Flowering time is a crucial agronomic trait that affects the adaptability and yield of soybeans. Despite extensive research aimed at uncovering the genetic basis of flowering time in soybean germplasm, investigations involving the soybean germplasm from Northeast China have been limited. Here, we elucidated the genetic basis of days to flowering (DTF) in the soybean germplasm grown in Northeast China by employing an integrated strategy, including association mapping, quantitative trait locus (QTL) analysis, haplotype analysis, and candidate gene analysis. Overall, the genome-wide association study (GWAS) revealed 15 single-nucleotide polymorphisms (SNPs) significantly linked with DTF across six GWAS models and four individual environments plus a combined environment (CE). Five stable QTL were identified, among which four (viz., qDTF8, qDTF12, qDTF15.1, and qDTF15.2) are reported for the first time, and the remaining one (qDTF19) was detected in previous studies. On the basis of the findings of expression and haplotype analysis, fourteen putative candidate genes were detected across the genomic intervals of these five QTL. Among these genes, Glyma.19 g197600 and Glyma.19 g200700 were confirmed through both expression and haplotype analysis. Moreover, the relationship of the haplotypes with gene expression indicates that Glyma.19 g197600 is a negative regulator of early flowering, thereby providing evidence of its role in flowering. This study reveals potential genetic loci and genes that could facilitate the expansion of soybean cultivation into regions with short growing seasons and long photoperiodic conditions across the globe.

Flavonoids are crucial secondary metabolites widely distributed in plants, playing vital roles in diverse biological processes. Although the flavonoid biosynthesis pathway has been extensively characterized, the transcriptional regulatory mechanisms remain poorly understood. In this study, we identify the miR166–ATHB14-LIKE module comprising the miR166 and its target gene ATHB14-LIKE as a key regulator of flavonoid biosynthesis in soybean (Glycine max). Knockdown of miR166 or overexpression of ATHB14-LIKE upregulated multiple flavonoid biosynthesis genes, leading to increased flavonoid accumulation. Conversely, miR166 overexpression suppressed these genes and reduced flavonoid levels. We further show that ATHB14-LIKE directly activates specific flavonoid biosynthesis genes by binding to their promoters. Additionally, ATHB14-LIKE forms homodimers and heterodimers with homologous proteins to regulate downstream flavonoid biosynthesis genes. Together, our findings demonstrate that the miR166–ATHB14-LIKE module controls soybean flavonoid content by coordinating the expression of key biosynthetic genes.

The rate of soybean canopy establishment largely determines photoperiodic sensitivity, subsequently influencing yield potential. However, assessing the rate of soybean canopy development in large-scale field breeding trials is both laborious and time-consuming. High-throughput phenotyping methods based on unmanned aerial vehicle (UAV) systems can be used to monitor and quantitatively describe the development of soybean canopies for different genotypes. In this study, high-resolution and time-series raw data from field soybean populations were collected using UAVs. The RGB (red, green, and blue) and infrared images are used as inputs to construct the multimodal image segmentation model—the RGB & Infrared Feature Fusion Segmentation Network (RIFSeg-Net). Subsequently, the segment anything model was employed to extract complete individual leaves from the segmentation results obtained from RIFSeg-Net. These leaf aspect ratios facilitated the accurate categorization of soybean populations into 2 distinct varieties: oval leaf type variety and lanceolate leaf type variety. Finally, dynamic modeling was conducted to identify 5 phenotypic traits associated with the canopy development rate that differed substantially among the classified soybean varieties. The results showed that the developed multimodal image segmentation model RIFSeg-Net for extracting soybean canopy cover from UAV images outperformed traditional deep learning image segmentation networks (precision = 0.94, recall = 0.93, F1-score = 0.93). The proposed method has high practical value in the field of germplasm resource identification. This approach could lead to the use of a practical tool for further genotypic differentiation analysis and the selection of target genes.

Drought stress limits agricultural productivity worldwide. Identifying and characterizing genetic components of drought stress-tolerance networks may improve crop resistance to drought stress. We show that the regulatory module formed by miR166 and its target gene, ATHB14-LIKE, functions in the regulation of drought tolerance in soybean (Glycine max). Drought stress represses the accumulation of miR166, leading to upregulation of its target genes. Optimal knockdown of miR166 in the stable transgenic line GmSTTM166 conferred drought tolerance without affecting yield. Expression of ABA signaling pathway genes was regulated by the miR166-mediated regulatory pathway, and ATHB14-LIKE directly activates some of these genes. There is a feedback regulation between ATHB14-LIKE and MIR166 genes, and ATHB14-LIKE inhibits MIR166 expression. These findings reveal that drought-triggered regulation of the miR166-mediated regulatory pathway increases plants drought resistance, providing new insights into drought stress regulatory network in soybean.

Soybean [Glycine max (L.) Merr.] provides a rich source of plant protein and oil worldwide. The commercial use of transgenic technology in soybean has become a classical example of the application of biotechnology to crop improvement. Although genetically modified soybeans have achieved commercial success, hybrid soybean breeding is also a potential way to increase soybean yield. Soybean cytoplasmic male-sterile (CMS) lines have been used in three-line hybrid breeding systems, but their application to exploiting soybean heterosis has been limited by rare germplasm resource of sterile lines. The generation of various genetic diversity male-sterile soybean lines will help to overcome the shortcoming. In this study, we used targeted editing of AMS homologs in soybean by CRISPR/Cas9 technology for the first time to generate stable male-sterile lines. Targeted editing of GmAMS1 resulted in a male-sterile phenotype, while editing of GmAMS2 failed to produce male-sterile lines. GmAMS1 functions not only in the formation of the pollen wall but also in the controlling the degradation of the soybean tapetum. CRISPR/Cas9 technology could be used to rapidly produce stable male-sterile lines, providing new sterile-line materials for soybean hybrid breeding systems.