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.

Cataloging SCN resistance loci in North American public soybean breeding programs.

Soybean cyst nematode (SCN) is a destructive pathogen of soybeans responsible for annual yield loss exceeding $1.5 billion in the United States. Here, we conducted a series of genome-wide association studies (GWASs) to understand the genetic landscape of SCN resistance in the University of Missouri soybean breeding programs (Missouri panel), as well as germplasm and cultivars within the United States Department of Agriculture (USDA) Uniform Soybean Tests-Northern Region (NUST). For the Missouri panel, we evaluated the resistance of breeding lines to SCN populations HG 2.5.7 (Race 1), HG 1.2.5.7 (Race 2), HG 0 (Race 3), HG 2.5.7 (Race 5), and HG 1.3.6.7 (Race 14) and identified seven quantitative trait nucleotides (QTNs) associated with SCN resistance on chromosomes 2, 8, 11, 14, 17, and 18. Additionally, we evaluated breeding lines in the NUST panel for resistance to SCN populations HG 2.5.7 (Race 1) and HG 0 (Race 3), and we found three SCN resistance-associated QTNs on chromosomes 7 and 18. Through these analyses, we were able to decipher the impact of seven major genetic loci, including three novel loci, on resistance to several SCN populations and identified candidate genes within each locus. Further, we identified favorable allelic combinations for resistance to individual SCN HG types and provided a list of available germplasm for integration of these unique alleles into soybean breeding programs. Overall, this study offers valuable insight into the landscape of SCN resistance loci in U.S. public soybean breeding programs and provides a framework to develop new and improved soybean cultivars with diverse plant genetic modes of SCN resistance.

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.

Identification of loci associated with water use efficiency and symbiotic nitrogen fixation in soybean.

Soybean (Glycine max) production is greatly affected by persistent and/or intermittent droughts in rainfed soybean-growing regions worldwide. Symbiotic N2 fixation (SNF) in soybean can also be significantly hampered even under moderate drought stress. The objective of this study was to identify genomic regions associated with shoot carbon isotope ratio (δ13C) as a surrogate measure for water use efficiency (WUE), nitrogen isotope ratio (δ15N) to assess relative SNF, N concentration ([N]), and carbon/nitrogen ratio (C/N). Genome-wide association mapping was performed with 105 genotypes and approximately 4 million single-nucleotide polymorphism markers derived from whole-genome resequencing information. A total of 11, 21, 22, and 22 genomic loci associated with δ13C, δ15N, [N], and C/N, respectively, were identified in two environments. Nine of these 76 loci were stable across environments, as they were detected in both environments. In addition to the 62 novel loci identified, 14 loci aligned with previously reported quantitative trait loci for different C and N traits related to drought, WUE, and N2 fixation in soybean. A total of 58 Glyma gene models encoding for different genes related to the four traits were identified in the vicinity of the genomic loci.

Assessment of Soybean Lodging Using UAV Imagery and Machine Learning.

Plant lodging is one of the most essential phenotypes for soybean breeding programs. Soybean lodging is conventionally evaluated visually by breeders, which is time-consuming and subject to human errors. This study aimed to investigate the potential of unmanned aerial vehicle (UAV)-based imagery and machine learning in assessing the lodging conditions of soybean breeding lines. A UAV imaging system equipped with an RGB (red-green-blue) camera was used to collect the imagery data of 1266 four-row plots in a soybean breeding field at the reproductive stage. Soybean lodging scores were visually assessed by experienced breeders, and the scores were grouped into four classes, i.e., non-lodging, moderate lodging, high lodging, and severe lodging. UAV images were stitched to build orthomosaics, and soybean plots were segmented using a grid method. Twelve image features were extracted from the collected images to assess the lodging scores of each breeding line. Four models, i.e., extreme gradient boosting (XGBoost), random forest (RF), K-nearest neighbor (KNN) and artificial neural network (ANN), were evaluated to classify soybean lodging classes. Five data preprocessing methods were used to treat the imbalanced dataset to improve classification accuracy. Results indicate that the preprocessing method SMOTE-ENN consistently performs well for all four (XGBoost, RF, KNN, and ANN) classifiers, achieving the highest overall accuracy (OA), lowest misclassification, higher F1-score, and higher Kappa coefficient. This suggests that Synthetic Minority Oversampling-Edited Nearest Neighbor (SMOTE-ENN) may be a good preprocessing method for using unbalanced datasets and the classification task. Furthermore, an overall accuracy of 96% was obtained using the SMOTE-ENN dataset and ANN classifier. The study indicated that an imagery-based classification model could be implemented in a breeding program to differentiate soybean lodging phenotype and classify lodging scores effectively.

Physical and sensory properties of soy-based ice cream formulated with cold-pressed high oleic low linolenic soybean oil.

The effect of cold-pressed SOYLEIC™ soybean oil (SOYLEIC) on the physical and sensory properties of soy-based ice cream was compared to commercial vegetable oil (COM-VO), commercial high oleic soybean oil (COM-HO), and heavy cream (CREAM). Fat sources had no significant effect on viscosity and fat globule size distribution of ice cream mixes. Ice cream made with COM-VO had the lowest overrun (p < 0.05) and higher degree of fat destabilization; however, no difference in hardness was found. Despite similar melting rate, the shape retention behavior during melting was different for SOYLEIC, COM-VO, and COM-HO compared to CREAM. No significant differences were found in texture attributes except mouth coating, which was higher for CREAM than COM-HO and SOYLEIC (p < 0.05). There was no significant difference in flavor attributes between SOYLEIC and CREAM, while COM-VO and COM-HO had higher off-flavor intensities (p < 0.05). Consumer acceptability results revealed that SOYLEIC and CREAM had significantly higher flavor liking and overall liking scores than COM-VO and COM-HO (p < 0.05). SOYLEIC and CREAM also had higher texture liking than COM-VO (p < 0.05). Overall, liking had the highest positive significant correlation with flavor liking (r = 0.996). PRACTICAL APPLICATION: Cold-pressed HOLL soybean oil has the potential to be used in formulating plant-based frozen desserts with equivalent texture but more acceptable flavor.

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.

Utilization of Plant Architecture Genes in Soybean to Positively Impact Adaptation to High Yield Environments.

Optimization of plant architecture by modifying stem termination and timing of flowering and maturity of soybean is a promising strategy to improve its adaptability to specific production environments. Therefore, it is important to choose a proper stem termination type and to understand morphological differences between each stem termination type under various environmental conditions. Variations in abruptness of stem termination have been generally classified into three classical genetic types, indeterminate (Dt1), determinate (dt1), and semi-determinate (Dt2). However, an additional stem termination type, termed tall determinate, and its genetic symbol, dt1-t, were introduced about 25 years ago. The tall determinate soybean lines show delayed cessation of apical stem growth and about 50% taller plant heights than the typical determinate soybeans, even though the genetic control of the tall determinate phenotype was found to be allelic to dt1. Despite the potential agronomic merits of the alternative stem termination type, knowledge about the tall determinate soybean remains limited. We clarified the molecular basis of the tall determinate stem termination type and examined potential agronomic merits of the alternative stem type under three different production environments in the US. Sequence analysis of the classical tall determinate soybean lines revealed that the dt1-t allele responsible for tall determinate stem architecture is caused by two of the identified independent missense alleles of dt1, dt1-t1 (R130K), and dt1-t2 (R62S). Also, from the comparison among soybean accessions belonging to each of the genotype categories for stem termination types, soybean accessions with tall determinate alleles were found to have a high discrepancy rate in phenotyping. Newly developed tall determinate late-maturing soybean germplasm lines had taller plant heights and a greater number of nodes with a similar stem diameter and similar pod density at the apical stem compared to typical determinate soybeans having dt1 (R166W) alleles in Southern environments in the US. The phenotype of increased pod-bearing nodes with lodging resistance has the potential to improve yield, especially grown in high yield environments. This study suggests an alternative strategy to remodel the shape of soybean plants, which can possibly lead to yield improvement through the modification of soybean plant architecture.

Candidate Genes Modulating Reproductive Timing in Elite US Soybean Lines Identified in Soybean Alleles of Arabidopsis Flowering Orthologs With Divergent Latitude Distribution.

Adaptation of soybean cultivars to the photoperiod in which they are grown is critical for optimizing plant yield. However, despite its importance, only the major loci conferring variation in flowering time and maturity of US soybean have been isolated. By contrast, over 200 genes contributing to floral induction in the model organism Arabidopsis thaliana have been described. In this work, putative alleles of a library of soybean orthologs of these Arabidopsis flowering genes were tested for their latitudinal distribution among elite US soybean lines developed in the United States. Furthermore, variants comprising the alleles of genes with significant differences in latitudinal distribution were assessed for amino acid conservation across disparate genera to infer their impact on gene function. From these efforts, several candidate genes from various biological pathways were identified that are likely being exploited toward adaptation of US soybean to various maturity groups.

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.

Resistance Gene Pyramiding and Rotation to Combat Widespread Soybean Cyst Nematode Virulence.

Soybean cyst nematode (SCN) is an important pathogen of soybean causing >$1 billion in yield losses annually in the United States. Planting SCN-resistant soybean cultivars is the primary management strategy. Resistance genes derived from the plant introduction (PI) 88788 (rhg1-b) and PI 548402 (Peking; rhg1-a and Rhg4) are the main types of resistance available in commercial cultivars. The PI 88788 rhg1-b resistance allele is found in the majority of SCN-resistant cultivars in the north central United States. The widespread use of PI 88788 rhg1-b has led to limited options for farmers to rotate resistance sources to manage SCN. Consequently, overreliance on a single type of resistance has resulted in the selection of SCN populations that have adapted to reproduce on these resistant cultivars. Here we evaluated the effectiveness of rotating soybean lines with different combinations of resistance genes to determine the best strategy for combating the widespread increase in virulent SCN and limit future nematode adaptation to resistant cultivars. Eight SCN populations were developed by continuous selection of a virulent SCN field population (Heterodera glycines [HG] type 1.2.5.7) on a single resistance source or in rotation with soybean pyramiding different resistance gene alleles derived from PI 88788 (rhg1-b), PI 437654 (rhg1-a and Rhg4), PI 468916 (cqSCN-006 and cqSCN-007), and PI 567516C (Chr10). SCN population densities were determined for eight generations. HG type tests were conducted after the eighth generation to evaluate population shifts. The continued use of rhg1-b or 006/007 had limited effectiveness for reducing SCN type 1.2.5.7 population density, whereas rotation to the use of rhg1-a/Rhg4 resistance significantly reduced SCN population density but selected for broader SCN virulence (HG type 1.2.3.5.6.7). A rotation of rhg1-a/Rhg4 with a pyramid of rhg1-b/006/007/Chr10 was the most effective combination at both reducing population density and minimizing selection pressure. Our results provide guidance for implementation of a strategic SCN resistance rotation plan to manage the widespread virulence on PI 88788 and sustain the future durability of SCN resistance genes.

Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology.

The efficiency of crop breeding programs is evaluated by the genetic gain of a primary trait of interest, e.g., yield, achieved in 1 year through artificial selection of advanced breeding materials. Conventional breeding programs select superior genotypes using the primary trait (yield) based on combine harvesters, which is labor-intensive and often unfeasible for single-row progeny trials (PTs) due to their large population, complex genetic behavior, and high genotype-environment interaction. The goal of this study was to investigate the performance of selecting superior soybean breeding lines using image-based secondary traits by comparing them with the selection of breeders. A total of 11,473 progeny rows (PT) were planted in 2018, of which 1,773 genotypes were selected for the preliminary yield trial (PYT) in 2019, and 238 genotypes advanced for the advanced yield trial (AYT) in 2020. Six agronomic traits were manually measured in both PYT and AYT trials. A UAV-based multispectral imaging system was used to collect aerial images at 30 m above ground every 2 weeks over the growing seasons. A group of image features was extracted to develop the secondary crop traits for selection. Results show that the soybean seed yield of the selected genotypes by breeders was significantly higher than that of the non-selected ones in both yield trials, indicating the superiority of the breeder's selection for advancing soybean yield. A least absolute shrinkage and selection operator model was used to select soybean lines with image features and identified 71 and 76% of the selection of breeders for the PT and PYT. The model-based selections had a significantly higher average yield than the selection of a breeder. The soybean yield selected by the model in PT and PYT was 4 and 5% higher than those selected by breeders, which indicates that the UAV-based high-throughput phenotyping system is promising in selecting high-yield soybean genotypes.

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.

The effects and interaction of soybean maturity gene alleles controlling flowering time, maturity, and adaptation in tropical environments.

BACKGROUND: Soybean is native to the temperate zones of East Asia. Poor yields of soybean in West African countries may be partially attributed to inadequate adaptation of soybean to tropical environments. Adaptation will require knowledge of the effects of allelic combinations of major maturity genes (E1, E2, and E3) and stem architecture. The long juvenile trait (J) influences soybean flowering time in short, ~ 12 h days, which characterize tropical latitudes. Soybean plant architecture includes determinate or indeterminate stem phenotypes controlled by the Dt1 gene. Understanding the influence of these genetic components on plant development and adaptation is key to optimize phenology and improve soybean yield potential in tropical environments. RESULTS: Soybean lines from five recombinant inbred populations were developed that varied in their combinations of targeted genes. The soybean lines were field tested in multiple environments and characterized for days to flowering (DTF), days to maturity (DTM), and plant height in locations throughout northern Ghana, and allelic combinations were determined for each line for associating genotype with phenotype. The results revealed significant differences based on genotype for DTF and DTM and allowed the comparison of different variant alleles of those genes. The mutant alleles of J and E1 had significant impact on DTF and DTM, and alleles of those genes interacted with each other for DTF but not DTM. The Dt1 gene significantly influenced plant height but not DTF or DTM. CONCLUSIONS: This research identified major and minor effect alleles of soybean genes that can be combined to control DTF, DTM, and plant height in short day tropical environments in Ghana. These phenotypes contribute to adaptation to a low latitude environment that can be optimized in a soybean breeding program with targeted selection of desired allele combinations. The knowledge of the genetic control of these traits will enhance molecular breeding to produce optimally adapted soybean varieties targeted to tropical environments.

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.

Mapping and confirmation of loci for salt tolerance in a novel soybean germplasm, Fiskeby III.

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

Genomic-assisted phylogenetic analysis and marker development for next generation soybean cyst nematode resistance breeding.

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is a serious soybean pest. The use of resistant cultivars is an effective approach for preventing yield loss. In this study, 19,652 publicly available soybean accessions that were previously genotyped with the SoySNP50K iSelect BeadChip were used to evaluate the phylogenetic diversity of SCN resistance genes Rhg1 and Rhg4 in an attempt to identify novel sources of resistance. The sequence information of soybean lines was utilized to develop KASPar (KBioscience Competitive Allele-Specific PCR) assays from single nucleotide polymorphisms (SNPs) of Rhg1, Rhg4, and other novel quantitative trait loci (QTL). These markers were used to genotype a diverse set of 95 soybean germplasm lines and three recombinant inbred line (RIL) populations. SNP markers from the Rhg1 gene were able to differentiate copy number variation (CNV), such as resistant-high copy (PI 88788-type), low copy (Peking-type), and susceptible-single copy (Williams 82) numbers. Similarly, markers for the Rhg4 gene were able to detect Peking-type (resistance) genotypes. The phylogenetic information of SCN resistance loci from a large set of soybean accessions and the gene/QTL specific markers that were developed in this study will accelerate SCN resistance breeding programs.

Evaluation of seed chemical quality traits and sensory properties of natto soybean.

Natto is a popular soyfood in Japan, and the U.S. is the largest supplier of natto soybeans. However, information on natto seed chemical and sensory properties is very limited. The objectives of this study were to evaluate differences of seed chemical and sensory properties among natto types and determine heritability and correlation. A total of 15 small-seeded natto genotypes (three superior, nine moderate and three inferior) were evaluated for protein, oil, calcium, manganese, boron and sugar content and processed into a natto product to evaluate appearance, stickiness, flavor, texture and shelf-life. The superior natto group had a higher sugar content but lower protein plus oil, calcium, manganese and boron content than other two groups. Most seed quality traits exhibited high heritability. The natto sensory preference was positively correlated with sucrose and oil content, but negatively correlated with seed hardness, protein, protein plus oil, calcium, manganese, and boron contents. Selecting soybean lines with low protein, protein plus oil, calcium, manganese, and boron content while with high sucrose will be an effective approach for soybean breeding for natto production.

Measurement of inorganic phosphorus in soybeans with near-infrared spectroscopy.

This study explored the feasibility of near-infrared (NIR) quantitative and qualitative models for soybean inorganic phosphorus (Pi), which is complementary to phytic acid, a component of nutritional and environmental importance. Spectra, consisting of diffuse reflectance (1100-2500 nm) of ground meal and single-bean transmittance (600-1900 nm) of whole seed, were collected on 191 recombinant inbred soybean lines. Partial least-squares regression models were individually developed for soy meal diffuse reflectance, single-bean transmittance, and averaged (24 beans/line) whole seed transmittance data. The best performance was obtained with diffuse reflectance data, in which the standard errors (rmsd) were 263 and 248 mg/kg for cross-validation and validation sets, respectively. Model accuracy was lower for the 24-bean average transmittance spectra and still lower for single beans. Despite the overall poorer modeling ability of Pi with respect to the common macronutrient NIR regressions, such as those for protein and oil, this technique holds promise for use in breeding programs.