Genome sequencing and population resequencing provide insights into the genetic basis of domestication and diversity of vegetable soybean

SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research

Soybean is a globally important crop for food, feed, oil, and nitrogen fixation. A variety of multi-omics studies have been carried out, generating datasets ranging from genotype to phenotype. In order to efficiently utilize these data for basic and applied research, a soybean multi-omics database with extensive data coverage and comprehensive data analysis tools was established. The Soybean Omics Database (SoyOD) integrates important new datasets with existing public datasets to form the most comprehensive collection of soybean multi-omics information. Compared to existing soybean databases, SoyOD incorporates an extensive collection of novel data derived from the deep-sequencing of 984 germplasms, 162 novel transcriptomic datasets from seeds at different developmental stages, 53 phenotypic datasets, and more than 2500 phenotypic images. In addition, SoyOD integrates existing data resources, including 59 assembled genomes, genetic variation data from 3904 soybean accessions, 225 sets of phenotypic data, and 1097 transcriptomic sequences covering 507 different tissues and treatment conditions. Moreover, SoyOD can be used to mine candidate genes for important agronomic traits, as shown in a case study on plant height. Additionally, powerful analytical and easy-to-use toolkits enable users to easily access the available multi-omics datasets, and to rapidly search genotypic and phenotypic data in a particular germplasm. The novelty, comprehensiveness, and user-friendly features of SoyOD make it a valuable resource for soybean molecular breeding and biological research. SoyOD is publicly accessible at https://bis.zju.edu.cn/soyod.

Genome-wide association study of sucrose content in vegetable soybean

BACKGROUND

Vegetable soybean is an important legume vegetable. High sucrose content is a significant quality characteristic of vegetable soybean that influences consumers' taste. However, the genetic basis of sucrose content in vegetable soybean is currently unclear.

RESULTS

In this study, the genome-wide association study (GWAS) of sucrose content in vegetable soybean was performed using Chinese soybean mini-core collection. The results showed a wide genetic variation for the sucrose content in the mini-core collection. The sucrose content of genotypes from HHR (Huanghuai region) and SR (Southern region) was higher than that of genotypes from NER (Northeast region) and NR (Northern region). Furthermore, 82,187 high quality SNPs (Single nucleotide polymorphism) were used for GWAS of sucrose content. Based on SNPs detected in multiple environments, the chromosome 8 19,496,314-19,698,413 bp interval was identified as the candidate interval. And Glyma.08g234100 was most likely to affect the sucrose content of vegetable soybean seeds.

CONCLUSIONS

This study has created new details to be used for breeding for high sucrose content in vegetable soybean.

Transcriptome profiling uncovers differentially expressed genes linked to nutritional quality in vegetable soybean

Vegetative soybean (maodou or edamame) serves as a nutrient-rich food source with significant potential for mitigating global nutritional deficiencies. This study undertook a thorough examination of the nutritional profiles and transcriptomic landscapes of six soybean cultivars, including three common cultivars (Heinong551, Heinong562, and Heinong63) and three fresh maodou cultivars (Heinong527, HeinongXS4, and HeinongXS5). Nutrient analysis of the seeds disclosed notable differences in the levels of protein, fat, soluble sugars, vitamin E, calcium, potassium, magnesium, manganese, iron, and zinc across the cultivars. Through comparative transcriptome profiling and RNA sequencing, distinct variations in differentially expressed genes (DEGs) were identified between fresh and traditional maodou cultivars. Functional enrichment analyses underscored the involvement of DEGs in critical biological processes, such as nutrient biosynthesis, seed development, and stress responses. Additionally, association studies demonstrated robust correlations between specific DEG expression patterns and seed nutrient compositions across the different cultivars. Sankey diagrams illustrated that DEGs are strongly linked with seed quality traits, revealing potential molecular determinants that govern variations in nutritional content. The identified DEGs and their relationships with nutritional profiles offer valuable insights for breeding programs focused on developing cultivars with improved nutritional quality, tailored to specific dietary needs or industrial applications.

Comparative transcriptome analysis of vegetable soybean grain discloses genes essential for grain quality

BACKGROUND

Vegetable soybean is an important vegetable crop in world. Seed size and soluble sugar content are considered crucial indicators of quality in vegetable soybean, and there is a lack of clarity on the molecular basis of grain quality in vegetable soybean.

RESULTS

In this context, we performed a comprehensive comparative transcriptome analysis of seeds between a high-sucrose content and large-grain variety (Zhenong 6, ZN6) and a low-sucrose content and small-grain variety (Williams 82, W82) at three developmental stages, i.e. stage R5 (Beginning Seed), stage R6 (Full Seed), and stage R7 (Beginning Maturity). The transcriptome analysis showed that 17,107 and 13,571 differentially expressed genes (DEGs) were identified in ZN6 at R6 (vs. R5) and R7 (vs. R6), respectively, whereas 16,203 and 16,032 were detected in W82. Gene expression pattern and DEGs functional enrichment proposed genotype-specific biological processes during seed development. The genes participating in soluble sugar biosynthesis such as FKGP were overexpressed in ZN6, whereas those responsible for lipid and protein metabolism such as ALDH3 were more enhanced in W82, exhibiting different dry material accumulation between two genotypes. Furthermore, hormone-associated transcriptional factors involved in seed size regulation such as BEH4 were overrepresented in ZN6, exhibiting different seed size regulation processes between two genotypes.

CONCLUSIONS

Herein, we not only discovered the differential expression of genes encoding metabolic enzymes involved in seed composition, but also identified a type of hormone-associated transcriptional factors overexpressed in ZN6, which may regulate seed size and soluble content. This study provides new insights into the underlying causes of differences in the soybean metabolites and appearance, and suggests that genetic data can be used to improve its appearance and textural quality.

Genome-Wide Association Analysis of Yield-Related Traits and Candidate Genes in Vegetable Soybean

Owing to the rising demand for vegetable soybean products, there is an increasing need for high-yield soybean varieties. However, the complex correlation patterns among quantitative traits with genetic architecture pose a challenge for improving vegetable soybean through breeding. Herein, a genome-wide association study (GWAS) was applied to 6 yield-related traits in 188 vegetable soybean accessions. Using a BLINK model, a total of 116 single nucleotide polymorphisms (SNPs) were identified for plant height, pod length, pod number, pod thickness, pod width, and fresh pod weight. Furthermore, a total of 220 genes were found in the 200 kb upstream and downstream regions of significant SNPs, including 11 genes encoding functional proteins. Among them, four candidate genes, Glyma.13G109100, Glyma.03G183200, Glyma.09G102200, and Glyma.09G102300 were analyzed for significant haplotype variations and to be in LD block, which encode MYB-related transcription factor, auxin-responsive protein, F-box protein, and CYP450, respectively. The relative expression of candidate genes in V030 and V071 vegetable soybean (for the plant height, pod number, and fresh pod weight of V030 were lower than those of the V071 strains) was significantly different, and these genes could be involved in plant growth and development via various pathways. Altogether, we identified four candidate genes for pod yield and plant height from vegetable soybean germplasm. This study provides insights into the genomic basis for improving soybean and crucial genomic resources that can facilitate genome-assisted high-yielding vegetable soybean breeding.

Multi-Omics Analysis of a Chromosome Segment Substitution Line Reveals a New Regulation Network for Soybean Seed Storage Profile

Soybean, a major source of oil and protein, has seen an annual increase in consumption when used in soybean-derived products and the broadening of its cultivation range. The demand for soybean necessitates a better understanding of the regulatory networks driving storage protein accumulation and oil biosynthesis to broaden its positive impact on human health. In this study, we selected a chromosome segment substitution line (CSSL) with high protein and low oil contents to investigate the underlying effect of donor introgression on seed storage through multi-omics analysis. In total, 1479 differentially expressed genes (DEGs), 82 differentially expressed proteins (DEPs), and 34 differentially expressed metabolites (DEMs) were identified in the CSSL compared to the recurrent parent. Based on Gene Ontology (GO) term analysis and the Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG), integrated analysis indicated that 31 DEGs, 24 DEPs, and 13 DEMs were related to seed storage functionality. Integrated analysis further showed a significant decrease in the contents of the seed storage lipids LysoPG 16:0 and LysoPC 18:4 as well as an increase in the contents of organic acids such as L-malic acid. Taken together, these results offer new insights into the molecular mechanisms of seed storage and provide guidance for the molecular breeding of new favorable soybean varieties.

ResNet incorporating the fusion data of RGB & hyperspectral images improves classification accuracy of vegetable soybean freshness

The freshness of vegetable soybean (VS) is an important indicator for quality evaluation. Currently, deep learning-based image recognition technology provides a fast, efficient, and low-cost method for analyzing the freshness of food. The RGB (red, green, and blue) image recognition technology is widely used in the study of food appearance evaluation. In addition, the hyperspectral image has outstanding performance in predicting the nutrient content of samples. However, there are few reports on the research of classification models based on the fusion data of these two sources of images. We collected RGB and hyperspectral images at four different storage times of VS. The ENVI software was adopted to extract the hyperspectral information, and the RGB images were reconstructed based on the downsampling technology. Then, the one-dimensional hyperspectral data was transformed into a two-dimensional space, which allows it to be overlaid and concatenated with the RGB image data in the channel direction, thereby generating fused data. Compared with four commonly used machine learning models, the deep learning model ResNet18 has higher classification accuracy and computational efficiency. Based on the above results, a novel classification model named ResNet-R &H, which is based on the residual networks (ResNet) structure and incorporates the fusion data of RGB and hyperspectral images, was proposed. The ResNet-R &H can achieve a testing accuracy of 97.6%, which demonstrates a significant enhancement of 4.0% and 7.2% compared to the distinct utilization of hyperspectral data and RGB data, respectively. Overall, this research is significant in providing a unique, efficient, and more accurate classification approach in evaluating the freshness of vegetable soybean. The method proposed in this study can provide a theoretical reference for classifying the freshness of fruits and vegetables to improve classification accuracy and reduce human error and variability.

Genetic and Phenotypic Characterization of Soybean Landraces Collected from the Zhejiang Province in China

The soybean is an important feed, industrial raw material, and food crop in the world due to its rich components. There is a long history of soybean cultivation with different types and rich resources in the Zhejiang province of China. It is important to understand genetic diversity as well as phenotypic variation for soybean breeding. The objective of this study was to analyze both genetic and phenotypic characteristics of the 78 soybean landraces collected, and to explore a potential advantage of germplasm resources for further application. These 78 autumn-type soybean landraces have been propagated, identified, and evaluated in both 2021 and 2022. There were agronomic, quality, and genetic variations according to the comprehensive analyses. There was a good consistency between seed size and seed coat color. There were significant differences of seed protein, fat, and sugar contents based upon the seed coat color. These soybean landraces were genotyped using 42 simple sequence repeat markers and then clustered into two groups. The two groups had a consistency with the seed coat color. This study gave us a combined understanding of both the phenotypic variation and the genetic diversity of the soybean landraces. Therefore, the reasonable crossing between different soybean types is highly recommended.

Population Structure and Genetic Diversity of the 175 Soybean Breeding Lines and Varieties Cultivated in West Siberia and Other Regions of Russia

Soybean is a leguminous plant cultivated in many countries and is considered important in the food industry due to the high levels of oil and protein content in the beans. The high demand for soybeans and its products in the industry requires the expansion of cultivation areas. Despite climatic restrictions, West Siberia is gradually expanding its area of soybean cultivation. In this study, we present the first analysis of the population structure and genetic diversity of the 175 soybean Glycine max breeding lines and varieties cultivated in West Siberia (103 accessions) and other regions of Russia (72 accessions), and we compare them with the cultivated soybean varieties from other geographical locations. Principal component analysis revealed several genetic clusters with different levels of genetic heterogeneity. Studied accessions are genetically similar to varieties from China, Japan, and the USA and are genetically distant to varieties from South Korea. Admixture analysis revealed four ancestry groups based on genetic ancestry and geographical origin, which are consistent with the regions of cultivation and origin of accessions and correspond to the principal component analysis result. Population statistics, including nucleotide diversity, Tajima's D, and linkage disequilibrium, are comparatively similar to those observed for studied accessions of a different origin. This study provides essential population and genetic information about the unique collection of breeding lines and varieties cultivated in West Siberia and other Russian regions to foster further evolutionary, genome-wide associations and functional breeding studies.

Morphological and microsatellite marker-based characterization and diversity analysis of novel vegetable soybean [Glycine max (L.) Merrill]

BACKGROUND

Vegetable soybean seeds are among the most popular and nutrient-dense beans in the world due to their delicious flavor, high yield, superior nutritional value, and low trypsin content. There is significant potential for this crop that Indian farmers do not fully appreciate because of the limited germplasm range. Therefore, the current study aims to identify the diverse lines of vegetable soybean and explore the diversity produced by hybridizing grain and vegetable-type soybean varieties. Indian researchers have not yet published work describing and analysing novel vegetable soybean for microsatellite markers and morphological traits.

METHODS AND RESULTS

Sixty polymorphic SSR markers and 19 morphological traits were used to evaluate the genetic diversity of 21 newly developed vegetable soybean genotypes. A total of 238 alleles, ranging from 2 to 8, were found, with a mean of 3.97 alleles per locus. The polymorphism information content varied from 0.05 to 0.85, with an average of 0.60. A variation of 0.25-0.58 with a mean of 0.43 was observed for Jaccard's dissimilarity coefficient.

CONCLUSION

The diverse genotypes identified can be helpful to understand the genetics of vegetable soybean traits and can be used in improvement programs; study also explains the utility of SSR markers for diversity analysis of vegetable soybean. Here, we identified the highly informative SSRs with PIC > 0.80 (satt199, satt165, satt167, satt191, satt183, satt202, and satt126), which apply to genetic structure analysis, mapping strategies, polymorphic marker surveys, and background selection in genomics-assisted breeding.

Global Status of Vegetable Soybean

Vegetable soybean, popularly known as edamame in Japan and mao dou in China is a specialty soybean. Green pods with physiologically mature beans are harvested, and whole pods or shelled beans are used as a fresh or frozen vegetable. Vegetable soybeans are prepared in diverse ways, and they are highly nutritious, with excellent taste properties. Unlike grain soybeans, it is perishable. In this review, the chronological progression of area, production, export, import, and expansion of vegetable soybeans and potential for further expansion is discussed. Available information on current ongoing research and development activities in various countries around the world are presented, and their relevance is discussed. At present, the production and consumption of vegetable soybeans are mainly in East and Southeast Asia, with Japan as the largest importing country that dictates the global market. However, interest and trend in cultivation of this crop in other regions has increased significantly. Lack of germplasm or suitable varieties is a major constraint in vegetable soybean production and expansion in countries outside East and Southeast Asia. Most of the vegetable soybean varieties are genetically related and are susceptible to biotic and abiotic stresses. Extensive research and breeding of vegetable soybeans are still restricted in a few countries such as China, Japan, Taiwan and the USA. The need for focused research and development activities with concern for the environment, farmers' and processors' profit, consumers' preference, quality, and nutrition are emphasized.

Promoter of Vegetable Soybean GmTIP1;6 Responds to Diverse Abiotic Stresses and Hormone Signals in Transgenic Arabidopsis

Tonoplast intrinsic proteins (TIPs), a sub-family of aquaporins (AQPs), are known to play important roles in plant abiotic stress responses. However, evidence for the promoters of TIPs involvement in abiotic stress processes remains scarce. In this study, the promoter of the vegetable soybean GmTIP1;6 gene, which had the highest similarity to TIP1-type AQPs from other plants, was cloned. Expression pattern analyses indicated that the GmTIP1;6 gene was dramatically induced by drought, salt, abscisic acid (ABA), and methyl jasmonate (MeJA) stimuli. Promoter analyses revealed that the GmTIP1;6 promoter contained drought, ABA, and MeJA cis-acting elements. Histochemical staining of the GmTIP1;6 promoter in transgenic Arabidopsis corroborated that it was strongly expressed in the vascular bundles of leaves, stems, and roots. Beta-glucuronidase (GUS) activity assays showed that the activities of the GmTIP1;6 promoter were enhanced by different concentrations of polyethylene glycol 6000 (PEG 6000), NaCl, ABA, and MEJA treatments. Integrating these results revealed that the GmTIP1;6 promoter could be applied for improving the tolerance to abiotic stresses of the transgenic plants by promoting the expression of vegetable soybean AQPs.

Identification of major genomic regions for soybean seed weight by genome-wide association study

The hundred-seed weight (HSW) is an important yield component and one of the principal breeding traits in soybean. More than 250 quantitative trait loci (QTL) for soybean HSW have been identified. However, most of them have a large genomic region or are environmentally sensitive, which provide limited information for improving the phenotype in marker-assisted selection (MAS) and identifying the candidate genes. Here, we utilized 281 soybean accessions with 58,112 single nucleotide polymorphisms (SNPs) to dissect the genetic basis of HSW in across years in the northern Shaanxi province of China through one single-locus (SL) and three multi-locus (ML) genome-wide association study (GWAS) models. As a result, one hundred and fifty-four SNPs were detected to be significantly associated with HSW in at least one environment via SL-GWAS model, and 27 of these 154 SNPs were detected in all (three) environments and located within 7 linkage disequilibrium (LD) block regions with the distance of each block ranged from 40 to 610 Kb. A total of 15 quantitative trait nucleotides (QTNs) were identified by three ML-GWAS models. Combined with the results of different GWAS models, the 7 LD block regions associated with HSW detected by SL-GWAS model could be verified directly or indirectly by the results of ML-GWAS models. Eleven candidate genes underlying the stable loci that may regulate seed weight in soybean were predicted. The significantly associated SNPs and the stable loci as well as predicted candidate genes may be of great importance for marker-assisted breeding, polymerization breeding, and gene discovery for HSW in soybean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01310-y.

Genome Assembly and Analysis of the Flavonoid and Phenylpropanoid Biosynthetic Pathways in Fingerroot Ginger (Boesenbergia rotunda)

Boesenbergia rotunda (Zingiberaceae), is a high-value culinary and ethno-medicinal plant of Southeast Asia. The rhizomes of this herb have a high flavanone and chalcone content. Here we report the genome analysis of B. rotunda together with a complete genome sequence as a hybrid assembly. B. rotunda has an estimated genome size of 2.4 Gb which is assembled as 27,491 contigs with an N50 size of 12.386 Mb. The highly heterozygous genome encodes 71,072 protein-coding genes and has a 72% repeat content, with class I TEs occupying ~67% of the assembled genome. Fluorescence in situ hybridization of the 18 chromosome pairs at the metaphase showed six sites of 45S rDNA and two sites of 5S rDNA. An SSR analysis identified 238,441 gSSRs and 4604 EST-SSRs with 49 SSR markers common among related species. Genome-wide methylation percentages ranged from 73% CpG, 36% CHG and 34% CHH in the leaf to 53% CpG, 18% CHG and 25% CHH in the embryogenic callus. Panduratin A biosynthetic unigenes were most highly expressed in the watery callus. B rotunda has a relatively large genome with a high heterozygosity and TE content. This assembly and data (PRJNA71294) comprise a source for further research on the functional genomics of B. rotunda, the evolution of the ginger plant family and the potential genetic selection or improvement of gingers.