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Grain legumes play a significant role in global food security. They have an advantage over cereals in that they can form symbiotic associations with nitrogen-fixing bacteria, making them self-sufficient in terms of nitrogen acquisition. In addition to this superior agronomic trait, grain legumes have excellent nutritional properties and are thus widely used as animal feed as well as in human nutrition. Current global trends towards increased legume consumption and availability of value-added products, as well as legume production in developing countries require the provision of improved cultivars with better productivity and adaptability. Intensive efforts are thus underway to elaborate genomic resources and gain an improved knowledge base in a number of legume crops. There is also an emerging understanding of the beneficial interactions between legume-associated organisms, particularly rhizobia and arbuscular mycorrhizal fungi, which result in improved nodulation and nutrient acquisition. The emerging focus on legume breeding for high sustainable yields as well as improved biotic and abiotic stress tolerance traits will serve to close the current gap between grain legume production and demand. With the support from policymakers, this increase in knowledge can be readily translated into increased crop production to meet the demands of an increasing global population.

Detection and quantification of transgenes are important in analyzing genetically modified organisms (GMOs). Quantitative polymerase chain reaction (qPCR) is commonly utilized for such purposes. However, qPCR has certain limitations in detecting and quantifying transgenes in GMOs, such as the need of certified reference materials, a standard curve, and possible affection by inhibitors. Therefore, alternative and possibly better methods are needed. Recent advances in digital PCR technologies have promised to allow accurate quantification of nucleic acids and therefore provided another useful technique to analyze GMOs. Thermo Fisher ScientificTM has recently commercialized the Applied BiosystemsTM QuantStudioTM 3D digital PCR system that can be used for a wide range of applications involving nucleic acids. It will be beneficial to the scientific community to show the applicability of this digital PCR system in detecting and quantifying transgenes in GMOs. In the present study, the transgenes present in the Roundup Ready Soybean (RR1, event 40-3-2) and Roundup Ready Soybean 2 (RR2, event MON89788) developed by Monsanto Corporation were analyzed by using this digital PCR system. The qPCR analysis results were included for comparison. Using specifically designed TaqMan assays, as low as 1% of the RR1 or RR2 soybean material was reliably detected and quantified on the dPCR platform. Therefore, digital PCR is a sensitive and reliable method to analyze the RR transgenic soybeans, and should be another useful tool for analyzing other transgenic plants.

Drought stress is one of the major limiting factors in soybean growth and productivity. Canopy leaf wilting (i.e. fast- and slow-wilting) is considered as an important visible symptom of soybeans under drought conditions. In soybean breeding programs, genotypes with the slow-wilting trait have been identified as drought-tolerant cultivars. Traditional method measures canopy leaf wilting traits using visual observations, which is subjective and time-consuming. Recent developments of field high-throughput phenotyping technology using Unmanned Aerial Vehicle (UAV)-based imagery have shown great potential in quantifying crop traits and detecting crop responses to abiotic and biotic stresses. The goal of this study was to investigate the potential use of UAV-based imagery in classifying soybean genotypes with fast- and slow-wilting traits. A UAV imaging system consisting of an RGB (Red-Green-Blue) camera, an infrared thermal camera, and a multispectral camera was used to collect imagery data of 116 soybean genotypes planted in a rain-fed breeding field at the reproductive stage. Visual-based canopy wilting scores were collected by breeders in the same day of imagery data collection. Seven image features were extracted, namely normalized difference vegetation index (NDVI), green-based NDVI (gNDVI), temperature, color hue, color saturation, canopy size and plant height for quantifying canopy wilting trait. Results show that all image features significantly (p-value

Xyloglucan endotransglycosylases/hydrolases (XTHs) are a class of enzymes involved in the construction and remodeling of cellulose/xyloglucan crosslinks and play an important role in regulating cell wall extensibility. However, little is known about this class of enzymes in soybean. Here, 61 soybean XTH genes (GmXTHs) were identified and classified into three subgroups through comparative phylogenetic analysis. Genome duplication greatly contributed to the expansion of GmXTH genes in soybean. A conserved amino acid motif responsible for the catalytic activity was identified in all GmXTHs. Further expression analysis revealed that most GmXTHs exhibited a distinct organ-specific expression pattern, and the expression level of many GmXTH genes was significantly associated with ethylene and flooding stress. To illustrate a possible role of XTH genes in regulating stress responses, the Arabidopsis AtXTH31 gene was overexpressed in soybean. The generated transgenic plants exhibited improved tolerance to flooding stress, with a higher germination rate and longer roots/hypocotyls during the seedling stage and vegetative growth stages. In summary, our combined bioinformatics and gene expression pattern analyses suggest that GmXTH genes play a role in regulating soybean stress responses. The enhanced soybean flooding tolerance resulting from the expression of an Arabidopsis XTH also supports the role of XTH genes in regulating plant flooding stress responses.

The root angle and fibrous root score determines soybean [Glycine max (L.) Merr.] productivity in water-limited environments. Studying root traits in the field is technically difficult to do nondestructively, and varying agroclimatic and edaphic factors create challenges, which could be circumvented using laboratory-based root studies with higher precision. In this study, we developed and validated a nondestructive root imaging platform and derived three-dimensional (3D) root features using algorithms that would predict the root response under field conditions. Nine soybean genotypes (five landrace accessions and four cultivars) were evaluated at seedling and reproductive stages in controlled environments and the field. Irrespective of the phenotyping platforms, soybean landraces showed higher phenotypic variation for different root architectural traits than cultivars. The plant introductions 200471 and 567731 had higher phenotypic values for root and shoot traits than cultivars Dunbar, Magellan, and Maverick. The seedling 3D root features—volume and surface area/volume ratio—were found to be the best predictors of field root response evaluated. This positive association is a promising step in using a nondestructive imaging system to screen soybean with a desired root system that matches different target environments. Thus, the selection based on accurate 3D root features will hasten the inclusion of root traits in soybean breeding programs specifically to improve productivity in harsh environments.

The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful "soybean bonanza" across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.

Xyloglucan endotransglycosylases/hydrolases (XTHs) are a class of enzymes involved in the construction and remodeling of cellulose/xyloglucan crosslinks and play an important role in regulating cell wall extensibility. However, little is known about this class of enzymes in soybean. Here, 61 soybean XTH genes (GmXTHs) were identified and classified into three subgroups through comparative phylogenetic analysis. Genome duplication greatly contributed to the expansion of GmXTH genes in soybean. A conserved amino acid motif responsible for the catalytic activity was identified in all GmXTHs. Further expression analysis revealed that most GmXTHs exhibited a distinct organ-specific expression pattern, and the expression level of many GmXTH genes was significantly associated with ethylene and flooding stress. To illustrate a possible role of XTH genes in regulating stress responses, the Arabidopsis AtXTH31 gene was overexpressed in soybean. The generated transgenic plants exhibited improved tolerance to flooding stress, with a higher germination rate and longer roots/hypocotyls during the seedling stage and vegetative growth stages. In summary, our combined bioinformatics and gene expression pattern analyses suggest that GmXTH genes play a role in regulating soybean stress responses. The enhanced soybean flooding tolerance resulting from the expression of an Arabidopsis XTH also supports the role of XTH genes in regulating plant flooding stress responses.

Natural genetic variations in waterlogging tolerance are controlled by multiple genes mapped as quantitative trait loci (QTLs) in major crops, including soybean (Glycine max L.). In this research, 2 novel QTLs associated with waterlogging tolerance were mapped from an elite/exotic soybean cross. The subsequent research was focused on a major QTL (qWT_Gm03) with the tolerant allele from the exotic parent. This QTL was isolated into near-isogenic backgrounds, and its effects on waterlogging tolerance were validated in multiple environments. Fine mapping narrowed qWT_Gm03 into a genomic region of

Salt stress is one of the major abiotic factors affecting crop growth and production. In general, soybean is sensitive to salt stress. The success of soybean improvement for salt tolerance depends on discovery and utilization of genetic variation in the germplasm. In this chapter, advance in salt-tolerant research and breeding was summarized by highlighting the genetic diversity, quantitative trait loci (QTL), identification of the major locus (Glyma03g32900), and improvement of soybean varieties in salt tolerance. The ion exclusion and tissue tolerance mechanisms regulated by this major locus are discussed. In addition, genomic resources and high-throughput phenotyping platforms that can facilitate a better understanding of phenotype-genotype association and formulate genomic-assisted breeding strategies are prospected.

International audience; Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.

The objectives were to (a) quantify the effects of high daytime temperature (HDT) from gametogenesis to full bloom on photosynthesis and pod set in soybean (Glycine max L. Merril) genotypes and (b) assess the relationships among photosynthesis, cardinal temperatures for pollen germination, in vitro pollen germination percentage, canopy reflectance, and pod-set percentage. Three field experiments were conducted, and Experiment I had HDT between gametogenesis and full bloom (36.5°C to 38.6°C) compared with Experiments II and III (29.5°C to 31.6°C; optimum temperature). HDT decreased photosynthesis (22%) and pod-set percent (11%) compared with Experiment III. Cultivars had higher photosynthesis and pod-set percent than plant introduction (PI) lines. The cultivars (i.e., IA3023 and KS4694) and PI lines (i.e., PI393540 and PI588026A) were HDT tolerant and susceptible, respectively. The decreased pod-set percentage in susceptible genotypes (PI lines) was associated with pollen characteristics. Significant positive (r2 ≥ 0.67) association between photosynthesis, cardinal temperatures for pollen germination (Topt and Tmax ) with pod-set percentage was observed. However, a negative (r2 ≥ -0.43) association between photosynthesis and pod set with canopy reflectance at visible spectrum was observed. In vitro pollen germination and canopy reflectance at visible spectrum can be used as a high-throughput phenotypic tool for breeding HDT-tolerant genotypes.

Natural genetic variations in waterlogging tolerance are controlled by multiple genes mapped as quantitative trait loci (QTLs) in major crops, including soybean (Glycine max L.). In this research, 2 novel QTLs associated with waterlogging tolerance were mapped from an elite/exotic soybean cross. The subsequent research was focused on a major QTL (qWT_Gm03) with the tolerant allele from the exotic parent. This QTL was isolated into near-isogenic backgrounds, and its effects on waterlogging tolerance were validated in multiple environments. Fine mapping narrowed qWT_Gm03 into a genomic region of380 Kbp excluding Rps1 gene for Phytophthora sojae resistance. The tolerant allele of qWT_Gm03 promotes root growth under nonstress conditions and favourable root plasticity under waterlogging, resulting in improved waterlogging tolerance, yield, and drought tolerance-related traits, possibly through more efficient water/nutrient uptakes. Meanwhile, involvement of auxin pathways was also identified in the regulation of waterlogging tolerance, as the genotypic differences of qWT_Gm03 in waterlogging tolerance and formation of adventitious/aerial roots can be complemented by an exogenous auxin-biosynthesis inhibitor. These findings provided genetic resources to address the urgent demand of improving waterlogging tolerance in soybean and revealed the determinant roles of root architecture and plasticity in the plant adaptation to waterlogging.

Our agricultural system and hence food security is threatened by combination of events, such as increasing population, the impacts of climate change, and the need to a more sustainable development. Evolutionary adaptation may help some species to overcome environmental changes through new selection pressures driven by climate change. However, success of evolutionary adaptation is dependent on various factors, one of which is the extent of genetic variation available within species. Genomic approaches provide an exceptional opportunity to identify genetic variation that can be employed in crop improvement programs. In this review, we illustrate some of the routinely used genomics‐based methods as well as recent breakthroughs, which facilitate assessment of genetic variation and discovery of adaptive genes in legumes. Although additional information is needed, the current utility of selection tools indicate a robust ability to utilize existing variation among legumes to address the challenges of climate uncertainty., Agriculture is facing a combination of factors that threaten global food security. In this review, we discuss some of the routinely used genomics‐based methods as well as recent breakthroughs that can help adapt legume crops to climate change by facilitating assessment of genetic variation and discovery of adaptive genes.

Limited information is available for soybean root traits and their plasticity under drought stress. To date, no studies have focused on examining diverse soybean germplasm for regulation of shoot and root response under water limited conditions across varying soil types. In this study, 17 genetically diverse soybean germplasm lines were selected to study root response to water limited conditions in clay (trial 1) and sandy soil (trial 2) in two target environments. Physiological data on shoot traits was measured at multiple crop stages ranging from early vegetative to pod filling. The phenotypic root traits, and biomass accumulation data are collected at pod filling stage. In trial 1, the number of lateral roots and forks were positively correlated with plot yield under water limitation and in trial 2, lateral root thickness was positively correlated with the hill plot yield. Plant Introduction (PI) 578477A and 088444 were found to have higher later root number and forks in clay soil with higher yield under water limitation. In sandy soil, PI458020 was found to have a thicker lateral root system and higher yield under water limitation. The genotypes identified in this study could be used to enhance drought tolerance of elite soybean cultivars through improved root traits specific to target environments.

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.

Key message We identified and characterized a mutant of soybean stachyose synthase gene controlling reduced stachyose content which benefit the soybean seed composition breeding program in the future. Abstract It has been shown that in soybean, increased sucrose and reduced raffinose family oligosaccharides would have a positive impact on the world’s feed industry by improving digestibility and feed efficiency. We searched for new sources of modified oligosaccharide content in a subset of the USDA Soybean Germplasm Collection and then identified plant introduction (PI) 603176A as having ultra-low stachyose content (0.5 %). We identified a 33-bp deletion mutant in the putative stachyose synthase gene (STS gene, Glyma19g40550) of PI 603176A. A co-dominate indel marker was successfully developed from this 33-bp deletion area and was genetically mapped into two F2:3 populations and a F4:5 population, which associated with low stachyose content in the progeny lines. These observations provided strong evidence that the STS gene is responsible for stachyose biosynthesis in the soybean plant. Expression of the sts gene remained at the normal level, suggesting the loss of function in the gene is due to defective protein function. This gene-based perfect genetic marker for low stachyose content can be useful for marker-assisted selection in soybean molecular breeding programs. Electronic supplementary material The online version of this article (doi:10.1007/s00122-015-2575-0) contains supplementary material, which is available to authorized users.

Many sources of drought and flooding tolerance have been identified in soybean, however underlying molecular and physiological mechanisms are poorly understood. Therefore, it is important to illuminate different plant responses to these abiotic stresses and understand the mechanisms that confer tolerance. Towards this goal we used four contrasting soybean (Glycine max) genotypes (PI 567690 - drought tolerant, Pana - drought susceptible, PI 408105A - flooding tolerant, S99-2281 - flooding susceptible) grown under greenhouse conditions and compared genotypic responses to drought and flooding at the physiological, biochemical, and cellular level. We also quantified these variations and tried to infer their role in drought and flooding tolerance in soybean. Our results revealed that different mechanisms contribute to reduction in net photosynthesis under drought and flooding stress. Under drought stress, ABA and stomatal conductance are responsible for reduced photosynthetic rate; while under flooding stress, accumulation of starch granules played a major role. Drought tolerant genotypes PI 567690 and PI 408105A had higher plastoglobule numbers than the susceptible Pana and S99-2281. Drought stress increased the number and size of plastoglobules in most of the genotypes pointing to a possible role in stress tolerance. Interestingly, there were seven fibrillin proteins localized within the plastoglobules that were up-regulated in the drought and flooding tolerant genotypes PI 567690 and PI 408105A, respectively, but down-regulated in the drought susceptible genotype Pana. These results suggest a potential role of Fibrillin proteins, FBN1a, 1b and 7a in soybean response to drought and flooding stress.

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.

Small RNAs are ubiquitous, versatile repressors and include (1) microRNAs (miRNAs), processed from mRNA forming stem-loops; and (2) small interfering RNAs (siRNAs), the latter derived in plants by a process typically requiring an RNA-dependent RNA polymerase. We constructed and analyzed an expression atlas of soybean (Glycine max) small RNAs, identifying over 500 loci generating 21-nucleotide phased siRNAs (phasiRNAs; from PHAS loci), of which 483 overlapped annotated protein-coding genes. Via the integration of miRNAs with parallel analysis of RNA end (PARE) data, 20 miRNA triggers of 127 PHAS loci were detected. The primary class of PHAS loci (208 or 41% of the total) corresponded to NB-LRR genes; some of these small RNAs preferentially accumulate in nodules. Among the PHAS loci, novel representatives of TAS3 and noncanonical phasing patterns were also observed. A noncoding PHAS locus, triggered by miR4392, accumulated preferentially in anthers; the phasiRNAs are predicted to target transposable elements, with their peak abundance during soybean reproductive development. Thus, phasiRNAs show tremendous diversity in dicots. We identified novel miRNAs and assessed the veracity of soybean miRNAs registered in miRBase, substantially improving the soybean miRNA annotation, facilitating an improvement of miRBase annotations and identifying at high stringency novel miRNAs and their targets.

Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.

The confirmation of a major locus associated with salt tolerance and mapping of a new locus, which could be beneficial for improving salt tolerance in soybean. Breeding soybean for tolerance to high salt conditions is important in some regions of the USA and world. Soybean cultivar Fiskeby III (PI 438471) in maturity group 000 has been reported to be highly tolerant to multiple abiotic stress conditions, including salinity. In this study, a mapping population of 132 F2 families derived from a cross of cultivar Williams 82 (PI 518671, moderately salt sensitive) and Fiskeby III (salt tolerant) was analyzed to map salt tolerance genes. The evaluation for salt tolerance was performed by analyzing leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC) after treatment with 120 mM NaCl under greenhouse conditions. Genotypic data for the F2 population were obtained using the SoySNP6K Illumina Infinium BeadChip assay. A major allele from Fiskeby III was significantly associated with LSS, CCR, LSC, and LCC on chromosome (Chr.) 03 with LOD scores of 19.1, 11.0, 7.7 and 25.6, respectively. In addition, a second locus associated with salt tolerance for LSC was detected and mapped on Chr. 13 with an LOD score of 4.6 and an R 2 of 0.115. Three gene-based polymorphic molecular markers (Salt-20, Salt14056 and Salt11655) on Chr.03 showed a strong predictive association with phenotypic salt tolerance in the present mapping population. These molecular markers will be useful for marker-assisted selection to improve salt tolerance in soybean.

Key message Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Abstract Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content’s negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement. Electronic supplementary material The online version of this article (doi:10.1007/s00122-017-2955-8) contains supplementary material, which is available to authorized users.

Background Soybean (Glycine max) production is significantly hampered by frequent droughts in many regions of the world including the United States. Identifying microRNA (miRNA)-controlled posttranscriptional gene regulation under drought will enhance our understanding of molecular basis of drought tolerance in this important cash crop. Indeed, miRNA profiles in soybean exposed to drought were studied but not from the primary root tips, which is not only a main zone of water uptake but also critical for water stress sensing and signaling. Methods Here we report miRNA profiles specifically from well-watered and water-stressed primary root tips (0 to 8 mm from the root apex) of soybean. Small RNA sequencing confirmed the expression of vastly diverse miRNA (303 individual miRNAs) population, and, importantly several conserved miRNAs were abundantly expressed in primary root tips. Results Notably, 12 highly conserved miRNA families were differentially regulated in response to water-deficit; six were upregulated while six others were downregulated at least by one fold (log2) change. Differentially regulated soybean miRNAs are targeting genes include auxin response factors, Cu/Zn Superoxide dismutases, laccases and plantacyanin and several others. Conclusions These results highlighted the importance of miRNAs in primary root tips both under control and water-deficit conditions; under control conditions, miRNAs could be important for cell division, cell elongation and maintenance of the root apical meristem activity including quiescent centre whereas under water stress differentially regulated miRNAs could decrease auxin signaling and oxidative stress as well as other metabolic processes that save energy and water. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0374-0) contains supplementary material, which is available to authorized users.

Association mapping studies in plants including soybean contribute to not only detecting the genetic basis of variation in yield, physiological, developmental, and morphological traits but also bringing together researchers to assemble core collections and develop genetic platforms for genotyping, phenotyping, analysis, and interpretation. The establishment of the unified mixed model greatly facilitated association mapping studies in plants and further methodology work in general. Association mapping is well positioned to exploit the advances in next-generation genomic technologies and high-through-put phenotyping. Genome-wide association studies are expected to increase dramatically once genome sequences are obtained. Moving forward, researchers in soybean and all other major plant genetics need to develop improved genetic designs and computational tools to address several challenges such as missing heritability, new gene identification, genotyping-by-sequencing, rare variants, imputation, high-throughput phenotyping, and integration of collective biological information and analytical tools into GWAS. In this chapter, we describe major progress in understanding population structure, advancements in design, and implementation of association mapping and summarize examples of association mapping in soybean. Finally, major opportunities with potential implications in soybean genetics are discussed as well.

Seed composition is one of the most important determinants of the economic values in soybean. The quality and quantity of different seed components, such as oil, protein, and carbohydrates, are crucial ingredients in food, feed, and numerous industrial products. Soybean researchers have successfully developed and utilized a diverse set of molecular markers for seed trait improvement in soybean breeding programs. It is imperative to design and develop molecular assays that are accurate, robust, high-throughput, cost-effective, and available on a common genotyping platform. In the present study, we developed and validated KASP (Kompetitive allele-specific polymerase chain reaction) genotyping assays based on previously known functional mutant alleles for the seed composition traits, including fatty acids, oligosaccharides, trypsin inhibitor, and lipoxygenase. These assays were validated on mutant sources as well as mapping populations and precisely distinguish the homozygotes and heterozygotes of the mutant genes. With the obvious advantages, newly developed KASP assays in this study can substitute the genotyping assays that were previously developed for marker-assisted selection (MAS). The functional gene-based assay resource developed using common genotyping platform will be helpful to accelerate efforts to improve soybean seed composition traits.

Genome sequencing yields an exceptional resource of genetic information. Knowledge of whole genome sequence information helps characterize individual genomes, transcriptional states and genetic variation in populations and provide genetic architecture associated with each trait. After the release of the first human genome assembly, other model organism assemblies became available; including the model plant Arabidopsis thaliana. The soybean community published the first reference genome of the variety Williams 82 in 2010. Soybean has important syntenic relationships with the other legume species and is a model plant for the legumes. In this chapter, we discuss about the soybean genome assemblies and annotations, and its fine-tuning in view of the next-generation sequencing technologies and bioinformatics tools. In addition, comparison of the structural variations between the cultivated reference genome with the available wild soybean genome information will be discussed. This is followed by the discussion on the opportunities of next-generation sequencing technologies and challenges that we anticipate on the development of more pangenomes and reference genomes for soybean. This will significantly affect the discovery of rare alleles associated with key agronomic and quality traits and shape up the next-generation breeding technologies and crop improvement.

Much research has been conducted on the changes in gene expression of the model plant Arabidopsis to low-oxygen stress. Flooding results in a low oxygen environment in the root zone. However, there is ample evidence that tolerance to soil flooding is more than tolerance to low oxygen alone. In this study, we investigated the physiological response and differential expression of root-related transcription factors (TFs) associated with the tolerance of soybean plants to soil flooding. Differential responses of PI408105A and S99-2281 plants to ten days of soil flooding were evaluated at physiological, morphological and anatomical levels. Gene expression underlying the tolerance response was investigated using qRT-PCR of root-related TFs, known anaerobic genes, and housekeeping genes. Biomass of flood-sensitive S99-2281 roots remained unchanged during the entire 10 days of flooding. Flood-tolerant PI408105A plants exhibited recovery of root growth after 3 days of flooding. Flooding induced the development of aerenchyma and adventitious roots more rapidly in the flood-tolerant than the flood-sensitive genotype. Roots of tolerant plants also contained more ATP than roots of sensitive plants at the 7th and 10th days of flooding. Quantitative transcript analysis identified 132 genes differentially expressed between the two genotypes at one or more time points of flooding. Expression of genes related to the ethylene biosynthesis pathway and formation of adventitious roots was induced earlier and to higher levels in roots of the flood-tolerant genotype. Three potential flood-tolerance TFs which were differentially expressed between the two genotypes during the entire 10-day flooding duration were identified. This study confirmed the expression of anaerobic genes in response to soil flooding. Additionally, the differential expression of TFs associated with soil flooding tolerance was not qualitative but quantitative and temporal. Functional analyses of these genes will be necessary to reveal their potential to enhance flooding tolerance of soybean cultivars.

The QTLs controlling alpha-linolenic acid concentration from wild soybean were mapped on nine soybean chromosomes with various phenotypic variations. New QTLs for alpha-linolenic acid were detected in wild soybean. Alpha-linolenic acid (ALA) is a polyunsaturated fatty acid desired in human and animal diets. Some wild soybean (Glycine soja) genotypes are high in ALA. The objective of this study was to identify quantitative trait loci (QTLs) controlling ALA concentration in a wild soybean accession, PI483463. In total, 188 recombinant inbred lines of F5:6, F5:7, and F5:8 generations derived from a cross of wild soybean PI483463 (~15 % ALA) and cultivar Hutcheson (~9 % ALA) were planted in four environments. Harvested seeds were used to measure fatty acid concentration. Single nucleotide polymorphism markers of the universal soybean linkage panel (USLP 1.0) and simple sequence repeat markers were used for molecular genotyping. Nine putative QTLs were identified that controlled ALA concentration by model-based composite interval mapping and mapped to different soybean chromosomes. The QTLs detected in four environments explained 2.4-7.9 % of the total phenotypic variation (PV). Five QTLs, qALA5_3, qALA6_1, qALA14_1, qALA15_1, and qALA17_1, located on chromosomes 5, 6, 14, 15, and 17 were identified by model-based composite interval mapping and composite interval mapping in two individual environments. Among them, qALA6_1 showed the highest contribution to the PV with 10.0-10.2 % in two environments. The total detected QTLs for additive and epistatic effects explained 52.4 % of the PV for ALA concentration. These findings will provide useful information for understanding genetic structure and marker-assisted breeding programs to increase ALA concentration in seeds derived from wild soybean PI483463.

Due to high costs of irrigation, limited availability of irrigation water in many locations and/or lack of irrigation capabilities, genetic improvement for drought tolerance is an effective method to reduce yield loss in soybean [Glycine max (L.) Merr.]. Slow wilting and minimal yield reduction under drought are important traits in evaluating drought tolerance. Two maturity group III soybean plant introductions (PIs, PI 567690 and PI 567731) and two elite cultivars (DKB38-52 and Pana) were evaluated with and without irrigation on a sandy soil. Drought was imposed by withholding irrigation at full bloom and continued until moderate wilting was shown by the fast leaf wilting in the check cultivar, Pana. Then, irrigation was resumed until maturity. Genotypes were scored for leaf wilting during the stress period, and yields were assessed at the end of the growing season and used to calculate a drought index. Yields of the exotic PIs were lower than those of the checks under both drought and well-watered conditions. However, the PIs exhibited significantly lower wilting and less yield loss under drought (higher drought index) than check cultivars. The two PIs may have useful genes to develop drought-tolerant germplasm and cultivars and maybe useful in genetic and physiological studies to decipher mechanisms responsible for improving yield under limited water availability.

The reaction catalyzed by squalene synthase (EC.2.5.1.21) that converts two molecules of farnesyl pyrophosphate to squalene represents a crucial branch point of the isoprenoid pathway in diverting carbon flux towards the biosynthesis of sterols. In the present study two soybean squalene synthase genes, GmSQS1 and GmSQS2, were identified in the soybean genome and functionally characterized for their roles in sterol biosynthesis. Both genes encode a deduced protein of 413 amino acids. Complementation assays showed that the two genes were able to convert yeast sterol auxotrophy erg9 mutant to sterol prototrophy. Expression of GmSQS1 and GmSQS2 was ubiquitous in roots, stem, leaves, flower and young seeds of soybean, however GmSQS1 transcript was preferential in roots while GmSQS2 transcript was more in leaves. Their expression was lower in response to dehydration treatments suggesting they might be negative regulators of water stress adaptation. Transgenic Arabidopsis plants overexpressing GmSQS1 driven by either constitutive or seed-specific promoters showed increases in the major end product sterols: campesterol, sitosterol and stigmasterol, which resulted in up to 50% increase in total sterol content in the seeds. The increase in the end product sterols by GmSQS1 overexpression was at the level achievable by previously reported overexpression of individual or combination of other key enzymes in the sterol pathway. Together the data demonstrate that soybean SQS genes play an important role in diverting carbon flux to the biosynthesis of the end product sterols in the seeds.

Soybean Knowledge Base (http://soykb.org) is a comprehensive web resource developed for bridging soybean translational genomics and molecular breeding research. It provides information for six entities including genes/proteins, microRNAs/sRNAs, metabolites, single nucleotide polymorphisms, plant introduction lines and traits. It also incorporates many multi-omics datasets including transcriptomics, proteomics, metabolomics and molecular breeding data, such as quantitative trait loci, traits and germplasm information. Soybean Knowledge Base has a new suite of tools such as In Silico Breeding Program for soybean breeding, which includes a graphical chromosome visualizer for ease of navigation. It integrates quantitative trait loci, traits and germplasm information along with genomic variation data, such as single nucleotide polymorphisms, insertions, deletions and genome-wide association studies data, from multiple soybean cultivars and Glycine soja.

The objective of this study was to use next-generation sequencing technologies to dissect quantitative trait loci (QTL) for southern root-knot nematode (RKN) resistance into individual genes in soybean. Two hundred forty-six recombinant inbred lines (RIL) derived from a cross between Magellan (susceptible) and PI 438489B (resistant) were evaluated for RKN resistance in a greenhouse and sequenced at an average of 0.19× depth. A sequence analysis pipeline was developed to identify and validate single-nucleotide polymorphisms (SNPs), infer the parental source of each SNP allele, and genotype the RIL population. Based on 109,273 phased SNPs, recombination events in RILs were identified, and a total of 3,509 bins and 3,489 recombination intervals were defined. About 50.8% of bins contain 1 to 10 genes. A linkage map was subsequently constructed by using bins as molecular markers. Three QTL for RKN resistance were identified. Of these, one major QTL was mapped to bin 10 of chromosome 10, which is 29.7 kb in size and harbors three true genes and two pseudogenes. Based on sequence variations and gene-expression analysis, the candidate genes underlying the major QTL for RKN resistance were pinpointed. They are Glyma10g02150 and Glyma10g02160, encoding a pectin methylesterase inhibitor and a pectin methylesterase inhibitor -pectin methylesterase, respectively. This QTL mapping approach not only combines SNP discovery, SNP validation, and genotyping, but also solves the issues caused by genome duplication and repetitive sequences. Hence, it can be widely used in crops with a reference genome to enhance QTL mapping accuracy.

Salt tolerance in soybean [Glycine max (L.) Merr.] is controlled by major quantitative trait loci (QTL) or single gene(s). Among soybean germplasm, wild soybean plant introduction PI 483463 was reported to have a single dominant gene for salt tolerance. The objective of this study was to genetically map the QTL in a recombinant inbred line (RIL) population derived from a cross between PI 483463 and Hutcheson. Simple sequence repeat (SSR) markers and universal soybean single nucleotide polymorphism (SNP) panel (the USLP 1.0) were utilized for molecular genotyping. The RILs were phenotyped in two independent tests in a greenhouse using a 1–5 scale visual rating method. The results showed that the salt tolerant QTL in PI 483463 was mapped to chromosome 3 in a genomic region between the Satt255 and BARC-038333-10036 markers. The favorable allele inherited from PI 483463 conferred tolerance to salinity and had an additive effect on reducing leaf scorch. A subset of 66 iso-lines was developed from the F3 families of the same cross and was used for genetic confirmation of the QTL. The integration of recombination events and the salt reaction data indicate that the QTL is located in the region of approximately a 658 kb segment between SSR03_1335 at nucleotide 40,505,992 and SSR03_1359 at nucleotide 41,164,735 on chromosome 3. This narrow region can facilitate further genomic research for salt tolerance in soybean including cloning salt tolerance genes.

Demand for soybean [Glycine max (L.) Merr.] meal has increased worldwide and soybean importers often offer premiums for soybean containing higher contents of protein and oil. objectives were to detect quantitative trait loci (QTL) associated with soybean seed protein, oil, and seed weight in a soybean mapping population and confirm detected QTL across genetic backgrounds and environments. Two populations of 216 and 156 recombinant inbred lines were developed from Magellan × pI 438489B and Magellan × pI 567516C crosses, respectively, and grown in two Missouri environments in 2008. More than 900 simple sequence repeat (SSr) and single nucleotide polymorphism (SNp) markers were used for mapping in each population. Across environments and genetic backgrounds, we have identified seven QTL for protein, six for oil, and four for seed weight. Two QTL were detected in common for protein and oil, one on chromosome (Chr.) 5 and another on Chr. 6. Additionally, we have detected one new seed weight QTL on Chr. 6, in the same region of protein and oil QTL. Confirmed protein and oil QTL on Chrs. 5 and 6 may be important targets to find candidate genes involved in modification of protein and oil contents and seed weight using genetic and genomic approaches. Also, SSr and SNp markers closely associated with these QTL can be useful for marker-assisted selection. S.M. Pathan and J.G. Shannon, National Center for Soybean Biotechnology (NCSB) and Division of Plant Sciences, Univ. of Missouri Delta Research Center, Portageville, MO 63873; T. Vuong, K. Clark, H.T. Nguyen, and D.A. Sleper, NCSB and Division of Plant Sciences, Univ. of Missouri, Columbia, MO 65211; C.A. Roberts, Division of Plant Sciences, Univ. of Missouri, Columbia, MO 65211; M.R. Ellersieck, Division of Statistics, Univ. of Missouri, Columbia, MO 65211; J.W. Burton, Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, NC 27607; D.L. Hyten, Pioneer Hi-Bred International Inc., Johnston, IA 50131; P.B. Cregan, Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705; J.-D. Lee, School of Applied Biosciences, Kyungpook National Univ., Daegu 702-701, Republic of Korea. S.M. Pathan and T. Vuong contributed equally to the article. Received 5 Mar. 2012. *Corresponding author (sleperd@missouri.edu). Abbreviations: BREC, Bradford Research and Extension Center; Chr., chromosome; DRC, Delta Research Center; H2, broad-sense heritability; LOD, logarithm of the odds; MPB, Magellan × PI 438489B; MPC, Magellan × PI 567516C; MQM, multiple-QTL method; MU, University of Missouri–Columbia; NIR, near-infrared reflectance; QTL, quantitative trait loci; RIL, recombinant inbred line; SBM, soybean meal; SCN, soybean cyst nematode; SNP, single nucleotide polymorphism; SSR, simple sequence repeat. Published in Crop Sci. 53:765–774 (2013). doi: 10.2135/cropsci2012.03.0153 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

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.

Soybean, one of the most important crops worldwide, is severely affected by abiotic stress. Drought and flooding are the major abiotic stresses impacting soybean yield. In this regard, understanding water uptake by plants, its utilization and transport has great importance. In plants, water transport is mainly governed by channel forming aquaporin proteins (AQPs). Tonoplast intrinsic proteins (TIPs) belong to the plant-specific AQP subfamily and are known to have a role in abiotic stress tolerance. In this study, 23 soybean TIP genes were identified based on the latest soybean genome annotation. TIPs were characterized based on conserved structural features and phylogenetic distribution. Expression analysis of soybean TIP genes in various tissues and under abiotic stress conditions demonstrated tissue/stress-response specific differential expression. The natural variations for TIP genes were analyzed using whole genome re-sequencing data available for a set of 106 diverse soybean genotypes including wild types, landraces and elite lines. Results revealed 81 SNPs and several large insertions/deletions in the coding region of TIPs. Among these, non-synonymous SNPs are most likely to have a greater impact on protein function and are candidates for molecular studies as well as for the development of functional markers to assist breeding. The solute transport function of two TIPs was further validated by expression in Xenopus laevis oocytes. GmTIP1;5 was shown to facilitate the rapid movement of water across the oocyte membrane, while GmTIP2;5 facilitated the movement of water and boric acid. The present study provides an initial insight into the possible roles of soybean TIP genes under abiotic stress conditions. Our results will facilitate elucidation of their precise functions during abiotic stress responses and plant development, and will provide potential breeding targets for modifying water movement in soybean.