timepoints in both roots and leaves. With this experimental design, we could identify iron stress response differences between Clark and Isoclark, evaluate the impact of iron stress duration, and link expression clusters with discrete biological functions and the transcription factor families that regulate them. We identified thousands of differentially expressed genes associated with soybean stress tolerant responses including the cell cycle, gene silencing, iron acquisition, and defense. In Clark, the number of differentially expressed genes and magnitude of expression increased with increasing iron stress duration. In contrast, Isoclark decreased the number and magnitude of differentially expressed genes across time. Differences in gene expression corresponded to phenotypic differences. The shifting expression patterns between timepoints and tissues suggests novel mechanisms for iron stress signaling between source and sink tissues.

The soybean (Glycine max&nbsp, 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.

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.

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. Electronic supplementary material The online version of this article (10.1007/s10142-019-00709-9) contains supplementary material, which is available to authorized users.

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.

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.

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. Electronic supplementary material The online version of this article (10.1186/s12870-019-1795-x) contains supplementary material, which is available to authorized users.

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 WileySons, Inc.

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.

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.

Technological advances coupled with the economic importance of soybean have led to increased efforts to understand gene function and associate genes with phenotypes of agronomic and fundamental interest. Functional genomics approaches aim to develop sufficient understanding needed to bridge the genotype-to-phenotype gap. In general terms, functional genomics approaches begin by using highly parallelized methods to analyze genomes, transcriptomes, proteomes, and metabolomes to generate hypotheses about genes that control phenotypes. Candidate genes are then tested for their contributions to phenotypes through various methods such as RNA silencing, genetic mutation, or overexpression. In this chapter, we review the current approaches, tools, and resources that are being applied for functional genomics research in soybean.

In soybean [Glycine max (L.) Merr.], iron deficiency results in interveinal chlorosis and decreased photosynthetic capacity, leading to stunting and yield loss. In this study, gene expression analyses investigated the role of soybean replication protein A (RPA) subunits during iron stress. Nine RPA homologs were significantly differentially expressed in response to iron stress in the near isogenic lines (NILs) Clark (iron efficient) and Isoclark (iron inefficient). RPA homologs exhibited opposing expression patterns in the two NILs, with RPA expression significantly repressed during iron deficiency in Clark but induced in Isoclark. We used virus induced gene silencing (VIGS) to repress GmRPA3 expression in the iron inefficient line Isoclark and mirror expression in Clark. GmRPA3-silenced plants had improved IDC symptoms and chlorophyll content under iron deficient conditions and also displayed stunted growth regardless of iron availability. RNA-Seq comparing gene expression between GmRPA3-silenced and empty vector plants revealed massive transcriptional reprogramming with differential expression of genes associated with defense, immunity, aging, death, protein modification, protein synthesis, photosynthesis and iron uptake and transport genes. Our findings suggest the iron efficient genotype Clark is able to induce energy controlling pathways, possibly regulated by SnRK1/TOR, to promote nutrient recycling and stress responses in iron deficient conditions.

Phosphorus, in its orthophosphate form (Pi), is one of the most limiting macronutrients in soils for plant growth and development. However, the whole-genome molecular mechanisms contributing to plant acclimation to Pi deficiency remain largely unknown. White lupin (Lupinus albus) has evolved unique adaptations for growth in Pi-deficient soils, including the development of cluster roots to increase root surface area. In this study, we utilized RNA-Seq technology to assess global gene expression in white lupin cluster roots, normal roots, and leaves in response to Pi supply. We de novo assembled 277,224,180 Illumina reads from 12 complementary DNA libraries to build what is to our knowledge the first white lupin gene index (LAGI 1.0). This index contains 125,821 unique sequences with an average length of 1,155 bp. Of these sequences, 50,734 were transcriptionally active (reads per kilobase per million reads ≥ 3), representing approximately 7.8% of the white lupin genome, using the predicted genome size of Lupinus angustifolius as a reference. We identified a total of 2,128 sequences differentially expressed in response to Pi deficiency with a 2-fold or greater change and P ≤ 0.05. Twelve sequences were consistently differentially expressed due to Pi deficiency stress in three species, Arabidopsis (Arabidopsis thaliana), potato (Solanum tuberosum), and white lupin, making them ideal candidates to monitor the Pi status of plants. Additionally, classic physiological experiments were coupled with RNA-Seq data to examine the role of cytokinin and gibberellic acid in Pi deficiency-induced cluster root development. This global gene expression analysis provides new insights into the biochemical and molecular mechanisms involved in the acclimation to Pi deficiency.

Iron deficiency chlorosis (IDC) in soybeans has proven to be a perennial problem in the calcareous soils of the U.S. upper Midwest. A historically difficult trait to study in fields, the use of hydroponics in a controlled greenhouse environment has provided a mechanism to study genetic variation while limiting environmental complications. IDC susceptible plants growing in calcareous soils and in iron-controlled hydroponic experiments often exhibit a characteristic chlorotic phenotype early in the growing season but are able to re-green later in the season. To examine the changes in gene expression of these plants, near-isogenic lines, iron efficient PI548553 (Clark) and iron inefficient PI547430 (IsoClark), developed for their response to iron deficiency stress [USDA, ARS, National Genetic Resources Program, Germplasm Resources Information Network - GRIN. (Online Database) National Germplasm Resources Laboratory, Beltsville, MD, 2004. Available: http://www.ars.grin.gov/cgi-bin/npgs/html/acc_search.pl?accid=PI+547430. [22] were grown in iron-deficient hydroponic conditions for one week, then transferred to iron sufficient conditions for another week. This induced a phenotypic response mimicking the growth of the plants in the field; initial chlorosis followed by re-greening. RNA was isolated from root tissue and transcript profiles were examined between the two near-isogenic lines using publicly available cDNA microarrays. By alleviating the iron deficiency stress our expectation was that plants would return to baseline expression levels. However, the microarray comparison identified four cDNAs that were under-expressed by a two-fold or greater difference in the iron inefficient plant compared to the iron efficient plant. This differential expression was re-examined and confirmed by real time PCR experimentation. Control experiments showed that these genes are not differentially expressed in plants grown continually under iron rich hydroponic conditions. The expression differences suggest potential residual effects of iron deficiency on plant health.

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 β-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. Electronic supplementary material The online version of this article (doi:10.1186/s12870-015-0649-4) contains supplementary material, which is available to authorized users.

Genetic and physical maps illustrate the arrangement of genes and DNA markers on a chromosome. The relative distances between positions on a genetic map are calculated using recombination frequencies, whereas a physical map is based on the actual number of nucleotide pairs between loci. These maps are a key resource for understanding genome organisation. They are the basis for map-based cloning and marker-assisted selection, serving as a bridge between breeding and sequencing research. A comparison of marker position and order may provide interesting insight into the evolutionary history of even distantly related species. Physical and genetic maps can unravel the complexities of large duplicated genomes intractable to sequencing efforts; whereas in species more amenable to genetic studies high-resolution maps provide the scaffold on which whole genome sequences are assembled. A complete genome sequence is a physical map at its highest resolution. Key Concepts: Genetic maps are based on the recombination frequency between molecular markers. These maps are population specific. Physical maps are an alignment of DNA sequences, with distance between markers measured in base pairs. Unique DNA sequences called molecular markers are compared to each other to determine correct marker order (genetic map) and used to identify overlapping segments of larger DNA pieces (physical map). Genetic mapping is based on recombination, the exchange of DNA sequence between sister chromatids during meiosis. High-resolution genetic and physical maps serve as the scaffold for genome sequence assembly. Tightly correlated marker order between species can identify conserved syntenic regions. Keywords: recombination; genome; molecular marker; synteny; genetic map; physical map

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.

A small fast neutron mutant population has been established from Phaseolus vulgaris cv. Red Hawk. We leveraged the available P. vulgaris genome sequence and high throughput next generation DNA sequencing to examine the genomic structure of five Phaseolus vulgaris cv. Red Hawk fast neutron mutants with striking visual phenotypes. Analysis of these genomes identified three classes of structural variation; between cultivar variation, natural variation within the fast neutron mutant population, and fast neutron induced mutagenesis. Our analyses focused on the latter two classes. We identified 23 large deletions (>40 bp) common to multiple individuals, illustrating residual heterogeneity and regions of structural variation within the common bean cv. Red Hawk. An additional 18 large deletions were identified in individual mutant plants. These deletions, ranging in size from 40 bp to 43,000 bp, are potentially the result of fast neutron mutagenesis. Six of the 18 deletions lie near or within gene coding regions, identifying potential candidate genes causing the mutant phenotype.

In soybean [Glycine max (L.) Merr.], iron deficiency results in interveinal chlorosis and decreased photosynthetic capacity, leading to stunting and yield loss. In this study, gene expression analyses investigated the role of soybean replication protein A (RPA) subunits during iron stress. Nine RPA homologs were significantly differentially expressed in response to iron stress in the near isogenic lines (NILs) Clark (iron efficient) and Isoclark (iron inefficient). RPA homologs exhibited opposing expression patterns in the two NILs, with RPA expression significantly repressed during iron deficiency in Clark but induced in Isoclark. We used virus induced gene silencing (VIGS) to repress GmRPA3 expression in the iron inefficient line Isoclark and mirror expression in Clark. GmRPA3-silenced plants had improved IDC symptoms and chlorophyll content under iron deficient conditions and also displayed stunted growth regardless of iron availability. RNA-Seq comparing gene expression between GmRPA3-silenced and empty vector plants revealed massive transcriptional reprogramming with differential expression of genes associated with defense, immunity, aging, death, protein modification, protein synthesis, photosynthesis and iron uptake and transport genes. Our findings suggest the iron efficient genotype Clark is able to induce energy controlling pathways, possibly regulated by SnRK1/TOR, to promote nutrient recycling and stress responses in iron deficient conditions.

Rpp4 (Resistance to Phakopsora pachyrhizi 4) confers resistance to Phakopsora pachyrhizi Sydow, the causal agent of Asian soybean rust (ASR). By combining expression profiling and virus induced gene silencing (VIGS), we are developing a genetic framework for Rpp4-mediated resistance. We measured gene expression in mock-inoculated and P. pachyrhizi-infected leaves of resistant soybean accession PI459025B (Rpp4) and the susceptible cultivar (Williams 82) across a 12-day time course. Unexpectedly, two biphasic responses were identified. In the incompatible reaction, genes induced at 12 h after infection (hai) were not differentially expressed at 24 hai, but were induced at 72 hai. In contrast, genes repressed at 12 hai were not differentially expressed from 24 to 144 hai, but were repressed 216 hai and later. To differentiate between basal and resistance-gene (R-gene) mediated defence responses, we compared gene expression in Rpp4-silenced and empty vector-treated PI459025B plants 14 days after infection (dai) with P. pachyrhizi. This identified genes, including transcription factors, whose differential expression is dependent upon Rpp4. To identify differentially expressed genes conserved across multiple P. pachyrhizi resistance pathways, Rpp4 expression datasets were compared with microarray data previously generated for Rpp2 and Rpp3-mediated defence responses. Fourteen transcription factors common to all resistant and susceptible responses were identified, as well as fourteen transcription factors unique to R-gene-mediated resistance responses. These genes are targets for future P. pachyrhizi resistance research.

Near-isogenic lines (NILs) are valuable genetic resources for many crop species, including soybean (Glycine max). The development of new molecular platforms promises to accelerate the mapping of genetic introgressions in these materials. Here, we compare some existing and emerging methodologies for genetic introgression mapping: single-feature polymorphism analysis, Illumina GoldenGate single nucleotide polymorphism (SNP) genotyping, and de novo SNP discovery via RNA-Seq analysis of next-generation sequence data. We used these methods to map the introgressed regions in an iron-inefficient soybean NIL and found that the three mapping approaches are complementary when utilized in combination. The comparative RNA-Seq approach offers several additional advantages, including the greatest mapping resolution, marker depth, and de novo marker utility for downstream fine-mapping analysis. We applied the comparative RNA-Seq method to map genetic introgressions in an additional pair of NILs exhibiting differential seed protein content. Furthermore, we attempted to optimize the comparative RNA-Seq approach by assessing the impact of sequence depth, SNP identification methodology, and post hoc analyses on SNP discovery rates. We conclude that the comparative RNA-Seq approach can be optimized with sufficient sampling and by utilizing a post hoc correction accounting for gene density variation that controls for false discoveries.

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

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. Abstract 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. Electronic supplementary material The online version of this article (doi:10.1007/s00122-016-2735-x) contains supplementary material, which is available to authorized users.

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. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1718-7) contains supplementary material, which is available to authorized users.

Background Iron is one of fourteen mineral elements required for proper plant growth and development of soybean (Glycine max L. Merr.). Soybeans grown on calcareous soils, which are prevalent in the upper Midwest of the United States, often exhibit symptoms indicative of iron deficiency chlorosis (IDC). Yield loss has a positive linear correlation with increasing severity of chlorotic symptoms. As soybean is an important agronomic crop, it is essential to understand the genetics and physiology of traits affecting plant yield. Soybean cultivars vary greatly in their ability to respond successfully to iron deficiency stress. Microarray analyses permit the identification of genes and physiological processes involved in soybean's response to iron stress. Results RNA isolated from the roots of two near isogenic lines, which differ in iron efficiency, PI 548533 (Clark; iron efficient) and PI 547430 (IsoClark; iron inefficient), were compared on a spotted microarray slide containing 9,728 cDNAs from root specific EST libraries. A comparison of RNA transcripts isolated from plants grown under iron limiting hydroponic conditions for two weeks revealed 43 genes as differentially expressed. A single linkage clustering analysis of these 43 genes showed 57% of them possessed high sequence similarity to known stress induced genes. A control experiment comparing plants grown under adequate iron hydroponic conditions showed no differences in gene expression between the two near isogenic lines. Expression levels of a subset of the differentially expressed genes were also compared by real time reverse transcriptase PCR (RT-PCR). The RT-PCR experiments confirmed differential expression between the iron efficient and iron inefficient plants for 9 of 10 randomly chosen genes examined. To gain further insight into the iron physiological status of the plants, the root iron reductase activity was measured in both iron efficient and inefficient genotypes for plants grown under iron sufficient and iron limited conditions. Iron inefficient plants failed to respond to decreased iron availability with increased activity of Fe reductase. Conclusion These experiments have identified genes involved in the soybean iron deficiency chlorosis response under iron deficient conditions. Single linkage cluster analysis suggests iron limited soybeans mount a general stress response as well as a specialized iron deficiency stress response. Root membrane bound reductase capacity is often correlated with iron efficiency. Under iron-limited conditions, the iron efficient plant had high root bound membrane reductase capacity while the iron inefficient plants reductase levels remained low, further limiting iron uptake through the root. Many of the genes up-regulated in the iron inefficient NIL are involved in known stress induced pathways. The most striking response of the iron inefficient genotype to iron deficiency stress was the induction of a profusion of signaling and regulatory genes, presumably in an attempt to establish and maintain cellular homeostasis. Genes were up-regulated that point toward an increased transport of molecules through membranes. Genes associated with reactive oxidative species and an ROS-defensive enzyme were also induced. The up-regulation of genes involved in DNA repair and RNA stability reflect the inhospitable cellular environment resulting from iron deficiency stress. Other genes were induced that are involved in protein and lipid catabolism; perhaps as an effort to maintain carbon flow and scavenge energy. The under-expression of a key glycolitic gene may result in the iron-inefficient genotype being energetically challenged to maintain a stable cellular environment. These experiments have identified candidate genes and processes for further experimentation to increase our understanding of soybeans' response to iron deficiency stress.

Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553) genotype and 200 candidate genes in the IsoClark (PI547430) genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs) specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in soybean is a result of a mutation in a transcription factor(s), which controls the expression of genes required in inducing an iron stress response.