Analysis of Shoot Architecture Traits in Edamame Reveals Potential Strategies to Improve Harvest Efficiency

Multi-Omics Analysis Provides Insights into Green Soybean in Response to Cold Stress

Green soybean (Glycine max (L.) Merrill) is a highly nutritious food that is a good source of protein and fiber. However, it is sensitive to low temperatures during the growing season, and enhancing cold tolerance has become a research hotspot for breeding improvement. Background/Objectives: The underlying molecular mechanisms of cold tolerance in green soybean are not well understood. Methods: Here, a comprehensive analysis of transcriptome and metabolome was performed on a cold-tolerant cultivar treated at 10 °C for 24 h. Results: Compared to control groups, we identified 17,011 differentially expressed genes (DEGs) and 129 differentially expressed metabolites (DEMs). The DEGs and DEMs were further subjected to KEGG functional analysis. Finally, 11 metabolites (such as sucrose, lactose, melibiose, and dehydroascorbate) and 17 genes (such as GOLS, GLA, UGDH, and ALDH) were selected as candidates associated with cold tolerance. Notably, the identified metabolites and genes were enriched in two common pathways: 'galactose metabolism' and 'ascorbate and aldarate metabolism'. Conclusions: The findings suggest that green soybean modulates the galactose metabolism and ascorbate and aldarate metabolism pathways to cope with cold stress. This study contributes to a deeper understanding of the complex molecular mechanisms enabling green soybeans to better avoid low-temperature damage.

Mapping and quantifying unique branching structures in lentil (Lens culinaris Medik.)

BACKGROUND

Lentil (Lens culinaris Medik.) is a globally-significant agricultural crop used to feed millions of people. Lentils have been cultivated in the Australian states of Victoria and South Australia for several decades, but efforts are now being made to expand their cultivation into Western Australia and New South Wales. Plant architecture plays a pivotal role in adaptation, leading to improved and stable yields especially in new expansion regions. Image-based high-throughput phenomics technologies provide opportunities for an improved understanding of plant development, architecture, and trait genetics. This paper describes a novel method for mapping and quantifying individual branch structures on immature glasshouse-grown lentil plants grown using a LemnaTec Scanalyser 3D high-throughput phenomics platform, which collected side-view RGB images at regular intervals under controlled photographic conditions throughout the experiment. A queue and distance-based algorithm that analysed morphological skeletons generated from images of lentil plants was developed in Python. This code was incorporated into an image analysis pipeline using open-source software (PlantCV) to measure the number, angle, and length of individual branches on lentil plants.

RESULTS

Branching structures could be accurately identified and quantified in immature plants, which is sufficient for calculating early vigour traits, however the accuracy declined as the plants matured. Absolute accuracy for branch counts was 77.9% for plants at 22 days after sowing (DAS), 57.9% at 29 DAS and 51.9% at 36 DAS. Allowing for an error of ± 1 branch, the associated accuracies for the same time periods were 97.6%, 90.8% and 79.2% respectively. Occlusion in more mature plants made the mapping of branches less accurate, but the information collected could still be useful for trait estimation. For branch length calculations, the amount of variance explained by linear mixed-effects models was 82% for geodesic length and 87% for Euclidean branch lengths. Within these models, both the mean geodesic and Euclidean distance measurements of branches were found to be significantly affected by genotype, DAS and their interaction. Two informative metrices were derived from the calculations of branch angle; 'splay' is a measure of how far a branch angle deviates from being fully upright whilst 'angle-difference' is the difference between the smallest and largest recorded branch angle on each plant. The amount of variance explained by linear mixed-effects models was 38% for splay and 50% for angle difference. These lower R2 values are likely due to the inherent difficulties in measuring these parameters, nevertheless both splay and angle difference were found to be significantly affected by cultivar, DAS and their interaction. When 276 diverse lentil genotypes with varying degrees of salt tolerance were grown in a glasshouse-based experiment where a portion were subjected to a salt treatment, the branching algorithm was able to distinguish between salt-treated and untreated lentil lines based on differences in branch counts. Likewise, the mean geodesic and Euclidean distance measurements of branches were both found to be significantly affected by cultivar, DAS and salt treatment. The amount of variance explained by the linear mixed-effects models was 57.8% for geodesic branch length and 46.5% for Euclidean branch length.

CONCLUSION

The methodology enabled the accurate quantification of the number, angle, and length of individual branches on glasshouse-grown lentil plants. This methodology could be applied to other dicotyledonous species.

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.

Effects of Climate Conditions before Harvest Date on Edamame Metabolome

Edamame is a green soybean that is rich in nutrients. Boiled edamame has been traditionally used for food in the East Asia region. It was known among farmers that conditions, such as temperature and climate on the day of harvest, affect the quality of edamame. Large-scale farmers harvest edamame on multiple days in the same year; however, the quality of edamame varies from day to day due to variations in climate conditions. In this study, we harvested edamame over several days between 2013 and 2018, obtained the climate conditions on the harvest date, and performed metabolome analysis using capillary electrophoresis mass spectrometry. To clarify the correlation between climate conditions before the harvest date and edamame components, comparative analyses of the obtained meteorological and metabolomic data were conducted. We found positive and negative correlations between the sunshine duration and average temperature, and the amounts of some edamame components. Furthermore, correlations were observed between the annual fluctuations in climate conditions and edamame components. Our findings suggest that the climate conditions before the date of harvesting are closely related to edamame quality.

Genome-wide association analysis of sucrose and alanine contents in edamame beans

The sucrose and Alanine (Ala) content in edamame beans significantly impacts the sweetness flavor of edamame-derived products as an important attribute to consumers' acceptance. Unlike grain-type soybeans, edamame beans are harvested as fresh beans at the R6 to R7 growth stages when beans are filled 80-90% of the pod capacity. The genetic basis of sucrose and Ala contents in fresh edamame beans may differ from those in dry seeds. To date, there is no report on the genetic basis of sucrose and Ala contents in the edamame beans. In this study, a genome-wide association study was conducted to identify single nucleotide polymorphisms (SNPs) related to sucrose and Ala levels in edamame beans using an association mapping panel of 189 edamame accessions genotyped with a SoySNP50K BeadChip. A total of 43 and 25 SNPs was associated with sucrose content and Ala content in the edamame beans, respectively. Four genes (Glyma.10g270800, Glyma.08g137500, Glyma.10g268500, and Glyma.18g193600) with known effects on the process of sucrose biosynthesis and 37 novel sucrose-related genes were characterized. Three genes (Gm17g070500, Glyma.14g201100 and Glyma.18g269600) with likely relevant effects in regulating Ala content and 22 novel Ala-related genes were identified. In addition, by summarizing the phenotypic data of edamame beans from three locations in two years, three PI accessions (PI 532469, PI 243551, and PI 407748) were selected as the high sucrose and high Ala parental lines for the perspective breeding of sweet edamame varieties. Thus, the beneficial alleles, candidate genes, and selected PI accessions identified in this study will be fundamental to develop edamame varieties with improved consumers' acceptance, and eventually promote edamame production as a specialty crop in the United States.