Tingting Wu

SUMMARY: Precise regulation of flowering time and maturity is critical for achieving high and stable soybean yields, and the circadian clock plays a central role in coordinating these developmental transitions. Soybean is a typical short‐day crop with a pronounced photoperiodic response; however, the molecular mechanisms linking circadian regulation to photoperiod‐dependent flowering and maturity remain incompletely understood. Here, we integrated genome‐wide association analysis with deep learning approaches using 257 soybean germplasm accessions spanning 14 maturity groups and identified GmRVE8a , a homolog of the Arabidopsis circadian clock gene REVEILLE , as a strong candidate locus associated with soybean maturity across two field environments. Haplotype analysis demonstrated that accessions carrying the GmRVE8a ^H1 haplotype consistently flowered and matured significantly later than those carrying GmRVE8a ^H2 . Functional validation revealed that knockout of GmRVE8a markedly accelerated flowering and maturity, whereas overexpression of GmRVE8a significantly delayed both processes. qRT‐PCR assays further suggested that GmRVE8a may repress flowering and delay maturity by promoting the expression of GmFT4 , a flowering‐inhibitory member of the FT family, and is unlikely to act by directly regulating E1 expression. Collectively, our findings suggest GmRVE8a as a circadian clock‐associated negative regulator of soybean flowering and maturity, and highlight it as a promising candidate for molecular breeding aimed at improving adaptation to diverse photoperiodic environments.

Ethylene response factor (ERF) proteins constitute a major branch of the AP2/ERF transcription factor superfamily and are conventionally divided into six groups (B1–B6) on the basis of conserved sequences and phylogenetic relationships. ERFs recognize cis-elements such as the GCC-box and dehydration-responsive element/C-repeat and assemble regulatory complexes with coactivators or corepressors. They thereby coordinate responses to drought, salinity, low and high temperatures, hypoxia, flooding, and pathogen attack. Their outputs are determined not by a single motif but by DNA-binding preference, interacting partners, tissue context, and post-translational control through mitogen-activated protein kinase phosphorylation, ubiquitination, and the N-degron pathway. Crop studies increasingly show that ERF alleles and regulatory modules can improve stress tolerance and disease resistance, although constitutive manipulation frequently compromises growth, yield, or quality. This review focuses on the narrowly defined ERF subfamily, evaluates the evidence linking classification, transcriptional regulation, protein stability, and stress phenotypes, and examines breeding strategies based on molecular markers, tissue-specific expression, cis-regulatory editing, and favorable alleles. We argue that progress now depends on causal analysis under combined stresses and multi-environment yield validation, enabling stress protection to be decoupled from agronomic penalties.

Soybean (Glycine max) is a critically important crop for oil, protein, feed, and food security in China. Expanding soybean cultivation into high-latitude regions represents one of the most direct and effective strategies to increase total production. In the present study, we employed KASP (Kompetitive Allele-Specific PCR) marker technology to systematically analyze 18 variant loci across 14 flowering-time genes in 443 soybean germplasm accessions adapted to high-latitude conditions in Arctic Village (Beiji Cun), Mohe City (>53° N), northeastern China. Our results revealed clear functional-tier-dependent selection gradients: key mutation sites (frequency > 96%) in upstream photoreceptors and core circadian clock genes, such as E2 and GmPRR3a, were nearly fixed in the population, whereas downstream flowering genes such as GmFT5b and GmFT2b remained under dynamic selection. Combinatorial analysis of early-maturity allelic variants identified 178 distinct genotype combinations, including six dominant types (n ≥ 10). Field phenotypic analysis demonstrated that the cumulative number of early-maturity alleles was significantly negatively correlated with flowering time, with specific allele combinations such as FT5a^A + FKF1b-hap3^T exhibiting particularly strong flower-promoting effects. A set of 80 highly enriched super-early-maturity accessions, including extreme materials such as MHL22002, were identified, providing valuable genetic resources and a theoretical framework for elucidating the flowering regulatory mechanisms of high-latitude soybean and for breeding super-early-maturing varieties.

Flowering time, determined by genetic loci and environmental cues, is crucial for soybeans' geographic distribution and regional adaptability. This study aimed to generate a workflow of genetic and environmental analysis for determinants of soybean flowering time. By investigating flowering time in both natural populations and recombinant inbred lines (RIL) across eight environments spanning from 18°15′10″ N to 43°49′02″ N across two years, we found that photothermal ratio (PTR) strongly correlated with early‐ and mid‐pre‐flowering stages (16–23 days after planting). We detected 298 Quantitative Trait Locus (QTLs) in the natural population and 20 QTLs in the RIL for trait mean and 6 plasticity indicators, with 6 QTLs and 58 QTLs overlapping. Notably, seven quantitative trait nucleotide (QTNs) and eight QTN by environment interactions were colocalised with the above plasticity QTLs. By integrating 82 main‐effect, plasticity and genotype‐by‐environment (G×E) interaction loci and environmental index PTR _16–23 , we proposed a simplified and stable prediction model with an average 4.40% and 2.42% increase in accuracy for flowering time in a single environment and across environments over that of 1726 genome‐wide flowering time loci, respectively. This study propels the field of adapting diverse genotypes to dynamic environments and addressing the challenges posed by climate change.

Soybean has been grown across diverse latitudes; however, its adaptation to low‐latitude, high‐altitude environments with short days and low temperature remains unclear. To understand the genetic basis of adaptation, we screened 200 diverse cultivars and conducted genome‐wide association studies (GWAS) in Bamei and Xianshui, Daofu country, Sichuan Province, China, in 2019 and 2023, respectively. Six agronomic traits: flowering time (DTF), maturity time, node number on main stem (NNM), plant height (PH), effective number of pods per plant and 100‐seed weight (HGW) were evaluated. Five MG I–II cultivars (Bamei) and 17 MG II–V cultivars (Xianshui) were screened as adaptive, exhibiting late flowering and maturity, tall stature, and high node and pod numbers. Adaptive cultivars predominantly carried the allelic combinations E1/e2‐ns/e3‐tr/E4 and E1/e2‐ns/E3/E4 (Bamei), and only E1/e2‐ns/E3/E4 (Xianshui). GWAS identified 9, 6, and 2 genomic regions associated with DTF, NNM and PH, respectively, with two regions linked to both DTF and PH. Most QTNs associated with DTF were located near known loci or Arabidopsis flowering gene homologues. Non‐synonymous mutations in GmPIE1, GmFY and GmIAA31 were associated with delayed flowering and taller plants. The adaptive cultivars, markers, and genes identified offer valuable resources for improving soybean adaptation to low‐latitude, high‐altitude regions.

Soybean [Glycine max (L.) Merr.] is a short-day (SD) plant that is sensitive to photoperiod, which influences flowering, maturity, and even adaptation. TEOSINTE-BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factors have been shown to regulate photoperiodic flowering. However, the roles of TCPs in SD plants such as soybean, rice, and maize remain largely unknown. In this study, we cloned the GmTCP40 gene from soybean and investigated its expression pattern and function. Compared with wild-type (WT) plants, GmTCP40-overexpression plants flowered earlier under long-day (LD) conditions but not under SD conditions. Consistent with this, the overexpression lines showed upregulation of the flowering-related genes GmFT2a, GmFT2b, GmFT5a, GmFT6, GmAP1a, GmAP1b, GmAP1c, GmSOC1a, GmSOC1b, GmFULa, and GmAG under LD conditions. Further investigation revealed that GmTCP40 binds to the GmAP1a promoter and promotes its expression. Analysis of the GmTCP40 haplotypes and phenotypes of soybean accessions demonstrated that one GmTCP40 haplotype (Hap6) may contribute to delayed flowering at low latitudes. Taken together, our findings provide preliminary insights into the regulation of flowering time by GmTCP40 while laying a foundation for future research on other members of the GmTCP family and for efforts to enhance soybean adaptability.

Key message A total of 101 QTNs were found to be associated with soybean flowering time responses to photo-thermal conditions; three candidate genes with non-synonymous substitutions were identified: Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). Abstract The flowering transition is a crucial component of soybean (Glycine max L. Merr.) development. The transition process is regulated by photoperiod, temperature, and their interaction. To examine the genetic architecture associated with temperature- and photo-thermal-mediated regulation of soybean flowering, we here performed a genome-wide association study using a panel of 201 soybean cultivars with maturity groups ranging from MG 000 to VIII. Each cultivar was grown in artificially controlled photoperiod and different seasons in 2017 and 2018 to assess the thermal response (TR) and the interactive photo-thermal response (IPT) of soybean flowering time. The panel contained 96,299 SNPs with minor allele frequencies > 5%; 33, 19, and 49 of these SNPs were significantly associated with only TR, only IPT, and both TR and IPT, respectively. Twenty-one SNPs were located in or near previously reported quantitative trait loci for first-flowering; 16 SNPs were located within 200 kb of the main-effect flowering genes GmFT2a, GmFT2b, GmFT3a, GmFT3b, GmFT5a, GmFT5b, GmCOL2b, GmPIF4b, and GmPIF4c, or near homologs of the known Arabidopsis thaliana flowering genes BBX19, VRN1, TFL1, FUL, AGL19, SPA1, HY5, PFT1, and EDF1. Natural non-synonymous allelic variations were identified in the candidate genes Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). Cultivars with different haplotypes showed significant variations in TR, IPT, and flowering time in multiple environments. The favorable alleles, candidate genes, and diagnostic SNP markers identified here provide valuable information for future improvement of soybean photo-thermal adaptability, enabling expansion of soybean production regions and improving plant resilience to global climate change.

Seed size is a critical agronomic trait that influences the yield and appearance quality of soybeans, making it a primary breeding objective with significant economic value. While the molecular mechanisms that regulate soybean seed size remain largely unknown, several functional molecular targets have been applied in breeding to create larger grain size materials. In this study, we utilized the CRISPR/Cas9 system to induce the targeted mutagenesis of GmEOD1, which encodes the E3 ubiquitin ligase. The resulting homozygous soybean mutant of GmEOD1 exhibited larger seed size and 100-seed weight, with no significant change in the average seed weight per plant. The sum of crude protein and oil content increased significantly in mutants while fatty acid composition remained unchanged. We identified six haplotypes among 156 soybean cultivars, with Hap1 and Hap2 representing the majority of cultivars with relatively higher 100-seed weight, suggesting that sequence variations of GmEOD1 may correlate with seed weight. Transcriptomic analysis across five stages of seed development revealed that stages one–three mainly focused on cell cycle, growth, wall synthesis and modification, photosynthesis, and sugar metabolism; promoting cell growth, reproduction, and carbon accumulation; and providing key intermediates for substance synthesis. Stages four–five focused on polysaccharide catabolism, xylan metabolism, and nutrient pool activity, promoting the accumulation of dry matter, such as sugars, proteins, and lipids in seeds. Weighted gene co-expression network analysis (WGCNA) of modules related to seed size revealed 13 hub genes involved in seed development regulation. This study provides a valuable theoretical basis and excellent opportunities for genetic editing of germplasm cells with subsequent molecular soybean seed size breeding, facilitating easier seed selection to improve soybean quality.

The flowering transition is a crucial component of soybean (Glycine max L. Merr.) development. The transition process is regulated by photoperiod, temperature, and their interaction. To examine the genetic architecture associated with temperature- and photo-thermal-mediated regulation of soybean flowering, we here performed a genome-wide association study (GWAS) using a panel of 201 soybean cultivars with maturity groups ranging from MG 000 to VIII. Each cultivar was grown in artificially-controlled photoperiod and different seasons in 2017 and 2018 to assess the thermal response (TR) and the interactive photo-thermal response (IPT) of soybean flowering time. The panel contained 96,299 SNPs with minor allele frequencies > 5%; 33, 19, and 49 of these SNPs were significantly associated with only TR, only IPT, and both TR and IPT, respectively. 21 SNPs were located in or near previously reported quantitative trait loci (QTL) for first-flowering; 16 SNPs were located within 200 kb of the main-effect flowering genes GmFT2a, GmFT2b, GmFT3a, GmFT3b, GmFT5a, GmFT5b, GmCOL2b, GmPIF4b, and GmPIF4c, or near homologs of the known Arabidopsis thaliana flowering genes BBX19, VRN1, TFL1, FUL,AGL19, SPA1, HY5, PFT1, and EDF1. Natural non-synonymous allelic variations were identified in the candidate genes Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). Cultivars with different haplotypes showed significant variations in TR, IPT, and flowering time in multiple environments. The favorable alleles, candidate genes, and diagnostic SNP markers identified here provide valuable information for future improvement of soybean photo-thermal adaptability, enabling expansion of soybean production regions and improving plant resilience to global climate change.