Laccase is a widely used industrial oxidase for food processing, dye synthesis, paper making, and pollution remediation. At present, laccases used by industries come mainly from fungi. Plants contain numerous genes encoding laccase enzymes that show properties which are distinct from that of the fungal laccases. These plant-specific laccases may have better potential for industrial purposes. The aim of this work was to conduct a genome-wide search for the soybean laccase genes and analyze their characteristics and specific functions. A total of 93 putative laccase genes (GmLac) were identified from the soybean genome. All 93 GmLac enzymes contain three typical Cu-oxidase domains, and they were classified into five groups based on phylogenetic analysis. Although adjacent members on the tree showed highly similar exon/intron organization and motif composition, there were differences among the members within a class for both conserved and differentiated functions. Based on the expression patterns, some members of laccase were expressed in specific tissues/organs, while some exhibited a constitutive expression pattern. Analysis of the transcriptome revealed that some laccase genes might be involved in providing resistance to oomycetes. Analysis of the selective pressures acting on the laccase gene family in the process of soybean domestication revealed that 10 genes could have been under artificial selection during the domestication process. Four of these genes may have contributed to the transition of the soft and thin stem of wild soybean species into strong, thick, and erect stems of the cultivated soybean species. Our study provides a foundation for future functional studies of the soybean laccase gene family.

The Fabaceae family, the third-largest among flowering plants, is nutritionally vital, providing rich sources of protein, dietary fiber, vitamins, and minerals. Leguminous plants, such as soybeans, peas, and chickpeas, typically contain two to three times more protein than cereals like wheat and rice, with low fat content (primarily unsaturated fats) and no cholesterol, making them essential for cardiovascular health and blood sugar management. Since the release of the soybean genome in 2010, genomic research in Fabaceae has advanced dramatically. High-quality reference genomes have been assembled for key species, including soybeans (Glycine max), common beans (Phaseolus vulgaris), chickpeas (Cicer arietinum), and model legumes like Medicago truncatula and Lotus japonicus, leveraging long-read sequencing, single-cell technologies, and improved assembly algorithms. These advancements have enabled telomere-to-telomere (T2T) assemblies, pan-genome constructions, and the identification of structural variants (SVs) and presence/absence variations (PAVs), enriching our understanding of genetic diversity and domestication history. Functional genomic tools, such as CRISPR-Cas9 gene editing, mutagenesis, and high-throughput omics (transcriptomics, metabolomics), have elucidated regulatory networks controlling critical traits like photoperiod sensitivity (e.g., E1 and Tof16 genes in soybeans), seed development (GmSWEET39 for oil/protein transport), nitrogen fixation efficiency, and stress resilience (e.g., Rpp3 for rust resistance). Genome-wide association studies (GWAS) and comparative genomics have further linked genetic variants to agronomic traits, such as pod size in peanuts (PSW1) and flowering time in common beans (COL2). This review synthesizes recent breakthroughs in legume genomics, highlighting the integration of multi-omic approaches to accelerate gene cloning and functional confirmation of the genes cloned.

Plants photoreceptors perceive changes in light quality and intensity and thereby regulate plant vegetative growth and reproductive development. By screening a γ irradiation-induced mutant library of the soybean (Glycine max) cultivar “Dongsheng 7”, we identified Gmeny, a mutant with elongated nodes, yellowed leaves, decreased chlorophyll contents, altered photosynthetic performance, and early maturation. An analysis of bulked DNA and RNA data sampled from a population segregating for Gmeny, using the BVF-IGV pipeline established in our laboratory, identified a 10 bp deletion in the first exon of the candidate gene Glyma.02G304700. The causative mutation was verified by a variation analysis of over 500 genes in the candidate gene region and an association analysis, performed using two populations segregating for Gmeny. Glyma.02G304700 (GmHY2a) is a homolog of AtHY2a in Arabidopsis thaliana, which encodes a PΦB synthase involved in the biosynthesis of phytochrome. A transcriptome analysis of Gmeny using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed changes in multiple functional pathways, including photosynthesis, gibberellic acid (GA) signaling, and flowering time, which may explain the observed mutant phenotypes. Further studies on the function of GmHY2a and its homologs will help us to understand its profound regulatory effects on photosynthesis, photomorphogenesis, and flowering time.

Background: The traits of the time to flowering and maturity and other important agronomic traits, e.g., plant height, the numbers of nodes and branches are key factors for the adaptability of soybean cultivars to a certain photoperiodic length and ecological environment. Correlation analysis of these traits will facilitate fine-tuning of phenotyping procedure for each trait. Methods: In this field investigation during 2017-2020 at two experimental stations in Heilongjiang Province, northern China, a total of 1133 cultivars or accessions were phenotyped for traits related to maturity, architecture, e.g. plant height, the numbers of nodes and branches and yield. Statistical analysis was performed to reveal the correlation between different traits, years and locations. Result: R1 (days to the first flowering stage) and R2 (days to the fully flowering stage) are strongly stable traits among different years and different locations in this study. Significant correlations were identified between maturity trait, plant height, the numbers of nodes and branches. However, the traits of the height of the first effective node and the pod number per plant demonstrated some weak correlation among different years or with these maturity traits. Therefore, phenotyping procedures in this study can be directly applicable for accurate evaluation of maturity and plant architecture-related traits e.g. plant height, the numbers of nodes and branches.