Identification of a novel major QTL and F-box candidate genes controlling seed dormancy in common wheat

Identification of a novel major QTL and F-box candidate genes controlling seed dormancy in common wheat | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of a novel major QTL and F-box candidate genes controlling seed dormancy in common wheat Yuxia Lyu, Yaoyao Zhao, Wenbo Lu, Xu Pan, Wei Gao, Litian Zhang, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8857089/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Moderate seed dormancy is essential for reducing pre-harvest sprouting (PHS) and ensuring uniform germination in cereal crops. In this study, seed dormancy was evaluated in 245 wheat varieties with diverse genetic backgrounds across seven environments, and genotypes were obtained using the Wheat 90K SNP array. Genome-wide association analysis identified 55 loci associated with seed dormancy, including a novel major locus, Qgi.245.ahau-4B.3 , on chromosome 4B. By integrating molecular marker development, re-GWAS, linkage mapping, and expression analysis, this locus was validated and two candidate genes underlying Qgi.245.ahau-4B.3 were identified: TraesCS4B02G118000 ( TaF-box-B1 ) and TraesCS4B02G118200 ( TaF-box-B2 ), both encoding F-box proteins. The expression levels of TaF-box-B1 and TaF-box-B2 were significantly lower in the moderate dormancy wheat variety Annong 1124 (AN1124) than in weak dormancy variety Annong 8455 (AN8455). Sequence and haplotype analyses showed that variations in TaF-box-B1 and TaF-box-B2 were completely linked, forming two haplotypes: TaF-box-Hap1 for strong dormancy and TaF-box-Hap2 for weak dormancy. Frequency analysis further revealed that the favorable haplotype TaF-box-Hap1 was predominantly distributed in the Middle and Lower Yangtze River winter wheat region, characterized by relatively high rainfall and humidity. These findings establish a robust foundation for molecular marker-assisted breeding of wheat varieties with enhanced climate resilience and stable PHS resistance, thereby contributing substantively to global food security. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Key message A novel major locus () controlling seed dormancy, and its candidate genes ( and ), were identified by integrating association and linkage mapping with expression and sequence variation analyses. Introduction Seed dormancy is a heritable trait that delays germination and enables plants to survive unfavorable environmental conditions. During domestication, seed dormancy been selectively reduced to increase emergence after sowing (Gubler et al., 2005). Premature release of seed dormancy can cause mature seeds to germinate in the field and result in pre-harvest sprouting (PHS) under rainy or high-humidity conditions at harvest. This not only substantially reduces yield and quality in cereal crops, but also creates serious challenges for post-harvest storage, processing, and utilization (Simsek et al., 2014). In wheat, PHS occurs frequently in many regions worldwide, including China, Europe, the United States, Japan, Canada, Australia, and South Africa (Jiang et al., 2022; Barrero et al., 2015; Li et al., 2022). PHS causes annual economic losses of approximately US$1 billion and poses a serious threat to global food security (Tai et al., 2021). Enhancing seed dormancy is therefore an effective and safe strategy for preventing PHS. Consequently, identifying genes associated with seed dormancy and developing gene-specific markers are essential for breeding wheat varieties with moderate dormancy to minimize PHS damage and ensure stable wheat production. Seed dormancy is a quantitative trait controlled by multiple genes (Tai et al., 2021). Considerable efforts have been devoted to elucidating the genetic basis of seed dormancy, and numerous quantitative trait loci (QTLs) and genes associated with seed dormancy have been identified in wheat (Liu et al., 2013; Shorinola et al., 2017; Zhu et al., 2019; Tai et al., 2021; Lang et al., 2021; Li et al., 2022; Tai et al., 2024; Zhang et al., 2025; Cheng et al., 2026). The QTL Qphs.pseru-3AS on chromosome 3A explains up to 58% of phenotypic variation in seed dormancy (Liu et al., 2008), and TaPHS1 ( TaMFT ), which encodes a MOTHER OF FLOWERING TIME-like protein, is the candidate gene underlying this locus (Liu et al., 2013). TaMKK3 , encoding mitogen-activated kinase kinase 3, is the candidate gene underlying the major locus Phs-A1 on chromosome 4A (Torada et al., 2016; Shorinola et al., 2017). The major locus qPHS.sicau-3D on chromosome 3D explains up to 42.47% of phenotypic variation in seed dormancy (Yang et al., 2019), and TaMyb10-D , encoding an R2R3-MYB transcription factor, is the candidate gene underlying this locus (Lang et al., 2021). TaPI4K-2A , encoding a phosphatidylinositol 4-kinase family protein, is the candidate gene underlying Qphs2A.7_nwafu on chromosome 2A (Tai et al., 2024). The three subgenome homologs of the phosphatase 2C protein gene TaPP2C-a6 co-localize with the QTLs QPhs.wsu-1A.2 , QPhs.wsu-1B.2 , and QPhs1D.1_nwafu on chromosomes 1A, 1B, and 1D, respectively. TaPP2C-a6 interacts with TaDOG1Ls, a DELAY OF GERMINATION 1-like (DOG1L) protein that plays a major role in regulating seed dormancy, and mediates wheat seed dormancy (Bentsink et al., 2006; Zhang et al., 2025). In addition, several seed dormancy-related genes, including TaVp1 , TaSdr , TaQsd1 , and TaJAZ1 , have been cloned using homology-based approaches (Yang et al., 2007; Chang et al., 2010; Zhang et al., 2014; Wei et al., 2019; Ju et al., 2019). TaVp1 ( Viviparous-1 ) is a homolog of Arabidopsis thaliana ABI3 ( ABA insensitive-3 ) and maize Vp-1 , and positively regulates wheat seed dormancy (Yang et al., 2007; Chang et al., 2010). Variation in the promoter of TaSdr-B , a homolog of rice OsSdr4 , is significantly associated with seed dormancy in wheat (Zhang et al., 2014). TaQsd1 , a homolog of barley Qsd1 encoding an alanine aminotransferase, regulates wheat seed dormancy mainly through abscisic acid (ABA) biosynthesis, catabolism, and signaling pathways (Wei et al., 2019). TaJAZ1 , a homolog of A. thaliana JAZ3 encoding a jasmonate ZIM-domain protein, negatively regulates wheat seed dormancy (Ju et al., 2019). Additional dormancy-related genes, including TaGATA1 , TaSRO1 , TaPKL , and TaGASR25 , have been identified in wheat using other approaches (Wei et al., 2023; Liu et al., 2023; Bai et al., 2025, Cheng et al., 2026). In summary, although many seed dormancy-related genes have been identified in wheat, their underlying genetic mechanisms and breeding potential remain unclear, which limits their practical application in improving PHS resistance through molecular breeding. Genome-wide association study (GWAS) is a research method that identifies the associations between genetic variations and complex traits on a genome-wide scale. It is a powerful tool for detecting the genes/QTL underlying complex traits (Tai et al., 2024; Lv et al., 2024). Linkage analysis is a genetic mapping approach employed to identify genomic loci associated with variation in a target trait, based on the co-segregation of genetic markers and the trait in different lines (Guo et al., 2023; Shorinola et al., 2016). GWAS offer high genomic resolution, utilize diverse and extensive biological samples, capture abundant genetic variation across the genome, and enable precise localization of trait-associated loci. However, GWAS are inherently susceptible to confounding effects arising from population stratification, which may lead to spurious associations and an elevated risk of false-positive locus identification (Price et al., 2006). Linkage analysis is generally conducted based on parental populations and is less affected by the population structure, resulting in higher reliability in loci localization (Shorinola et al., 2016). Therefore, combining GWAS with linkage analysis may lead to more reliable results. In this study, we used an association panel of 245 wheat varieties and an recombinant inbred line (RIL) population derived from Annong 8455 × Annong 1124 cross to investigate the germination index (GI) in different environments to explore genomic regions and candidate genes related to seed dormancy. The objectives of this study were to (1) identify genetic loci associated with seed dormancy in wheat based on GWAS, (2) narrow down the target interval of the novel major locus Qgi.245.ahau-4B.3 based on linkage analysis, (3) identify the candidate genes underlying Qgi.245.ahau-4B.3 , and (4) assess the frequency distribution of the favorable haplotype of the candidate gene. This study provides valuable gene resources and molecular markers for breeding wheat varieties with moderate seed dormancy and improved PHS resistance. Materials and Methods Plant materials and field experiments The association panel of 245 wheat varieties reported previously was used for association mapping (Pan et al., 2024 ; Lv et al., 2024 ). The panel was evaluated at five experimental stations of Anhui Agricultural University: Hefei, Anhui (HF; 2020–2021 and 2021–2022; 117°213′E, 31°919′N); Huaibei, Anhui (HB; 2020–2021 and 2021–2022; 116°75′E, 33°76′N); Bengbu, Anhui (BB; 2021–2022; 116°873′E, 33°102′N); Suzhou, Anhui (SZ; 2021–2022; 117°11′E, 33°88′N); and Jiyuan, Henan (JY; 2020–2021; 112°59′E, 35°09′N). The seven environments were designated HF21, HF22, HB21, HB22, BB22, SZ22, and JY21. An F 8 RIL population (AA-RIL; 179 lines), derived from a cross between Annong 8455 (AN8455; weak dormancy; average GI = 0.65) and Annong 1124 (AN1124; moderate dormancy; average GI = 0.37) (Evaluation of wheat seed dormancy can be referred to Chang et al., 2010 ), was used for linkage analysis to validate the novel QTL Qgi.245.ahau-4B.3 . The AA-RIL population was grown at two experimental stations: Hefei, Anhui (HF; 2022–2023 and 2023–2024; 117°21′E, 31°91′N) and Huaibei, Anhui (HB; 2023–2024; 116°75′E, 33°76′N). The three environments were designated HF23, HF24, and HB24. All trials were conducted with two replications using a randomized block design. Each line was planted in a single-row plot 2.0 m in length with a row spacing of 0.2 m. Field management and disease control followed standard local practices for wheat production. Phenotypic evaluation Seed dormancy was evaluated using the GI according to the methods of Zhu et al. ( 2019 ) and Yan et al. ( 2023 ). For each accession, 50 well-filled seeds were used per replicate, with two replicates. Seeds were placed in Petri dishes, supplied with 5 mL of sterile water, and incubated in a growth chamber at 20 ℃, with a 14 h light/10 h dark photoperiod and 80% relative humidity. Germinated seeds were counted and removed every 24 hours, and germination was defined by appearance of white embryos. The GI was calculated after three days using the following formula: GI = (3n 1 + 2n 2 + n 3 ) / (3N), where N is the total number of seeds, and n 1 , n 2 , and n 3 are the numbers of seeds that germinated on days one, two, and three, respectively. Descriptive statistics, correlation analysis, and Mann-Whitney U-test were performed using SPSS v25 (IBM Corporation, Armonk, NY, USA). Best linear unbiased prediction (BLUP) and broad-sense heritability ( H 2 ) were estimated using the R package “Ime4” (Lv et al., 2024 ). Genotyping and genome-wide association study A total of 245 wheat varieties were genotypes using the Wheat 90K single nucleotide polymorphism (SNP) array together with 13 published dormancy-related markers. These markers included SNP.646, MFT-222, MFT-A1, and MFT-A2 for TaMFT-3A (Liu et al., 2015 ; Nakamura et al., 2015 ; Lei et al., 2013 ; Jiang et al., 2018 ); TaMFT-3B 2 for TaMFT-3B (Vetch et al., 2022 ); TaMKK3-A-caps for TaMKK3 (Shorinola et al., 2017 ); Vp1B3 and Vp1-b2 for TaVp1 (Yang et al., 2007 ; Chang et al., 2010 ); QSD1 and QSD3 for TaQsd1 (Wei et al., 2019 ); Sdr-5 for TaSdr-B1 (Zhang et al., 2014 ); Sdr-2A for TaSdr-A1 (Zhang et al., 2017 ); PM19-A1 for TaPM19 (Barrero et al., 2015 ), and STS-Myb10 for TaMyb10-D (Lang et al., 2021 ). In total, 32,368 SNPs from the Wheat 90K array and the 13 dormancy-related markers were used for association analysis. Population structure analysis and genome-wide association study (GWAS) procedures followed those described in our previous study (Pan et al., 2024 ). Marker-trait associations (MTAs) were detected using mixed linear models (MLMs) implemented in TASSEL 5.0, with -log10( P ) = 4.0 as the exploratory significance threshold. A Q matrix inferred by STRUCTURE and a kinship matrix generated in TASSEL 5.0 were included as covariates to account for population structure and relatedness and to reduce false-positive associations. Major QTLs were defined as loci in at least three environments and explaining more than 10% of the phenotypic variation (PVE). Molecular marker development To validate the major QTL Qgi.245.ahau-4B.3 , SNPs located within the linkage disequilibrium (LD) decay interval were converted into cleaved amplified polymorphic sequence (CAPS) markers. SNP information was obtained from the resequencing data of 145 wheat accessions (Hao et al., 2020 ). In total, 17 CAPS markers were developed (Table S2). Primer design for CAPS marker development was performed using Primer Premier v5.0. Linkage map construction and QTL validation in different genetic backgrounds The AA-RIL population comprising 179 lines and the two parental lines (AN8455 and AN1124) was genotyped using the Wheat 16K SNP array (Mol Breeding; http://www.molbreeding.com ). After removing markers that were monomorphic between the parents and those with a missing rate > 20% or a minor allele frequency (MAF) < 0.3, a total of 3,431 markers were retained for linkage map construction. The 17 CAPS markers flanking Qgi.245.ahau-4B.3 , the PHS-related marker STS-Myb10 , and the 3,431 SNP markers were jointly used to construct the genetic map of the AA-RIL population. Linkage map construction was performed using QTL IciMapping v4.2 (Li et al., 2022 ). QTL analysis was performed using the constructed genetic map and the additive model of inclusive composite interval mapping (ICIM-ADD) implemented in QTL IciMapping v4.2 (Li et al., 2022 ). The logarithm of odds (LOD) threshold was set to 2.5, and the walking step was 1 cM. QTLs separated by 10% of the phenotypic variation were defined as major QTLs. Prediction and expression analysis of candidate genes Candidate regions were defined as the overlapping intervals identified by both association and linkage analyses. Genes within these regions were retrieved from the IWGSC RefSeq v1.0 annotation database ( https://wheat-urgi.versailles.inra.fr/ ). To analyze the expression patterns of candidate genes, seeds of AN1124 (moderate dormancy) and AN8455 (weak dormancy) were sampled after 1, 6, 9, 12, 24, and 36 h of imbibition. Total RNA was extracted using a total RNA kit (Takara). Real time quantitative PCR (RT-qPCR) was performed using an Accurate Biology system. All reactions were conducted in triplicate. Primer sequences for the candidate genes are listed in Table S2. The wheat actin gene ( TraesCS1D02G020000 ) was used as the internal reference. Sequence variation and haplotype analysis of candidate genes The full-length sequences of TaF-box-B1 ( TraesCS4B02G118000 ) and TaF-box-B2 ( TraesCS4B02G118200 ) were obtained from the IWGSC RefSeq v1.0 database. Primer sets were designed using Primer premier v5.0 and used to amplify the genomic sequences of TaF-box-B1 and TaF-box-B2 from AN8455 and AN1124. Sequence assembly and alignment were performed using DNAMAN v7.0 ( https://www.lynnon.com ). Changes in promoter cis -acting elements were analyzed using PlantCARE ( https://bioinformatics.psb.ugent.be/webtools/plantcare/html/ ). Haplotype analysis of TaF-box-B1 and TaF-box-B2 was conducted using resequencing data from 145 wheat accessions. Gene-specific markers were developed based on key sequence variants in TaF-box-B1 and TaF-box-B2 and used to genotype 431 improved varieties and 108 landraces. Subsequent U-tests were performed to validate the associations of TaF-box-B1 and TaF-box-B2 with seed dormancy. Results Phenotypic variation and heritability of seed dormancy Statistical analysis showed that the GI values of the 245 wheat varieties varied significantly across the seven environments and BLUP datasets (Table S1 ). The GIs ranged from 0.00 to 1.00, with standard deviations (SD) of 0.09–0.25 and coefficients of variation (CV) of 10.47–77.91%. Correlation analysis revealed highly significant correlations in GI among environments, with correlation coefficients ranging from 0.34 to 0.88 (Fig. 1 A). The H 2 of GI was 0.61, indicating a substantial genetic contribution to variation in seed dormancy (Table S1 ). In addition, GI exhibited an approximately normal distribution in all environments, supporting that seed dormancy is a quantitative trait controlled by multiple genes (Fig. 1 ). Genome-wide identification of seed dormancy–associated loci GWAS was performed using the GI data from seven environments and BLUP values for the 245 wheat varieties, together with genotypic data from the Wheat 90K SNP array. In total, 70 significant MTAs for seed dormancy were detected (Table S3; Fig. 2 ). Based on the LD decay of the A, B, and D subgenomes (Pan et al., 2024 ), these MTAs were grouped into 55 loci (Table S3). The loci were distributed on chromosomes 1A (7), 1B (1), 1D (4), 2B (12), 2D (2), 3A (3), 3B (2), 3D (3), 4B (3), 5A (4), 5B (2), 5D (1), 6B (1), 6D (1), 7A (2), 7B (5), and 7D (2), explaining 6.64–13.90% of the phenotypic variation. Among these loci, Qgi.245.ahau-2D.2 was detected in five environments (HB21, HB22, JY21, BB22, and SZ22) and in the BLUP dataset, explaining 7.76-13.00% of the phenotypic variation. Notably, Qgi.245.ahau-4B.3 was identified in four environments (HB21, HB22, JY21, and BB22) and in the BLUP dataset, explaining 9.09–13.90% of the phenotypic variation. Compared with previously reported loci, Qgi.245.ahau-4B.3 was therefore considered a novel major locus for seed dormancy. In addition, the known STS-Myb marker associated with seed color and dormancy, corresponding to Qgi.245.ahau-3D.3 , showed significant association with GI in HF21 and BB22 and with the BLUP values, explaining 6.86–8.16% of the phenotypic variation (Table S3). To further refine the target interval of the novel major locus Qgi.245.ahau-4B.3 , 17 CAPS markers were developed and integrated with the Wheat 90K SNP markers for re-GWAS. Sixteen of the 17 markers showed stable and significant association with seed dormancy across environments (Table S4; Fig. 3 A, B). The candidate interval was thereby narrowed to a region from 133.59 to 145.81 Mb on chromosome 4B, further supporting the association of Qgi.245.ahau-4B.3 with seed dormancy. Validation of the novel seed dormancy locus Qgi.245.ahau-4B.3 To validate the novel locus Qgi.245.ahau-4B.3 , an AA-RIL population derived from a cross between AN8455 (weak dormancy) and AN1124 (moderate dormancy) was used, based on the genotypic differences between the two parents at this locus. A high-density genetic map of the AA-RIL population was constructed using the 17 CAPS markers, the dormancy-related marker STS-Myb, and 3,431 SNPs from the Wheat 16K SNP array. The resulting genetic map spanned 5,449.32 cM, with the number of markers per chromosome ranging from 26 (2D) to 443 (3B). The A, B, and D subgenomes covered 2,168.96, 1,965.10, and 1,315.26 cM, respectively (Table S5). QTL mapping identified eight loci significantly associated with seed dormancy on chromosomes 1A, 3A, 3D, 4A, 4B, 4D, 5B, and 7B, explaining 3.30-25.12% of phenotypic variation (Table S6). Among these, Qgi.AA.ahau-4B , located at 136.67–138.30 Mb on chromosome 4B, was consistently detected in all three environments (HF23, HF24, and HB24), with LOD values ranging from 4.82 to 17.16 and explaining 9.61–25.12% of the phenotypic variation. Importantly, Qgi.AA.ahau-4B co-localized with Qgi.245.ahau-4B.3 identified in the association panel, indicating that they represent the same locus (Fig. 3 C). Accordingly, Qgi.245.ahau-4B.3 was further delimited to a 1.63 Mb interval (136.67–138.30 Mb) on chromosome 4B. Prediction of candidate genes underlying Qgi.245.ahau-4B.3 Within the 1.63 Mb interval of Qgi.245.ahau-4B.3 , five high-confidence genes were annotated in the IWGSC RefSeq v1.0 genome assembly (Table S7). To identify candidate genes underlying Qgi.245.ahau-4B.3 , the expression of these five genes was examined in seeds of the moderate dormancy variety AN1124 and the weak dormancy variety AN8455 after 1, 6, 9, 12, 24, and 36 h of imbibition (Fig. 4 ), representing the dormancy release process. Among the five genes, the expression levels of TraesCS4B02G118000 and TraesCS4B02G118200 in AN1124 were consistently and significantly lower than that in AN8455 (Fig. 4 D and 4 F). Both TraesCS4B02G118000 and TraesCS4B02G118200 encode F-box proteins and were designated TaF-box-B1 and TaF-box-B2 , respectively. Given that F-box proteins play important roles in the regulation of seed dormancy in diverse plant species through crosstalk with phytohormone signaling pathways (Ariizumi et al., 2007; Ariizumi et al., 2011 ; Gong et al., 2022 ; Varshney et al., 2023 ; Song et al., 2012 ), TaF-box-B1 and TaF-box-B2 were selected as candidate genes underlying Qgi.245.ahau-4B.3 . Sequence variation analysis of candidate genes TaF-box-B1 and TaF-box-B2 To investigate sequence variation in TaF-box-B1 and TaF-box-B2 between AN1124 and AN8455, the promoter and coding regions of both genes were cloned and compared. TaF-box-B1 is 1,323 bp in length and consists of a single exon encoding a 441 aa protein containing an F-box domain (Fig. 5 A). Sequence alignment revealed six polymorphisms between AN1124 and AN8455, including three in the promoter region and three in the coding region (Table S8). Promoter analysis showed that the T/C polymorphism at -821 bp resulted in the presence of the CGTCA motif and TGACG motif in AN1124, the A/G polymorphism at -804 bp resulted in the presence of the ABRE and G-box in AN8455, whereas the G/C polymorphism at -1292 bp did not alter predicted cis -elements. In the coding region, the A/delA polymorphism at + 65 bp caused a frameshift mutation, the A/G polymorphism at + 989 bp resulted in an amino acid substitution from glutamate (E) to glycine (G), and the C/T polymorphism at + 1091 bp caused a substitution from alanine (A) to valine (V) (Table S8; Fig. 5 A). TaF-box-B2 is 1,763 bp in length and also consists of a single exon encoding a 458 aa protein containing an F-box domain (Fig. 5 C). Sequence alignment identified nine polymorphisms, including five in the promoter region, two in the 5’ untranslated (UTR) region, and two in the coding region (Table S8). Promoter analysis indicated that only the T/C polymorphism at -1191 bp resulted in the presence of the A-box and CCGTCC motif in AN1124, whereas the remaining four promoter polymorphisms did not alter predicted cis -elements. In the coding region, the A/G polymorphism at + 65 bp resulted in an amino acid substitution from lysine (K) to arginine (R), and the C/T polymorphism at + 1091 bp caused a substitution from methionine (M) to threonine (T) (Table S8; Fig. 5 C). Haplotype analysis and phenotypic effects of TaF-box-B1 and TaF-box-B2 To further investigate natural variation in TaF-box-B1 and TaF-box-B2 among wheat accessions, sequence information covering the promoter region (1,500 bp upstream of the ATG start codon) and the coding region was extracted from the resequencing data of 145 wheat accessions (Hao et al., 2020 ). After removing accessions with missing sequences, six and nine polymorphic sites were identified in TaF-box-B1 and TaF-box-B2 , respectively, consistent with the sequence variation detected above (Table S9). Haplotype analysis showed that each gene contained two haplotypes, designated B1-Hap1 and B1-Hap2 for TaF-box-B1 , and B2-Hap1 and B2-Hap2 for TaF-box-B2 (Fig. 5 A, C). To distinguish the haplotypes of TaF-box-B1 and TaF-box-B2 , two CAPS markers (B1 + 65 and B2 + 65, respectively) were developed based on the A/del A frameshift polymorphism at + 65 bp in the coding region of TaF-box-B1 and the A/G missense polymorphism at + 65 bp in the coding region of TaF-box-B2 (Fig. 5 B). For TaF-box-B1 , the delA and A alleles corresponded to B1-Hap1 and B1-Hap2 , respectively (Fig. 5 D). For TaF-box-B2 , the G and A alleles corresponded to B2-Hap1 and B2-Hap2 , respectively. To validate the association of TaF-box-B1 and TaF-box-B2 with seed dormancy, 431 wheat varieties from different Chinese wheat-growing regions were genotyped using the B1 + 65 and B2 + 65 markers. After excluding accessions with missing data, the two markers showed complete linkage in the 431 varieties (Table S10). Accordingly, B1-Hap1 and B2-Hap1 were combined and defined as TaF-box-Hap1 , whereas B1-Hap2 and B2-Hap2 were combined and defined as TaF-box-Hap2 . The U-test results indicated a highly significant difference in GI between varieties carrying TaF-box-Hap1 and TaF-box-Hap2 ( P < 0.0001). Varieties carrying TaF-box-Hap1 exhibited significantly lower GI values (strong dormancy) than those carrying TaF-box-Hap2 (weak dormancy) (Fig. 5 E). These results indicate that TaF-box-Hap1 and TaF-box-Hap2 represent the candidate haplotypes underlying Qgi.245.ahau-4B.3 for seed dormancy. In addition, the effects of TaF-box-Hap1 (strong dormancy) and TaF-box-Hap2 (weak dormancy) on yield-related traits were evaluated in 431 wheat varieties. No significant differences were observed between the two haplotypes for thousand grain weight (TGW), number of grains per spike (NGPS), tiller number (TN), or plant height (PH) (Fig. 5 F-I). These results indicate that the favorable haplotype TaF-box-Hap1 associated with strong dormancy is a promising target for improving seed dormancy and PHS resistance in wheat. Geographic distribution and breeding utilization of TaF-box-4B-Hap1 To further evaluate the potential application of TaF-box-Hap1 in wheat breeding, its distribution frequency was analyzed in 108 landraces and 431 improved varieties collected from four major wheat-growing regions of China, including the Yellow and Huaihai River winter wheat region (HWW), the Middle and Lower Yangtze River winter wheat region (YRWW), the Southwest winter wheat region (SWW), and the Northern winter wheat region (NWW) (Tabel S10). The overall frequency of TaF-box-Hap1 was 34.47% in improved varieties and 6.48% in landraces (Fig. 6 A). Among the four regions, TaF-box-Hap1 showed the highest frequency in YRWW (54.10%), followed by SWW (33.33%), HWW (25.79%), and NWW (18.18%) (Fig. 6 B). These results indicate a clear regional bias in the distribution of TaF-box-Hap1 across Chinese wheat-growing areas and suggest that this haplotype has been preferentially selected in the YRWW, which is characterized by relatively high rainfall and humidity. Discussion With increasingly severe climate change and more frequent extreme weather events, PHS in wheat has become a global threat to food security (Zhang et al., 2025 ). Breeding wheat varieties with moderate seed dormancy is therefore a key strategy for mitigating this problem. The identification of seed dormancy-related genes and the development of functional markers will facilitate the genetic improvement of PHS resistance in wheat. Comparison with previously reported seed dormancy and pre-harvest sprouting loci Numerous QTLs and genes associated with seed dormancy have previously been identified in wheat using diverse genetic populations. In the present study, 55 loci associated with seed dormancy were detected by GWAS. Comparative analysis showed that seven of these loci overlapped with previously reported QTLs or genes. For example, Qgi.245.ahau-2B.3 (105.91-108.24 Mb) on chromosome 2B overlapped with GCR-QTL7 (102.36-118.23 Mb, which controls grain color and PHS in wheat (Zhou et al., 2017 ). Qgi.245.ahau-2B.6 (140.78-144.43 Mb) on chromosome 2B overlapped with QSGR.sau-2B.1 (137.86-158.38 Mb) controlling wheat PHS (Li et al., 2022 ). Qgi.245.ahau-2D.2 (approximately 650.32 Mb) on chromosome 2D overlapped with Qphs.ahau-2D.2 (628.2-650.3 Mb) controlling wheat PHS (Zhu et al., 2019 ). On chromosome 4B, Qgi.245.ahau-4B.1 (approximately 31.71 Mb) and Qgi.245.ahau-4B.2 (40.78–40.87 Mb) overlapped with QPhs.spa-4B (15.8–98.7 Mb), which controls wheat PHS (Kumar et al., 2015 ). Qgi.245.ahau-5A.1 (approximately 3.40 Mb) on chromosome 5A overlapped with Qphs.ahau-5A (0.0-4.8 Mb) controlling wheat PHS (Zhu et al., 2019 ). In addition, Qgi.245.ahau-3D.3 (570.80 Mb) on chromosome 3D was located close to TaMYB10-3D (570.80 Mb), which is associated with seed color and dormancy (Lang et al., 2021 ). Notably, Qgi.245.ahau-4B.3 (136.67–138.30 Mb) on chromosome 4B was confirmed as a major locus through re-GWAS and linkage analysis. By comparison, although several loci related to seed dormancy and PHS resistance have previously been reported on chromosome 4B, including QGI.nmbu-4BL (BA00631502, 409.74 Mb), QGI.nmbu-4BS (wsnp_Ex_c13357_21054802, 11.35 Mb), QGI.nmbu-4BL (wsnp_Ex_c4148_7495656, 657.1 Mb), gwm251 (568.6 Mb), wmc48 (98.7 Mb), and QPhs.spa-4B (wmc617b-wmc48a, 15.8–98.7 Mb) (Jaiswal et al., 2012 ; Begum et al., 2024 ; Vahramians et al., 2024; Kumar et al., 2015 ), none of these loci coincided with the physical interval of Qgi.245.ahau-4B.3. Therefore, we suggest that Qgi.245.ahau-4B.3 is a novel locus related to seed dormancy. Subsequently, the novel locus Qgi.245.ahau-4B.3 was further validated using the AA-RIL population derived from a cross between AN1124 and AN8455. In this population, another locus ( Qgi.AA.ahau-3A ) was detected on chromosome 3A at 0.00-711.26 Mb. Previous studies have reported that TaMFT-3A and TaMyb10-A on chromosome 3A are associated with seed dormancy. Therefore, the two parental lines were first genotyped using the SNP.646, MFT-222, MFT-A1, and MFT-A2 markers for TaMFT-3A (Liu et al., 2015 ; Nakamura et al., 2015 ; Lei et al., 2013 ; Jiang et al., 2018 ), as well as the TaMyb10-A_In/Del marker for TaMyb10-A (Lang et al., 2024 ). Only the TaMyb10-A_In/Del marker showed polymorphism between AN1124 and AN8455. Subsequently, all 179 lines of the AA-RIL population were genotyped using the TaMyb10-A_In/Del marker for re-mapping. Finally, Qgi.AA.ahau-3A was refined to the interval of 701.01-711.29 Mb, within which TaMyb10-A (703.91 Mb) is located (Table S11). These results suggest that TaMyb10-A is the most likely candidate gene underlying Qgi.AA.ahau-3A . Potential roles of TaF-box-B1 and TaF-box-B2 in regulating seed dormancy Previous studies have shown that F-box proteins play an important regulatory role in seed dormancy and germination, primarily through their involvement in phytohormone signaling pathways. In A. thaliana , the F-box gene SLEEPY1 ( SLY1 ) acts as a positive regulator of the gibberellin (GA) signaling pathway. Upon GA binding to the GID1 receptor, the SCF-type E3 ubiquitin ligase complex containing SLY1 is activated, leading to the ubiquitination and subsequent degradation of DELLA proteins, which are key negative regulators of the GA signaling pathway, thereby promoting seed germination (Ariizumi et al., 2007, 2011 ). Gong et al. ( 2022 ) reported that the F-Box / DUF295 Brassiceae-specific 2 ( FDB2 ) gene negatively regulates ABA-mediated inhibition of seed germination in A. thaliana . Overexpression of FDB2 reduced seed sensitivity to ABA, whereas fdb2 mutants exhibited hypersensitivity to ABA. Varshney et al. ( 2023 ) demonstrated that the F-box protein SKIP31 promotes the degradation of jasmonate ZIM-domain (JAZ) proteins through the ubiquitin-proteasome pathway. In wheat, TaJAZ1, which is most closely related to A. thaliana JAZ3, negatively regulates ABA-inhibited seed germination by interacting with TaABI5 (ABA insensitive 5), a key positive transcript factor in the ABA signaling pathway (Ju et al., 2019 ). Thus SKIP31-mediated JAZ degradation activates downstream ABA signaling and is critical for balancing seed dormancy and germination. In rice, the F-box protein OsFbx352 influences ABA homeostasis by downregulating ABA biosynthesis genes and upregulating ABA catabolism genes, thereby reducing ABA levels in seeds and affecting dormancy (Song et al., 2012 ). In the present study, by integrating association mapping, linkage mapping, expression profiling, sequence variation, and haplotype analysis, we identified TaF-box-B1 and TaF-box-B2 , both encoding F-box proteins, as candidate genes underlying Qgi.245.ahau-4B.3 . However, their regulatory mechanisms in wheat seed dormancy remain largely unknown and warrant further investigation. Breeding potential of TaF-box-B1 and TaF-box-B2 for improving PHS resistance Seed dormancy is a complex trait controlled by multiple genes, and pyramiding favorable alleles is an effective strategy for enhancing seed dormancy and PHS resistance in wheat. In this study, two gene-specific CAPS markers (B1 + 65 and B2 + 65) were developed for TaF-box-B1 and TaF-box-B2 , respectively. Notably, B1 + 65 and B2 + 65 were completely linked and defined two haplotypes ( TaF-box-Hap1 and TaF-box-Hap2 ), of which TaF-box-Hap1 was significantly associated with stronger seed dormancy. Importantly, the favorable haplotype TaF-box-Hap1 showed no negative effects on yield-related traits. Therefore, TaF-box-Hap1 represents a promising target for the genetic improvement of PHS resistance in wheat. In addition, the favorable haplotype TaF-box-Hap1 occurred at a higher frequency in southern than in northern wheat-growing regions, where rainfall and humidity are typically higher. In summary, by integrating association mapping, linkage mapping, expression profiling, sequence variation, and haplotype analysis, we identified a novel major locus ( Qgi.245.ahau-4B.3 ) and its candidate genes ( TaF-box-B1 and TaF-box-B2 ) controlling seed dormancy. We further identified a favorable haplotype ( TaF-box-Hap1 ) associated with strong dormancy but not affecting yield-related traits, and demonstrated its practical value for wheat breeding. These findings contribute to a better understanding of the genetic basis of seed dormancy and provide valuable gene resources and molecular markers for improving PHS resistance in wheat. Author contribution statement HPZ, CC, and CXM initiated the project, designed the study, and revised the paper; YXL, YYZ, and WBL completed the experiment, and prepared the manuscript; XP, WG, LTZ, HFW, ZYY, RHW, TFS, BBT, JJC, and JL assisted in the cultivation, management, and phenotyping of experimental materials. All authors read the manuscript and approved it for publication. Declarations Author contribution statement HPZ, CC, and CXM initiated the project, designed the study, and revised the paper; YXL, YYZ, and WBL completed the experiment, and prepared the manuscript; XP, WG, LTZ, HFW, ZYY, RHW, TFS, BBT, JJC, and JL assisted in the cultivation, management, and phenotyping of experimental materials. All authors read the manuscript and approved it for publication. Funding This work was supported by the Innovation Project of Bio-breeding Laboratory of Anhui Province (No.2025SWYZ0330), the National Natural Science Foundation of China (32572414; 32372069), the Agriculture Research System of Anhui Province (AHCYTX-02), and Jiangsu Collaborative Innovation Center for Modern Crop Production (JCIC-MCP). Conflict of interest The authors declare that they have no conflict of interest. References Ariizumi T, Lawrence PK, Steber CM (2011) The role of two F-box proteins, SLEEPY1 and SNEEZY, in Arabidopsis gibberellin signaling. Plant Physiol 155(2): 765-775. Ariizumi T, Steber CM (2007) Seed germination of GA-insensitive sleepy1 mutants does not require RGL2 protein disappearance in Arabidopsis . Plant Cell 19(3): 791-804. Bai W, Yang Z, Yu X, Huang S, Wang Y, Jing Y, Zhang Y, Sun J (2025) Wheat PKL genes regulate pre-harvest sprouting and yield-related traits. J Genet Genomics 52(9): 1148-1150. 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Additional Declarations No competing interests reported. Supplementary Files TableS111.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 17 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviews received at journal 29 Mar, 2026 Reviewers agreed at journal 17 Mar, 2026 Reviewers agreed at journal 08 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 15 Feb, 2026 First submitted to journal 11 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8857089","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596357518,"identity":"cd36270d-ec47-42e1-a346-02dbe0ba84e8","order_by":0,"name":"Yuxia 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University","correspondingAuthor":false,"prefix":"","firstName":"Chuanxi","middleName":"","lastName":"Ma","suffix":""},{"id":596357538,"identity":"a26f7f5f-3ef3-4044-97b9-ba79852c4fb1","order_by":14,"name":"Cheng Chang","email":"","orcid":"","institution":"Anhui Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Chang","suffix":""},{"id":596357541,"identity":"8c8ad07d-fc66-49f3-8db6-4d4a0242368a","order_by":15,"name":"Haiping Zhang","email":"","orcid":"","institution":"Anhui Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Haiping","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-02-12 03:38:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8857089/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8857089/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103619632,"identity":"50d675c4-c61f-40ce-a1a8-4d66b6196be6","added_by":"auto","created_at":"2026-02-27 17:52:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":249579,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical analysis of germination index (GI). (\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003ePhenotypic performance, distribution, and pairwise correlations of GI among 245 wheat varieties across environments. (\u003cstrong\u003eB\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003ePhenotypic performance, distribution, and pairwise correlations of GI in the AA-RIL population across environments. In the pair plots, bivariate scatter plots are shown below the diagonal, histograms are shown on the diagonal, and pairwise correlation coefficients are shown above the diagonal. *** and * indicate significance at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001 and \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/e7ed14afdcdc72c382b1d1b0.png"},{"id":103619634,"identity":"3ec4613f-e443-45fe-a784-ecbf894707c5","added_by":"auto","created_at":"2026-02-27 17:52:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":735498,"visible":true,"origin":"","legend":"\u003cp\u003eManhattan plots of germination index (GI) and BLUP values. The horizontal black line indicates the genome-wide significance threshold [-log\u003csub\u003e10\u003c/sub\u003e(\u003cem\u003ep\u003c/em\u003e) = 4.0], and significant loci exceeding the threshold are highlighted in red. Manhattan plots were generated using GI data from Hefei in 2020-2021 (\u003cstrong\u003eA\u003c/strong\u003e), Jiyuan in 2020-2021 (\u003cstrong\u003eB\u003c/strong\u003e), Huaibei in 2020-2021 (\u003cstrong\u003eC\u003c/strong\u003e), Hefei in 2021-2022 (\u003cstrong\u003eD\u003c/strong\u003e), Huaibei in 2021-2022 (\u003cstrong\u003eE\u003c/strong\u003e), Bengbu in 2021-2022 (\u003cstrong\u003eF\u003c/strong\u003e), Suzhou in 2021-2022 (\u003cstrong\u003eG\u003c/strong\u003e), and the BLUP dataset (\u003cstrong\u003eH\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/b29e22ea3f16c88dc6d77285.png"},{"id":104399170,"identity":"62981b78-79cf-4842-b1d6-c468e7ffd5dd","added_by":"auto","created_at":"2026-03-11 12:04:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":276385,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of the novel major seed dormancy QTL \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e. (\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eManhattan plot for chromosome 4B obtained by re-GWAS. The black dashed line indicates the significance threshold [-log\u003csub\u003e10\u003c/sub\u003e(\u003cem\u003ep\u003c/em\u003e) = 4.0], and the red dashed line indicates the candidate interval.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eB\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eLinkage disequilibrium heat map of the target region on chromosome 4B. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eDetection of the major QTL \u003cem\u003eQgi.AA.ahau-4B\u003c/em\u003e for seed dormancy in the AA-RIL population. The black dashed line indicates the significance threshold [LOD = 2.5].\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/85cf3233135acc9df4ea6636.png"},{"id":104399199,"identity":"bc692b15-cae2-4844-abc2-10cb0b3723ab","added_by":"auto","created_at":"2026-03-11 12:05:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":163092,"visible":true,"origin":"","legend":"\u003cp\u003eExpression analysis of candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e. (\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eRepresentative images of AN1124 and AN8455 seeds after 1, 6, 9, 12, 24, and 36 h of imbibition. (\u003cstrong\u003eB-F\u003c/strong\u003e) Expression profiles of the five candidate genes at different imbibition stages in AN1124 and AN8455. ns indicates no significant difference. * and ** indicate significance at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05 and \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, respectively.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/c3d11b27cc0d5fb898ec369d.png"},{"id":104399110,"identity":"74fc0e3f-6ee9-4acd-8434-4848f0c3701b","added_by":"auto","created_at":"2026-03-11 12:04:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":203243,"visible":true,"origin":"","legend":"\u003cp\u003eSequence variation and haplotype analysis of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e. (\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eGene structure and haplotypes of \u003cem\u003eTaF-box-B1\u003c/em\u003e. (\u003cstrong\u003eB\u003c/strong\u003e) Detection of the CAPS marker B1+65 for \u003cem\u003eTaF-box-B1\u003c/em\u003e.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eGene structure and haplotypes of \u003cem\u003eTaF-box-B2\u003c/em\u003e. (\u003cstrong\u003eD\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eDetection of the CAPS marker B2+65 for \u003cem\u003eTaF-box-B2\u003c/em\u003e. (\u003cstrong\u003eE-I\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eComparison of germination index (GI) and yield-related traits between wheat varieties carrying the two haplotypes\u003cem\u003e TaF-box-Hap1 \u003c/em\u003eand\u003cem\u003e TaF-box-Hap2\u003c/em\u003e. Yield-related traits include thousand grain weight (TGW), number of grains per spike (NGPS), tillering number (TN), and plant height (PH). ns indicates no significant difference and **** indicates significance at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/0f492f14472a0e668a2bfa82.png"},{"id":103619636,"identity":"35a86760-5b3d-43bf-82a3-9c11b36a7977","added_by":"auto","created_at":"2026-02-27 17:52:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":92153,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2.\u003c/em\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Frequencies of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e in landraces and improved varieties. (\u003cstrong\u003eB\u003c/strong\u003e) Frequencies of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2\u003c/em\u003ein four major Chinese wheat-growing regions: Middle and Lower Yangtze River winter wheat region (YRWW), Southwest winter wheat region (SWW), Yellow and Huai River winter wheat region (HWW), and Northern winter wheat region (NWW).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/781b0301cd56009498852332.png"},{"id":104407494,"identity":"6a66d94b-e719-40ff-8aeb-9d71406be8b9","added_by":"auto","created_at":"2026-03-11 12:38:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2655555,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/e84283c5-cf38-40db-a017-6a38db6e73f8.pdf"},{"id":103619635,"identity":"e93789d1-48ee-43d5-8f25-1dc005d9a41c","added_by":"auto","created_at":"2026-02-27 17:52:37","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":79254,"visible":true,"origin":"","legend":"","description":"","filename":"TableS111.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8857089/v1/73d976fc66d2553d7720d966.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of a novel major QTL and F-box candidate genes controlling seed dormancy in common wheat","fulltext":[{"header":"Key message","content":"\u003cp\u003eA novel major locus () controlling seed dormancy, and its candidate genes ( and ), were identified by integrating association and linkage mapping with expression and sequence variation analyses.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSeed dormancy is a heritable trait that delays germination and enables plants to survive unfavorable environmental conditions. During domestication, seed dormancy been selectively reduced to increase emergence after sowing (Gubler et al., 2005). Premature release of seed dormancy can cause mature seeds to germinate in the field and result in pre-harvest sprouting (PHS) under rainy or high-humidity conditions at harvest. This not only substantially reduces yield and quality in cereal crops, but also creates serious challenges for post-harvest storage, processing, and utilization (Simsek et al., 2014). In wheat, PHS occurs frequently in many regions worldwide, including China, Europe, the United States, Japan, Canada, Australia, and South Africa (Jiang et al., 2022; Barrero et al., 2015; Li et al., 2022). PHS causes annual economic losses of approximately US$1 billion and poses a serious threat to global food security (Tai et al., 2021). Enhancing seed dormancy is therefore an effective and safe strategy for preventing PHS.\u0026nbsp;Consequently, identifying genes associated with seed dormancy and developing gene-specific markers are essential for breeding wheat varieties with moderate dormancy to minimize PHS damage and ensure stable wheat production.\u003c/p\u003e\n\u003cp\u003eSeed dormancy is a quantitative trait controlled by multiple genes (Tai et al., 2021). Considerable efforts have been devoted to elucidating the genetic basis of seed dormancy, and numerous quantitative trait loci (QTLs) and genes associated with seed dormancy have been identified in wheat (Liu et al., 2013; Shorinola et al., 2017; Zhu et al., 2019; Tai et al., 2021; Lang et al., 2021; Li et al., 2022; Tai et al., 2024; Zhang et al., 2025; Cheng et al., 2026). The QTL \u003cem\u003eQphs.pseru-3AS\u003c/em\u003e on chromosome 3A explains up to 58% of phenotypic variation in seed dormancy (Liu et al., 2008), and \u003cem\u003eTaPHS1\u003c/em\u003e (\u003cem\u003eTaMFT\u003c/em\u003e), which encodes a MOTHER OF FLOWERING TIME-like protein, is the candidate gene underlying this locus (Liu et al., 2013). \u003cem\u003eTaMKK3\u003c/em\u003e, encoding mitogen-activated kinase kinase 3, is the candidate gene underlying the major locus \u003cem\u003ePhs-A1\u003c/em\u003e on chromosome 4A (Torada et al., 2016; Shorinola et al., 2017). The major locus \u003cem\u003eqPHS.sicau-3D\u003c/em\u003e on chromosome 3D explains up to 42.47% of phenotypic variation in seed dormancy (Yang et al., 2019), and \u003cem\u003eTaMyb10-D\u003c/em\u003e, encoding an R2R3-MYB transcription factor, is the candidate gene underlying this locus (Lang et al., 2021). \u003cem\u003eTaPI4K-2A\u003c/em\u003e, encoding a phosphatidylinositol 4-kinase family protein, is the candidate gene underlying \u003cem\u003eQphs2A.7_nwafu\u003c/em\u003e on chromosome 2A (Tai et al., 2024). The three subgenome homologs of the phosphatase 2C protein gene \u003cem\u003eTaPP2C-a6\u003c/em\u003e co-localize with the QTLs \u003cem\u003eQPhs.wsu-1A.2\u003c/em\u003e, \u003cem\u003eQPhs.wsu-1B.2\u003c/em\u003e, and \u003cem\u003eQPhs1D.1_nwafu\u003c/em\u003e on chromosomes 1A, 1B, and 1D, respectively. TaPP2C-a6 interacts with TaDOG1Ls, a DELAY OF GERMINATION 1-like (DOG1L) protein that plays a major role in regulating seed dormancy, and mediates wheat seed dormancy (Bentsink et al., 2006; Zhang et al., 2025).\u003c/p\u003e\n\u003cp\u003eIn addition, several seed dormancy-related genes, including \u003cem\u003eTaVp1\u003c/em\u003e, \u003cem\u003eTaSdr\u003c/em\u003e, \u003cem\u003eTaQsd1\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003eand \u003cem\u003eTaJAZ1\u003c/em\u003e, have been cloned using homology-based approaches (Yang et al., 2007; Chang et al., 2010; Zhang et al., 2014; Wei et al., 2019; Ju et al., 2019). \u003cem\u003eTaVp1\u003c/em\u003e (\u003cem\u003eViviparous-1\u003c/em\u003e) is a homolog of \u003cem\u003eArabidopsis thaliana\u003c/em\u003e \u003cem\u003eABI3\u003c/em\u003e (\u003cem\u003eABA insensitive-3\u003c/em\u003e) and maize \u003cem\u003eVp-1\u003c/em\u003e, and positively regulates wheat seed dormancy (Yang et al., 2007; Chang et al., 2010). Variation in the promoter of \u003cem\u003eTaSdr-B\u003c/em\u003e, a homolog of rice \u003cem\u003eOsSdr4\u003c/em\u003e, is significantly associated with seed dormancy in wheat (Zhang et al., 2014). \u003cem\u003eTaQsd1\u003c/em\u003e, a homolog of barley \u003cem\u003eQsd1\u003c/em\u003e encoding an alanine aminotransferase, regulates wheat seed dormancy mainly through abscisic acid (ABA)\u0026nbsp;biosynthesis, catabolism, and signaling pathways (Wei et al., 2019). \u003cem\u003eTaJAZ1\u003c/em\u003e, a homolog of \u003cem\u003eA. thaliana\u003c/em\u003e \u003cem\u003eJAZ3\u003c/em\u003e encoding a jasmonate ZIM-domain protein, negatively regulates wheat seed dormancy (Ju et al., 2019). Additional dormancy-related genes, including\u003cem\u003e\u0026nbsp;TaGATA1\u003c/em\u003e, \u003cem\u003eTaSRO1\u003c/em\u003e, \u003cem\u003eTaPKL\u003c/em\u003e, and \u003cem\u003eTaGASR25\u003c/em\u003e, have been identified in wheat using other approaches (Wei et al., 2023; Liu et al., 2023; Bai et al., 2025, Cheng et al., 2026). In summary, although many seed dormancy-related genes have been identified in wheat, their underlying genetic mechanisms and breeding potential remain unclear, which limits their practical application in improving PHS resistance through molecular breeding.\u003c/p\u003e\n\u003cp\u003eGenome-wide association study (GWAS) is a research method that identifies the associations between genetic variations and complex traits on a genome-wide scale. It is a powerful tool for detecting the genes/QTL underlying complex traits (Tai et al., 2024; Lv et al., 2024). Linkage analysis is a genetic mapping approach employed to identify genomic loci associated with variation in a target trait, based on the co-segregation of genetic markers and the trait in different lines (Guo et al., 2023; Shorinola et al., 2016). GWAS offer high genomic resolution, utilize diverse and extensive biological samples, capture abundant genetic variation across the genome, and enable precise localization of trait-associated loci. However, GWAS are inherently susceptible to confounding effects arising from population stratification, which may lead to spurious associations and an elevated risk of false-positive locus identification (Price et al., 2006). Linkage analysis is generally conducted based on parental populations and is less affected by the population structure, resulting in higher reliability in loci localization (Shorinola et al., 2016). Therefore, combining GWAS with linkage analysis may lead to more reliable results.\u003c/p\u003e\n\u003cp\u003eIn this study, we used an association panel of 245 wheat varieties and an recombinant inbred line (RIL) population derived from Annong 8455 × Annong 1124 cross to investigate the germination index (GI) in different environments to explore genomic regions and candidate genes related to seed dormancy. The objectives of this study were to (1) identify genetic loci associated with seed dormancy\u0026nbsp;in wheat based on GWAS, (2) narrow down the target interval of the novel major locus \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e based on linkage analysis, (3) identify the candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, and (4) assess the frequency distribution of the favorable haplotype of the candidate gene. This study provides valuable gene resources and molecular markers for breeding wheat varieties with moderate seed dormancy and improved PHS resistance.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and field experiments\u003c/h2\u003e \u003cp\u003eThe association panel of 245 wheat varieties reported previously was used for association mapping (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lv et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The panel was evaluated at five experimental stations of Anhui Agricultural University: Hefei, Anhui (HF; 2020\u0026ndash;2021 and 2021\u0026ndash;2022; 117\u0026deg;213\u0026prime;E, 31\u0026deg;919\u0026prime;N); Huaibei, Anhui (HB; 2020\u0026ndash;2021 and 2021\u0026ndash;2022; 116\u0026deg;75\u0026prime;E, 33\u0026deg;76\u0026prime;N); Bengbu, Anhui (BB; 2021\u0026ndash;2022; 116\u0026deg;873\u0026prime;E, 33\u0026deg;102\u0026prime;N); Suzhou, Anhui (SZ; 2021\u0026ndash;2022; 117\u0026deg;11\u0026prime;E, 33\u0026deg;88\u0026prime;N); and Jiyuan, Henan (JY; 2020\u0026ndash;2021; 112\u0026deg;59\u0026prime;E, 35\u0026deg;09\u0026prime;N). The seven environments were designated HF21, HF22, HB21, HB22, BB22, SZ22, and JY21.\u003c/p\u003e \u003cp\u003eAn F\u003csub\u003e8\u003c/sub\u003e RIL population (AA-RIL; 179 lines), derived from a cross between Annong 8455 (AN8455; weak dormancy; average GI\u0026thinsp;=\u0026thinsp;0.65) and Annong 1124 (AN1124; moderate dormancy; average GI\u0026thinsp;=\u0026thinsp;0.37) (Evaluation of wheat seed dormancy can be referred to Chang et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), was used for linkage analysis to validate the novel QTL \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e. The AA-RIL population was grown at two experimental stations: Hefei, Anhui (HF; 2022\u0026ndash;2023 and 2023\u0026ndash;2024; 117\u0026deg;21\u0026prime;E, 31\u0026deg;91\u0026prime;N) and Huaibei, Anhui (HB; 2023\u0026ndash;2024; 116\u0026deg;75\u0026prime;E, 33\u0026deg;76\u0026prime;N). The three environments were designated HF23, HF24, and HB24.\u003c/p\u003e \u003cp\u003eAll trials were conducted with two replications using a randomized block design. Each line was planted in a single-row plot 2.0 m in length with a row spacing of 0.2 m. Field management and disease control followed standard local practices for wheat production.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePhenotypic evaluation\u003c/h2\u003e \u003cp\u003e Seed dormancy was evaluated using the GI according to the methods of Zhu et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Yan et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For each accession, 50 well-filled seeds were used per replicate, with two replicates. Seeds were placed in Petri dishes, supplied with 5 mL of sterile water, and incubated in a growth chamber at 20 ℃, with a 14 h light/10 h dark photoperiod and 80% relative humidity. Germinated seeds were counted and removed every 24 hours, and germination was defined by appearance of white embryos. The GI was calculated after three days using the following formula:\u003c/p\u003e \u003cp\u003eGI = (3n\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;2n\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;n\u003csub\u003e3\u003c/sub\u003e) / (3N),\u003c/p\u003e \u003cp\u003ewhere N is the total number of seeds, and n\u003csub\u003e1\u003c/sub\u003e, n\u003csub\u003e2\u003c/sub\u003e, and n\u003csub\u003e3\u003c/sub\u003e are the numbers of seeds that germinated on days one, two, and three, respectively.\u003c/p\u003e \u003cp\u003eDescriptive statistics, correlation analysis, and Mann-Whitney U-test were performed using SPSS v25 (IBM Corporation, Armonk, NY, USA). Best linear unbiased prediction (BLUP) and broad-sense heritability (\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) were estimated using the R package \u0026ldquo;Ime4\u0026rdquo; (Lv et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenotyping and genome-wide association study\u003c/h3\u003e\n\u003cp\u003eA total of 245 wheat varieties were genotypes using the Wheat 90K single nucleotide polymorphism (SNP) array together with 13 published dormancy-related markers. These markers included SNP.646, MFT-222, MFT-A1, and MFT-A2 for \u003cem\u003eTaMFT-3A\u003c/em\u003e (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nakamura et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lei et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); TaMFT-3B\u003cem\u003e2\u003c/em\u003e for \u003cem\u003eTaMFT-3B\u003c/em\u003e (Vetch et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); TaMKK3-A-caps for \u003cem\u003eTaMKK3\u003c/em\u003e (Shorinola et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); Vp1B3 and Vp1-b2 for \u003cem\u003eTaVp1\u003c/em\u003e (Yang et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Chang et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); QSD1 and QSD3 for \u003cem\u003eTaQsd1\u003c/em\u003e (Wei et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Sdr-5 for \u003cem\u003eTaSdr-B1\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e); Sdr-2A for \u003cem\u003eTaSdr-A1\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); PM19-A1 for \u003cem\u003eTaPM19\u003c/em\u003e (Barrero et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and STS-Myb10 for \u003cem\u003eTaMyb10-D\u003c/em\u003e (Lang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In total, 32,368 SNPs from the Wheat 90K array and the 13 dormancy-related markers were used for association analysis.\u003c/p\u003e \u003cp\u003ePopulation structure analysis and genome-wide association study (GWAS) procedures followed those described in our previous study (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Marker-trait associations (MTAs) were detected using mixed linear models (MLMs) implemented in TASSEL 5.0, with -log10(\u003cem\u003eP\u003c/em\u003e)\u0026thinsp;=\u0026thinsp;4.0 as the exploratory significance threshold. A Q matrix inferred by STRUCTURE and a kinship matrix generated in TASSEL 5.0 were included as covariates to account for population structure and relatedness and to reduce false-positive associations. Major QTLs were defined as loci in at least three environments and explaining more than 10% of the phenotypic variation (PVE).\u003c/p\u003e\n\u003ch3\u003eMolecular marker development\u003c/h3\u003e\n\u003cp\u003eTo validate the major QTL \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, SNPs located within the linkage disequilibrium (LD) decay interval were converted into cleaved amplified polymorphic sequence (CAPS) markers. SNP information was obtained from the resequencing data of 145 wheat accessions (Hao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In total, 17 CAPS markers were developed (Table S2). Primer design for CAPS marker development was performed using Primer Premier v5.0.\u003c/p\u003e\n\u003ch3\u003e\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cb\u003eLinkage map construction and QTL validation in different genetic backgrounds\u003c/b\u003e\u003c/div\u003e \u003cp\u003eThe AA-RIL population comprising 179 lines and the two parental lines (AN8455 and AN1124) was genotyped using the Wheat 16K SNP array (Mol Breeding; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.molbreeding.com\u003c/span\u003e\u003cspan address=\"http://www.molbreeding.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). After removing markers that were monomorphic between the parents and those with a missing rate\u0026thinsp;\u0026gt;\u0026thinsp;20% or a minor allele frequency (MAF)\u0026thinsp;\u0026lt;\u0026thinsp;0.3, a total of 3,431 markers were retained for linkage map construction. The 17 CAPS markers flanking \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, the PHS-related marker \u003cem\u003eSTS-Myb10\u003c/em\u003e, and the 3,431 SNP markers were jointly used to construct the genetic map of the AA-RIL population. Linkage map construction was performed using QTL IciMapping v4.2 (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eQTL analysis was performed using the constructed genetic map and the additive model of inclusive composite interval mapping (ICIM-ADD) implemented in QTL IciMapping v4.2 (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The logarithm of odds (LOD) threshold was set to 2.5, and the walking step was 1 cM. QTLs separated by \u0026lt;\u0026thinsp;1 cM or sharing the same marker were considered to represent the same QTL. QTLs detected in at least two environments and explaining\u0026thinsp;\u0026gt;\u0026thinsp;10% of the phenotypic variation were defined as major QTLs.\u003c/p\u003e\n\u003ch3\u003ePrediction and expression analysis of candidate genes\u003c/h3\u003e\n\u003cp\u003eCandidate regions were defined as the overlapping intervals identified by both association and linkage analyses. Genes within these regions were retrieved from the IWGSC RefSeq v1.0 annotation database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wheat-urgi.versailles.inra.fr/\u003c/span\u003e\u003cspan address=\"https://wheat-urgi.versailles.inra.fr/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To analyze the expression patterns of candidate genes, seeds of AN1124 (moderate dormancy) and AN8455 (weak dormancy) were sampled after 1, 6, 9, 12, 24, and 36 h of imbibition. Total RNA was extracted using a total RNA kit (Takara). Real time quantitative PCR (RT-qPCR) was performed using an Accurate Biology system. All reactions were conducted in triplicate. Primer sequences for the candidate genes are listed in Table S2. The wheat \u003cem\u003eactin\u003c/em\u003e gene (\u003cem\u003eTraesCS1D02G020000\u003c/em\u003e) was used as the internal reference.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSequence variation and haplotype analysis of candidate genes\u003c/h2\u003e \u003cp\u003eThe full-length sequences of \u003cem\u003eTaF-box-B1\u003c/em\u003e (\u003cem\u003eTraesCS4B02G118000\u003c/em\u003e) and \u003cem\u003eTaF-box-B2\u003c/em\u003e (\u003cem\u003eTraesCS4B02G118200\u003c/em\u003e) were obtained from the IWGSC RefSeq v1.0 database. Primer sets were designed using Primer premier v5.0 and used to amplify the genomic sequences of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e from AN8455 and AN1124. Sequence assembly and alignment were performed using DNAMAN v7.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.lynnon.com\u003c/span\u003e\u003cspan address=\"https://www.lynnon.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Changes in promoter \u003cem\u003ecis\u003c/em\u003e-acting elements were analyzed using PlantCARE (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinformatics.psb.ugent.be/webtools/plantcare/html/\u003c/span\u003e\u003cspan address=\"https://bioinformatics.psb.ugent.be/webtools/plantcare/html/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHaplotype analysis of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e was conducted using resequencing data from 145 wheat accessions. Gene-specific markers were developed based on key sequence variants in \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e and used to genotype 431 improved varieties and 108 landraces. Subsequent U-tests were performed to validate the associations of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e with seed dormancy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePhenotypic variation and heritability of seed dormancy\u003c/h2\u003e \u003cp\u003eStatistical analysis showed that the GI values of the 245 wheat varieties varied significantly across the seven environments and BLUP datasets (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The GIs ranged from 0.00 to 1.00, with standard deviations (SD) of 0.09\u0026ndash;0.25 and coefficients of variation (CV) of 10.47\u0026ndash;77.91%. Correlation analysis revealed highly significant correlations in GI among environments, with correlation coefficients ranging from 0.34 to 0.88 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The \u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e of GI was 0.61, indicating a substantial genetic contribution to variation in seed dormancy (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In addition, GI exhibited an approximately normal distribution in all environments, supporting that seed dormancy is a quantitative trait controlled by multiple genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGenome-wide identification of seed dormancy\u0026ndash;associated loci\u003c/h2\u003e \u003cp\u003eGWAS was performed using the GI data from seven environments and BLUP values for the 245 wheat varieties, together with genotypic data from the Wheat 90K SNP array. In total, 70 significant MTAs for seed dormancy were detected (Table S3; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Based on the LD decay of the A, B, and D subgenomes (Pan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), these MTAs were grouped into 55 loci (Table S3). The loci were distributed on chromosomes 1A (7), 1B (1), 1D (4), 2B (12), 2D (2), 3A (3), 3B (2), 3D (3), 4B (3), 5A (4), 5B (2), 5D (1), 6B (1), 6D (1), 7A (2), 7B (5), and 7D (2), explaining 6.64\u0026ndash;13.90% of the phenotypic variation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong these loci, \u003cem\u003eQgi.245.ahau-2D.2\u003c/em\u003e was detected in five environments (HB21, HB22, JY21, BB22, and SZ22) and in the BLUP dataset, explaining 7.76-13.00% of the phenotypic variation. Notably, \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e was identified in four environments (HB21, HB22, JY21, and BB22) and in the BLUP dataset, explaining 9.09\u0026ndash;13.90% of the phenotypic variation. Compared with previously reported loci, \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e was therefore considered a novel major locus for seed dormancy. In addition, the known STS-Myb marker associated with seed color and dormancy, corresponding to \u003cem\u003eQgi.245.ahau-3D.3\u003c/em\u003e, showed significant association with GI in HF21 and BB22 and with the BLUP values, explaining 6.86\u0026ndash;8.16% of the phenotypic variation (Table S3).\u003c/p\u003e \u003cp\u003eTo further refine the target interval of the novel major locus \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, 17 CAPS markers were developed and integrated with the Wheat 90K SNP markers for re-GWAS. Sixteen of the 17 markers showed stable and significant association with seed dormancy across environments (Table S4; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). The candidate interval was thereby narrowed to a region from 133.59 to 145.81 Mb on chromosome 4B, further supporting the association of \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e with seed dormancy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eValidation of the novel seed dormancy locus\u003c/b\u003e \u003cb\u003eQgi.245.ahau-4B.3\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo validate the novel locus \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, an AA-RIL population derived from a cross between AN8455 (weak dormancy) and AN1124 (moderate dormancy) was used, based on the genotypic differences between the two parents at this locus. A high-density genetic map of the AA-RIL population was constructed using the 17 CAPS markers, the dormancy-related marker STS-Myb, and 3,431 SNPs from the Wheat 16K SNP array. The resulting genetic map spanned 5,449.32 cM, with the number of markers per chromosome ranging from 26 (2D) to 443 (3B). The A, B, and D subgenomes covered 2,168.96, 1,965.10, and 1,315.26 cM, respectively (Table S5).\u003c/p\u003e \u003cp\u003eQTL mapping identified eight loci significantly associated with seed dormancy on chromosomes 1A, 3A, 3D, 4A, 4B, 4D, 5B, and 7B, explaining 3.30-25.12% of phenotypic variation (Table S6). Among these, \u003cem\u003eQgi.AA.ahau-4B\u003c/em\u003e, located at 136.67\u0026ndash;138.30 Mb on chromosome 4B, was consistently detected in all three environments (HF23, HF24, and HB24), with LOD values ranging from 4.82 to 17.16 and explaining 9.61\u0026ndash;25.12% of the phenotypic variation. Importantly, \u003cem\u003eQgi.AA.ahau-4B\u003c/em\u003e co-localized with \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e identified in the association panel, indicating that they represent the same locus (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Accordingly, \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e was further delimited to a 1.63 Mb interval (136.67\u0026ndash;138.30 Mb) on chromosome 4B.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrediction of candidate genes underlying\u003c/b\u003e \u003cb\u003eQgi.245.ahau-4B.3\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWithin the 1.63 Mb interval of \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, five high-confidence genes were annotated in the IWGSC RefSeq v1.0 genome assembly (Table S7). To identify candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, the expression of these five genes was examined in seeds of the moderate dormancy variety AN1124 and the weak dormancy variety AN8455 after 1, 6, 9, 12, 24, and 36 h of imbibition (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), representing the dormancy release process. Among the five genes, the expression levels of \u003cem\u003eTraesCS4B02G118000\u003c/em\u003e and \u003cem\u003eTraesCS4B02G118200\u003c/em\u003e in AN1124 were consistently and significantly lower than that in AN8455 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Both \u003cem\u003eTraesCS4B02G118000\u003c/em\u003e and \u003cem\u003eTraesCS4B02G118200\u003c/em\u003e encode F-box proteins and were designated \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e, respectively. Given that F-box proteins play important roles in the regulation of seed dormancy in diverse plant species through crosstalk with phytohormone signaling pathways (Ariizumi et al., 2007; Ariizumi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Gong et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Varshney et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e were selected as candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSequence variation analysis of candidate genes\u003c/b\u003e \u003cb\u003eTaF-box-B1\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eTaF-box-B2\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate sequence variation in \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e between AN1124 and AN8455, the promoter and coding regions of both genes were cloned and compared. \u003cem\u003eTaF-box-B1\u003c/em\u003e is 1,323 bp in length and consists of a single exon encoding a 441 aa protein containing an F-box domain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Sequence alignment revealed six polymorphisms between AN1124 and AN8455, including three in the promoter region and three in the coding region (Table S8). Promoter analysis showed that the T/C polymorphism at -821 bp resulted in the presence of the CGTCA motif and TGACG motif in AN1124, the A/G polymorphism at -804 bp resulted in the presence of the ABRE and G-box in AN8455, whereas the G/C polymorphism at -1292 bp did not alter predicted \u003cem\u003ecis\u003c/em\u003e-elements. In the coding region, the A/delA polymorphism at +\u0026thinsp;65 bp caused a frameshift mutation, the A/G polymorphism at +\u0026thinsp;989 bp resulted in an amino acid substitution from glutamate (E) to glycine (G), and the C/T polymorphism at +\u0026thinsp;1091 bp caused a substitution from alanine (A) to valine (V) (Table S8; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eTaF-box-B2\u003c/em\u003e is 1,763 bp in length and also consists of a single exon encoding a 458 aa protein containing an F-box domain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Sequence alignment identified nine polymorphisms, including five in the promoter region, two in the 5\u0026rsquo; untranslated (UTR) region, and two in the coding region (Table S8). Promoter analysis indicated that only the T/C polymorphism at -1191 bp resulted in the presence of the A-box and CCGTCC motif in AN1124, whereas the remaining four promoter polymorphisms did not alter predicted \u003cem\u003ecis\u003c/em\u003e-elements. In the coding region, the A/G polymorphism at +\u0026thinsp;65 bp resulted in an amino acid substitution from lysine (K) to arginine (R), and the C/T polymorphism at +\u0026thinsp;1091 bp caused a substitution from methionine (M) to threonine (T) (Table S8; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cb\u003eHaplotype analysis and phenotypic effects of\u003c/b\u003e \u003cb\u003eTaF-box-B1\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eTaF-box-B2\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo further investigate natural variation in \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e among wheat accessions, sequence information covering the promoter region (1,500 bp upstream of the ATG start codon) and the coding region was extracted from the resequencing data of 145 wheat accessions (Hao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). After removing accessions with missing sequences, six and nine polymorphic sites were identified in \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e, respectively, consistent with the sequence variation detected above (Table S9). Haplotype analysis showed that each gene contained two haplotypes, designated \u003cem\u003eB1-Hap1\u003c/em\u003e and \u003cem\u003eB1-Hap2\u003c/em\u003e for \u003cem\u003eTaF-box-B1\u003c/em\u003e, and \u003cem\u003eB2-Hap1\u003c/em\u003e and \u003cem\u003eB2-Hap2\u003c/em\u003e for \u003cem\u003eTaF-box-B2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, C).\u003c/p\u003e \u003cp\u003eTo distinguish the haplotypes of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e, two CAPS markers (B1\u0026thinsp;+\u0026thinsp;65 and B2\u0026thinsp;+\u0026thinsp;65, respectively) were developed based on the A/del A frameshift polymorphism at +\u0026thinsp;65 bp in the coding region of \u003cem\u003eTaF-box-B1\u003c/em\u003e and the A/G missense polymorphism at +\u0026thinsp;65 bp in the coding region of \u003cem\u003eTaF-box-B2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). For \u003cem\u003eTaF-box-B1\u003c/em\u003e, the delA and A alleles corresponded to \u003cem\u003eB1-Hap1\u003c/em\u003e and \u003cem\u003eB1-Hap2\u003c/em\u003e, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). For \u003cem\u003eTaF-box-B2\u003c/em\u003e, the G and A alleles corresponded to \u003cem\u003eB2-Hap1\u003c/em\u003e and \u003cem\u003eB2-Hap2\u003c/em\u003e, respectively.\u003c/p\u003e \u003cp\u003eTo validate the association of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e with seed dormancy, 431 wheat varieties from different Chinese wheat-growing regions were genotyped using the B1\u0026thinsp;+\u0026thinsp;65 and B2\u0026thinsp;+\u0026thinsp;65 markers. After excluding accessions with missing data, the two markers showed complete linkage in the 431 varieties (Table S10). Accordingly, \u003cem\u003eB1-Hap1\u003c/em\u003e and \u003cem\u003eB2-Hap1\u003c/em\u003e were combined and defined as \u003cem\u003eTaF-box-Hap1\u003c/em\u003e, whereas \u003cem\u003eB1-Hap2\u003c/em\u003e and \u003cem\u003eB2-Hap2\u003c/em\u003e were combined and defined as \u003cem\u003eTaF-box-Hap2\u003c/em\u003e. The U-test results indicated a highly significant difference in GI between varieties carrying \u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Varieties carrying \u003cem\u003eTaF-box-Hap1\u003c/em\u003e exhibited significantly lower GI values (strong dormancy) than those carrying \u003cem\u003eTaF-box-Hap2\u003c/em\u003e (weak dormancy) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). These results indicate that \u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e represent the candidate haplotypes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e for seed dormancy.\u003c/p\u003e \u003cp\u003eIn addition, the effects of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e (strong dormancy) and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e (weak dormancy) on yield-related traits were evaluated in 431 wheat varieties. No significant differences were observed between the two haplotypes for thousand grain weight (TGW), number of grains per spike (NGPS), tiller number (TN), or plant height (PH) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-I). These results indicate that the favorable haplotype \u003cem\u003eTaF-box-Hap1\u003c/em\u003e associated with strong dormancy is a promising target for improving seed dormancy and PHS resistance in wheat.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGeographic distribution and breeding utilization of\u003c/b\u003e \u003cb\u003eTaF-box-4B-Hap1\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo further evaluate the potential application of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e in wheat breeding, its distribution frequency was analyzed in 108 landraces and 431 improved varieties collected from four major wheat-growing regions of China, including the Yellow and Huaihai River winter wheat region (HWW), the Middle and Lower Yangtze River winter wheat region (YRWW), the Southwest winter wheat region (SWW), and the Northern winter wheat region (NWW) (Tabel S10). The overall frequency of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e was 34.47% in improved varieties and 6.48% in landraces (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Among the four regions, \u003cem\u003eTaF-box-Hap1\u003c/em\u003e showed the highest frequency in YRWW (54.10%), followed by SWW (33.33%), HWW (25.79%), and NWW (18.18%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). These results indicate a clear regional bias in the distribution of \u003cem\u003eTaF-box-Hap1\u003c/em\u003e across Chinese wheat-growing areas and suggest that this haplotype has been preferentially selected in the YRWW, which is characterized by relatively high rainfall and humidity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith increasingly severe climate change and more frequent extreme weather events, PHS in wheat has become a global threat to food security (Zhang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Breeding wheat varieties with moderate seed dormancy is therefore a key strategy for mitigating this problem. The identification of seed dormancy-related genes and the development of functional markers will facilitate the genetic improvement of PHS resistance in wheat.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eComparison with previously reported seed dormancy and pre-harvest sprouting loci\u003c/h2\u003e \u003cp\u003eNumerous QTLs and genes associated with seed dormancy have previously been identified in wheat using diverse genetic populations. In the present study, 55 loci associated with seed dormancy were detected by GWAS. Comparative analysis showed that seven of these loci overlapped with previously reported QTLs or genes. For example, \u003cem\u003eQgi.245.ahau-2B.3\u003c/em\u003e (105.91-108.24 Mb) on chromosome 2B overlapped with \u003cem\u003eGCR-QTL7\u003c/em\u003e (102.36-118.23 Mb, which controls grain color and PHS in wheat (Zhou et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eQgi.245.ahau-2B.6\u003c/em\u003e (140.78-144.43 Mb) on chromosome 2B overlapped with \u003cem\u003eQSGR.sau-2B.1\u003c/em\u003e (137.86-158.38 Mb) controlling wheat PHS (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). \u003cem\u003eQgi.245.ahau-2D.2\u003c/em\u003e (approximately 650.32 Mb) on chromosome 2D overlapped with \u003cem\u003eQphs.ahau-2D.2\u003c/em\u003e (628.2-650.3 Mb) controlling wheat PHS (Zhu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). On chromosome 4B, \u003cem\u003eQgi.245.ahau-4B.1\u003c/em\u003e (approximately 31.71 Mb) and \u003cem\u003eQgi.245.ahau-4B.2\u003c/em\u003e (40.78\u0026ndash;40.87 Mb) overlapped with \u003cem\u003eQPhs.spa-4B\u003c/em\u003e (15.8\u0026ndash;98.7 Mb), which controls wheat PHS (Kumar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). \u003cem\u003eQgi.245.ahau-5A.1\u003c/em\u003e (approximately 3.40 Mb) on chromosome 5A overlapped with \u003cem\u003eQphs.ahau-5A\u003c/em\u003e (0.0-4.8 Mb) controlling wheat PHS (Zhu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition, \u003cem\u003eQgi.245.ahau-3D.3\u003c/em\u003e (570.80 Mb) on chromosome 3D was located close to \u003cem\u003eTaMYB10-3D\u003c/em\u003e (570.80 Mb), which is associated with seed color and dormancy (Lang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e (136.67\u0026ndash;138.30 Mb) on chromosome 4B was confirmed as a major locus through re-GWAS and linkage analysis. By comparison, although several loci related to seed dormancy and PHS resistance have previously been reported on chromosome 4B, including \u003cem\u003eQGI.nmbu-4BL\u003c/em\u003e (BA00631502, 409.74 Mb), \u003cem\u003eQGI.nmbu-4BS\u003c/em\u003e (wsnp_Ex_c13357_21054802, 11.35 Mb), \u003cem\u003eQGI.nmbu-4BL\u003c/em\u003e (wsnp_Ex_c4148_7495656, 657.1 Mb), gwm251 (568.6 Mb), wmc48 (98.7 Mb), and \u003cem\u003eQPhs.spa-4B\u003c/em\u003e (wmc617b-wmc48a, 15.8\u0026ndash;98.7 Mb) (Jaiswal et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Begum et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vahramians et al., 2024; Kumar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), none of these loci coincided with the physical interval of \u003cem\u003eQgi.245.ahau-4B.3.\u003c/em\u003e Therefore, we suggest that \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e is a novel locus related to seed dormancy. Subsequently, the novel locus \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e was further validated using the AA-RIL population derived from a cross between AN1124 and AN8455. In this population, another locus (\u003cem\u003eQgi.AA.ahau-3A\u003c/em\u003e) was detected on chromosome 3A at 0.00-711.26 Mb. Previous studies have reported that \u003cem\u003eTaMFT-3A\u003c/em\u003e and \u003cem\u003eTaMyb10-A\u003c/em\u003e on chromosome 3A are associated with seed dormancy. Therefore, the two parental lines were first genotyped using the SNP.646, MFT-222, MFT-A1, and MFT-A2 markers for \u003cem\u003eTaMFT-3A\u003c/em\u003e (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nakamura et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lei et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as well as the TaMyb10-A_In/Del marker for \u003cem\u003eTaMyb10-A\u003c/em\u003e (Lang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Only the TaMyb10-A_In/Del marker showed polymorphism between AN1124 and AN8455. Subsequently, all 179 lines of the AA-RIL population were genotyped using the TaMyb10-A_In/Del marker for re-mapping. Finally, \u003cem\u003eQgi.AA.ahau-3A\u003c/em\u003e was refined to the interval of 701.01-711.29 Mb, within which \u003cem\u003eTaMyb10-A\u003c/em\u003e (703.91 Mb) is located (Table S11). These results suggest that \u003cem\u003eTaMyb10-A\u003c/em\u003e is the most likely candidate gene underlying \u003cem\u003eQgi.AA.ahau-3A\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePotential roles of\u003c/b\u003e \u003cb\u003eTaF-box-B1\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eTaF-box-B2\u003c/b\u003e \u003cb\u003ein regulating seed dormancy\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePrevious studies have shown that F-box proteins play an important regulatory role in seed dormancy and germination, primarily through their involvement in phytohormone signaling pathways. In \u003cem\u003eA. thaliana\u003c/em\u003e, the F-box gene \u003cem\u003eSLEEPY1\u003c/em\u003e (\u003cem\u003eSLY1\u003c/em\u003e) acts as a positive regulator of the gibberellin (GA) signaling pathway. Upon GA binding to the GID1 receptor, the SCF-type E3 ubiquitin ligase complex containing SLY1 is activated, leading to the ubiquitination and subsequent degradation of DELLA proteins, which are key negative regulators of the GA signaling pathway, thereby promoting seed germination (Ariizumi et al., 2007, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Gong et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that the \u003cem\u003eF-Box\u003c/em\u003e/\u003cem\u003eDUF295 Brassiceae-specific 2\u003c/em\u003e (\u003cem\u003eFDB2\u003c/em\u003e) gene negatively regulates ABA-mediated inhibition of seed germination in \u003cem\u003eA. thaliana\u003c/em\u003e. Overexpression of \u003cem\u003eFDB2\u003c/em\u003e reduced seed sensitivity to ABA, whereas \u003cem\u003efdb2\u003c/em\u003e mutants exhibited hypersensitivity to ABA. Varshney et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) demonstrated that the F-box protein SKIP31 promotes the degradation of jasmonate ZIM-domain (JAZ) proteins through the ubiquitin-proteasome pathway. In wheat, TaJAZ1, which is most closely related to \u003cem\u003eA. thaliana\u003c/em\u003e JAZ3, negatively regulates ABA-inhibited seed germination by interacting with TaABI5 (ABA insensitive 5), a key positive transcript factor in the ABA signaling pathway (Ju et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus SKIP31-mediated JAZ degradation activates downstream ABA signaling and is critical for balancing seed dormancy and germination. In rice, the F-box protein OsFbx352 influences ABA homeostasis by downregulating ABA biosynthesis genes and upregulating ABA catabolism genes, thereby reducing ABA levels in seeds and affecting dormancy (Song et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the present study, by integrating association mapping, linkage mapping, expression profiling, sequence variation, and haplotype analysis, we identified \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e, both encoding F-box proteins, as candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e. However, their regulatory mechanisms in wheat seed dormancy remain largely unknown and warrant further investigation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBreeding potential of\u003c/b\u003e \u003cb\u003eTaF-box-B1\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eTaF-box-B2\u003c/b\u003e \u003cb\u003efor improving PHS resistance\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSeed dormancy is a complex trait controlled by multiple genes, and pyramiding favorable alleles is an effective strategy for enhancing seed dormancy and PHS resistance in wheat. In this study, two gene-specific CAPS markers (B1\u0026thinsp;+\u0026thinsp;65 and B2\u0026thinsp;+\u0026thinsp;65) were developed for \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e, respectively. Notably, B1\u0026thinsp;+\u0026thinsp;65 and B2\u0026thinsp;+\u0026thinsp;65 were completely linked and defined two haplotypes (\u003cem\u003eTaF-box-Hap1\u003c/em\u003e and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e), of which \u003cem\u003eTaF-box-Hap1\u003c/em\u003e was significantly associated with stronger seed dormancy. Importantly, the favorable haplotype \u003cem\u003eTaF-box-Hap1\u003c/em\u003e showed no negative effects on yield-related traits. Therefore, \u003cem\u003eTaF-box-Hap1\u003c/em\u003e represents a promising target for the genetic improvement of PHS resistance in wheat. In addition, the favorable haplotype \u003cem\u003eTaF-box-Hap1\u003c/em\u003e occurred at a higher frequency in southern than in northern wheat-growing regions, where rainfall and humidity are typically higher.\u003c/p\u003e \u003cp\u003eIn summary, by integrating association mapping, linkage mapping, expression profiling, sequence variation, and haplotype analysis, we identified a novel major locus (\u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e) and its candidate genes (\u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e) controlling seed dormancy. We further identified a favorable haplotype (\u003cem\u003eTaF-box-Hap1\u003c/em\u003e) associated with strong dormancy but not affecting yield-related traits, and demonstrated its practical value for wheat breeding. These findings contribute to a better understanding of the genetic basis of seed dormancy and provide valuable gene resources and molecular markers for improving PHS resistance in wheat.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAuthor contribution statement\u003c/b\u003e HPZ, CC, and CXM initiated the project, designed the study, and revised the paper; YXL, YYZ, and WBL completed the experiment, and prepared the manuscript; XP, WG, LTZ, HFW, ZYY, RHW, TFS, BBT, JJC, and JL assisted in the cultivation, management, and phenotyping of experimental materials. All authors read the manuscript and approved it for publication.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution statement\u003c/strong\u003e HPZ, CC, and CXM initiated the project, designed the study, and revised the paper; YXL, YYZ, and WBL completed the experiment, and prepared the manuscript; XP, WG, LTZ, HFW, ZYY, RHW, TFS, BBT, JJC, and JL assisted in the cultivation, management, and phenotyping of experimental materials. All authors read the manuscript and approved it for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This work was supported by the Innovation Project of Bio-breeding Laboratory of Anhui Province (No.2025SWYZ0330), the National Natural Science Foundation of China (32572414; 32372069), the Agriculture Research System of Anhui Province (AHCYTX-02), and Jiangsu Collaborative Innovation Center for Modern Crop Production (JCIC-MCP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare that they have no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAriizumi T, Lawrence PK, Steber CM (2011) The role of two F-box proteins, SLEEPY1 and SNEEZY, in \u003cem\u003eArabidopsis\u003c/em\u003e gibberellin signaling. 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Theor Appl Genet 132(11): 2947-2963.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8857089/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8857089/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eModerate seed dormancy is essential for reducing pre-harvest sprouting (PHS) and ensuring uniform germination in cereal crops. In this study, seed dormancy was evaluated in 245 wheat varieties with diverse genetic backgrounds across seven environments, and genotypes were obtained using the Wheat 90K SNP array. Genome-wide association analysis identified 55 loci associated with seed dormancy, including a novel major locus, \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003e, on chromosome 4B. By integrating molecular marker development, re-GWAS, linkage mapping, and expression analysis, this locus was validated and two candidate genes underlying \u003cem\u003eQgi.245.ahau-4B.3\u003c/em\u003ewere identified: \u003cem\u003eTraesCS4B02G118000\u003c/em\u003e (\u003cem\u003eTaF-box-B1\u003c/em\u003e) and \u003cem\u003eTraesCS4B02G118200 \u003c/em\u003e(\u003cem\u003eTaF-box-B2\u003c/em\u003e), both encoding F-box proteins. The expression levels of \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003e were significantly lower in the moderate dormancy wheat variety Annong 1124 (AN1124) than in weak dormancy variety Annong 8455 (AN8455). Sequence and haplotype analyses showed that variations in \u003cem\u003eTaF-box-B1\u003c/em\u003e and \u003cem\u003eTaF-box-B2\u003c/em\u003ewere completely linked, forming two haplotypes: \u003cem\u003eTaF-box-Hap1\u003c/em\u003e for strong dormancy and \u003cem\u003eTaF-box-Hap2\u003c/em\u003e for weak dormancy. Frequency analysis further revealed that the favorable haplotype \u003cem\u003eTaF-box-Hap1\u003c/em\u003e was predominantly distributed in the Middle and Lower Yangtze River winter wheat region, characterized by relatively high rainfall and humidity. These findings establish a robust foundation for molecular marker-assisted breeding of wheat varieties with enhanced climate resilience and stable PHS resistance, thereby contributing substantively to global food security.\u003c/p\u003e","manuscriptTitle":"Identification of a novel major QTL and F-box candidate genes controlling seed dormancy in common wheat","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 17:52:20","doi":"10.21203/rs.3.rs-8857089/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-17T22:51:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-17T02:35:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T01:56:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199972839543751353037470885792409481474","date":"2026-03-17T09:09:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259545525774576903945237525438310330657","date":"2026-03-09T02:45:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T13:18:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T22:58:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-15T05:17:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Theoretical and Applied Genetics","date":"2026-02-12T03:26:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fca595c6-87bb-498d-9401-8c5c257f9fee","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T08:39:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 17:52:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8857089","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8857089","identity":"rs-8857089","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}