Development of a Standardized Soybean Cyst Nematode Screening Assay in Pennycress and Identification of Resistant Germplasm.

The prospect of incorporating pennycress as an oilseed cover crop in the Midwest's corn-soybean rotation system has drawn researcher and farmer attention. The inclusion of pennycress will be beneficial as it provides an excellent soil cover to reduce soil erosion and nutrient leaching while serving as an additional source for oilseed production and income. However, pennycress is an alternative host for soybean cyst nematode (SCN), which is a major biological threat to soybean that needs to be addressed for sustainable pennycress adoption into our current production systems. To develop a standardized SCN resistance screening strategy in pennycress, we tested and optimized five parameters: (i) germination stimulants, (ii) inoculation timing, (iii) inoculation rate, (iv) experimental incubation time, and (v) susceptible checks. The standardized SCN resistance screening protocol includes the following: (i) treating pennycress seeds with gibberellic acid for 24 h, (ii) transplanting seedlings 12 to 15 days after initiating germination and inoculating 10 to 12 days after transplantation, (iii) inoculating at a rate of 1,500 eggs/100 cc soil (1,500 eggs per plant), (iv) processing roots at 30 days after inoculation, and (v) using susceptible pennycress accession Ames 32869 to calculate the female index. The standardized protocol was used to quantify the response of a diverse set of pennycress accessions for response against SCN HG type 1.2.5.7 and HG type 7. While there were no highly resistant pennycress lines identified, 15 were rated as moderately resistant to HG type 1.2.5.7, and eight were rated moderately resistant to HG type 7. The resistant lines identified in this study could be utilized to develop SCN-resistant pennycress cultivars. The study also opens a new avenue for research to understand SCN-pennycress interactions through molecular and genomic studies. This knowledge could aid in the successful inclusion of pennycress as a beneficial cover/oilseed crop in the United States Midwest.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Bowman-Birk Inhibitor Mutants of Soybean Generated by CRISPR-Cas9 Reveal Drastic Reductions in Trypsin and Chymotrypsin Inhibitor Activities.

Despite the high quality of soybean protein, raw soybeans and soybean meal cannot be directly included in animal feed mixtures due to the presence of Kunitz (KTi) and Bowman-Birk protease inhibitors (BBis), which reduces animal productivity. Heat treatment can substantially inactivate trypsin and chymotrypsin inhibitors (BBis), but such treatment is energy-intensive, adds expense, and negatively impacts the quality of seed proteins. As an alternative approach, we have employed CRISPR/Cas9 gene editing to create mutations in BBi genes to drastically lower the protease inhibitor content in soybean seed. Agrobacterium-mediated transformation was used to generate several stable transgenic soybean events. These independent CRISPR/Cas9 events were examined in comparison to wild-type plants using Sanger sequencing, proteomic analysis, trypsin/chymotrypsin inhibitor activity assays, and qRT-PCR. Collectively, our results demonstrate the creation of an allelic series of loss-of-function mutations affecting the major BBi gene in soybean. Mutations in two of the highly expressed seed-specific BBi genes lead to substantial reductions in both trypsin and chymotrypsin inhibitor activities.

Genomic prediction models for traits differing in heritability for soybean, rice, and maize.

BACKGROUND: Genomic selection is a powerful tool in plant breeding. By building a prediction model using a training set with markers and phenotypes, genomic estimated breeding values (GEBVs) can be used as predictions of breeding values in a target set with only genotype data. There is, however, limited information on how prediction accuracy of genomic prediction can be optimized. The objective of this study was to evaluate the performance of 11 genomic prediction models across species in terms of prediction accuracy for two traits with different heritabilities using several subsets of markers and training population proportions. Species studied were maize (Zea mays, L.), soybean (Glycine max, L.), and rice (Oryza sativa, L.), which vary in linkage disequilibrium (LD) decay rates and have contrasting genetic architectures. RESULTS: Correlations between observed and predicted GEBVs were determined via cross validation for three training-to-testing proportions (90:10, 70:30, and 50:50). Maize, which has the shortest extent of LD, showed the highest prediction accuracy. Amongst all the models tested, Bayes B performed better than or equal to all other models for each trait in all the three crops. Traits with higher broad-sense and narrow-sense heritabilities were associated with higher prediction accuracy. When subsets of markers were selected based on LD, the accuracy was similar to that observed from the complete set of markers. However, prediction accuracies were significantly improved when using a subset of total markers that were significant at P ≤ 0.05 or P ≤ 0.10. As expected, exclusion of QTL-associated markers in the model reduced prediction accuracy. Prediction accuracy varied among different training population proportions. CONCLUSIONS: We conclude that prediction accuracy for genomic selection can be improved by using the Bayes B model with a subset of significant markers and by selecting the training population based on narrow sense heritability.

Epistatic interaction between Rhg1-a and Rhg2 in PI 90763 confers resistance to virulent soybean cyst nematode populations.

KEY MESSAGE: An epistatic interaction between SCN resistance loci rhg1-a and rhg2 in PI 90763 imparts resistance against virulent SCN populations which can be employed to diversify SCN resistance in soybean cultivars. With more than 95% of the $46.1B soybean market dominated by a single type of genetic resistance, breeding for soybean cyst nematode (SCN)-resistant soybean that can effectively combat the widespread increase in virulent SCN populations presents a significant challenge. Rhg genes (for Resistance to Heterodera glycines) play a key role in resistance to SCN; however, their deployment beyond the use of the rhg1-b allele has been limited. In this study, quantitative trait loci (QTL) were mapped using PI 90763 through two biparental F3:4 recombinant inbred line (RIL) populations segregating for rhg1-a and rhg1-b alleles against a SCN HG type 1.2.5.7 (Race 2) population. QTL located on chromosome 18 (rhg1-a) and chromosome 11 (rhg2) were determined to confer SCN resistance in PI 90763. The rhg2 gene was fine-mapped to a 169-Kbp region pinpointing GmSNAP11 as the strongest candidate gene. We demonstrated a unique epistatic interaction between rhg1-a and rhg2 loci that not only confers resistance to multiple virulent SCN populations. Further, we showed that pyramiding rhg2 with the conventional mode of resistance, rhg1-b, is ineffective against these virulent SCN populations. This highlights the importance of pyramiding rhg1-a and rhg2 to maximize the impact of gene pyramiding strategies toward management of SCN populations virulent on rhg1-b sources of resistance. Our results lay the foundation for the next generation of soybean resistance breeding to combat the number one pathogen of soybean.

Genomic prediction using training population design in interspecific soybean populations.

Agronomically important traits generally have complex genetic architecture, where many genes have a small and largely additive effect. Genomic prediction has been demonstrated to increase genetic gain and efficiency in plant breeding programs beyond marker-assisted selection and phenotypic selection. The objective of this study was to evaluate the impact of allelic origin, marker density, training population size, and cross-validation schemes on the accuracy of genomic prediction models in an interspecific soybean nested association mapping (NAM) panel. Three cross-validation schemes were used: (a) Within-Family (WF): training population and predictions are made exclusively within each family; (b) Across All families (AF): all the individuals from the three families were randomly assigned to either the training or validation set; (c) Leave one Family out (LFO): each family is predicted using a training set that contains the other two families. Predictive abilities increased with training population size up to 350 individuals, but no significant gains were noted beyond 250 individuals in the training population. The number of markers had a limited impact on the observed predictive ability across traits; increasing markers used in the model above 1000 revealed no significant increases in prediction accuracy. Predictive abilities for AF were not significantly different from the WF method, and predictive abilities across populations for the WF method had a range of 0.58 to 0.70 for maturity, protein, meal, and oil. Our results also showed encouraging prediction accuracies for grain yield (0.58-0.69) using the WF method. Partitioning genomic prediction between G. max and G. soja alleles revealed useful information to select material with a larger allele contribution from both parents and could accelerate allele introgression from exotic germplasm into the elite soybean gene pool. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01203-6.

Nested association mapping of important agronomic traits in three interspecific soybean populations.

KEY MESSAGE: Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.

Effect of Heat Stress on Seed Protein Composition and Ultrastructure of Protein Storage Vacuoles in the Cotyledonary Parenchyma Cells of Soybean Genotypes That Are Either Tolerant or Sensitive to Elevated Temperatures.

High growth temperatures negatively affect soybean (Glycine max (L.) Merr) yields and seed quality. Soybean plants, heat stressed during seed development, produce seed that exhibit wrinkling, discoloration, poor seed germination, and have an increased potential for incidence of pathogen infection and an overall decrease in economic value. Soybean breeders have identified a heat stress tolerant exotic landrace genotype, which has been used in traditional hybridization to generate experimental genotypes, with improved seed yield and heat tolerance. Here, we have investigated the seed protein composition and ultrastructure of cotyledonary parenchyma cells of soybean genotypes that are either susceptible or tolerant to high growth temperatures. Biochemical analyses of seed proteins isolated from heat-tolerant and heat-sensitive genotypes produced under 28/22 °C (control), 36/24 °C (moderate), and 42/26 °C (extreme) day/night temperatures revealed that the accumulation in soybean seeds of lipoxygenase, the ß-subunit of ß-conglycinin, sucrose binding protein and Bowman-Birk protease inhibitor were negatively impacted by extreme heat stress in both genotypes, but these effects were less pronounced in the heat-tolerant genotype. Western blot analysis showed elevated accumulation of heat shock proteins (HSP70 and HSP17.6) in both lines in response to elevated temperatures during seed fill. Transmission electron microscopy showed that heat stress caused dramatic structural changes in the storage parenchyma cells. Extreme heat stress disrupted the structure and the membrane integrity of protein storage vacuoles, organelles that accumulate seed storage proteins. The detachment of the plasma membrane from the cell wall (plasmolysis) was commonly observed in the cells of the sensitive line. In contrast, these structural changes were less pronounced in the tolerant genotype, even under extreme heat stress, cells, for the most part, retained their structural integrity. The results of our study demonstrate the contrasting effects of heat stress on the seed protein composition and ultrastructural alterations that contribute to the tolerant genotype's ability to tolerate high temperatures during seed development.

Demonstration of highly efficient dual gRNA CRISPR/Cas9 editing of the homeologous GmFAD2-1A and GmFAD2-1B genes to yield a high oleic, low linoleic and α-linolenic acid phenotype in soybean.

BACKGROUND: CRISPR/Cas9 gene editing is now revolutionizing the ability to effectively modify plant genomes in the absence of efficient homologous recombination mechanisms that exist in other organisms. However, soybean is allotetraploid and is commonly viewed as difficult and inefficient to transform. In this study, we demonstrate the utility of CRISPR/Cas9 gene editing in soybean at relatively high efficiency. This was shown by specifically targeting the Fatty Acid Desaturase 2 (GmFAD2) that converts the monounsaturated oleic acid (C18:1) to the polyunsaturated linoleic acid (C18:2), therefore, regulating the content of monounsaturated fats in soybean seeds. RESULTS: We designed two gRNAs to guide Cas9 to simultaneously cleave two sites, spaced 1Kb apart, within the second exons of GmFAD2-1A and GmFAD2-1B. In order to test whether the Cas9 and gRNAs would perform properly in transgenic soybean plants, we first tested the CRISPR construct we developed by transient hairy root transformation using Agrobacterium rhizogenesis strain K599. Once confirmed, we performed stable soybean transformation and characterized ten, randomly selected T0 events. Genotyping of CRISPR/Cas9 T0 transgenic lines detected a variety of mutations including large and small DNA deletions, insertions and inversions in the GmFAD2 genes. We detected CRISPR- edited DNA in all the tested T0 plants and 77.8% of the events transmitted the GmFAD2 mutant alleles to T1 progenies. More importantly, null mutants for both GmFAD2 genes were obtained in 40% of the T0 plants we genotyped. The fatty acid profile analysis of T1 seeds derived from CRISPR-edited plants homozygous for both GmFAD2 genes showed dramatic increases in oleic acid content to over 80%, whereas linoleic acid decreased to 1.3-1.7%. In addition, transgene-free high oleic soybean homozygous genotypes were created as early as the T1 generation. CONCLUSIONS: Overall, our data showed that dual gRNA CRISPR/Cas9 system offers a rapid and highly efficient method to simultaneously edit homeologous soybean genes, which can greatly facilitate breeding and gene discovery in this important crop plant.

Deletion of the SACPD-C Locus Alters the Symbiotic Relationship Between Bradyrhizobium japonicum USDA110 and Soybean, Resulting in Elicitation of Plant Defense Response and Nodulation Defects.

Legumes form symbiotic associations with soil-dwelling bacteria collectively called rhizobia. This association results in the formation of nodules, unique plant-derived organs, within which the rhizobia are housed. Rhizobia-encoded nitrogenase facilitates the conversion of atmospheric nitrogen into ammonia, which is utilized by the plants for its growth and development. Fatty acids have been shown to play an important role in root nodule symbiosis. In this study, we have investigated the role of stearoyl-acyl carrier protein desaturase isoform C (SACPD-C), a soybean enzyme that catalyzes the conversion of stearic acid into oleic acid, which is expressed in developing seeds and in nitrogen-fixing nodules. In-depth cytological investigation of nodule development in sacpd-c mutant lines M25 and MM106 revealed gross anatomical alteration in the sacpd-c mutants. Transmission electron microscopy observations revealed ultrastructural alterations in the sacpd-c mutants that are typically associated with plant defense response to pathogens. In nodules of two sacpd-c mutants, the combined jasmonic acid (JA) species (JA and the isoleucine conjugate of JA) were found to be reduced and 12-oxophytodienoic acid (OPDA) levels were significantly higher relative to wild-type lines. Salicylic acid levels were not significantly different between genotypes, which is divergent from previous studies of sacpd mutant studies on vegetative tissues. Soybean nodule phytohormone profiles were very divergent from those of roots, and root profiles were found to be almost identical between mutant and wild-type genotypes. The activities of antioxidant enzymes, ascorbate peroxidase, and superoxide dismutase were also found to be higher in nodules of sacpd-c mutants. PR-1 gene expression was extremely elevated in M25 and MM106, while the expression of nitrogenase was significantly reduced in these sacpd-c mutants, compared with the parent 'Bay'. Two-dimensional gel electrophoresis and matrix-assisted laser desorption-ionization time of flight mass spectrometry analyses confirmed sacpd-c mutants also accumulated higher amounts of pathogenesis-related proteins in the nodules. Our study establishes a major role for SACPD-C activity as essential for proper maintenance of soybean nodule morphology and physiology and indicates that OPDA signaling is likely to be involved in attenuation of nodule biotic defense responses.

Deletions of the SACPD-C locus elevate seed stearic acid levels but also result in fatty acid and morphological alterations in nitrogen fixing nodules.

BACKGROUND: Soybean (Glycine max) seeds are the primary source of edible oil in the United States. Despite its widespread utility, soybean oil is oxidatively unstable. Until recently, the majority of soybean oil underwent chemical hydrogenation, a process which also generates trans fats. An alternative to chemical hydrogenation is genetic modification of seed oil through identification and introgression of mutant alleles. One target for improvement is the elevation of a saturated fat with no negative cardiovascular impacts, stearic acid, which typically constitutes a minute portion of seed oil (~3%). RESULTS: We examined radiation induced soybean mutants with moderately increased stearic acid (10-15% of seed oil, ~3-5 X the levels in wild-type soybean seeds) via comparative whole genome hybridization and genetic analysis. The deletion of one SACPD isoform encoding gene (SACPD-C) was perfectly correlated with moderate elevation of seed stearic acid content. However, SACPD-C deletion lines were also found to have altered nodule fatty acid composition and grossly altered morphology. Despite these defects, overall nodule accumulation and nitrogen fixation were unaffected, at least under laboratory conditions. CONCLUSIONS: Although no yield penalty has been reported for moderate elevated seed stearic acid content in soybean seeds, our results demonstrate that genetic alteration of seed traits can have unforeseen pleiotropic consequences. We have identified a role for fatty acid biosynthesis, and SACPD activity in particular, in the establishment and maintenance of symbiotic nitrogen fixation.

Identification of genomic regions associated with the plasticity of carbon 13 ratio in soybean.

Improving water use efficiency (WUE) for soybean [Glycine max (L.) Merr.] through selection for high carbon isotope (C13) ratio may increase drought tolerance, but increased WUE may limit growth in productive environments. An ideal genotype would be plastic for C13 ratio; that is, be able to alter C13 ratio in response to the environment. Our objective was to identify genomic regions associated with C13 ratio plasticity, C13 ratio stability, and overall C13 ratio in two panels of diverse Maturity Group IV soybean accessions. A second objective was to identify accessions that differed in their C13 ratio plasticity. Panel 1 (205 accessions) was evaluated in seven irrigated and four drought environments, and Panel 2 (373 accessions) was evaluated in four environments. Plasticity was quantified as the slope from regressing C13 ratio of individual genotypes against an environmental index calculated based on the mean within and across environments. The regression intercept was considered a measure of C13 ratio over all environments, and the root mean square error was considered a measure of stability. Combined over both panels, genome-wide association mapping (GWAM) identified 19 single nucleotide polymorphisms (SNPs) for plasticity, 39 SNPs for C13 ratio, and 16 SNPs for stability. Among these SNPs, 71 candidate genes had annotations associated with transpiration or water conservation and transport, root development, root hair elongation, and stomatal complex morphogenesis. The genomic regions associated with plasticity and stability identified in the current study will be a useful resource for implementing genomic selection for improving drought tolerance in soybean.

Loss-of-function of an α-SNAP gene confers resistance to soybean cyst nematode.

Plant-parasitic nematodes are one of the most economically impactful pests in agriculture resulting in billions of dollars in realized annual losses worldwide. Soybean cyst nematode (SCN) is the number one biotic constraint on soybean production making it a priority for the discovery, validation and functional characterization of native plant resistance genes and genetic modes of action that can be deployed to improve soybean yield across the globe. Here, we present the discovery and functional characterization of a soybean resistance gene, GmSNAP02. We use unique bi-parental populations to fine-map the precise genomic location, and a combination of whole genome resequencing and gene fragment PCR amplifications to identify and confirm causal haplotypes. Lastly, we validate our candidate gene using CRISPR-Cas9 genome editing and observe a gain of resistance in edited plants. This demonstrates that the GmSNAP02 gene confers a unique mode of resistance to SCN through loss-of-function mutations that implicate GmSNAP02 as a nematode virulence target. We highlight the immediate impact of utilizing GmSNAP02 as a genome-editing-amenable target to diversify nematode resistance in commercially available cultivars.

Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession.

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line ('Osage') with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

Loss-of-function mutations affecting a specific Glycine max R2R3 MYB transcription factor result in brown hilum and brown seed coats.

BACKGROUND: Although modern soybean cultivars feature yellow seed coats, with the only color variation found at the hila, the ancestral condition is black seed coats. Both seed coat and hila coloration are due to the presence of phenylpropanoid pathway derivatives, principally anthocyanins. The genetics of soybean seed coat and hilum coloration were first investigated during the resurgence of genetics during the 1920s, following the rediscovery of Mendel's work. Despite the inclusion of this phenotypic marker into the extensive genetic maps developed for soybean over the last twenty years, the genetic basis behind the phenomenon of brown seed coats (the R locus) has remained undetermined until now. RESULTS: In order to identify the gene responsible for the r gene effect (brown hilum or seed coat color), we utilized bulk segregant analysis and identified recombinant lines derived from a population segregating for two phenotypically distinct alleles of the R locus. Fine mapping was accelerated through use of a novel, bioinformatically determined set of Simple Sequence Repeat (SSR) markers which allowed us to delimit the genomic region containing the r gene to less than 200 kbp, despite the use of a mapping population of only 100 F6 lines. Candidate gene analysis identified a loss of function mutation affecting a seed coat-specific expressed R2R3 MYB transcription factor gene (Glyma09g36990) as a strong candidate for the brown hilum phenotype. We observed a near perfect correlation between the mRNA expression levels of the functional R gene candidate and an UDP-glucose:flavonoid 3-O-glucosyltransferase (UF3GT) gene, which is responsible for the final step in anthocyanin biosynthesis. In contrast, when a null allele of Glyma09g36990 is expressed no upregulation of the UF3GT gene was found. CONCLUSIONS: We discovered an allelic series of four loss of function mutations affecting our R locus gene candidate. The presence of any one of these mutations was perfectly correlated with the brown seed coat/hilum phenotype in a broadly distributed survey of soybean cultivars, barring the presence of the epistatic dominant I allele or gray pubescence, both of which can mask the effect of the r allele, resulting in yellow or buff hila. These findings strongly suggest that loss of function for one particular seed coat-expressed R2R3 MYB gene is responsible for the brown seed coat/hilum phenotype in soybean.

Phenotyping and Quantitative Trait Locus Analysis for the Limited Transpiration Trait in an Upper-Mid South Soybean Recombinant Inbred Line Population ("Jackson" × "KS4895"): High Throughput Aquaporin Inhibitor Screening.

Soybean is most often grown under rainfed conditions and negatively impacted by drought stress in the upper mid-south of the United States. Therefore, identification of drought-tolerance traits and their corresponding genetic components are required to minimize drought impacts on productivity. Limited transpiration (TRlim) under high vapor pressure deficit (VPD) is one trait that can help conserve soybean water-use during late-season drought. The main research objective was to evaluate a recombinant inbred line (RIL) population, from crossing two mid-south soybean lines ("Jackson" × "KS4895"), using a high-throughput technique with an aquaporin inhibitor, AgNO3, for the TRlim trait. A secondary objective was to undertake a genetic marker/quantitative trait locus (QTL) genetic analysis using the AgNO3 phenotyping results. A set of 122 soybean genotypes (120-RILs and parents) were grown in controlled environments (32/25-d/n °C). The transpiration rate (TR) responses of derooted soybean shoots before and after application of AgNO3 were measured under 37°C and >3.0 kPa VPD. Then, the decrease in transpiration rate (DTR) for each genotype was determined. Based on DTR rate, a diverse group (slow, moderate, and high wilting) of 26 RILs were selected and tested for the whole plant TRs under varying levels of VPD (0.0-4.0 kPa) at 32 and 37°C. The phenotyping results showed that 88% of slow, 50% of moderate, and 11% of high wilting genotypes expressed the TRlim trait at 32°C and 43, 10, and 0% at 37°C, respectively. Genetic mapping with the phenotypic data we collected revealed three QTL across two chromosomes, two associated with TRlim traits and one associated with leaf temperature. Analysis of Gene Ontologies of genes within QTL regions identified several intriguing candidate genes, including one gene that when overexpressed had previously been shown to confer enhanced tolerance to abiotic stress. Collectively these results will inform and guide ongoing efforts to understand how to deploy genetic tolerance for drought stress.

Identification and Confirmation of Loci Associated With Canopy Wilting in Soybean Using Genome-Wide Association Mapping.

Drought causes significant soybean [Glycine max (L.) Merr.] yield losses each year in rain-fed production systems of many regions. Genetic improvement of soybean for drought tolerance is a cost-effective approach to stabilize yield under rain-fed management. The objectives of this study were to confirm previously reported soybean loci and to identify novel loci associated with canopy wilting (CW) using a panel of 200 diverse maturity group (MG) IV accessions. These 200 accessions along with six checks were planted at six site-years using an augmented incomplete block design with three replications under irrigated and rain-fed treatments. Association mapping, using 34,680 single nucleotide polymorphisms (SNPs), identified 188 significant SNPs associated with CW that likely tagged 152 loci. This includes 87 SNPs coincident with previous studies that likely tagged 68 loci and 101 novel SNPs that likely tagged 84 loci. We also determined the ability of genomic estimated breeding values (GEBVs) from previous research studies to predict CW in different genotypes and environments. A positive relationship (P ≤ 0.05;0.37 ≤ r ≤ 0.5) was found between observed CW and GEBVs. In the vicinity of 188 significant SNPs, 183 candidate genes were identified for both coincident SNPs and novel SNPs. Among these 183 candidate genes, 57 SNPs were present within genes coding for proteins with biological functions involved in plant stress responses. These genes may be directly or indirectly associated with transpiration or water conservation. The confirmed genomic regions may be an important resource for pyramiding favorable alleles and, as candidates for genomic selection, enhancing soybean drought tolerance.

Intricate environment-modulated genetic networks control isoflavone accumulation in soybean seeds.

BACKGROUND: Soybean (Glycine max [L] Merr.) seed isoflavones have long been considered a desirable trait to target in selection programs for their contribution to human health and plant defense systems. However, attempts to modify seed isoflavone contents have not always produced the expected results because their genetic basis is polygenic and complex. Undoubtedly, the extreme variability that seed isoflavones display over environments has obscured our understanding of the genetics involved. RESULTS: In this study, a mapping population of RILs with three replicates was analyzed in four different environments (two locations over two years). We found a total of thirty-five main-effect genomic regions and many epistatic interactions controlling genistein, daidzein, glycitein and total isoflavone accumulation in seeds. The use of distinct environments permitted detection of a great number of environment-modulated and minor-effect QTL. Our findings suggest that isoflavone seed concentration is controlled by a complex network of multiple minor-effect loci interconnected by a dense epistatic map of interactions. The magnitude and significance of the effects of many of the nodes and connections in the network varied depending on the environmental conditions. In an attempt to unravel the genetic architecture underlying the traits studied, we searched on a genome-wide scale for genomic regions homologous to the most important identified isoflavone biosynthetic genes. We identified putative candidate genes for several of the main-effect and epistatic QTL and for QTL reported by other groups. CONCLUSIONS: To better understand the underlying genetics of isoflavone accumulation, we performed a large scale analysis to identify genomic regions associated with isoflavone concentrations. We not only identified a number of such regions, but also found that they can interact with one another and with the environment to form a complex adaptable network controlling seed isoflavone levels. We also found putative candidate genes in several regions and overall we advanced the knowledge of the genetics underlying isoflavone synthesis.

Soybean seed lipoxygenase genes: molecular characterization and development of molecular marker assays.

Soybean seeds contain three lipoxygenase (Lox) enzymes that are controlled by separate genes, Lox1, Lox2 and Lox3. Lipoxygenases play a role in the development of unpleasant flavors in foods containing soybean by oxidation of polyunsaturated fatty acids. Null alleles for all three enzymes have been identified, lox1, lox2 and lox3, and are known to be inherited as simple recessive alleles. Previous studies determined that a missense mutation rendered Lox2 inactive; however, the genetic cause of either lox1 or lox3 mutation was not known. The objectives of this study were the molecular characterization of both lox1 and lox3 mutant alleles and the development of molecular markers to accelerate breeding for Lox-free soybean varieties. We identified two independent mutant alleles as the genetic causes of the lack of Lox1 in seeds of two lox1 mutant soybean lines. Similarly, a mutant allele that truncates Lox3 in a lox3 mutant soybean line was identified. Molecular markers were designed and confirmed to distinguish mutant, wild type, and heterozygous individuals for Lox1, Lox2 and Lox3 genes. Genotype and Lox phenotype analysis showed a perfect association between the inheritance of homozygous lox mutant alleles and the lack of Lox activity. Molecular characterization of a seed-lipoxygenase-free soybean line led to the discovery that an induced recombination event within the Lox1 gene was responsible for breaking the tight linkage in repulsion phase between mutant alleles at the Lox1 and Lox2 loci. The molecular resources developed in this work should accelerate the inclusion of the lipoxygenase-free trait in soybean varieties.

Genome-Wide Association Mapping of Dark Green Color Index using a Diverse Panel of Soybean Accessions.

Nitrogen (N) plays a key role in plants because it is a major component of RuBisCO and chlorophyll. Hence, N is central to both the dark and light reactions of photosynthesis. Genotypic variation in canopy greenness provides insights into the variation of N and chlorophyll concentration, photosynthesis rates, and N2 fixation in legumes. The objective of this study was to identify significant loci associated with the intensity of greenness of the soybean [Glycine max (L.) Merr.] canopy as determined by the Dark Green Color Index (DGCI). A panel of 200 maturity group IV accessions was phenotyped for canopy greenness using DGCI in three environments. Association mapping identified 45 SNPs that were significantly (P ≤ 0.0003) associated with DGCI in three environments, and 16 significant SNPs associated with DGCI averaged across all environments. These SNPs likely tagged 43 putative loci. Out of these 45 SNPs, eight were present in more than one environment. Among the identified loci, 21 were located in regions previously reported for N traits and ureide concentration. Putative loci that were coincident with previously reported genomic regions may be important resources for pyramiding favorable alleles for improved N and chlorophyll concentrations, photosynthesis rates, and N2 fixation in soybean.

Comparing Different Statistical Models and Multiple Testing Corrections for Association Mapping in Soybean and Maize.

Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to nucleotide sequences by exploiting historical recombination events. A major problem in AM is controlling false positives that can arise from population structure and family relatedness. False positives are often controlled by incorporating covariates for structure and kinship in mixed linear models (MLM). These MLM-based methods are single locus models and can introduce false negatives due to over fitting of the model. In this study, eight different statistical models, ranging from single-locus to multilocus, were compared for AM for three traits differing in heritability in two crop species: soybean (Glycine max L.) and maize (Zea mays L.). Soybean and maize were chosen, in part, due to their highly differentiated rate of linkage disequilibrium (LD) decay, which can influence false positive and false negative rates. The fixed and random model circulating probability unification (FarmCPU) performed better than other models based on an analysis of Q-Q plots and on the identification of the known number of quantitative trait loci (QTLs) in a simulated data set. These results indicate that the FarmCPU controls both false positives and false negatives. Six qualitative traits in soybean with known published genomic positions were also used to compare these models, and results indicated that the FarmCPU consistently identified a single highly significant SNP closest to these known published genes. Multiple comparison adjustments (Bonferroni, false discovery rate, and positive false discovery rate) were compared for these models using a simulated trait having 60% heritability and 20 QTLs. Multiple comparison adjustments were overly conservative for MLM, CMLM, ECMLM, and MLMM and did not find any significant markers; in contrast, ANOVA, GLM, and SUPER models found an excessive number of markers, far more than 20 QTLs. The FarmCPU model, using less conservative methods (false discovery rate, and positive false discovery rate) identified 10 QTLs, which was closer to the simulated number of QTLs than the number found by other models.