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Plant parasitic nematodes are a major yield-limiting factor of soybean in the United States and Canada. It has been indicated that soybean cyst nematode (SCN; Heterodera glycines Ichinohe) and reniform nematode (RN; Rotylenchulus reniformis Linford and Oliveira) resistance could be genetically related. For many years, fragmentary data have shown this relationship. This report evaluates RN reproduction on 418 plant introductions (PIs) selected from the U.S. Department of Agriculture Soybean Germplasm Collection with reported SCN resistance. The germplasm was divided into two tests of 214 PIs reported as resistant and 204 PIs reported as moderately resistant to SCN. The defining and reporting of RN resistance changed several times in the last 30 years, causing inconsistencies in RN resistance classification among multiple experiments. Comparison of four RN resistance classification methods was performed: (i) ≤10% as compared with the susceptible check, (ii) using normalized reproduction index (RI) values, and using (iii) transformed data log10(x), and (iv) transformed data log10(x + 1) in an optimal univariate k-means clustering analysis. The method of transformed data log10(x) was selected as the most accurate for classification of RN resistance. Among 418 PIs with reported SCN resistance, the log10(x) method grouped 59 PIs (15%) as resistant and 130 PIs (31%) as moderately resistant to RN. Genotyping of a subset of the most resistant PIs to both nematode species revealed their strong correlation with rhg1-a allele. This research identified genotypes with resistance to two nematode species and potential new sources of RN resistance that could be valuable to breeders in developing resistant cultivars.

The widespread adoption of genetically modified (GM) dicamba-tolerant (DT) soybean was followed by numerous reports of off-target dicamba damage and yield losses across most soybean-producing states. In this study, a subset of the USDA Soybean Germplasm Collection consisting of 382 genetically diverse soybean accessions originating from 15 countries was used to identify genomic regions associated with soybean response to off-target dicamba exposure. Accessions were genotyped with the SoySNP50K BeadChip and visually screened for damage in environments with prolonged exposure to off-target dicamba. Two models were implemented to detect significant marker-trait associations: the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and a model that allows the inclusion of population structure in interaction with the environment (G×E) to account for variable patterns of genotype responses in different environments. Most accessions (84%) showed a moderate response, either moderately tolerant or moderately susceptible, with approximately 8% showing tolerance and susceptibility. No differences in off-target dicamba damage were observed across maturity groups and centers of origin. Both models identified significant associations in regions of chromosomes 10 and 19. The BLINK model identified additional significant marker-trait associations on chromosomes 11, 14, and 18, while the G×E model identified another significant marker-trait association on chromosome 15. The significant SNPs identified by both models are located within candidate genes possessing annotated functions involving different phases of herbicide detoxification in plants. These results entertain the possibility of developing non-GM soybean cultivars with improved tolerance to off-target dicamba exposure and potentially other synthetic auxin herbicides. Identification of genetic sources of tolerance and genomic regions conferring higher tolerance to off-target dicamba may sustain and improve the production of other non-DT herbicide soybean production systems, including the growing niche markets of organic and conventional soybean.

Genetic improvement of soybean, one of the major crops providing edible oil and protein-rich food, is important to ensure balanced nutrition for the growing world population. To make soybean cultiv...

Phosphorus (P) is an essential macronutrient for all organisms. Phosphate (Pi) deficiency reduces grain yield and quality in wheat. Understanding how wheat responds to Pi deficiency at the global transcriptional level remains limited. We revisited the available RNA-seq transcriptome from Pi-starved wheat roots and shoots subjected to Pi starvation. Genome-wide transcriptome resetting was observed under Pi starvation, with a total of 917 and 2338 genes being differentially expressed in roots and shoots, respectively. Chromosomal distribution analysis of the gene triplets and differentially expressed genes (DEGs) revealed that the D genome displayed genome induction bias and, specifically, the chromosome 2D might be a key contributor to Pi-limiting triggered gene expression response. Alterations in multiple metabolic pathways pertaining to secondary metabolites, transcription factors and Pi uptake-related genes were evidenced. This study provides genomic insight and the dynamic landscape of the transcriptional changes contributing to the hexaploid wheat during Pi starvation. The outcomes of this study and the follow-up experiments have the potential to assist the development of Pi-efficient wheat cultivars.

There is a decrease in the land available for rice cultivation due to the rapid conversion to urban uses. Subsequently, acid soil could be an alternative land cultivating rice, but will require the use of aluminum (Al)-tolerant rice varieties. This Al tolerance trait is genetically controlled, and there is a need to discover more genes needed to develop Al-tolerant rice. Therefore, the objective of this study was to clone and characterize a novel Al tolerance gene isolated from a local cultivar of Indonesian rice. The gene cloning was conducted based on the rye/rice microsynteny relationship. In addition, the root growth and gene expression analyses were performed to verify the role of the gene on Al tolerance in gene-silenced rice and in overexpressed transgenic tobacco. The results showed an Al tolerance candidate gene, OsGERLP, was successfully cloned from rice cv. Hawara Bunar, with its gene encoding a protein similar to a bacterial ribosomal L32 protein. Additionally, the analysis showed that low gene expression caused the gene-silenced rice to be sensitive to Al, while high expression induced the Al tolerance in transgenic tobacco. Furthermore, it was discovered that the gene expression level in both plants was in line with the lower expression of the OsFRDL4 gene in the silenced rice and the high expression of the MATE gene in transgenic tobacco also with the higher citrate secretion from transgenic tobacco roots. In conclusion, the OsGERLP gene could act as a regulator for other Al tolerance genes, with the potential to develop Al-tolerant rice varieties.

The continuous evolution and spread of virulent forms of the soybean cyst nematode (SCN) driven by the environment and anthropogenic intervention is a serious threat to the soybean production worldwide, including China. Especially in China, the implemented measures to control SCN are insufficient for sustainable agricultural development yet. We summarized our knowledge about the spread and spatial distribution of SCN in China and the virulence diversity in the main soybean growing areas. To reveal the genetic relatedness and diversity of SCN populations, we re-sequenced 53 SCN genomes from the Huang-Huai Valleys, one of the two main soybean growing areas in China. We identified spreading patterns linked to the local agroecosystems and topographies. Moreover, we disclosed the first evidence for the selection of complex virulence in the field even under low selection pressure in an example from North Shanxi. SCN is present in all soybean growing areas in China but SCN susceptible cultivars are still largely grown indicating that SCN-related damage and financial loss have not received the attention they deserve yet. To prevent increasing yield losses and to improve the acceptance of resistant cultivars by the growers, we emphasized that it is time to accelerate SCN resistance breeding, planting resistant cultivars to a larger extent, and to support farmers to implement a wider crop rotation for sustainable development of the soybean production in China.

Southern root-knot nematode [SRKN, Meloidogyne incognita (Kofold & White) Chitwood] is a plant-parasitic nematode challenging to control due to its short life cycle, a wide range of hosts, and limited management options, of which genetic resistance is the main option to efficiently control the damage caused by SRKN. To date, a major quantitative trait locus (QTL) mapped on chromosome (Chr.) 10 plays an essential role in resistance to SRKN in soybean varieties. The confidence of discovered trait-loci associations by traditional methods is often limited by the assumptions of individual single nucleotide polymorphisms (SNPs) always acting independently as well as the phenotype following a Gaussian distribution. Therefore, the objective of this study was to conduct machine learning (ML)-based genome-wide association studies (GWAS) utilizing Random Forest (RF) and Support Vector Machine (SVM) algorithms to unveil novel regions of the soybean genome associated with resistance to SRKN. A total of 717 breeding lines derived from 330 unique bi-parental populations were genotyped with the Illumina Infinium BARCSoySNP6K BeadChip and phenotyped for SRKN resistance in a greenhouse. A GWAS pipeline involving a supervised feature dimension reduction based on Variable Importance in Projection (VIP) and SNP detection based on classification accuracy was proposed. Minor effect SNPs were detected by the proposed ML-GWAS methodology but not identified using Bayesian-information and linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Enriched Compressed Mixed Linear Model (ECMLM) models. Besides the genomic region on Chr. 10 that can explain most of SRKN resistance variance, additional minor effects SNPs were also identified on Chrs. 10 and 11. The findings in this study demonstrated that overfitting in GWAS may lead to lower prediction accuracy, and the detection of significant SNPs based on classification accuracy limited false-positive associations. The expansion of the basis of the genetic resistance to SRKN can potentially reduce the selection pressure over the major QTL on Chr. 10 and achieve higher levels of resistance.

Recent growth in crop genomic and trait data have opened opportunities for the application of novel approaches to accelerate crop improvement. Machine learning and deep learning are at the forefront of prediction-based data analysis. However, few approaches for genotype to phenotype prediction compare machine learning with deep learning and further interpret the models that support the predictions. This study uses genome wide molecular markers and traits across 1110 soybean individuals to develop accurate prediction models. For 13/14 sets of predictions, XGBoost or random forest outperformed deep learning models in prediction performance. Top ranked SNPs by F-score were identified from XGBoost, and with further investigation found overlap with significantly associated loci identified from GWAS and previous literature. Feature importance rankings were used to reduce marker input by up to 90%, and subsequent models maintained or improved their prediction performance. These findings support interpretable machine learning as an approach for genomic based prediction of traits in soybean and other crops.

Summary Pigeon pea (Cajanus cajan) is an important orphan crop mainly grown by smallholder farmers in India and Africa. Here, we present the first pigeon pea pangenome based on 89 accessions mainly from India and the Philippines, showing that there is significant genetic diversity in Philippine individuals that is not present in Indian individuals. Annotation of variable genes suggests that they are associated with self‐fertilization and response to disease. We identified 225 SNPs associated with nine agronomically important traits over three locations and two different time points, with SNPs associated with genes for transcription factors and kinases. These results will lead the way to an improved pigeon pea breeding programme.

This review provides a wide-ranging assessment of approaches to reduce the impact of heat stress on food crops., To ensure the food security of future generations and to address the challenge of the ‘no hunger zone’ proposed by the FAO (Food and Agriculture Organization), crop production must be doubled by 2050, but environmental stresses are counteracting this goal. Heat stress in particular is affecting agricultural crops more frequently and more severely. Since the discovery of the physiological, molecular, and genetic bases of heat stress responses, cultivated plants have become the subject of intense research on how they may avoid or tolerate heat stress by either using natural genetic variation or creating new variation with DNA technologies, mutational breeding, or genome editing. This review reports current understanding of the genetic and molecular bases of heat stress in crops together with recent approaches to creating heat-tolerant varieties. Research is close to a breakthrough of global relevance, breeding plants fitter to face the biggest challenge of our time.

Phenotypic variation and correlations among root traits form the basis for selecting and breeding soybean varieties with efficient access to water and nutrients and better adaptation to abiotic stresses. Therefore, it is important to develop a simple and consistent system to study root traits in soybean. In this study, we adopted the semi-hydroponic system to investigate the variability in root morphological traits of 171 soybean genotypes popularized in the Yangtze and Huaihe River regions, eastern China. Highly diverse phenotypes were observed: shoot height (18.7–86.7 cm per plant with a median of 52.3 cm); total root length (208–1663 cm per plant with a median of 885 cm); and root mass (dry weight) (19.4–251 mg per plant with a median of 124 mg). Both total root length and root mass exhibited significant positive correlation with shoot mass (p ≤ 0.05), indicating their relationship with plant growth and adaptation strategies. The nine selected traits contributed to one of the two principal components (eigenvalues > 1), accounting for 78.9% of the total genotypic variation. Agglomerative hierarchical clustering analysis separated the 171 genotypes into five major groups based on these root traits. Three selected genotypes with contrasting root systems were validated in soil-filled rhizoboxes (1.5 m deep) until maturity. Consistent ranking of the genotypes in some important root traits at various growth stages between the two experiments indicates the reliability of the semi-hydroponic system in phenotyping root trait variability at the early growth stage in soybean germplasms.

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306), map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020), identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single-reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.

In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome-wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole-genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single-nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)-like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker-assisted selection.

Summary Soybean cyst nematode (SCN) is the most devastating plant‐parasitic nematode. Most commercial soybean varieties with SCN resistance are derived from PI88788. Resistance derived from PI88788 is breaking down due to narrow genetic background and SCN population shift. PI88788 requires mainly the rhg1‐b locus, while ‘Peking’ requires rhg1‐a and Rhg4 for SCN resistance. In the present study, whole genome re‐sequencing of 106 soybean lines was used to define the Rhg haplotypes and investigate their responses to the SCN HG‐Types. The analysis showed a comprehensive profile of SNPs and copy number variations (CNV) at these loci. CNV of rhg1 (GmSNAP18) only contributed towards resistance in lines derived from PI88788 and ‘Cloud’. At least 5.6 copies of the PI88788‐type rhg1 were required to confer SCN resistance, regardless of the Rhg4 (GmSHMT08) haplotype. However, when the GmSNAP18 copies dropped below 5.6, a ‘Peking’‐type GmSHMT08 haplotype was required to ensure SCN resistance. This points to a novel mechanism of epistasis between GmSNAP18 and GmSHMT08 involving minimum requirements for copy number. The presence of more Rhg4 copies confers resistance to multiple SCN races. Moreover, transcript abundance of the GmSHMT08 in root tissue correlates with more copies of the Rhg4 locus, reinforcing SCN resistance. Finally, haplotype analysis of the GmSHMT08 and GmSNAP18 promoters inferred additional levels of the resistance mechanism. This is the first report revealing the genetic basis of broad‐based resistance to SCN and providing new insight into epistasis, haplotype‐compatibility, CNV, promoter variation and its impact on broad‐based disease resistance in plants.

Soybean seeds are rich in secondary metabolites which are beneficial for human health, including tocopherols. Tocopherols play an important role in human and animal nutrition thanks to their antioxidant activity. In this study, the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306) was used to map quantitative trait loci (QTL) for seed α-tocopherol, β-tocopherol, δ -tocopherol, γ-tocopherol, and total tocopherol contents in Carbondale, IL over two years. Also, the identification of the candidate genes involved in soybean tocopherols biosynthetic pathway was performed. A total of 32 QTL controlling various seed tocopherol contents have been identified and mapped on Chrs. 1, 2, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, and 20. One major and novel QTL was identified on Chr. 6 with an R2 of 27.8, 9.9, and 6.9 for δ-tocopherol, α-tocopherol, and total tocopherol content, respectively. Reverse BLAST analysis of the genes that were identified in Arabidopsis allowed the identification of 37 genes involved in soybean tocopherol pathway, among which 11 were located close to the identified QTLs. The tocopherol cyclase gene (TC) Glyma.06G084100 is located close to the QTLs controlling δ-tocopherol (R2 = 27.8), α-tocopherol (R2 = 9.96), and total-tocopherol (R2 = 6.95). The geranylgeranyl diphosphate reductase (GGDR) Glyma.05G026200 gene is located close to a QTL controlling total tocopherol content in soybean (R2 = 4.42). The two methylphytylbenzoquinol methyltransferase (MPBQ-MT) candidate genes Glyma.02G002000 and Glyma.02G143700 are located close to a QTL controlling δ-tocopherol content (R2 = 3.57). The two γ-tocopherol methyltransferase (γ-TMT) genes, Glyma.12G014200 and Glyma.12G014300, are located close to QTLs controlling (γ+ß) tocopherol content (R2 = 8.86) and total tocopherol (R2 = 5.94). The identified tocopherol seed QTLs and candidate genes will be beneficial in breeding programs to develop soybean cultivars with high tocopherol contents.

Symbiotic nitrogen fixation, which is carried out by the legume-rhizobia partnership, is a major source of nitrogen acquisition in natural ecosystems and in agriculture. The benefits to the plant gained through the rhizobial-legume symbiosis can be further enhanced by associations of the legume with arbuscular mycorrhiza. The progressive engagement of the legume host with the rhizobial bacteria and mycorrhizal fungi requires an extensive exchange of signalling molecules. These signals alter the transcriptional profiles of the partners, guiding and enabling extensive microbial and fungal proliferation in the roots. Such interactions and associations are greatly influenced by environmental stresses, which also severely limit the productivity of legume crops. Part II of the Special Issue on Legumes provides new insights into the mechanisms that underpin sustainable symbiotic partnerships, as well as the effects of abiotic stresses, such as drought, waterlogging, and salinity on legume biology. The requirement for germplasm and new breeding methods is discussed as well as the future of legume production in the face of climate change.

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.

Reniform nematode (RN, Rotylenchulus reniformis Linford & Oliveira) has emerged as one of the most important plant parasitic nematodes of soybean [Glycine max (L.) Merr.]. Planting resistant varieties is the most effective strategy for nematode management. The objective of this study was to identify quantitative trait loci (QTL) for RN resistance in an exotic soybean line, PI 438489B, using two linkage maps constructed from the Universal Soybean Linkage Panel (USLP 1.0) and next‐generation whole‐genome resequencing (WGRS) technology. Two QTL controlling RN resistance were identified—the soybean cyst nematode (SCN, Heterodera glycines) resistance gene GmSNAP18 at the rhg1 locus and its paralog GmSNAP11. Strong association between resistant phenotype and haplotypes of the GmSNAP11 and GmSNAP18 was observed. The results indicated that GmSNAP11 possibly could have epistatic effect on GmSNAP18, or vice versa, with the presence of a significant correlation in RN resistance of rhg1‐a GmSNAP18 vs. rhg1‐b GmSNAP18. Most importantly, our preliminary data suggested that GmSNAP18 and GmSNAP11 proteins physically interact in planta, suggesting that they belong to the same pathway for resistance. Unlike GmSNAP18, no indication of GmSNAP11 copy number variation was found. Moreover, gene‐based single nucleotide polymorphism (SNP) markers were developed for rapid detection of RN or SCN resistance at these loci. Our analysis substantiates synergic interaction between GmSNAP11 and GmSNAP18 genes and confirms their roles in RN as well as SCN resistance. These results could contribute to a better understanding of evolution and subfunctionalization of genes conferring resistance to multiple nematode species and provide a framework for further investigations.

The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soybean accessions derived from the USDA Soybean Germplasm Collection, including both wild and cultivated lineages, to assess genomewide changes in gene and allele frequency during domestication and breeding. We identified 3,765 genes that are absent from the Lee reference genome assembly and assessed the presence/absence of all genes across this population. In addition to a loss of genetic diversity, we found a significant reduction in the average number of protein-coding genes per individual during domestication and subsequent breeding, though with some genes and allelic variants increasing in frequency associated with selection for agronomic traits. This analysis provides a genomic perspective of domestication and breeding in this important oilseed crop.

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Aluminium (Al) toxicity inhibits soybean root growth, leading to insufficient water and nutrient uptake. Two soybean lines (‘Magellan’ and PI 567731) were identified differing in Al tolerance, as determined by primary root length ratio, total root length ratio, and root tip number ratio under Al stress. Serious root necrosis was observed in PI 567731, but not in Magellan under Al stress. An F8 recombinant inbred line population derived from a cross between Magellan and PI 567731 was used to map the quantitative trait loci (QTL) for Al tolerance. Three QTL on chromosomes 3, 13, and 20, with tolerant alleles from Magellan, were identified. qAl_Gm13 and qAl_Gm20 explained large phenotypic variations (13–27%) and helped maintain root elongation and initiation under Al stress. In addition, qAl_Gm13 and qAl_Gm20 were confirmed in near-isogenic backgrounds and were identified to epistatically regulate Al tolerance via internal detoxification instead of Al3+ exclusion. Phylogenetic and pedigree analysis identified the tolerant alleles of both loci derived from the US ancestral line, A.K.[FC30761], originally from China. Our results provide novel genetic resources for breeding Al-tolerant soybean and suggest that internal detoxification contributes to soybean tolerance to excessive soil Al.

Transporters, a class of membrane proteins that facilitate exchange of solutes including diverse molecules and ions across the cellular membrane, are vital component for the survival of all organisms. Understanding plant transporters is important to get insight of the basic cellular processes, physiology, and molecular mechanisms including nutrient uptake, signaling, response to external stress, and many more. In this regard, extensive analysis of transporters predicted in soybean and other plant species was performed. In addition, an integrated database for soybean transporter protein, SoyTD, was developed that will facilitate the identification, classification, and extensive characterization of transporter proteins by integrating expression, gene ontology, conserved domain and motifs, gene structure organization, and chromosomal distribution features. A comprehensive analysis was performed to identify highly confident transporters by integrating various prediction tools. Initially, 7541 transmembrane (TM) proteins were predicted in the soybean genome; out of these, 3306 non-redundant transporter genes carrying two or more transmembrane domains were selected for further analysis. The identified transporter genes were classified according to a standard transporter classification (TC) system. Comparative analysis of transporter genes among 47 plant genomes provided insights into expansion and duplication of transporter genes in land plants. The whole genome resequencing (WGRS) and tissue-specific transcriptome datasets of soybean were integrated to investigate the natural variants and expression profile associated with transporter(s) of interest. Overall, SoyTD provides a comprehensive interface to study genetic and molecular function of soybean transporters. SoyTD is publicly available at http://artemis.cyverse.org/soykb_dev/SoyTD/.

Over the past 70 years, the world has witnessed extraordinary growth in crop productivity, enabled by a suite of technological advances, including higher yielding crop varieties, improved farm management, synthetic agrochemicals, and agricultural mechanization. While this “Green Revolution” intensified crop production, and is credited with reducing famine and malnutrition, its benefits were accompanied by several undesirable collateral effects (Pingali, 2012). These include a narrowing of agricultural biodiversity, stemming from increased monoculture and greater reliance on a smaller number of crops and crop varieties for the majority of our calories. This reduction in diversity has created vulnerabilities to pest and disease epidemics, climate variation, and ultimately to human health (Harlan, 1972). The value of crop diversity has long been recognized (Vavilov, 1992). A global system of genebanks (e.g., www.genebanks.org/genebanks/) was established in the 1970s to conserve the abundant genetic variation found in traditional “landrace” varieties of crops and in crop wild relatives (Harlan, 1972). While preserving crop variation is a critical first step, the time has come to make use of this variation to breed more resilient crops. The DivSeek International Network (https://divseekintl.org/) is a scientific, not-for-profit organization that aims to accelerate such efforts.

Wild soybean species (Glycine soja Siebold & Zucc.) comprise a unique resource to widen the genetic base of cultivated soybean [Glycine max (L.) Merr.] for various agronomic traits. An inter-specific mapping population derived from a cross of cultivar Williams 82 and PI 483460B, a wild soybean accession, was utilized for genetic characterization of root architecture traits. The objectives of this study were to identify and characterize quantitative trait loci (QTL) for seedling shoot and root architecture traits, as well as to determine additive/epistatic interaction effects of identified QTLs. A total of 16,469 single nucleotide polymorphisms (SNPs) developed for the Illumina beadchip genotyping platform were used to construct a high resolution genetic linkage map. Among the 11 putative QTLs identified, two significant QTLs on chromosome 7 were determined to be associated with total root length (RL) and root surface area (RSA) with favorable alleles from the wild soybean parent. These seedling root traits, RL (BARC_020495_04641 ~ BARC_023101_03769) and RSA (SNP02285 ~ SNP18129_Magellan), could be potential targets for introgression into cultivated soybean background to improve both tap and lateral roots. The RL QTL region harbors four candidate genes with higher expression in root tissues: Phosphofructokinase (Glyma.07g126400), Snf7 protein (Glyma.07g127300), unknown functional gene (Glyma.07g127900), and Leucine Rich-Repeat protein (Glyma.07g127100). The novel alleles inherited from the wild soybean accession could be used as molecular markers to improve root system architecture and productivity in elite soybean lines.

Flooding threatens soybean production and limits soybean yields worldwide. The most effective and economic approach to decrease loss of yield due to flooding is to develop flood-tolerant soybean cultivars. The objective of this study was to identify genetic loci and candidate genes associated with flooding tolerance. A panel of 384 soybean plant introductions (PIs) was evaluated for flooding tolerance in two consecutive years in the field. The plant foliar damage score was used to index soybean response to flooding stress. A total of 42,291 SNP markers were obtained from the Illumina Infinium SoySNP50K BeadChip database. After filtration for quality control, 31,125 SNPs were used for genome-wide association mapping utilizing four different models (regression linear model (GLM), mixed linear model (MLM), compressed mixed linear model (CMLM), and enriched compressed mixed linear model (ECMLM)). Fourteen SNPs were identified to be associated with flooding tolerance across all environments and models at a significance level of −Log10 (P) ≥ 2.5. Five SNPs were located within the coding regions of five candidate genes. Several PIs with lower best linear unbiased prediction (BLUPs) of the breeding values and a large number of favorable flood-tolerant alleles were found as new genetic sources for use in soybean breeding programs.

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNPs)-based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter Class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, 3 significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem, and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions.

Summary The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil, and high sucrose. In this study, an interspecific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3× depth. Based on 91 342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high‐resolution bin map was developed (4070 bins). In addition to bin mapping, quantitative trait loci (QTL) analysis for protein, oil, and sucrose was performed using 3343 polymorphic SNPs (3K‐SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared, and a significant concordance was observed between bin and 3K‐SNP markers. Importantly, the bin map derived from next‐generation sequencing technology enhanced mapping resolution (from 1325 to 50 Kb). A total of five, nine, and four QTLs were identified for protein, oil, and sucrose content, respectively, and some of the QTLs coincided with soybean domestication‐related genomic loci. The major QTL for protein and oil were mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL were identified on Chr. 8 (qSuc_08) and harbours putative genes involved in sugar transport. In addition, genome‐wide association using 91 342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL‐based haplotype using whole‐genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean.

Soybean (Glycine max [L.] Merr.) cultivars are generally sensitive to flooding stress. The plant growth is severely affected and grain yield is largely reduced in the flooded field. It is important to develop flood-tolerant soybean cultivars for grain production in regions of heavy rainfalls worldwide. In this study, a total of 722 soybean genotypes were evaluated for flooding tolerance at R1 stages (first flower at any node) in the 5-year flooding screening tests. Differential soybean genotypes exhibited diverse responses to flooding stress with that plant foliar damage score (FDS) and plant survival rate (PSR) ranged from 1.9 to 8.8 and 3.4% to 81.7%, respectively (p

Summary Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole‐genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single‐nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1‐Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene‐centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss‐of‐function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.

Background Brassinosteroids (BRs) play a crucial role in plant vegetative growth and reproductive development. The transcription factors BZR1 and BES1/BZR2 are well characterized as downstream regulators of the BR signaling pathway in Arabidopsis and rice. Soybean contains four BZR1-like proteins (GmBZLs), and it was reported that GmBZL2 plays a conserved role in BR signaling regulation. However, the roles of other GmBZLs have not been thoroughly studied, and the targets of GmBZLs in soybean remain unclear. Results In this study, we first characterized GmBZL3 in soybean from gene expression patterns, conserved domains in coding sequences, and genomic replication times of four GmBZL orthologous. The results indicated that GmBZL3 might play conserved roles during soybean development. The overexpression of GmBZL3P219L in the Arabidopsis BR-insensitive mutant bri1–5 partially rescued the phenotypic defects including BR-insensitivity, which provides further evidence that GmBZL3 functions are conserved between soybean and the homologous Arabidopsis genes. In addition, the identification of the GmBZL3 target genes through ChIP-seq technology revealed that BR has broad roles in soybean and regulates multiple pathways, including other hormone signaling, disease-related, and immunity response pathways. Moreover, the BR-regulated GmBZL3 target genes were further identified, and the results demonstrate that GmBZL3 is a major transcription factor responsible for BR-regulated gene expression and soybean growth. A comparison of GmBZL3 and AtBZR1/BES1 targets demonstrated that GmBZL3 might play conserved as well as specific roles in the soybean BR signaling network. Finally, the identification of two natural soybean varieties of the GmBZL3 mutantion by SNP analysis could facilitate the understanding of gene function during soybean development in the future. Conclusions We illustrate here that GmBZL3 orchestrates a genome-wide transcriptional response that underlies BR-mediated soybean early vegetative growth, and our results support that BRs play crucial regulatory roles in soybean morphology and gene expression levels. Electronic supplementary material The online version of this article (10.1186/s12870-019-1677-2) contains supplementary material, which is available to authorized users.

We report reference-quality genome assemblies and annotations for two accessions of soybean (Glycine max) and for one accession of Glycine soja, the closest wild relative of G.max. The G.max assemblies provided are for widely used US cultivars: the northern line Williams82 (Wm82) and the southern line Lee. The Wm82 assembly improves the prior published assembly, and the Lee and G.soja assemblies are new for these accessions. Comparisons among the three accessions show generally high structural conservation, but nucleotide difference of 1.7single-nucleotide polymorphisms (snps) per kb between Wm82 and Lee, and 4.7snpsperkb between these lines and G.soja. snp distributions and comparisons with genotypes of the Lee and Wm82 parents highlight patterns of introgression and haplotype structure. Comparisons against the US germplasm collection show placement of the sequenced accessions relative to global soybean diversity. Analysis of a pan-gene collection shows generally high conservation, with variation occurring primarily in genomically clustered gene families. We found approximately 40-42 inversions per chromosome between either Lee or Wm82v4 and G.soja, and approximately 32 inversions per chromosome between Wm82 and Lee. We also investigated five domestication loci. For each locus, we found two different alleles with functional differences between G.soja and the two domesticated accessions. The genome assemblies for multiple cultivated accessions and for the closest wild ancestor of soybean provides a valuable set of resources for identifying causal variants that underlie traits for the domestication and improvement of soybean, serving as a basis for future research and crop improvement efforts for this important crop species.

Slow canopy wilting (SW) is a water conservation trait controlled by quantitative trait loci (QTLs) in late maturity group soybeans [Glycine max (L.) Merr.]. Recently, two exotic (landraces) plant introductions (PI 567690 and PI 567731) were identified as new SW lines in early maturity groups. Here, we show that the two PIs share the same water conservation strategy of limited maximum transpiration rates as PI 416937. However, in contrast to PI 416937, the transpiration rates of these PIs were sensitive to an aquaporin inhibitor, indicating an independence between limited maximum transpiration and the lack of silver-sensitive aquaporins. Yield tests of selected recombinant inbred lines from two elite/exotic crosses provide direct evidence to support the benefit of SW in drought tolerance. Four SW QTLs mapped in a Pana×PI 567690 cross at multiple environments were found to be co-located with previous reports. Moreover, two new SW QTLs were mapped on chromosomes 6 and 10 from a Magellan×PI 567731 cross. These two QTLs explain the observed relatively large contributions of 20-30% and were confirmed in a near-isogenic background. These findings demonstrate the importance of SW in yield protection under drought and provide genetic resources for improving drought tolerance in early maturity group soybeans.

Wheat breeding nowadays must address producers and consumers' desire. According to the last FAO report, a dramatic decrease in wheat production is expected in the next decades mainly due to the upcoming climate change. The identification of the processes which are triggered by heat stress and how thermotolerance develops in wheat is an active research topic. Genomic approach may help wheat breeding since it allows direct study on the genotype and relationship with the phenotype. Here the isolation and characterization of four members of the chloroplast-localized small heat shock proteins (sHSP) encoded by the Hsp26 gene family is reported. Furthermore, two high throughput TILLING (Targeting Induced Local Lesions In Genomes) approaches in vivo and in silico were used for the identification of new alleles within this family. Small heat shock proteins are known to prevent the irreversible aggregation of misfolded proteins and contribute to the acquisition of thermotolerance. Chloroplast-localized sHSPs protect the photosynthetic machinery during episodes of high temperature stress. The modulation of the newly discovered genes within the sHsp26 family has been analyzed in vivo and by the ExpVIP platform widening the abiotic stress analysis; and their involvement in the heat stress response has been demonstrated. In addition, in this study a total of 50 TILLING mutant lines have been identified. A set of KASP (Kompetitive Allele Specific PCR) markers was also developed to follow the specific mutations in the ongoing backcrosses, applicable to high throughput genotyping approaches and usable in marker assisted selection breeding programs.

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

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.

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.

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.

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.

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.

Drought provokes a number of physiological changes in plants including oxidative damage. Ascorbic acid (AsA), also known as vitamin C, is one of the most abundant water-soluble antioxidant compound present in plant tissues. However, little is known on the regulation of AsA biosynthesis under drought stress conditions. In the current work we analyze the effects of water deficit on the biosynthesis of AsA by measuring its content, in vivo biosynthesis and the expression level of genes in the Smirnoff-Wheeler pathway in one of the major legume crop, soybean (Glycine max L. Merr). Since the pathway has not been described in legumes, we first searched for the putative orthologous genes in the soybean genome. We observed a significant genetic redundancy, with multiple genes encoding each step in the pathway. Based on RNA-seq analysis, expression of the complete pathway was detected not only in leaves but also in root tissue. Putative paralogous genes presented differential expression patterns in response to drought, suggesting the existence of functional specialization mechanisms. We found a correlation between the levels of AsA and GalLDH biosynthetic rates in leaves of drought-stressed soybean plants. However, the levels of GalLDH transcripts did not show significant differences under water deficit conditions. Among the other known regulators of the pathway, only the expression of VTC1 genes correlated with the observed decline in AsA in leaves. This work was supported by the Spanish Ministry of Economy and Competitiveness (AGL 2011–23738 to EG and a “Juan de la Cierva” JCI-2012-13175 post-doctoral contract to EL) the Fundación Caja Navarra project FCN2016-7442 to EG and the project 2016/PI013 LEGUMINOSAS from the Government of Navarra to EL. AS received a Ph.D. fellowship from the Public University of Navarra (1287/2011).

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.