The genetic basis of shoot architecture in soybean

Multi-Scale Attention Network for Vertical Seed Distribution in Soybean Breeding Fields

The increase in the global population is leading to a doubling of the demand for protein. Soybean (Glycine max), a key contributor to global plant-based protein supplies, requires ongoing yield enhancements to keep pace with increasing demand. Precise, on-plant seed counting and localization may catalyze breeding selection of shoot architectures and seed localization patterns related to superior performance in high planting density and contribute to increased yield. Traditional manual counting and localization methods are labor-intensive and prone to error, necessitating more efficient approaches for yield prediction and seed distribution analysis. To solve this, we propose MSANet: a novel deep learning framework tailored for counting and localization of soybean seeds on mature field-grown soy plants. A multi-scale attention map mechanism was applied to maximize model performance in seed counting and localization in soybean breeding fields. We compared our model with a previous state-of-the-art model using the benchmark dataset and an enlarged dataset, including various soybean genotypes. Our model outperforms previous state-of-the-art methods on all datasets across various soybean genotypes on both counting and localization tasks. Furthermore, our model also performed well on in-canopy 360° video, dramatically increasing data collection efficiency. We also propose a technique that enables previously inaccessible insights into the phenotypic and genetic diversity of single plant vertical seed distribution, which may accelerate the breeding process. To accelerate further research in this domain, we have made our dataset and software publicly available: https://github.com/UTokyo-FieldPhenomics-Lab/MSANet.

Molecular Regulation of Shoot Architecture in Soybean

Soybean (Glycine max [L.] Merr.) serves as a major source of protein and oil for humans and animals. Shoot architecture, the spatial arrangement of a plant's above-ground organs, strongly affects crop yield and is therefore a critical agronomic trait. Unlike wheat and rice crops that have greatly benefitted from the Green Revolution, soybean yield has not changed significantly in the past six decades owing to its unique shoot architecture. Soybean is a pod-bearing crop with pods adhered to the nodes, and variation in shoot architecture traits, such as plant height, node number, branch number and number of seeds per pod, directly affects the number of pods and seeds per plant, thereby determining yield. In this review, we summarize the relationship between soybean yield and these major components of shoot architecture. We also describe the latest advances in identifying the genes and molecular mechanisms underlying soybean shoot architecture and discuss possible directions and approaches for breeding new soybean varieties with ideal shoot architecture and improved yield.

Identification and mapping of a recessive allele, dt3, specifying semideterminate stem growth habit in soybean

KEY MESSAGE

A locus, dt3, modulating semideterminancy in soybean, was discovered by a combination of genome-wide association studies and linkage mapping with multiple distinct biparental populations. Stem growth habit is a key architectural trait in many plants that contributes to plant productivity and environmental adaptation. In soybean, stem growth habit is classified as indeterminate, semideterminate, or determinate, of which semideterminacy is often considered as a counterpart of the "Green Revolution" trait in cereals that significantly increased grain yields. It has been demonstrated that semideterminacy in soybean is modulated by epistatic interaction between two loci, Dt1 on chromosome 19 and Dt2 on chromosome 18, with the latter as a negative regulator of the former. Here, we report the discovery of a third locus, Dt3, modulating soybean stem growth habit, which was delineated to a ~ 196-kb region on chromosome 10 by a combination of allelic and haplotypic analysis of the Dt1 and Dt2 loci in the USDA soybean Germplasm Collection, genome-wide association studies with three subsets of the collection, and linkage mapping with four biparental populations derived from crosses between one of two elite indeterminate cultivars and each of four semideterminate varieties possessing neither Dt2 nor dt1. These four semideterminate varieties are recessive mutants (i.e., dt3/dt3) in the Dt1/Dt1;dt2/dt2 background. As the semideterminacy modulated by the Dt2 allele has unfavorable pleotropic effects such as sensitivity to drought stress, dt3 may be an ideal alternative for use to develop semideterminate cultivars that are more resilient to such an environmental stress. This study enhances our understanding of the genetic factors underlying semideterminacy and enables more accurate marker-assisted selection for stem growth habit in soybean breeding.

Cytokinin and Metabolites Affect Rhizome Growth and Development in Kentucky Bluegrass (Poa pratensis)

Rhizome growth and development is regulated by phytohormone. However, endogenous phytohormones affect rhizome initiation, and sustained growth in perennial grass species remains elusive. In this study, we investigated the morphological characteristics and the content of indole-3-acetic acid (IAA), zeatin (ZT), gibberellic acid (GA3), and abscisic acid (ABA) in the rhizomes of two different Kentucky bluegrass. Using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS), we performed metabolite analysis of two different rhizomes. In our study, the multi-rhizome Kentucky bluegrass material 'Yuzhong' had an average of 1113 rhizomes, while the few-rhizome material 'Anding' had an average of 347 rhizomes. The diameter of rhizome and length of rhizome internode in 'Yuzhong' were 1.68-fold and 1.33-fold higher than that of the 'Anding', respectively. The rhizome dry weight of 'Yuzhong' was 75.06 g, while the 'Anding' was 20.79 g. 'Yuzhong' had a higher ZT content (5.50 μg·g-1), which is 2.4-fold that of 'Anding' (2.27 μg·g-1). In contrast, the IAA, ABA, and GA3 content of rhizome were markedly higher in 'Anding' than 'Yuzhong'. Correlation analysis revealed significant correlations between ZT and ZT/ABA with the number of rhizomes, diameter of rhizome, and length of rhizome internode, whereas IAA, ABA, GA3, and IAA/ZT were opposite. In the metabolic profiles, we identified 163 differentially expressed metabolites (DEMs) (60 upregulated and 103 downregulated) in positive ion mode and 75 DEMs (36 upregulated and 39 downregulated) in negative ion mode. Histidine metabolism and ABC transporters pathways were the most significantly enriched in the positive and negative ion mode, respectively, both of which are involved in the synthesis and transport of cytokinin. These results indicate that cytokinin is crucial for rhizome development and promotes rhizome germination and growth of Kentucky bluegrass.