SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits.

KEY MESSAGE: Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes. Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.

Genome-wide analysis of KIX gene family for organ size regulation in soybean (Glycine max L.).

The KIX domain, conserved among various nuclear and co-activator factors, acts as a binding site that interacts with other transcriptional activators and co-activators, playing a crucial role in gene expression regulation. In plants, the KIX domain is involved in plant hormone signaling, stress response regulation, cell cycle control, and differentiation, indicating its potential relevance to crop productivity. This study aims to identify and characterize KIX domains within the soybean (Glycine max L.) genome to predict their potential role in improving crop productivity. The conservation and evolutionary history of the KIX domains were explored in 59 plant species, confirming the presence of the KIX domains in diverse plants. Specifically, 13 KIX domains were identified within the soybean genome and classified into four main groups, namely GmKIX8/9, GmMED15, GmHAC, and GmRECQL, through sequence alignment, structural analysis, and phylogenetic tree construction. Association analysis was performed between KIX domain haplotypes and soybean seed-related agronomic traits using re-sequencing data from a core collection of 422 accessions. The results revealed correlations between SNP variations observed in GmKIX8-3 and GmMED15-4 and soybean seed phenotypic traits. Additionally, transcriptome analysis confirmed significant expression of the KIX domains during the early stages of soybean seed development. This study provides the first characterization of the structural, expression, genomic haplotype, and molecular features of the KIX domain in soybean, offering a foundation for functional analysis of the KIX domain in soybean and other plants.

A Genome-Wide Association Study of Protein, Oil, and Amino Acid Content in Wild Soybean (Glycine soja).

Soybean (Glycine max L.) is a globally important source of plant proteins, oils, and amino acids for both humans and livestock. Wild soybean (Glycine soja Sieb. and Zucc.), the ancestor of cultivated soybean, could be a useful genetic source for increasing these components in soybean crops. In this study, 96,432 single-nucleotide polymorphisms (SNPs) across 203 wild soybean accessions from the 180K Axiom® Soya SNP array were investigated using an association analysis. Protein and oil content exhibited a highly significant negative correlation, while the 17 amino acids exhibited a highly significant positive correlation with each other. A genome-wide association study (GWAS) was conducted on the protein, oil, and amino acid content using the 203 wild soybean accessions. A total of 44 significant SNPs were associated with protein, oil, and amino acid content. Glyma.11g015500 and Glyma.20g050300, which contained SNPs detected from the GWAS, were selected as novel candidate genes for the protein and oil content, respectively. In addition, Glyma.01g053200 and Glyma.03g239700 were selected as novel candidate genes for nine of the amino acids (Ala, Asp, Glu, Gly, Leu, Lys, Pro, Ser, and Thr). The identification of the SNP markers related to protein, oil, and amino acid content reported in the present study is expected to help improve the quality of selective breeding programs for soybeans.

Genetic Diversity of Korean Wild Soybean Core Collections and Genome-Wide Association Study for Days to Flowering.

The utilization of wild soybean germplasms in breeding programs increases genetic diversity, and they contain the rare alleles of traits of interest. Understanding the genetic diversity of wild germplasms is essential for determining effective strategies that can improve the economic traits of soybeans. Undesirable traits make it challenging to cultivate wild soybeans. This study aimed to construct a core subset of 1467 wild soybean accessions of the total population and analyze their genetic diversity to understand their genetic variations. Genome-wild association studies were conducted to detect the genetic loci underlying the time to flowering for a core subset collection, and they revealed the allelic variation in E genes for predicting maturity using the available resequencing data of wild soybean. Based on principal component and cluster analyses, 408 wild soybean accessions in the core collection covered the total population and were explained by 3 clusters representing the collection regions, namely, Korea, China, and Japan. Most of the wild soybean collections in this study had the E1e2E3 genotype according to association mapping and a resequencing analysis. Korean wild soybean core collections can provide helpful genetic resources to identify new flowering and maturity genes near the E gene loci and genetic materials for developing new cultivars, facilitating the introgression of genes of interest from wild soybean.

Quantitative Trait Loci (QTL) Analysis of Seed Protein and Oil Content in Wild Soybean (Glycine soja).

Soybean seeds consist of approximately 40% protein and 20% oil, making them one of the world's most important cultivated legumes. However, the levels of these compounds are negatively correlated with each other and regulated by quantitative trait loci (QTL) that are controlled by several genes. In this study, a total of 190 F2 and 90 BC1F2 plants derived from a cross of Daepung (Glycine max) with GWS-1887 (G. soja, a source of high protein), were used for the QTL analysis of protein and oil content. In the F2:3 populations, the average protein and oil content was 45.52% and 11.59%, respectively. A QTL associated with protein levels was detected at Gm20_29512680 on chr. 20 with a likelihood of odds (LOD) of 9.57 and an R2 of 17.2%. A QTL associated with oil levels was also detected at Gm15_3621773 on chr. 15 (LOD: 5.80; R2: 12.2%). In the BC1F2:3 populations, the average protein and oil content was 44.25% and 12.14%, respectively. A QTL associated with both protein and oil content was detected at Gm20_27578013 on chr. 20 (LOD: 3.77 and 3.06; R2 15.8% and 10.7%, respectively). The crossover to the protein content of BC1F3:4 population was identified by SNP marker Gm20_32603292. Based on these results, two genes, Glyma.20g088000 (S-adenosyl-l-methionine-dependent methyltransferases) and Glyma.20g088400 (oxidoreductase, 2-oxoglutarate-Fe(II) oxygenase family protein), in which the amino acid sequence had changed and a stop codon was generated due to an InDel in the exon region, were identified.

The discovery of novel SNPs associated with group A soyasaponin biosynthesis from Korea soybean core collection.

Soyasaponin is a type of glycoside such as steroids, steroidal alkaloids or triterpenes, which enhance the body immunity. In order to efficiently identify genes and markers related to the soyasaponin, we used a 180K Axiom® SoyaSNP array and whole genome resequencing data from the Korean soybean core collection. As a result of conducting GWAS for group A soyasaponin (Aa and Ab derivatives), 16 significant common markers associated with Aa and Ab derivatives were mapped to chromosome 7, and three candidate genes including Glyma.07g254600 were detected. The functional haplotypes for candidate genes showed that Aa and Ab contents were mainly determined by alleles of AX-90322128, the marker of Glyma.07g254600. In addition, 14 novel SNPs variants closely associated with Aa and Ab derivatives were discovered for Glyma.07g254600. Therefore, the results of this study that identified soyasaponin-associated markers and useful genes utilizing various genomic information could provide insight into functional soybean breeding.

Effect of Soybean Volatiles on the Behavior of the Bean Bug, Riptortus pedestris.

The bean bug, Riptortus pedestris, is a polyphagous insect that feeds primarily on leguminous plants, especially soybean (Glycine max). Although the bean bug is an economically important pest of soybean, little is known about how the insect locates soybean fields. In this study, we examined the electroantennogram responses of R. pedestris to soybean volatiles and examined the behavioral responses of the adult bean bugs. R. pedestris adults were attracted more to their host-plant soybean, even when physical contact was absent, than to air or a non-host plant. Accordingly, we hypothesized that R. pedestris can recognize soybean through a plant's volatile organic compounds (VOCs). Five VOCs were identified from intact soybean plants at the vegetative stage: (Z)-3-hexen-1-ol, (Z)-3-hexenyl acetate, 4-ethylbenzaldehyde, α-farnesene, and methyl salicylate. Response spectra of the antennae to these volatiles clearly showed that both male and female R. pedestris can detect soybean volatiles. The adult bean bugs did not show behavioral orientation to any individual compounds but showed significant orientation to a particular blend of synthetic soybean volatiles when tested under laboratory conditions. In the field, this soybean volatile blend did not significantly attract the bean bugs, but it did interact synergistically with the aggregation pheromone to attract the bean bugs. These results highlight the role of host plant volatiles in the sensory ecology of R. pedestris and help explain colonization pattern of the bean bugs in soybean fields.

Genome-Wide Association Study for Ultraviolet-B Resistance in Soybean (Glycine max L.).

The depletion of the stratospheric ozone layer is a major environmental issue and has increased the dosage of ultraviolet-B (UV-B) radiation reaching the Earth's surface. Organisms are negatively affected by enhanced UV-B radiation, and especially in crop plants this may lead to severe yield losses. Soybean (Glycine max L.), a major legume crop, is sensitive to UV-B radiation, and therefore, it is required to breed the UV-B-resistant soybean cultivar. In this study, 688 soybean germplasms were phenotyped for two categories, Damage of Leaf Chlorosis (DLC) and Damage of Leaf Shape (DLS), after supplementary UV-B irradiation for 14 days. About 5% of the germplasms showed strong UV-B resistance, and GCS731 was the most resistant genotype. Their phenotypic distributions showed similar patterns to the normal, suggesting UV-B resistance as a quantitative trait governed by polygenes. A total of 688 soybean germplasms were genotyped using the Axiom® Soya 180K SNP array, and a genome-wide association study (GWAS) was conducted to identify SNPs significantly associated with the two traits, DLC and DLS. Five peaks on chromosomes 2, 6, 10, and 11 were significantly associated with either DLC or DLS, and the five adjacent genes were selected as candidate genes responsible for UV-B resistance. Among those candidate genes, Glyma.02g017500 and Glyma.06g103200 encode cryptochrome (CRY) and cryptochrome 1 (CRY1), respectively, and are known to play a role in DNA repair during photoreactivation. Real-time quantitative RT-PCR (qRT-PCR) results revealed that CRY1 was expressed significantly higher in the UV-B-resistant soybean compared to the susceptible soybean after 6 h of UV-B irradiation. This study is the first GWAS report on UV-B resistance in soybean, and the results will provide valuable information for breeding UV-B-resistant soybeans in preparation for climate change.

The patterns of deleterious mutations during the domestication of soybean.

Globally, soybean is a major protein and oil crop. Enhancing our understanding of the soybean domestication and improvement process helps boost genomics-assisted breeding efforts. Here we present a genome-wide variation map of 10.6 million single-nucleotide polymorphisms and 1.4 million indels for 781 soybean individuals which includes 418 domesticated (Glycine max), 345 wild (Glycine soja), and 18 natural hybrid (G. max/G. soja) accessions. We describe the enhanced detection of 183 domestication-selective sweeps and the patterns of putative deleterious mutations during domestication and improvement. This predominantly selfing species shows 7.1% reduction of overall deleterious mutations in domesticated soybean relative to wild soybean and a further 1.4% reduction from landrace to improved accessions. The detected domestication-selective sweeps also show reduced levels of deleterious alleles. Importantly, genotype imputation with this resource increases the mapping resolution of genome-wide association studies for seed protein and oil traits in a soybean diversity panel.

Genome-wide association and epistatic interactions of flowering time in soybean cultivar.

Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom® SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis.

Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits.

Chromosomal features revealed by comparison of genetic maps of Glycine max and Glycine soja.

Recombination is a crucial component of evolution and breeding. New combinations of variation on chromosomes are shaped by recombination. Recombination is also involved in chromosomal rearrangements. However, recombination rates vary tremendously among chromosome segments. Genome-wide genetic maps are one of the best tools to study variation of recombination. Here, we describe high density genetic maps of Glycine max and Glycine soja constructed from four segregating populations. The maps were used to identify chromosomal rearrangements and find the highly predictable pattern of cross-overs on the broad scale in soybean. Markers on these genetic maps were used to evaluate assembly quality of the current soybean reference genome sequence. We find a strong inversion candidate larger than 3 Mb based on patterns of cross-overs. We also identify quantitative trait loci (QTL) that control number of cross-overs. This study provides fundamental insights relevant to practical strategy for breeding programs and for pan-genome researches.

Dissection of soybean populations according to selection signatures based on whole-genome sequences.

BACKGROUND: Domestication and improvement processes, accompanied by selections and adaptations, have generated genome-wide divergence and stratification in soybean populations. Simultaneously, soybean populations, which comprise diverse subpopulations, have developed their own adaptive characteristics enhancing fitness, resistance, agronomic traits, and morphological features. The genetic traits underlying these characteristics play a fundamental role in improving other soybean populations. RESULTS: This study focused on identifying the selection signatures and adaptive characteristics in soybean populations. A core set of 245 accessions (112 wild-type, 79 landrace, and 54 improvement soybeans) selected from 4,234 soybean accessions was re-sequenced. Their genomic architectures were examined according to the domestication and improvement, and accessions were then classified into 3 wild-type, 2 landrace, and 2 improvement subgroups based on various population analyses. Selection and gene set enrichment analyses revealed that the landrace subgroups have selection signals for soybean-cyst nematode HG type 0 and seed development with germination, and that the improvement subgroups have selection signals for plant development with viability and seed development with embryo development, respectively. The adaptive characteristic for soybean-cyst nematode was partially underpinned by multiple resistance accessions, and the characteristics related to seed development were supported by our phenotypic findings for seed weights. Furthermore, their adaptive characteristics were also confirmed as genome-based evidence, and unique genomic regions that exhibit distinct selection and selective sweep patterns were revealed for 13 candidate genes. CONCLUSIONS: Although our findings require further biological validation, they provide valuable information about soybean breeding strategies and present new options for breeders seeking donor lines to improve soybean populations.

Korean soybean core collection: Genotypic and phenotypic diversity population structure and genome-wide association study.

A core collection is a subset that represents genetic diversity of the total collection. Soybean (Glycine max (L.) Merr.) is one of major food and feed crops. It is the world's most cultivated annual herbaceous legume. Constructing a core collection for soybean could play a pivotal role in conserving and utilizing its genetic variability for research and breeding programs. To construct and evaluate a Korean soybean core collection, genotypic and phenotypic data as well as population structure, were analyzed. The Korean soybean core collection consisted of 430 accessions selected from 2,872 collections based on Affymetrix Axiom® 180k SoyaSNP array data. The core collection represented 99% of genotypic diversity of the total collection. Analysis of population structure clustered the core collection into five subpopulations. Accessions from South Korea and North Korea were distributed across five subpopulations. Analysis of molecular variance indicated that only 2.01% of genetic variation could be explained by geographic origins while 16.18% of genetic variation was accounted for by subpopulations. Genome-wide association study (GWAS) for days to flowering, flower color, pubescent color, and growth habit confirmed that the core collection had the same genetic diversity for tested traits as the total collection. The Korean soybean core collection was constructed based on genotypic information of the 180k SNP data. Size and phenotypic diversity of the core collection accounted for approximately 14.9% and 18.1% of the total collection, respectively. GWAS of core and total collections successfully confirmed loci associated with tested traits. Consequently, the present study showed that the Korean soybean core collection could provide fundamental and practical material and information for both soybean genetic research and breeding programs.

GmBRC1 is a Candidate Gene for Branching in Soybean (Glycine max (L.) Merrill).

Branch number is one of the main factors affecting the yield of soybean (Glycine max (L.)). In this study, we conducted a genome-wide association study combined with linkage analysis for the identification of a candidate gene controlling soybean branching. Five quantitative trait nucleotides (QTNs) were associated with branch numbers in a soybean core collection. Among these QTNs, a linkage disequilibrium (LD) block qtnBR6-1 spanning 20 genes was found to overlap a previously identified major quantitative trait locus qBR6-1. To validate and narrow down qtnBR6-1, we developed a set of near-isogenic lines (NILs) harboring high-branching (HB) and low-branching (LB) alleles of qBR6-1, with 99.96% isogenicity and different branch numbers. A cluster of single nucleotide polymorphisms (SNPs) segregating between NIL-HB and NIL-LB was located within the qtnBR6-1 LD block. Among the five genes showing differential expression between NIL-HB and NIL-LB, BRANCHED1 (BRC1; Glyma.06G210600) was down-regulated in the shoot apex of NIL-HB, and one missense mutation and two SNPs upstream of BRC1 were associated with branch numbers in 59 additional soybean accessions. BRC1 encodes TEOSINTE-BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTORS 1 and 2 transcription factor and functions as a regulatory repressor of branching. On the basis of these results, we propose BRC1 as a candidate gene for branching in soybean.

Genetic diversity patterns and domestication origin of soybean.

KEY MESSAGE: Genotyping data of a comprehensive Korean soybean collection obtained using a large SNP array were used to clarify global distribution patterns of soybean and address the evolutionary history of soybean. Understanding diversity and evolution of a crop is an essential step to implement a strategy to expand its germplasm base for crop improvement research. Accessions intensively collected from Korea, which is a small but central region in the distribution geography of soybean, were genotyped to provide sufficient data to underpin population genetic questions. After removing natural hybrids and duplicated or redundant accessions, we obtained a non-redundant set comprising 1957 domesticated and 1079 wild accessions to perform population structure analyses. Our analysis demonstrates that while wild soybean germplasm will require additional sampling from diverse indigenous areas to expand the germplasm base, the current domesticated soybean germplasm is saturated in terms of genetic diversity. We then showed that our genome-wide polymorphism map enabled us to detect genetic loci underlying flower color, seed-coat color, and domestication syndrome. A representative soybean set consisting of 194 accessions was divided into one domesticated subpopulation and four wild subpopulations that could be traced back to their geographic collection areas. Population genomics analyses suggested that the monophyletic group of domesticated soybeans was likely originated at a Japanese region. The results were further substantiated by a phylogenetic tree constructed from domestication-associated single nucleotide polymorphisms identified in this study.

Differences in the metabolic profiles and antioxidant activities of wild and cultivated black soybeans evaluated by correlation analysis.

Wild soybeans are considered a potential resource for soybean domestication and an important source of genetic diversity for soybean crop improvement. Understanding metabolite-caused bioactivity differences between cultivated and wild soybeans is essential for designing a soybean with enhanced nutritional traits. In this study, the non-targeted metabolic profiling of 26 soybean varieties, 15 wild black soybeans (WBS) and 11 cultivated black soybeans (CBS), using liquid chromatography-mass spectrometry (LC-MS) in combination with multivariate analysis revealed significant differences in 25 differential metabolites. Among these, the soyasaponins Ab and Bb were found to be characteristic metabolites expressed more substantially in CBS than in WBS. Three different antioxidant assays and correlation analysis identified major and minor antioxidants that contributed to WBS having an antioxidant activity 4- to 8-fold stronger than that of CBS. Epicatechin, procyanidin B2, and cyanidin-3-O-glucoside were identified by both association analysis and the online LC-ABTS radical scavenging assay as being major antioxidants.