qHSW_11, a major quantitative trait locus controlling seed weight in soybean, was fine-mapped to a 340-kb region on chromosome 11, and Glyma.11G239000 is the candidate gene responsible for seed weight. A KASP marker could therefore be useful for selecting high-seed-weight lines in soybean breeding. Seed weight is a critical determinant of yield in soybean. The mechanism underlying seed weight remains poorly understood in soybean. In this study, a recombinant inbred line (RIL) population derived from the cross between Jidou17 and Zhonghuang13 was employed to identify QTLs associated with seed weight. A major locus, qHSW_11, which was consistently detected across three consecutive years, explained 9.51–15.13

Improving soybean plant architecture is critical for enhancing yield potential. To dissect the genetics of related traits, a recombinant inbred line population of 175 F9:12 families (derived from Glycine max cultivars Jidou 12 [female] × Ji NF58 [male]) was used for quantitative trait locus (QTL) mapping. Four key traits—plant height, bottom pod height, node number on main stem, and branch number—were analyzed across six environments (two growing seasons × three locations) via two methods: composite interval mapping (CIM, QTL Cartographer v2.5) and mixed-model-based composite interval mapping (MCIM, QTLNetwork 2.0). A total of 22 stable QTLs were detected, with phenotypic variation explained (PVE) of 1.2–52.5%. Co-localized QTLs (due to significant trait correlations) concentrated in three genomic intervals: Satt286-Sat_251 (LG C2/chromosome 06), Satt156-Satt229 (LG L/chromosome 19), and Satt581-Sat_190 (LG O/chromosome 10). A novel QTL (qBPH-O-2) for bottom pod height was identified on LG O. Major QTLs with QTL-by-environment (QE) interactions were found on LG A1 (plant height, node number on main stem) and qBN-C2-1 (branch number, high additive effects + QE interactions). These findings support marker-assisted selection (MAS), targeted plant architecture improvement, and gene pyramiding in soybean breeding.

Plant height is a key agronomic trait in soybean that is closely associated with yield potential. Nevertheless, the molecular mechanisms underlying its regulation remain largely elusive. In this study, we employed a recombinant inbred line (RIL) population comprising 271 lines evaluated across six environments to dissect the genetic architecture of plant height. A total of eleven quantitative trait loci (QTLs) associated with plant height were identified, including four novel loci (qPH5-1, qPH6-1, qPH6-2, and qPH17-1). Among these, four stable major QTLs (qPH2-1, qPH10-1, qPH18-1, and qPH19-2) were consistently detected across multiple environments, each explaining more than 10 % of the phenotypic variance. Resequencing analysis of the parental lines suggested that E1, E2, Dt2, and E3 represent candidate genes underlying qPH6-3, qPH10-1, qPH18-1, and qPH19-2, respectively. Importantly, Glyma.02G057500 (GmDWF4.2), a soybean ortholog of Arabidopsis AtDWF4, was mapped within the qPH2-1 interval and exhibited exon polymorphisms between the two parental lines, Jidou17 and Suinong14. Functional assays demonstrated that both GmDWF4.2JD17 and GmDWF4.2SN14 partially rescued the dwarf phenotype of the Arabidopsis dwf4-102 mutant. Notably, heterologous overexpression of GmDWF4.2SN14 in wild-type Arabidopsis resulted in a significantly greater increase in plant height compared to that of GmDWF4.2JD17. Overall, our findings demonstrate that GmDWF4.2 functions as a positive regulator of plant height in soybean and further reveal that the GmDWF4.2SN14 haplotype confers a stronger promotive effect on this trait. These findings contribute to elucidating the genetic regulatory mechanisms of soybean plant height and provide a theoretical foundation for refining molecular marker-assisted selection strategies for this agronomic trait.

IntroductionSoybean is an indispensable crop supplying protein and oil for humans and animals, and playing an essential role in global food security. Drought represses soybean seed germination, reducing biomass accumulation and even inhibiting yield.MethodsIn order to dissect the genetic components underlying soybean drought tolerance during different development stage, a natural population containing 140 accessions was employed to evaluate seven drought tolerance-related traits under water-welled and drought stress conditions. Subsequently, genome-wide association study (GWAS) was conducted based on 150K single nucleotide polymorphism (SNP) markers of “Zhongdouxin-1”. And the drought tolerance coefficient of seven different traits were analyzed with seven GWAS models.ResultsA total of 1807 significant SNPs were detected across 20 chromosome, including 569 SNPs for germination stage, and 1242 SNPs for seedling stage. Of 569 SNPs identified in germination stage, 354 SNPs on chromosomes 2, 7, 13, 14, and 17 accounting for 62.21%. Among 1242 SNPs found in seedling stage, 869 SNPs on chromosomes 11, 14, 15, 17 and 18 accounting for 69.97%. Moreover, among 1807 significant SNPs, 163 SNPs exhibited pleiotropic effects, of which 23 were located in exon, 21 in intron, 12 in 5’UTR or 3’UTR and 11 in upstream or downstream. Furthermore, 249 stable SNPs were detected by more than four GWAS models. According to these stable SNPs, RNA expression levels and gene annotations, four causal genes (Glyma.02G080200, Glyma.11G056200, Glyma.12G188900, and Glyma.18G110200) conferring soybean drought tolerance were detected, which participated in ethylene stimulus response, water deprivation response, and proteolysis.DiscussionCollectively, 249 stable SNPs, 163 pleiotropic SNPs and four candidate genes identified in present study provided promising molecular resources and reliable foundation for drought resistance improvement and marker-assisted selective breeding in soybean.

Background: Soybean is an important crop with multiple uses for oil, food, and feed, providing 50% of the vegetable protein and 20% of the edible oil in the world. The WD40 family genes play crucial regulatory roles in growth, development, secondary metabolism, and stress responses. However, the definition of WD40 family genes in soybean remained unclear, which limited their application potential in genetic improvement. Methods: To identify soybean WD40 family members and screen candidate genes for breeding improvement, this study performed genome-wide identification of the soybean WD40 gene family via bioinformatic approaches based on the latest Williams 82 reference genome (Wm82.a6.v1). Meanwhile, the function of the family gene GmWD40-257 regulating seed quality was analyzed. Results: The results showed that a total of 458 GmWD40 genes were identified, which were distributed on the 20 chromosomes. Subcellular localization showed that most members were mainly concentrated in the nucleus, chloroplast, and cytoplasm. Phylogenetic tree analysis divided the 458 GmWD40 genes into eight groups. Synteny analysis identified 160 syntenic genes between soybean and Arabidopsis thaliana. Conserved motif analysis identified ten core motifs. The promoter regions of GmWD40 contained 19 types of cis-acting elements. Functional analysis revealed that the nonsense mutation of GmWD40-257 significantly reduced the content of oil, palmitic acid, oleic acid, linoleic acid, α-linolenic acid and soluble sugar, while significantly increasing the contents of protein, γ-tocopherol and δ-tocopherol. Conclusions: A total of 458 members of the WD40 gene family were identified in soybean. Among these, GmWD40-257 was found to positively regulate the contents of soybean oil, palmitic acid, oleic acid, linoleic acid, α-linolenic acid and soluble sugar, while negatively regulating the contents of soybean protein, γ-tocopherol and δ-tocopherol.

Soybean sprouts are a nutritionally enriched vegetable commodity of considerable commercial importance in Asian markets. This study evaluated 188 soybean accessions from the Huang-Huai ecological region to identify elite germplasm for sprout production through multi-trait phenotypic assessment. Four agronomically important traits were quantified under controlled germination conditions: germination rate (GR), fresh weight (FW), soluble sugar (SS) content, and isoflavone (IF) content. Considerable genetic variation was detected across all four traits. Correlation analysis revealed a strong positive association between GR and FW (r = 0.86, P < 0.001), while SS and IF contents showed trait independence, suggesting distinct genetic control mechanisms. Comprehensive evaluation using multi-trait selection indices identified seven superior accessions with exceptional sprout performance: Pudou 955, Shengdou 29, Shengdou 2, Zhoudou 25, Zhoudou 26, Zhudou 19, and Xudou 14. Zhoudou 26 exhibited outstanding GR (97%) and IF accumulation (3508.09 µg/g), while Shengdou 2 demonstrated superior FW (61.74 g) and SS content (2.09%). These accessions may serve as genetic resources for marker-assisted breeding and functional genomics approaches targeting sprout-specific traits. The identified germplasm offers a basis for developing soybean cultivars better suited to sprout production.

BACKGROUND SOYBEAN MOSAIC VIRUS (SMV): Represents one of the most prevalent and destructive diseases affecting major soybean-producing regions, significantly impacting both soybean yield and quality. This study aimed to investigate the variation in soybean resistance to the SMV SC7 strain, identify the associated resistance loci, and predict potential candidate genes. RESULTS: The study investigated a collection of 290 soybean germplasm materials, distinguished by their extensive genetic diversity. Inoculation with the SMV SC7 strain for resistance identification revealed that 18.2% of the materials exhibited high resistance (HR), while 6.8% displayed high susceptibility (HS). Based on four models for GWAS analysis, five significant single nucleotide polymorphisms (SNPs) associated with SMV resistance were identified on chromosomes 11, 13(two SNPs), 16, and 17. Two known resistance loci reconfirmed on chromosome 13. Furthermore, the loci Chr11_27826328, Chr16_34392503, and Chr17_18822285 were located on chromosomes 11, 16, and 17, respectively. A candidate gene related to SMV resistance, Glyma.16g182700, has been identified on chromosome 16. Haplotype analysis of this gene demonstrated significant differences in SMV resistance between materials containing Hap1 and those possessing Hap2. Compared to random SNPs, the 100 GWAS-significant markers yielded higher genomic prediction accuracy. And a plateau in accuracy was reached at approximately 6000 markers. CONCLUSIONS: This study reveals the genetic architecture underlying soybean resistance to the SMV SC7 strain, identifies a key candidate gene, and enhances the accuracy of GS by incorporating significant SNPs. These findings provide valuable resources for marker-assisted selection and the genetic improvement of SMV-resistant soybean varieties.

Soybean [Glycine max (L.) Merr.] is a major crop for global protein and oil production, yet most cultivated varieties contain only 35-42% protein. HJ117 is a soybean accession with high protein content (52.99%), but the genetic basis of this trait is not well characterized. Identifying the major loci controlling protein accumulation in HJ117 is necessary to develop improved high-protein varieties through marker-assisted breeding. We conducted QTL mapping and genome-wide association studies (GWAS) using two recombinant inbred line (RIL) populations: XH1617 (183 lines from Xudou16 × HJ117) and QH3417 (171 lines from Qihuang34 × HJ117). Seed protein and oil content were evaluated across three growing seasons (2019, 2021, 2022). Both traits showed continuous distributions with high broad-sense heritability (h2b > 0.91), confirming their quantitative genetic basis. Quantitative trait locus (QTL) mapping identified nine stable loci across both populations, including three major loci, qtl-15, qtl-20, and qtl-20-1, on the chromosome. 15 and 20, consistently detected across populations and years. These loci explained 7.20-41.50% of phenotypic variance (LOD = 2.97-19.82). GWAS analysis of the same 357 accessions, comprising both RIL populations and three parental lines, improved mapping resolution within linkage-derived intervals, identifying 168 significant SNPs, including chromosome_15_943943_T_C, that colocalized with Locus15 and provide markers suitable for marker-assisted selection. Additive effect analysis revealed that 96.70% of protein-enhancing alleles originated from HJ117. The stable QTL regions harbor candidate genes (GmSWEET10 (Glycine max SUGARS WILL EVENTUALLY BE EXPORTED TRANSPORTER 10), GmSop20 (Glycine max Seed oil-to-protein 20), and POWR1 (Protein and Oil With Regulatory role 1)) involved in sugar transport and nutrient partitioning during seed development. These results provide validated genetic markers and positional data for the major loci controlling protein content in HJ117, with potential utility for marker-assisted selection in high-protein soybean breeding programs.

Soybean is a short-day crop that exhibits high sensitivity to photoperiod variation. Changes in photoperiod regulate flowering and developmental processes in soybean, ultimately influencing its yield, quality, and geographical adaptability. However, the genetic mechanisms underlying variation in soybean growth periods remain poorly understood. In this study, flowering duration (FD), maturity duration (MD), reproductive duration (RD), and the ratio of reproductive to flowering duration (RD/FD) were investigated in both a natural population and a recombinant inbred line (RIL) population. Linkage analysis and genome-wide association studies (GWAS) were employed to identify genetic loci associated with growth period-related traits. A total of 51 quantitative trait loci (QTLs) controlling growth period traits were detected in the RIL population, among which 12 QTLs were consistently identified across multiple environments, demonstrating environmental stability and pleiotropic effects on multiple growth period traits. Concurrently, 119 significant quantitative trait nucleotides (QTNs) associated with growth period traits were identified in the natural population, including six environmentally stable QTNs and four pleiotropic QTNs that influenced multiple traits. Through integrated linkage and association analyses, two major loci were mapped on chromosomes 4 and 19. Additionally, three candidate genes were identified on chromosome 4, among which Glyma.04G125500 encodes a histone-lysine N-methyltransferase protein. Haplotype analysis further confirmed that allelic variation in this gene was significantly associated with variation in growth period traits. Furthermore, kompetitive allele-specific PCR (KASP) marker validation demonstrated that Tof11 significantly modulated growth period variation under both e1e1/e2e2 and E1E1/E2E2 genetic backgrounds. Collectively, these findings provide a theoretical foundation for elucidating the genetic and molecular mechanisms underlying the regulation of soybean growth period traits.

As the ancestor and close relative of soybeans, wild soybeans exhibit strong salt tolerance and are ideal materials for discovering salt-tolerant genes. Expansins are a type of cell wall-loosening protein that plays an active role in regulating plant salt tolerance. We previously obtained the wild soybean expansin gene GsEXPB1, which is specifically transcribed in roots and actively responds to salt stress. Overexpression of this gene significantly promotes the growth of soybean hairy roots under salt stress. To further elucidate the function of the gene in regulating plant tolerance to salt stress, this study obtained soybean hairy roots that overexpress the GsEXPB1 gene and silence its homologous gene GmEXPB4 through RNAi. Under salt stress, the overexpression of the GsEXPB1 gene significantly promoted the growth of soybean hairy roots, while the hairy roots that were silenced for the GmEXPB4 gene exhibited an opposite phenotype. Physiological assay results indicate that GsEXPB1 enhances the tolerance of soybean hairy roots to salt stress by regulating the antioxidant system and Na+/K+ content. In soybean lines overexpressing GsEXPB1, the germination rate of seeds and root growth indicators under salt stress were significantly improved compared to those of wild-type plants. Meanwhile, GsEXPB1 enhances the tolerance of transgenic lines to salt stress by actively regulating the antioxidant system, osmotic adjustment system, chlorophyll content, cell wall components, and Na+/K+ levels, significantly promoting growth and increasing the number of flowers and grain weight. This study reveals the physiological mechanism by which GsEXPB1 enhances soybean salt tolerance, providing a theoretical basis and relevant references for the application of this gene in the breeding of new soybean salt-tolerant varieties.

Rare-allele variants are important for crop improvement because they can be linked to important traits. However, genome-wide distribution and annotation of rare-allele variants have not been reported. We analyzed sequencing data from 1556 soybean accessions and found 6,533,419 rare-allele variants in Glycine max and 941,274 in Glycine soja populations. Although the total number of variants was 20% less in G. max than G. soja, the number of rare-allele variants in G. max was six times that in G. soja. Among the rare-allele variants in G. max, 19.16% were novel mutations that did not exist in G. soja. Domestication and artificial selection have not only reduced overall genetic diversity but also the frequency of variants of cultivated soybean. Rare-allele variants were mainly located in intergenic and noncoding regions rather than coding regions, and in heterochromatin regions rather than euchromatic regions. There were 121,450 rare-allele variations in 36,213 G. max genes and 20,645 in 12,332 G. soja genes, resulting in nonsynonymous, stop gain or stop loss mutations. This study provided the first comprehensive understanding of rare-allele variants in wild and cultivated soybean genomes and its potential impact on gene functions. This information will be valuable for future studies aimed at improving soybean varieties, as these variants may help reveal the underlying mechanisms controlling traits and have the potential to improve stress resistance, yield, and adaptability to environments.

Soybean (Glycine max) seeds are rich in amino acids, offering key nutritional and physiological benefits. In this study, 290 soybean accessions from the USDA Germplasm Collection based in Urbana, IL Information Network (GRIN) were analyzed. Four Genome-Wide Association Study (GWAS) models—Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Multi-Locus Mixed Model (MLMM)—identified two significant Single Nucleotide Polymorphisms (SNPs) associated with arginine content: Gm06_19014194_ss715593808 (LOD = 9.91, 3.91% variation) at 19,014,194 bp on chromosome 6 and Gm11_2054710_ss715609614 (LOD = 9.05, 19% variation) at 2,054,710 bp on chromosome 11. Two candidate genes, Glyma.06g203200 and Glyma.11G028600, were found in the two SNP marker regions, respectively. Genomic Prediction (GP) was performed for arginine content using several models: Bayes A (BA), Bayes B (BB), Bayesian LASSO (BL), Bayesian Ridge Regression (BRR), Ridge Regression Best Linear Unbiased Prediction (rrBLUP), Random Forest (RF), and Support Vector Machine (SVM). A high GP accuracy was observed in both across- and cross-populations, supporting Genomic Selection (GS) for breeding high-arginine soybean cultivars. This study holds significant commercial potential by providing valuable genetic resources and molecular tools for improving the nutritional quality and market value of soybean cultivars. Through the identification of SNP markers associated with high arginine content and the demonstration of high prediction accuracy using genomic selection, this research supports the development of soybean accessions with enhanced protein profiles. These advancements can better meet the demands of health-conscious consumers and serve high-value food and feed markets.

Enhancing the oil or protein content of soybean, a major crop for oil and protein production is highly desirable. GmSWEET10a encodes a sugar transporter that is strongly selected during domestication and breeding, increasing seed size and oil content. GmSWEET10b is functionally similar to GmSWEET10a, yet has not been artificially selected. Here, AlphaFold is used to find that C-terminal variants of GmSWEET10a can endow enhanced or reduced transport activity. Guided by AlphaFold, the functionality is improved for GmSWEET10a in terms of oil content through gene editing. Furthermore, novel GmSWEET10b haplotypes possessing strengthened or weakened sugar-transport capabilities that are absent in nature are engineered. Consequently, soybean oil content or protein content in independent GmSWEET10b gene-edited lines during multi-year and multi-site field trials is consistently increased, without negatively affecting yield. The study demonstrates that the combination of AlphaFold-guided protein design and gene editing has the potential to generate novel beneficial alleles, which can optimize protein function in the context of crop breeding.

Soybean is an important crop worldwide that provides ~ 50% oil for humans. Salinity is a major abiotic stress that inhibits soybean growth and yield. Dissecting the genetic basis of salt tolerance is an effective way for soybean plants to combat salt-related yield losses. In this study, the variety salt tolerance index (STIv) of a natural population of 140 soybean germplasms was calculated in terms of plant height (PH), leaf area (LA), shoot fresh weight (SFW) and shoot dry weight (SDW), which were measured under normal condition and in a 1.50% NaCl solution. GWAS analysis was subsequently conducted on the basis of STIv and 150 K SNP markers of “Zhongdouxin-1”. The results revealed that 365 significant SNPs located on 19 chromosomes (excluding Gm03) were associated with STIv. Among them, 108 SNPs were associated with LA-STIv, 71 SNPs associated with PH-STIv, 95 SNPs associated with SDW-STIv and 91 SNPs associated with SFW-STIv. A total of 333 genes were identified according to the flanking region (150 kb) of the significant SNPs. 333 genes were identified. Based on gene functional annotations, SNP mutations, and RNA expressions, nine causal genes responsible for soybean salt tolerance were identified. Thus, the significantly associated SNPs and candidate genes detected in this study might provide novel insights into soybean salt tolerance in breeding programs.

Objectives: Soybean serves as a crucial source of protein and oil. Wild soybean (Glycine soja) shares genetic similarities with cultivated soybean (Glycine max) but exhibits richer diversity due to lower genetic bottlenecks. The high allelic diversity in wild soybeans provides traits for environmental adaptation, which is useful for cultivated soybeans through breeding. Considering that soybeans originated in northern China and that Hengshui Lake, as a wetland environment, plays a crucial role in preserving species diversity, 17 wild soybean resources at this site were collected and then re-sequenced on the Illumina NovaSeq6000 platform with a depth of 10×. Data description: In this study, we collected 17 wild soybean accessions from Hengshui Lake in Hebei Province, China, and performed re-sequencing on the Illumina NovaSeq6000 platform, followed by SNPs identification. Subsequently, we incorporated an additional 62 wild soybean genomic datasets and utilized ADMIXTURE, neighbor-joining tree, and principal component analysis to elucidate population characteristics. The results revealed that these wild soybean accessions could be divided into seven distinct subpopulations.

Enhancing nitrogen-use efficiency is essential for boosting crop yields and advancing sustainable agriculture, particularly in the absence of synthetic fertilizers. Despite the inherent nitrogen-fixation capacity of the staple legume crop soybean (Glycine max) by symbiotic rhizobia, improving nitrogen use has been challenging. Here, a role for the auxin-efflux transporters PIN3a and PIN3b in soybean nitrate acquisition is uncovered. PIN3a/b localizes to the plasma membrane, and high environmental nitrate induces PIN3a degradation and its accumulation at cell junctions. Disrupting PIN3 homologs results in auxin over-accumulation, impairs pavement-cell polarity, and enhances signaling via the transcription factors ARF and STF3/4. These transcription factors separately bind to and activate the NPF2.13 promoter, thereby strengthening nitrate uptake. pin3ab and pin3abd mutants have enhanced nitrate acquisition and resistant to high nitrate on pavement-cell growth. The elevated nitrogen accumulation translates to higher oil contents in pin3ab mutant seeds in an elite cultivar background across multiple years and field locations. The findings shed light on the regulation of nitrate uptake in crop-plant development and demonstrate the unexpected potential of manipulating auxin transporters to enhance soybean nitrogen-use efficiency and agronomic performance.

Soybean serves as a crucial source of protein and oil. Wild soybean (Glycine soja) shares genetic similarities with cultivated soybean (Glycine max) but exhibits richer diversity due to lower genetic bottlenecks. The high allelic diversity in wild soybeans provides traits for environmental adaptation, which is useful for cultivated soybeans through breeding. Considering that soybeans originated in northern China and that Hengshui Lake, as a wetland environment, plays a crucial role in preserving species diversity, 17 wild soybean resources at this site were collected and then re-sequenced on the Illumina NovaSeq6000 platform with a depth of 10×. In this study, we collected 17 wild soybean accessions from Hengshui Lake in Hebei Province, China, and performed re-sequencing on the Illumina NovaSeq6000 platform, followed by SNPs identification. Subsequently, we incorporated an additional 62 wild soybean genomic datasets and utilized ADMIXTURE, neighbor-joining tree, and principal component analysis to elucidate population characteristics. The results revealed that these wild soybean accessions could be divided into seven distinct subpopulations.

Soybean mosaic virus (SMV), a pathogen responsible for inducing leaf mosaic or necrosis symptoms, significantly compromises soybean seed yield and quality. According to the classification system in the United States, SMV is categorized into seven distinct strains (G1 to G7). In this study, we performed a genome-wide association study (GWAS) in GAPIT3 using four analytical models (MLM, MLMM, FarmCPU, and BLINK) on 218 soybean accessions. We identified 22 SNPs significantly associated with G1 resistance across chromosomes 1, 2, 3, 12, 13, 17, and 18. Notably, a major quantitative trait locus (QTL) spanning 873 kb (29.85-30.73 Mb) on chromosome 13 exhibited strong association with SMV G1 resistance, including the four key SNP markers: Gm13_29459954_ss715614803, Gm13_29751552_ss715614847, Gm13_30293949_ss715614951, and Gm13_30724301_ss715615024. Within this QTL, four candidate genes were identified: Glyma.13G194100, Glyma.13G184800, Glyma.13G184900, and Glyma.13G190800 (3Gg2). The genomic prediction (GP) accuracies ranged from 0.60 to 0.83 across three GWAS-derived SNP sets using five models, demonstrating the feasibility of GP for SMV-G1 resistance. These findings could provide a useful reference in soybean breeding targeting SMV-G1 resistance.

The soybean is a critical source of vegetable protein, but its proteome remains undercharacterized. Here, we quantify 12,855 proteins across 14 soybean organs using 4D data-independent acquisition mass spectrometry (4D-DIA-MS), creating the most extensive soybean proteome dataset to date. Organ-specific protein expression and co-expression analyses highlight functional specificity with significant differences in protein-transcript abundance across organs. We also map N6-methyladenosine (m6A) modifications, identifying their key role in post-transcriptional protein regulation. Integrative analysis of the proteome and m6A methylome identifies a novel regulator in m6A methylation. This comprehensive proteomic and m6A landscape advances our understanding of soybean biology and provides a valuable resource for crop improvement.

The quiescent center (QC) resides in a reversible G 0 state in which cells are not actively dividing and yet retain their proliferation competence upon stimulation. How this quiescent state is molecularly defined and stably maintained is a fascinating question. Here, we uncover a dual role for LEAF AND FLOWER RELATED (LFR), a component of the SWITCH/SUCROSE NONFERMENTABLE (SWI/SNF) chromatin-remodeling complex, in maintaining quiescence of the QC. We demonstrate that LFR is recruited to the chromatin of core transcription factors (TFs) PLETHORA 1 (PLT1), PLT2, SCARECROW (SCR), and WUSCHEL - RELATED HOMEOBOX (WOX5) via physical interactions with them. Moreover, the autoregulatory binding of these TFs reciprocally requires LFR. Functioning as a chromatin wrench, LFR relaxes the chromatin at PLT1 , PLT2 , and SCR loci to sustain their positive autoregulation, thereby contributing to the prevention of QC cell division. Conversely, LFR compacts WOX5 chromatin to enforce negative autoregulation and simultaneously promotes CYCD3;3 expression to counteract WOX5-mediated repression, thus ensuring the proliferation competence of the QC. Furthermore, WOX5 throws a wrench into LFR binding at the CYCD3;3 promoter, establishing a regulatory circuit that precisely modulates CYCD3;3 expression, a D-type cyclin whose appropriate level is critical for QC quiescence. Consequently, the QC is maintained in a proliferation-competent but arrested state. Our findings establish the LFR-containing SWI/SNF complex as a key regulatory node that coordinates TF autoregulation with cell-cycle control to maintain QC quiescence.