Genome-Wide Association Study to Identify Bakanae Disease Resistance- Related QTLs Carrying Novel Candidate Genes in Rice (Oryza sativa L.)

Genome-Wide Association Study to Identify Bakanae Disease Resistance- Related QTLs Carrying Novel Candidate Genes in Rice (Oryza sativa L.) | 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 Genome-Wide Association Study to Identify Bakanae Disease Resistance- Related QTLs Carrying Novel Candidate Genes in Rice (Oryza sativa L.) Yuting Zeng, Fang-Yuan Cao, Ah-Rim Lee, Dongryung Lee, Backki Kim, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6309254/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 Bakanae disease is a rice disease whose importance is increasing considerably in several rice-growing countries, leading to incremental production losses. In this study, qBK9 was identified via GWASs based on 169 Korean landrace accessions. Furthermore, 5 genes in the qBK9 region were identified as potential candidates, which demonstrated notable expression differences between resistant and susceptible accessions. Finally, OsUBC18 encoded a ubiquitin-conjugating enzyme significantly downregulated in the resistant rice cultivars. Os UBC18 T-DNA insertion mutants presented significantly reduced bakanae resistance. A single nucleotide polymorphism (SNP) in the promoter region of OsUBC18 is responsible for its differential expression, leading to alterations in rice bakanae resistance. Moreover, genes associated with the gibberellin (GA) pathway, which plays a role in bakanae disease, were down-regulated in OsUBC18 T-DNA mutant lines. These findings suggest that OsUBC18 is a gene associated with bakanae resistance, and its expression enhances rice immunity via reduced GA-related genes. Biological sciences/Genetics/Agricultural genetics Biological sciences/Plant sciences/Plant breeding Biological sciences/Plant sciences/Plant genetics rice bakanae disease genome-wide association study (GWAS) gibberellin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Background Bakanae disease, caused by Fusarium fujikuroi , has become a major global concern in Asia, Africa as well as in North America and Italy [ 1 , 2 ], resulting in high (3.0-95.4%) yield losses [ 3 , 4 ]. Bakanae disease, also called foolish seedling, is attributed to the production of gibberellic acid(GA) which infected seedlings with yellow and abnormal elongation [ 5 ]. The disease impacts rice plants from the germination to the mature stage, resulting in severe seed infections[ 6 ]. The most common management practices for bakanae disease include seed treatment with hot water or fungicides [ 3 , 7 ]. However, the hot water immersion method for seed disinfection is ineffective for severely infected rice seeds, because hot water cannot reach the rice seed pericarp [ 8 ]. Additionally, fungicide application cannot fully control fungal spores, and fungicide-resistant strains of bakanae have been reported [ 1 , 9 ]. Therefore, cultivating resistant rice varieties presents a more economical and environmentally friendly way to control this disease. Several quantitative trait loci (QTLs) associated with bakanae disease have been identified on chromosomes 1 ( qB1, qBK1 [ 10 ], qBK1.1 , qBK1.2, qBK1.3 [ 11 ], qFfR1 [ 12 ], qBK1 WD [ 13 ], qBK1 (z) [ 14 ]), 2 ( qBK2.1 ) [ 15 ], 3 ( qBK3.1 ), 4 (qBK4 T ) [ 16 ], 6 ( qFfR6 ) [ 12 ], 9 ( qFfR9 ) [ 17 ] and 10 ( qB10 ) with the help of biparental mapping population. In recent years, genome-wide association studies (GWASs) have emerged as a more efficient alternative for identifying loci and candidate genes, offering faster results than previous techniques. Volante et al. [ 18 ], reported two QTLs related to bakanae disease on chromosome 1 ( qBK1_628091 ) and chromosome 4 ( qBK4_31750955 ) via a GWAS approach. Ji et al. [ 19 ] revealed that typical leucine repeat‒receptor-like protein (LRR‒RLP) family proteins located in the candidate region are related to increased resistance to bakanae disease. Cheng et al. [ 20 ] identified one differentially expressed gene involved in the jasmonic acid signaling pathway through the transcriptome of bakanae -resistant and bakanae -susceptible varieties. Additionally, qRT-PCR analysis revealed that the expression of jasmonate ZIM domain genes was repressed after bakanae treatment. Song et al. [ 21 ] revealed that expression of the WRKY transcription factor gene OsWRKY114 enhances bakanae resistance, and the transcript expression levels of gibberellin and jasmonic acid-related genes required for plant susceptibility to bakanae were increased in OsWRKY114 -overexpressing rice plants. The objective of the present study was to apply GWAS analysis to identify QTLs or genes related to bakanae resistance in rice via 169 Korean landrace accessions. This study aimed to improve rice breeding programs by analyzing bakanae resistance in Korean landrace rice. Material and methods Plant materials and genotyping In this study, 169 Korean landrace accessions were used to evaluate bakanae resistance at the seedling stage. Seeds from all the accessions were acquired from the Rural Development Administration (RDA) GenBank, Jeonju, Republic of Korea ( http://genebank.rda.go.kr ) (Table S1 ). Shingwang and Ilpum were used as resistant and susceptible controls, respectively. The resistance of “Shingwang” and “Ilpum” to bakanae differed [ 22 ]. The isolate used for inoculation, CF283, has been reported to be tolerant to tebuconazole and benomyl treatment [ 23 ]. Phenotyping for bakanae resistance This study was performed according to the methods of Kim et al. [ 24 ] and Hur et al. [ 22 ] For inoculation, the Fusarium fujikuroi CF283 was cultured in potato dextrose broth (PDB) and diluted with water to a concentration of 1×10 6 spores/mL. Thirty seeds per accession were subsequently placed in separate tissue embedding cassettes and soaked in the pathogen mixture for 3 days in the dark at 26°C. After inoculation, the seeds were sown in seedling boxes and grown in a greenhouse for 3 weeks to identify their phenotype(28 ± 3℃day, 28 ± 3℃night, 12h light). The phenotype was estimated based on the methods of Kim et al. [ 24 ], Hur et al. [ 22 ] and Kwon et al. [ 25 ]. Yellowish-green, thin, dwarfing, abnormal root development, and elongated seedlings and those that were stunted or dead were classified as bakanae -specific phenotypes. Plants with the same phenotype as untreated plants, that is, slightly elongated seedlings that then grew without any thinness and yellowish coloring were regarded as healthy plants [ 24 ]. The response of each plant to the pathogen was evaluated by calculating the number of plants showing resistance in each line after the population’s viability was rated at 5 levels (1-resistant to 9-susceptible). In each population, plants whose symptoms of bakanae disease were difficult to identify were considered resistant (scores of 1 and 3), whereas plants whose symptoms were severe or irreversible and dead plants were classified as susceptible plants (score of 9). Moreover, the plants that presented the mildest symptoms were classified as moderately resistant plants (scores of 5 and 7). To minimize the potential for bias in subjective scoring, scoring was performed independently by one experienced researcher. Further, we transform the score number as numeric data to standardize the data for statistical analyses and comparisons. The resistance of each accession was calculated as (sum of individuals * resistance score; resistance 1, moderate 0.5, susceptible 0)/germinated individuals. The estimated proportion of healthy plants was converted to a percentage. Analysis of population structure Genotyping of the association panel was performed via a KNU Axiom Oryza 580K Genotyping Array and Affymetrix Power Tools, revealing 266,042 SNPs in the population, which were filtered so that SNPs with missing percentage 3% and a heterozygosis ratio < 5%[ 26 , 27 ]. The population structure analysis of the 169 accessions was performed via ADMIXTURE 1.3.0, with subgroups assigned according to the delta K value [ 28 ]. Principal component analysis (PCA) and plot visualization were performed via the prcomp R package [ 29 ]. A phylogenetic tree was constructed with phylip 3.698 ( https://phylipweb.github.io/phylip/ ) based on the genotypes of 169 rice accessions. Genome-wide association study (GWAS) analysis The Genome Association and Prediction Integrated Tool (GAPIT) was used to perform GWASs via the R package [ 30 ]. The general linear model (GLM), mixed linear model (MLM), compressed MLM (CMLM), and fixed and random model circulating probability unification (FarmCPU) were applied. The four models were chosen to ensure a comprehensive and robust GWAS analysis, leveraging their complementary strengths[ 30 ]. A genome-wide threshold was calculated via the formula “-log10(1/number of effective SNPs)” [ 31 ]. Identifying candidate genes for bakanae resistance GWAS analysis was used to identify candidate genes for bakanae resistance in rice. All significantly associated SNPs within the linkage disequilibrium (LD) decay distance were defined as one site, and the range of each LD decay upstream and downstream of the SNP was used to mine candidate genes. The LD decay rate of the population was measured as the chromosomal distance where the average r 2 decreased to half its maximum value [ 32 ]. For the expression patterns, the RNA-seq data of datasets with accession numbers SAMN13972374 to SAMN13972381 were obtained from the NCBI database ( https://www.ncbi.nlm.nih.gov/sra/ ) [ 33 ]. Zerawchanica karatals (ZK) was moderately susceptible, and Tainung 67 (TNG67) was moderately resistant after F. fujikuroi inoculation. The reads were mapped to the rice reference genome sequence (IRGSP-1.0, http://rapdb.dna.arc.go.jp/download/irgsp1.html ) via the HISAT2 tool [ 34 ] (Table S2). Only reads with a perfect match or one mismatch were further analyzed. Gene expression levels were quantified as fragments per kilobase of transcript per million fragments mapped (FPKM) values via FeatureCounts [ 35 ]. We used a threshold of log2 fold-change > 1 to filter out genes with low expression changes, ensuring that the selected genes had biologically significant alterations in expression. Gene expression analysis Gene expression was detected in bakanae resistance accessions (“Hongdo (ja127, R1)” and “Agudicar (ja202, R2)) and bakanae susceptible accessions (“Qin (ja002, S1)” and “(ja220, S2)”) after bakanae inoculation 1, 2, and 3 weeks(wpi). The bakanae resistance scores of R1, R2, S1, and S2 were 92.6, 94.6, 3.6, and 0.0, respectively. Total RNA was extracted from the stem tissues via TRIzol™ Reagent (Thermo Fisher Scientific, Waltham, MA, USA). The cDNA libraries were then synthesized using SuperScript™ III Reverse Transcriptase (Thermo Fisher Scientific) from total RNA samples (2 µg per sample). The primer sets (Table S3) each candidate gene ( Os09g0293400 , Os09g0293900 , Os09g0294000 , Os09g0294300 and Os09g0295300 ) and the gibberellin (GA) signaling-related genes ( OsGID1 , OsXTH8 , GA20OX2 , and GA3ox1 ) were generated via Primer 3 (v. 0.4.0) ( https://bioinfo.ut.ee/primer3-0.4.0/ ). Relative transcript expression levels of candidate genes were calculated via the 2 −△△CT method. The expression data were obtained from three biological and three technical replicates per treatment, and relative transcript expression levels were calculated with the 2 −△△CT method. The rice OsActin was used as an endogenous reference gene. Natural allelic variations in candidate genes and haplotypes The haplotypes of the genes of interest were determined via a Korean landrace collection and the Molecular Breeding Knowledgebase (MBK) genotype database, which integrates information from 6345 rice germplasms [ 36 ]. The genotype of 169 landrace, which was removed from missing and heterozygote loci, was used as haplotype analysis in promoter and genomic regions. The gene structure was determined via the Gene Structure Display Server 2.0 ( http://gsds.gao-lab.org/ ). The level of genetic diversity (π) of 169 landraces was used to identify genomic regions affected by domestication with a 100-kb. T-DNA mutant information The T-DNA insertion mutant of OsUBC18 (PFG_5A-00147. L) with a “Dongjin” background from the Korean mutant population [ 37 ]. The vector of the T-DNA mutant was activated by tagging pGA2715. We obtained 2 homozygous mutant plants using the primers to verify (Supplemental Table S1 ) Results Phenotypic variation in Bakanae resistance After 3 weeks in the greenhouse, bakanae resistance at the seedling stage was evaluated phenotypically based on the standard evaluation system. Most of the accessions were classified as moderately resistant (48.5%), with 32.5% and 18.9% of the accessions classified as resistant and susceptible, respectively (Fig. 1 A). To obtain the phenotypes as numeric data, the estimated proportion of healthy plants was converted to a percentage. The average bakanae resistance score percentage of the 169 accessions was 46.23%. The accessions “Baek Cheon(ja038)”, “Sando(ja105)” and “Yonanco(ja220)” were the most susceptible, with a score of 0%, followed by “Godudo (ja181)”, with a score of 3.60%. The accessions “Hongdo(ja127)”, “Annamjo(ja253)” and “Gangweondo(ja177)” were the most resistant, with resistance score percentages greater than 92%. (Fig. 1 B) “Sando(ja105)” and “Yonanco(ja220)” were the most susceptible, with a score of 0%, followed by “Godudo (ja181)”, with a score of 3.60%. The accessions “Hongdo(ja127)”, “Annamjo(ja253)” and “Gangweondo(ja177)” were the most resistant, with resistance score percentages greater than 92%. (Fig. 1B) Analysis of the genetic diversity and population structure of 169 rice accessions The natural population contained 164 japonica and 5 indica accessions was used in this study. After the elimination of the monomorphic loci and loci with minor allele frequencies (MAFs) < 0.03, 74,111 SNPs were retained from a total of 266,042 SNPs for association analysis. The SNPs number of each chromosome was 2699 to 15515, in which the chromosome 1 had the highest SNPs and the chromosome 9 had the lowest SNPs. (Supplementary Fig. 2A). The structure output and the information taken from the literature were also compared with results from a principal component analysis (PCA) (Supplementary Fig. 2B). The first, second, and third components accounted for 78.59%, 10.99%, and 10.41% of the variation, respectively. Model-based analysis of the panel structure was performed with Admixture, and the cross-validation (CV) error score indicated that K = 3 was the most likely value (Supplementary Fig. 2C). At K = 3, 14.79% of the accessions were classified as admixed, whereas at higher K values, the percentage increased to over 44.68% (Supplementary Fig. 2D). The structure analysis at K = 3 identified a subpopulation with 63 accessions, a second group with 62 accessions, a third group with 19 accessions, and an admixture subpopulation with 25 accessions (Supplementary Fig. 2D). PCA1 separated the varieties into 3 subpopulations, mainly corresponding to subpopulations 1 and 2, as defined by the structure analysis at K = 3. Phylogenetic tree analysis revealed that these 169 rice accessions formed four clades, with Clade 1 containing 16 accessions, clade 2 containing 19 accessions, clade 3 containing 22 accessions, and Clade 4 containing 112 accessions (Fig. 2 A). Clades 1, 2, and 3 comprised Subgroup 2, whereas clade 4 contained mainly Subgroups 1 and 3 (Fig. 2 A). based on the results of the structural and phylogenetic analyses, we divided the 169 rice accessions into four groups (Fig. 2 A). The group1 mainly contained the varieties from Clade 1, Clade 2 and Clade 3, while the varieties from Clade 4 divided into group2, group3, and group4 (Fig. 2 A). We further analyzed the changes in the percentages of bakanae resistance scores in the different groups. Group 1 changed from 5.6 to 91.4, group 2 changed from 3.7 to 87.9, group 3 changed from 0 to 94.6, and group 4 changed from 0 to 92.6(Fig. 2 B). The average percentages of bakanae resistance in Group 1 to Group 4 were 46.3, 51.5, 47.0, and 37.98, respectively. Statistical analysis using ANOVA showed differences among the groups (p < 0.05). The mean bakanae resistance score percentage of group 4 was significantly lower than that of the other groups (Fig. 2 B). Loci associated with bakanae resistance according to GWAS To identify the genetic loci responsible for the variation in bakanae resistance in rice accessions, an association analysis was performed using the FarmCPU, CMLM, GLM, and MLM methods, with a significance threshold of –log 10 P ≥ 4.8(Table S3). Finally, we selected the QTLs that overlapped in all models (Fig. 3 ). For the FarmCPU model, we detected two loci located on chromosome 9 and 6. For the CMLM model, we only detected one loci located on chromosome 9. For the GLM model, we detected five loci that are very near located on chromosome 9. For the MLM model, we also detected one loci located on chromosome 9. One QTL ( qBK9 ) on chromosome 9 was identified in a Korean landrace accession under bakanae inoculation. The qBK9 showed an effect size of about 1.5 in association with resistance to bakanae . Twenty-five of the 169 accessions (14.79%) carried the resistance “C” allele at position 6,944,283 and presented an average bakanae resistance score of 72.30%. The accessions carrying the alternative “T” allele had an average bakanae resistance score of 41.71%. Identification of candidate genes colocalized with significant SNPs The LD decay of chromosome 9 across the 169 rice varieties was 280 kb (r 2 = 0.38) (Supplementary Fig. S3). Thus, the areas 280 kb upstream and downstream of the lead SNPs were considered candidate regions. Thus, we obtained 38 candidate genes corresponding to the identified QTLs for bakanae resistance via Ensemble Plants ( https://plants.ensembl.org/ ) (Table S5). Within this region, 13 associated SNPs were detected; however, all the SNPs were located in the intergenic regions between the 7 genes (Fig. 4 B). Using these significant SNPs, all the accessions were divided into eight haplotypes (Fig. 4 C). Most accessions (83) contained hap2. The accessions in group 1 and group 2 contained hap1 and hap2, whereas the group 3 and group 4 accessions contained hap3, hap4, and hap5, respectively. In combination with the bakanae resistance score percentage, the average score percentage in hap3 was significantly greater than that in the other haplotypes (Fig. 4 D). Identification of candidate genes with public RNA-seq data and qPCR To identify 38 candidate genes associated with bakanae resistance, we integrated public RNA-seq data with our qPCR analysis. We first examined the expression patterns via public RNA-seq data from bakanae -inoculated plants within the candidate region. We identified five genes ( OsUBC18(Os09g0293400) , Os09g0293900 , Os09g0294000 , Os09g0294300 , and Os09g0295300 ) expressed in both bakanae -susceptible and bakanae -resistant varieties (Supplementary Fig. 4). Among these genes, OsUBC18(Os09g0293400) and Os09g0295300 had downregulated in the bakanae -resistant variety but upregulated expression in the susceptible variety. For gene Os09g0293900, it was upregulated in both the resistant and susceptible varieties. Os09g0294000 and Os09g0294300 were both downregulated in the resistant and susceptible varieties. Os09g0295300 , which contains 384 codons and encodes an expressed protein, was predicted to encode a hypothetical protein whose function is unknown. We then analyzed the expression patterns of 7 genes that were near to significant SNP and 5 genes selected from public RNA-seq data by qPCR (Fig. 5 ). Among those genes, Os09g0293400(OsUBC18) was overlapped. Among the 7 genes related to significant SNP, the expression of two genes ( Os09g0292900 and Os09g0293400(OsUBC18)) was detected by qPCR. The expression of Os09g0292900 was similar in all the accessions at 2 wpi. The expression of Os09g0293400(OsUBC18) was downregulated in the resistant group but upregulated in the susceptible group at 1, 2, and 3 wpi (Fig. 5 D-F). For the 4 genes selected from RNA-seq data, all genes were detected expression patterns by qPCR. The expression of Os09g0293900 was upregulated at 1 wpi (Fig. 6 A) and downregulated at 2 wpi (Fig. 6 B) in both groups but upregulated in the resistant group and downregulated in the susceptible group at 3 wpi (Fig. 6 C). For the Os09g0294000 gene, the expression levels were low in all the varieties at 1 wpi except S2(Fig. 6 D). At 2 wpi, Os09g0294000 expression was significantly upregulated in S2 after bakanae inoculation (Fig. 6 E). At 3 wpi, expression was upregulated in all varieties (Fig. 6 F). Os09g0294300 expression was downregulated in the resistant group but upregulated only in S2 at 1 wpi (Fig. 6 G). At 2 wpi, Os09g0294300 expression was downregulated in R1 and S1(Fig. 6 H). At 3 wpi, Os09g0294300 expression was downregulated in R1 and S2 but upregulated in S1 (Fig. 6 I). Os09g0295300 expression was downregulated in the resistant group and upregulated in the susceptible group at 1 wpi (Fig. 6 J). At 2 and 3 wpi, it was downregulated in all the varieties (Fig. 6 K, L). Among those results, genes Os09g0293900 and Os09g0295300 show a similar expression pattern in the resistance group (R1, R2) or susceptible group (S1, S2). For gene Os09g0293900 , it was upregulated in the resistance group and downregulated in the susceptible group at 1 and 3 wpi. For gene Os09g0295300 , it was downregulated in the resistance group and downregulated in the susceptible group at 1 wpi OsUBC18 expression negatively regulates resistance to bakanae disease. To investigate whether OsUBC18 is involved in rice bakanae resistance, we obtained T-DNA insertion lines from the Salk Institute Genomic Analysis Laboratory (Fig. 7 A). The expression levels of OsUBC18 in the T-DNA mutants were lower than those in the wild type (Fig. 7 B). We then inoculated both mutant and wild-type “Dongjin”. Two days postinoculation, the plant root length of both the wild-type and mutant plants was significantly affected (Fig. 7 C, D), and the shoot length of the wild-type plants also significantly decreased (Fig. 7 E). After one week post-inoculation, the root length significantly decreased in both the wild-type and mutant plants (Fig. 7 G). The wild-type plant heights significantly decreased, whereas the heights of the two T-DNA mutants slightly decreased (Fig. 7 H). After three weeks, the bakanae resistance score percentage of the T-DNA mutant was significantly greater than that of the wild type (Fig. 7 I, J). The Dongjin, OsUBC18-1 , and OsUBC18-2 received resistance scores of 28.5%, 80%, and 80.7%, respectively. Notably, the root length and plant height of the T-DNA mutant and the two mutants decreased after bakanae inoculation (Fig. 7 K, L). Based on these observations, the T-DNA mutant line presented greater resistance to bakanae disease than did the wild type. Inhibited GA signaling observed in the T-DNA OsUBC18 mutant Gibberellin (GA) plays a central role in plant growth and development 23 . We found that the height of the T-DNA OsUBC18 mutant was significantly shorter than that of the wild-type plants (Fig. 8 ). Song et al. reported that the resistant gene OsWRKY114 represses GA signaling [ 37 ]. Based on this observation, we hypothesized that OsUBC18 expression may repress GA signaling. To test this hypothesis, we analyzed the expression pattern of OsGID1 , OsXTH8 , GA20 OX 2 , and GA3 OX 1 which were related to the GA pathway in the OsUBC18 T-DNA mutant lines (Fig. 8 ). The expression level of that gene in wild type were all lower than in the OsUBC18 T-DNA mutant lines. The downregulation of OsGID1 and OsXTH8 expression, which are GA receptor- and GA response-specific markers of GA signaling, respectively, suggests that OsUBC18 expression suppresses GA signaling in rice (Fig. 8 A, B). Furthermore, GA20 OX 2 and GA3 OX 1 are key enzymes that regulate GA biosynthesis. These results confirm our hypothesis that the bakanae resistance mutant line of OsUBC18 represses the GA pathway (Fig. 8 C, D). Natural allelic variations in OsUBC18 OsUBC18 encodes a conserved ~ 150-residue ubiquitin-conjugating domain. There are LTR, MYB, WRE3, CAT-box, Box4, CGTCA-motif, W box, TAT-box, CAAT-Box, and STRE binding motifs for transcription factors in the 2-kb OsUBC18 promoter region (Table 1 ). A comparison of the OsUBC18 promoter and genomic region from our landrace SNP genotype dataset revealed one SNP (snp_6945916) in the 2.0 kb region upstream of the translation start site, representing two haplotypes (landrace_hap1 and landrace_hap2) in OsUBC18 (Fig. 9 A). Notably, in combination with the bakanae resistance phenotype, landrace_hap2 was significantly more resistant to bakanae disease than landrace_hap1 was (Fig. 9 B). Then we compared the expression levels of two haplotypes (Fig. 9 C). The expression level of “C” haplotype (landrace_hap1) was higher than the “T” haplotype (landrace_hap2). Those indicate that the expression level of OsUBC18 may influenced by the snp_6945916 SNP in the promoter. Table 1 Cis element information for the OsUBC18 promoter region Name Sequence Start Position Annotation Reference LTR CCGAAA 364 Inducible expression by powdery mildew and brown spot [ 38 ] MYB TAACTG 581 plant growth and development, stress responses, hormone signal regulation, and pathogen defense in plants [ 39 ] WRE3 CCACCT 721 response to biotic stresses and, interact with WRKY transcription [ 40 ] CAT-box GCCACT 749 a handful of sugar-regulated genes such as sporamine and amylase genes in sweet potato and rice. [ 41 ] Box4 ATTAAT 914 light-responsive elements [ 42 ] CGTCA-motif CGTCA 1064 The cis-acting-regulatory element involved in the MeJA responsiveness [ 43 ] MYB CCGTTG 1083 combining with MYB transcription factors, Water response, Drought response, salt response [ 43 ] CAAT-box CAAAT 1156 Common cis-acting elements in promoter and enhancer regions [ 43 ] W box TTGACC 1166 Fungal elicitor, oomycetes, fungi, bacteria, positive regulators of senescence [ 44 ] [ 45 , 46 ] CAAT-box CAAT 1398 Common cis-acting elements in promoter and enhancer regions [ 43 ] CGTCA-motif CGTCA 1519 The cis-acting-regulatory element involved in the MeJA responsiveness [ 43 ] TATA-box ATATAA 1559 Core promoter/enhancer element [ 43 ] CAAT-box CCAAT 1718 Common cis-acting elements in promoter and enhancer regions [ 43 ] STRE AGGG 1814 stresses response [ 43 ] We then performed haplotype analysis using the promoter and genomic sequences of OsUBC18 from 5,459 rice accessions publicly available from the Molecular Breeding Knowledgebase (MBKbase). There were 90 SNPs and 4 indels, which consisted of 120 haplotypes. Regarding snp_6945916, we measured its frequency among 5,429 rice accessions and reported that 68.35% of the accessions carried the snp_6945916_C allele, whereas 31.65% of the accessions carried the snp_6945916_T allele. Most accessions belonging to the indica subpopulation carried the snp_6945916_T allele (65.98%), indicating that snp_6945916_T arose after differentiation of the indica subpopulation. Analysis of the dominant haplotypes (hap1-hap4) in OsUBC18 from the MBKbase genotype revealed that they are strongly associated with either japonica or indica accessions. For example, hap1 was present mainly in japonica (69.3% of temperate japonica, 13.8% of tropical japonica, and 6% of japonica). Furthermore, hap2, hap3, and hap4 were the major haplotypes of the indica accessions (89.9% of hap2 in indica; 91.1% of hap3 in indica; 91.0% of hap4 in indica) (Fig. 9 D). We further analyze the nucleotide diversity (π value) on chromosome 9 to study the genetic diversity of OsUBC18. The π value of chromosome 9 was 0.000055 which was higher than OsUBC18 (0.000038) These results illustrate the sequence of OsUBC18 in landrace populations was conserved (Fig. 9 E). Discussion In this study, we used F. fujimura grown on PDA as inoculum and tissue-embedding cassettes used as large-scale infection. This method provided the reproducible infection necessary to assay disease for large-scale screening and uniform disease development. However, harvesting bacterial culture from PDA is time-consuming. Based on this reason, we lack the experimental replicates in this study. Lee et al.[ 47 ] used F. fujimura grown on PDB and cultured for one week to save time in harvesting fungi. The concentration was adjusted to 1×10 6 spores/mL. We plan to include replicates in further studies to validate these findings. A genome-wide association study (GWAS) revealed the qBK9 QTL on chromosome 9, which is highly associated with the observed phenotypic variation in response to bakanae infection in 169 Korean landrace accessions. In addition to qBK9 , other QTLs have been identified on chromosomes 1, 3, 4, 9, and 10. qBK9 is close to qFfR9 , as reported by Kang et al. [ 17 ], who used F2 and F3 plants derived from crossing the bakanae -resistant Korean japonica rice variety “Samgwang” with the susceptible variety “Junam”. They reported a major QTL at 30.1 centimorgan (cM) on chromosome 9 with a logarithm of the odds score of 60.3. Previous studies have reported that landraces are defined as dynamic populations of cultivated plants with historical origins and distinct identities, lack formal crop improvement, and are often genetically diverse, locally adapted, and associated with traditional farming systems [ 48 ]. Lee et al. [ 49 ] showed that the Korean rice landrace has high genetic diversity compared with the Korean japonica cultivar and that this result highlights the potential value of landraces. It may be inferred that qBK9 is a new QTL related to bakanae resistance. The qBK9 locus associated with the 280 kb upstream and downstream regions included 38 genes. Within this region, thirteen associated SNPs were detected, all of which were located in intergenic regions close to genes such as Os09g0290900 , Os09g0291500 , Os09g0291700 , Os09g0292101 , Os09g0292400 , Os09g0292900 and Os09g0293400(OsUBC18) . A public RNA-seq dataset related to bakanae disease revealed another five genes ( Os09g0293400(OsUBC18) , Os09g0293900 , Os09g0294000 , Os09g0294300 , and Os09g0295300 ) were related to bakanae disease. Among those genes, Os09g0293400(OsUBC18) was not only related to significant SNP but also detected in RNA-seq data. Then we verified the gene expression pattern between bakanae resistance (R1, R2) and susceptible (S1, S2) groups after bakanae inoculation 1, 2, and 3 wpi by qPCR. As a result, Os09g0293900 and Os09g0295300 show a similar expression pattern in the resistance group (R1, R2) or susceptible group (S1, S2). For gene Os09g0293900 , it was upregulated in the resistance group and downregulated in the susceptible group at 1 and 3 wpi. For gene Os09g0295300 , it was downregulated in the resistance group and downregulated in the susceptible group at 1 wpi. For gene Os09g0293900 , also called OsFKBP53, it was encoding a member of the FK506-binding proteins (FKBP)-type immunophilin family protein. In rice, there are 29 FKBPs gene family members[ 50 ]. The FKBPs join the cyclophilins (CYPs) under the umbrella term ‘immunophilin’ due to their discovery as cellular receptors for immunosuppressant drug ligands FK506 and rapamycin[ 51 ]. Studies on maize, Chlamydomonas, and Arabidopsis showed that one of the FKBPs, FKBP12, plays a regulator of plant germination, development, and mRNA splicing[ 52 ]. However, no evidence related to rice diseases was found for gene Os09g0293900. OsUBC18 is predicted to be a member of the ubiquitin-conjugating enzyme-encoding gene family. In plants, ubiquitination plays an important role in response to biotic and abiotic stresses [ 53 ]. Liu et al. [ 54 ] reported that OsUBC26 is involved in the defense against blast ( Magnaporthe oryzae ). Liu et al. [ 55 ] revealed that OsUBC13-RNAi lines presented a significant increase in resistance to rice blast and rice bacterial blight ( Xanthomonas oryzae pv oryzae ). The gene function of Os09g0295300 was unknown. Based on the GWAS study, RNA-seq analysis, and expression pattern, we consider Os09g0293400 ( OsUBC18 ) to be a potential bakanae disease resistance-related gene at this locus. We found that the T-DNA mutation of OsUBC18 significantly increased bakanae resistance. Additionally, the GA signaling-related genes that will repress the GA pathway were downregulated after bakanae inoculated in the T-DNA mutant of OsUBC18. Bakanae disease of rice is because by the GAs produced by the fungus F. fujikuroi [ 56 ]. Kim et al. reported that GA3-treated and bakanae -affected seedlings showed similar phenotypes[ 24 ]. These findings potentially indicate that the T-DNA mutant of OsUBC18 improved innate immunity against bakanae via the inhibition of GA signaling. To further validate the involvement of GA signaling in the observed phenotypes, we aim to test GA levels and enzyme activity in T-DNA mutant of OsUBC18 as well as additional genetic backgrounds. Natural allelic variation in OsUBC18 revealed that an SNP (snp_6945916) in the promoter region is important for its expression at the transcript level and leads to bakanae resistance. The expression level of the “C” haplotype (landrace_hap1) was higher than the “T” haplotype (landrace_hap2) which has higher bakanae disease than landrace_hap1 (Fig. 9 B, C). Allele frequency among 5,429 rice accessions revealed that 68.35% of the accessions carried the snp_6945916_C allele, whereas 31.65% of the accessions carried the snp_6945916_T allele (Fig. 9 D). Nucleotide diversity (π value) on chromosome 9 the π value of OsUBC18 (0.000038) was lower than the average π value on chromosome 9 (0.000055). Those results illustrate the sequence of OsUBC18 in landrace populations was conserved and it was controlled by artificial selection. To clarify this, it might be necessary to further investigate the detailed genomic diversity among cultivated rice and wild rice. Conclusions In summary, through GWAS, we identified a novel bakanae resistance gene, OsUBC18 , which belongs to the ubiquitin-conjugating enzyme-encoding gene family. In this study, we performed a GWAS to quickly and accurately identify the bakanae resistance-related genes in rice. Declarations Ethics approval and consent to participate Not Applicable Consent for publication Not Applicable Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2024-00391988 ) and supported by the New Breeding Technologies Development Program ( No. RS-2024-00322502 ), Rural Development Administration, Korea. Authors' contributions Zeng Y: Data curation, Methodology, Investigation, Validation, Writing – original draft. 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Liu X, Song L, Zhang H, Lin Y, Shen X, Guo J, Su M, Shi G, Wang Z, Lu GD: Rice ubiquitin‐conjugating enzyme OsUBC26 is essential for immunity to the blast fungus Magnaporthe oryzae . Molecular Plant Pathology 2021, 22 (12):1613-1623. Liu J, Nie B, Yu B, Xu F, Zhang Q, Wang Y, Xu W: Rice ubiquitin‐conjugating enzyme OsUbc13 negatively regulates immunity against pathogens by enhancing the activity of OsSnRK1a . Plant Biotechnology Journal 2023, 21 (8):1590-1610. Hedden P: The current status of research on gibberellin biosynthesis . Plant and Cell Physiology 2020, 61 (11):1832-1849. Additional Declarations No competing interests reported. Supplementary Files supplementarymaterial.docx Supplementary information Supplementary Figure 1. Population structure analysis and phenotype distribution in different groups. (A) Phylogenetic tree of 169 rice accessions based on genotype. First circle: phylogenetic tree analysis results; different clades are indicated by different colors; second circle: structural analysis results; green yellow: subgroup 1; dark olive green: subgroup 2; Indian Red: subgroup 3; dark red: subgroup 4; third circle: group information based on structure and phylogenetic analysis; the triangle sign is indica. (B) Box plots of the percentages of bakanae resistance scores among the 169 accessions in the different groups. The different letters indicate significant differences according to one-way ANOVA followed by Tukey's test (P<0.05). Supplementary Figure 2. Expression analysis of candidate regions via public RNA-seq. Data. TNG67 is a bakanae -resistant variety, and ZK is a susceptible variety. Supplementary Table 1. Accession information used in this study Supplementary Table 2. Mapping results of RNA-seq reads of Zerawchanica karatals (ZK) and Tainung 67 (TNG67) under dH2O-treated or F. fujikuroi-inoculated conditions Supplementary Table 3 Primers used in this study Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 May, 2025 Reviews received at journal 12 May, 2025 Reviews received at journal 17 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 04 Apr, 2025 Editor assigned by journal 01 Apr, 2025 Submission checks completed at journal 31 Mar, 2025 First submitted to journal 26 Mar, 2025 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. 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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-6309254","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446830846,"identity":"d938d650-ddfa-4fa6-a0f1-8894b66cf402","order_by":0,"name":"Yuting Zeng","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Yuting","middleName":"","lastName":"Zeng","suffix":""},{"id":446830847,"identity":"36008818-98f5-442d-a511-c7f9fd20d414","order_by":1,"name":"Fang-Yuan Cao","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Fang-Yuan","middleName":"","lastName":"Cao","suffix":""},{"id":446830848,"identity":"029d9a59-f823-4de4-b40b-9026206fbd25","order_by":2,"name":"Ah-Rim Lee","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Ah-Rim","middleName":"","lastName":"Lee","suffix":""},{"id":446830850,"identity":"4de6c7ce-bad7-4a59-87bc-8f1043e02357","order_by":3,"name":"Dongryung Lee","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Dongryung","middleName":"","lastName":"Lee","suffix":""},{"id":446830851,"identity":"5dffe80d-5c68-4572-918a-b7dbe4bf1d8d","order_by":4,"name":"Backki Kim","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Backki","middleName":"","lastName":"Kim","suffix":""},{"id":446830853,"identity":"832d8868-acc9-44ca-8aaa-7ca2998d4d2c","order_by":5,"name":"Soon-Wook Kwon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFACNhBhg+BLEKkljXQth0nQIj8jLU3i447zeQbnDz97wFBjxyA5+wB+LQY30o5JzjxzuxjIMDdgOJbMIM2XQECLdHrbbd6224kbbjCYSTCwHWCQ4yHksNlgLecSN5w//k2C4R8RWhhupx0DajmQuOFAjpkEY9sBBmlCWgzuP0v/ObMtuVjyRk6ZRGJfMo9kDyGH9RwzNvjYZpfHd/74NokP3+zkJM4QchgUJMBIgj5B0zIKRsEoGAWjABsAAOKWQMfhCwGmAAAAAElFTkSuQmCC","orcid":"","institution":"Pusan National University","correspondingAuthor":true,"prefix":"","firstName":"Soon-Wook","middleName":"","lastName":"Kwon","suffix":""}],"badges":[],"createdAt":"2025-03-26 06:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6309254/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6309254/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81373262,"identity":"d52b04d5-73b2-46f8-bae8-e5f10e9c0ab4","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40568,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of \u003cem\u003ebakanae\u003c/em\u003e resistance in 169 rice accessions. (A) Frequency of \u003cem\u003ebakanae\u003c/em\u003e resistance scores. (B) Frequency of the \u003cem\u003ebakanae\u003c/em\u003e resistance score percentages. scores of 1 and 3: Resistant. Scores of 5 and 7: Moderately resistant. score 9: Susceptible\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/711f30ea4c109b8a4f1158ef.jpg"},{"id":81373263,"identity":"ffe4cf2c-a36f-4f52-ae6a-870a8060a7c3","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121044,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation structure analysis and phenotype distribution in different groups. (A) Phylogenetic tree of 169 rice accessions based on genotype.\u003c/p\u003e\n\u003cp\u003eFirst circle: phylogenetic tree analysis results; different clades are indicated by different colors;\u003c/p\u003e\n\u003cp\u003eSecond circle: structural analysis results; green yellow: subgroup 1; dark olive green: subgroup 2; Indian Red: subgroup 3; dark red: subgroup 4;\u003c/p\u003e\n\u003cp\u003eThird circle: group information based on structure and phylogenetic analysis; the triangle sign is indica.\u003c/p\u003e\n\u003cp\u003e(B) Box plots of the percentages of \u003cem\u003ebakanae\u003c/em\u003e resistance scores among the 169 accessions in the different groups. The different letters indicate significant differences according to one-way ANOVA followed by Tukey's test (P\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/aff97eb8db39cb9161f9d1f7.jpg"},{"id":81373264,"identity":"835cf90a-611c-45ce-84aa-893bdf0815d9","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":94507,"visible":true,"origin":"","legend":"\u003cp\u003eQTLs identified via GWASs related to bakanae disease in rice. (A) Manhattan plots and (B) quantile‒quantile (QQ) plots of bakanae resistance trait accessions generated via the GLM, MLM, CMLM and FarmCPU methods. The upper red line of the Manhattan plots indicates the threshold (-log(p)=4.8) for significant SNPs (FDR-unadjusted p value\u0026lt;0.0001). The red box means overlapped in all models.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/90d32ae773a8adbbe02718ff.jpg"},{"id":81373602,"identity":"216d4aa4-fdcd-46ec-a1bc-1c5bcb93fcd1","added_by":"auto","created_at":"2025-04-25 11:05:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":118559,"visible":true,"origin":"","legend":"\u003cp\u003eLD block of \u003cem\u003ebakanae\u003c/em\u003e resistance. (A) Manhattan plots. (B) LD block for \u003cem\u003eqBK9\u003c/em\u003e; the red line represents SNPs. (C) Haplotype analysis of the candidate region. (D) Box plots of \u003cem\u003ebakanae\u003c/em\u003e resistance score percentages among the different haplotypes.The upper red line of the Manhattan plots indicates the threshold (-log(p)=4) for significant SNPs.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/c537edeb89778b611b27fdcb.jpg"},{"id":81373267,"identity":"2053cde5-b5a7-43a1-a391-06f6ce71b2bc","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":101277,"visible":true,"origin":"","legend":"\u003cp\u003eExpression analysis of Os09g0292900 (A-C), Os09g0293400 (D-E) after 1, 2 or 3 weeks of \u003cem\u003ebakanae\u003c/em\u003e inoculation. *, p\u0026lt;0.05 **, p\u0026lt;0.01 (Student’s t-test) indicate significant differences.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/5412bed22eca566c00793ec7.jpg"},{"id":81373269,"identity":"5ab944ff-b607-4b7b-8a8d-f6779ba6eb6e","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":102787,"visible":true,"origin":"","legend":"\u003cp\u003eExpression analysis of \u003cem\u003eOs09g0293900\u003c/em\u003e (A-C), \u003cem\u003eOs09g0294000\u003c/em\u003e (D-F), \u003cem\u003eOs09g0294300\u003c/em\u003e (G-H) and \u003cem\u003eOs09g0295300\u003c/em\u003e (J-L) after 1, 2 or 3 weeks of\u003cem\u003e bakanae\u003c/em\u003e inoculation. *, p\u0026lt;0.05 **, p\u0026lt;0.01 (Student’s t test) indicate significant differences.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/c21a48cb0e96c850391cec82.jpg"},{"id":81374498,"identity":"1e6a2d70-f764-4583-a141-2020fa67bb6e","added_by":"auto","created_at":"2025-04-25 11:13:52","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":118653,"visible":true,"origin":"","legend":"\u003cp\u003eThe phenotypes of the \u003cem\u003eOsUBC18\u003c/em\u003e T-DNA mutant lines. (A) Schematic representation of the gene structure of \u003cem\u003eOsUBC18\u003c/em\u003e and the T-DNA insertion sites. (B) Relative expression of \u003cem\u003eOsUBC18\u003c/em\u003e in the wild type (Dongjin) and T-DNA mutants (OsUBC18-1, OsUBC18-2). (C-E) 2 days after \u003cem\u003ebakanae\u003c/em\u003e inoculation. Phenotype (C), root length (D) and plant shoot length (E). (F-H) 1 week after \u003cem\u003ebakanae\u003c/em\u003e inoculation. \u0026nbsp;Phenotype (F), root length (G) and plant height (H). (I-L) 3 weeks after \u003cem\u003ebakanae\u003c/em\u003e inoculation. Phenotype (I), \u003cem\u003ebakanae\u003c/em\u003e resistance score percentage (J), root length (K) and plant height (L). The different letters indicate significant differences according to one-way ANOVA followed by Tukey's test (P\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/f933cff69a7db8feb3fec437.jpg"},{"id":81373285,"identity":"d2a9cc3d-b9db-443b-8a54-c5091a89cc2c","added_by":"auto","created_at":"2025-04-25 10:57:53","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":47146,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eOsUBC18\u003c/em\u003eis involved in GA responses. Transcript expression levels of genes involved in GA signaling (A, B) and GA biosynthesis (C, D). *, p\u0026lt;0.05 **, p\u0026lt;0.01 (Student’s t test) indicate significant differences.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/4e62d9158eb0f434e69a608c.jpg"},{"id":81373275,"identity":"69ebb942-0807-4e06-91fa-6ca713b73fbc","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":176315,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype analysis and nucleotide diversity analysis of \u003cem\u003eOsUBC18\u003c/em\u003e. (A) Haplotype analysis of \u003cem\u003eOsUBC18\u003c/em\u003e in the Korean landrace and MBKBASE genotype databases. (B) \u003cem\u003eBakanae\u003c/em\u003e resistance score percentagesbetween different landrace haplotypes. (C) Relative expression of the effects of the SNP in the \u003cem\u003eOsUBC18\u003c/em\u003epromoter. The values are the means ± SDs, and the different letters indicate significant differences according to one-way ANOVA followed by Tukey's test (P\u0026lt;0.05). (D) Haplotype distribution of \u003cem\u003eOsUBC18\u003c/em\u003e in different subgroups in the MBKBASE genotype database. (E) Genetic diversity analysis of chromosome 9. The \u003cem\u003eOsUBC18\u003c/em\u003e gene is indicated by a red marker.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/eb2ee96345c99cbd421e2aa0.jpg"},{"id":81374866,"identity":"7c25018f-4c25-4718-a980-26f1ae48af89","added_by":"auto","created_at":"2025-04-25 11:21:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4269673,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/41b7227e-d6a7-4919-90fa-e0eee3bc8f6b.pdf"},{"id":81373279,"identity":"c2a156c1-d88e-4b98-b3c9-fc05418d0449","added_by":"auto","created_at":"2025-04-25 10:57:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":541749,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1. Population structure analysis and phenotype distribution in different groups. (A) Phylogenetic tree of 169 rice accessions based on genotype. First circle: phylogenetic tree analysis results; different clades are indicated by different colors; second circle: structural analysis results; green yellow: subgroup 1; dark olive green: subgroup 2; Indian Red: subgroup 3; dark red: subgroup 4; third circle: group information based on structure and phylogenetic analysis; the triangle sign is indica. (B) Box plots of the percentages of \u003cem\u003ebakanae\u003c/em\u003e resistance scores among the 169 accessions in the different groups. The different letters indicate significant differences according to one-way ANOVA followed by Tukey's test (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2. Expression analysis of candidate regions via public RNA-seq. Data. TNG67 is a \u003cem\u003ebakanae\u003c/em\u003e-resistant variety, and ZK is a susceptible variety.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e. Accession information used in this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e. Mapping results of RNA-seq reads of Zerawchanica karatals (ZK) and Tainung 67 (TNG67) under dH2O-treated or F. fujikuroi-inoculated conditions\u003c/p\u003e\n\u003cp\u003eSupplementary Table 3 Primers used in this study\u003c/p\u003e","description":"","filename":"supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6309254/v1/f31dea1f95b546c8b3c32a20.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genome-Wide Association Study to Identify Bakanae Disease Resistance- Related QTLs Carrying Novel Candidate Genes in Rice (Oryza sativa L.)","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cem\u003eBakanae\u003c/em\u003e disease, caused by \u003cem\u003eFusarium fujikuroi\u003c/em\u003e, has become a major global concern in Asia, Africa as well as in North America and Italy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], resulting in high (3.0-95.4%) yield losses [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. \u003cem\u003eBakanae\u003c/em\u003e disease, also called foolish seedling, is attributed to the production of gibberellic acid(GA) which infected seedlings with yellow and abnormal elongation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The disease impacts rice plants from the germination to the mature stage, resulting in severe seed infections[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The most common management practices for \u003cem\u003ebakanae\u003c/em\u003e disease include seed treatment with hot water or fungicides [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the hot water immersion method for seed disinfection is ineffective for severely infected rice seeds, because hot water cannot reach the rice seed pericarp [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, fungicide application cannot fully control fungal spores, and fungicide-resistant strains of \u003cem\u003ebakanae\u003c/em\u003e have been reported [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, cultivating resistant rice varieties presents a more economical and environmentally friendly way to control this disease.\u003c/p\u003e \u003cp\u003eSeveral quantitative trait loci (QTLs) associated with \u003cem\u003ebakanae\u003c/em\u003e disease have been identified on chromosomes 1 (\u003cem\u003eqB1, qBK1\u003c/em\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], \u003cem\u003eqBK1.1\u003c/em\u003e, \u003cem\u003eqBK1.2, qBK1.3\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], \u003cem\u003eqFfR1\u003c/em\u003e [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], \u003cem\u003eqBK1\u003c/em\u003e\u003csup\u003e\u003cem\u003eWD\u003c/em\u003e\u003c/sup\u003e [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], \u003cem\u003eqBK1\u003c/em\u003e\u003csup\u003e\u003cem\u003e(z)\u003c/em\u003e\u003c/sup\u003e [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]), 2 (\u003cem\u003eqBK2.1\u003c/em\u003e) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], 3 (\u003cem\u003eqBK3.1\u003c/em\u003e), 4 \u003cem\u003e(qBK4\u003c/em\u003e\u003csup\u003e\u003cem\u003eT\u003c/em\u003e\u003c/sup\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], 6 (\u003cem\u003eqFfR6\u003c/em\u003e) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], 9 (\u003cem\u003eqFfR9\u003c/em\u003e) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and 10 (\u003cem\u003eqB10\u003c/em\u003e) with the help of biparental mapping population. In recent years, genome-wide association studies (GWASs) have emerged as a more efficient alternative for identifying loci and candidate genes, offering faster results than previous techniques. Volante et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], reported two QTLs related to \u003cem\u003ebakanae\u003c/em\u003e disease on chromosome 1 (\u003cem\u003eqBK1_628091\u003c/em\u003e) and chromosome 4 (\u003cem\u003eqBK4_31750955\u003c/em\u003e) via a GWAS approach. Ji et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] revealed that typical leucine repeat‒receptor-like protein (LRR‒RLP) family proteins located in the candidate region are related to increased resistance to \u003cem\u003ebakanae\u003c/em\u003e disease. Cheng et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] identified one differentially expressed gene involved in the jasmonic acid signaling pathway through the transcriptome of \u003cem\u003ebakanae\u003c/em\u003e-resistant and \u003cem\u003ebakanae\u003c/em\u003e-susceptible varieties. Additionally, qRT-PCR analysis revealed that the expression of jasmonate ZIM domain genes was repressed after \u003cem\u003ebakanae\u003c/em\u003e treatment. Song et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] revealed that expression of the WRKY transcription factor gene \u003cem\u003eOsWRKY114\u003c/em\u003e enhances \u003cem\u003ebakanae\u003c/em\u003e resistance, and the transcript expression levels of gibberellin and jasmonic acid-related genes required for plant susceptibility to \u003cem\u003ebakanae\u003c/em\u003e were increased in \u003cem\u003eOsWRKY114\u003c/em\u003e-overexpressing rice plants.\u003c/p\u003e \u003cp\u003eThe objective of the present study was to apply GWAS analysis to identify QTLs or genes related to \u003cem\u003ebakanae\u003c/em\u003e resistance in rice via 169 Korean landrace accessions. This study aimed to improve rice breeding programs by analyzing \u003cem\u003ebakanae\u003c/em\u003e resistance in Korean landrace rice.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and genotyping\u003c/h2\u003e \u003cp\u003eIn this study, 169 Korean landrace accessions were used to evaluate \u003cem\u003ebakanae\u003c/em\u003e resistance at the seedling stage. Seeds from all the accessions were acquired from the Rural Development Administration (RDA) GenBank, Jeonju, Republic of Korea (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genebank.rda.go.kr\u003c/span\u003e\u003cspan address=\"http://genebank.rda.go.kr\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Shingwang and Ilpum were used as resistant and susceptible controls, respectively. The resistance of \u0026ldquo;Shingwang\u0026rdquo; and \u0026ldquo;Ilpum\u0026rdquo; to \u003cem\u003ebakanae\u003c/em\u003e differed [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The isolate used for inoculation, CF283, has been reported to be tolerant to tebuconazole and benomyl treatment [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePhenotyping for\u003c/b\u003e \u003cb\u003ebakanae\u003c/b\u003e \u003cb\u003eresistance\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study was performed according to the methods of Kim et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Hur et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] For inoculation, the \u003cem\u003eFusarium fujikuroi\u003c/em\u003e CF283 was cultured in potato dextrose broth (PDB) and diluted with water to a concentration of 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e spores/mL. Thirty seeds per accession were subsequently placed in separate tissue embedding cassettes and soaked in the pathogen mixture for 3 days in the dark at 26\u0026deg;C. After inoculation, the seeds were sown in seedling boxes and grown in a greenhouse for 3 weeks to identify their phenotype(28\u0026thinsp;\u0026plusmn;\u0026thinsp;3℃day, 28\u0026thinsp;\u0026plusmn;\u0026thinsp;3℃night, 12h light). The phenotype was estimated based on the methods of Kim et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], Hur et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Kwon et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Yellowish-green, thin, dwarfing, abnormal root development, and elongated seedlings and those that were stunted or dead were classified as \u003cem\u003ebakanae\u003c/em\u003e-specific phenotypes. Plants with the same phenotype as untreated plants, that is, slightly elongated seedlings that then grew without any thinness and yellowish coloring were regarded as healthy plants [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The response of each plant to the pathogen was evaluated by calculating the number of plants showing resistance in each line after the population\u0026rsquo;s viability was rated at 5 levels (1-resistant to 9-susceptible). In each population, plants whose symptoms of \u003cem\u003ebakanae\u003c/em\u003e disease were difficult to identify were considered resistant (scores of 1 and 3), whereas plants whose symptoms were severe or irreversible and dead plants were classified as susceptible plants (score of 9). Moreover, the plants that presented the mildest symptoms were classified as moderately resistant plants (scores of 5 and 7). To minimize the potential for bias in subjective scoring, scoring was performed independently by one experienced researcher. Further, we transform the score number as numeric data to standardize the data for statistical analyses and comparisons. The resistance of each accession was calculated as (sum of individuals * resistance score; resistance 1, moderate 0.5, susceptible 0)/germinated individuals. The estimated proportion of healthy plants was converted to a percentage.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of population structure\u003c/h3\u003e\n\u003cp\u003eGenotyping of the association panel was performed via a KNU Axiom Oryza 580K Genotyping Array and Affymetrix Power Tools, revealing 266,042 SNPs in the population, which were filtered so that SNPs with missing percentage\u0026thinsp;\u0026lt;\u0026thinsp;1%, a minor allele frequency (MAF)\u0026thinsp;\u0026gt;\u0026thinsp;3% and a heterozygosis ratio\u0026thinsp;\u0026lt;\u0026thinsp;5%[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The population structure analysis of the 169 accessions was performed via ADMIXTURE 1.3.0, with subgroups assigned according to the delta K value [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Principal component analysis (PCA) and plot visualization were performed via the prcomp R package [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A phylogenetic tree was constructed with phylip 3.698 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://phylipweb.github.io/phylip/\u003c/span\u003e\u003cspan address=\"https://phylipweb.github.io/phylip/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) based on the genotypes of 169 rice accessions.\u003c/p\u003e\n\u003ch3\u003eGenome-wide association study (GWAS) analysis\u003c/h3\u003e\n\u003cp\u003eThe Genome Association and Prediction Integrated Tool (GAPIT) was used to perform GWASs via the R package [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The general linear model (GLM), mixed linear model (MLM), compressed MLM (CMLM), and fixed and random model circulating probability unification (FarmCPU) were applied. The four models were chosen to ensure a comprehensive and robust GWAS analysis, leveraging their complementary strengths[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A genome-wide threshold was calculated via the formula \u0026ldquo;-log10(1/number of effective SNPs)\u0026rdquo; [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eIdentifying candidate genes for\u003c/b\u003e \u003cb\u003ebakanae\u003c/b\u003e \u003cb\u003eresistance\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGWAS analysis was used to identify candidate genes for \u003cem\u003ebakanae\u003c/em\u003e resistance in rice. All significantly associated SNPs within the linkage disequilibrium (LD) decay distance were defined as one site, and the range of each LD decay upstream and downstream of the SNP was used to mine candidate genes. The LD decay rate of the population was measured as the chromosomal distance where the average r\u003csup\u003e2\u003c/sup\u003e decreased to half its maximum value [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. For the expression patterns, the RNA-seq data of datasets with accession numbers SAMN13972374 to SAMN13972381 were obtained from the NCBI database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/sra/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/sra/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Zerawchanica karatals (ZK) was moderately susceptible, and Tainung 67 (TNG67) was moderately resistant after \u003cem\u003eF. fujikuroi\u003c/em\u003e inoculation. The reads were mapped to the rice reference genome sequence (IRGSP-1.0, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rapdb.dna.arc.go.jp/download/irgsp1.html\u003c/span\u003e\u003cspan address=\"http://rapdb.dna.arc.go.jp/download/irgsp1.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) via the HISAT2 tool [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] (Table S2). Only reads with a perfect match or one mismatch were further analyzed. Gene expression levels were quantified as fragments per kilobase of transcript per million fragments mapped (FPKM) values via FeatureCounts [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. We used a threshold of log2 fold-change\u0026thinsp;\u0026gt;\u0026thinsp;1 to filter out genes with low expression changes, ensuring that the selected genes had biologically significant alterations in expression.\u003c/p\u003e\n\u003ch3\u003eGene expression analysis\u003c/h3\u003e\n\u003cp\u003eGene expression was detected in \u003cem\u003ebakanae\u003c/em\u003e resistance accessions (\u0026ldquo;Hongdo (ja127, R1)\u0026rdquo; and \u0026ldquo;Agudicar (ja202, R2)) and \u003cem\u003ebakanae\u003c/em\u003e susceptible accessions (\u0026ldquo;Qin (ja002, S1)\u0026rdquo; and \u0026ldquo;(ja220, S2)\u0026rdquo;) after \u003cem\u003ebakanae\u003c/em\u003e inoculation 1, 2, and 3 weeks(wpi). The \u003cem\u003ebakanae\u003c/em\u003e resistance scores of R1, R2, S1, and S2 were 92.6, 94.6, 3.6, and 0.0, respectively. Total RNA was extracted from the stem tissues via TRIzol\u0026trade; Reagent (Thermo Fisher Scientific, Waltham, MA, USA).\u003c/p\u003e \u003cp\u003eThe cDNA libraries were then synthesized using SuperScript\u0026trade; III Reverse Transcriptase (Thermo Fisher Scientific) from total RNA samples (2 \u0026micro;g per sample). The primer sets (Table S3) each candidate gene (\u003cem\u003eOs09g0293400\u003c/em\u003e, \u003cem\u003eOs09g0293900\u003c/em\u003e, \u003cem\u003eOs09g0294000\u003c/em\u003e, \u003cem\u003eOs09g0294300\u003c/em\u003e and \u003cem\u003eOs09g0295300\u003c/em\u003e) and the gibberellin (GA) signaling-related genes (\u003cem\u003eOsGID1\u003c/em\u003e, \u003cem\u003eOsXTH8\u003c/em\u003e, \u003cem\u003eGA20OX2\u003c/em\u003e, and \u003cem\u003eGA3ox1\u003c/em\u003e) were generated via Primer 3 (v. 0.4.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfo.ut.ee/primer3-0.4.0/\u003c/span\u003e\u003cspan address=\"https://bioinfo.ut.ee/primer3-0.4.0/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Relative transcript expression levels of candidate genes were calculated via the 2\u003csup\u003e\u0026minus;△△CT\u003c/sup\u003e method. The expression data were obtained from three biological and three technical replicates per treatment, and relative transcript expression levels were calculated with the 2\u003csup\u003e\u0026minus;△△CT\u003c/sup\u003e method. The rice OsActin was used as an endogenous reference gene.\u003c/p\u003e\n\u003ch3\u003eNatural allelic variations in candidate genes and haplotypes\u003c/h3\u003e\n\u003cp\u003eThe haplotypes of the genes of interest were determined via a Korean landrace collection and the Molecular Breeding Knowledgebase (MBK) genotype database, which integrates information from 6345 rice germplasms [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The genotype of 169 landrace, which was removed from missing and heterozygote loci, was used as haplotype analysis in promoter and genomic regions. The gene structure was determined via the Gene Structure Display Server 2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gsds.gao-lab.org/\u003c/span\u003e\u003cspan address=\"http://gsds.gao-lab.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The level of genetic diversity (π) of 169 landraces was used to identify genomic regions affected by domestication with a 100-kb.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eT-DNA mutant information\u003c/h2\u003e \u003cp\u003eThe T-DNA insertion mutant of \u003cem\u003eOsUBC18\u003c/em\u003e (PFG_5A-00147. L) with a \u0026ldquo;Dongjin\u0026rdquo; background from the Korean mutant population [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The vector of the T-DNA mutant was activated by tagging pGA2715. We obtained 2 homozygous mutant plants using the primers to verify (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePhenotypic variation in\u003c/strong\u003e \u003cstrong\u003eBakanae\u003c/strong\u003e \u003cstrong\u003eresistance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter 3 weeks in the greenhouse, \u003cem\u003ebakanae\u003c/em\u003e resistance at the seedling stage was evaluated phenotypically based on the standard evaluation system. Most of the accessions were classified as moderately resistant (48.5%), with 32.5% and 18.9% of the accessions classified as resistant and susceptible, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). To obtain the phenotypes as numeric data, the estimated proportion of healthy plants was converted to a percentage. The average \u003cem\u003ebakanae\u003c/em\u003e resistance score percentage of the 169 accessions was 46.23%. The accessions \u0026ldquo;Baek Cheon(ja038)\u0026rdquo;, \u0026ldquo;Sando(ja105)\u0026rdquo; and \u0026ldquo;Yonanco(ja220)\u0026rdquo; were the most susceptible, with a score of 0%, followed by \u0026ldquo;Godudo (ja181)\u0026rdquo;, with a score of 3.60%. The accessions \u0026ldquo;Hongdo(ja127)\u0026rdquo;, \u0026ldquo;Annamjo(ja253)\u0026rdquo; and \u0026ldquo;Gangweondo(ja177)\u0026rdquo; were the most resistant, with resistance score percentages greater than 92%. (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB)\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;Sando(ja105)\u0026rdquo; and \u0026ldquo;Yonanco(ja220)\u0026rdquo; were the most susceptible, with a score of 0%, followed by \u0026ldquo;Godudo (ja181)\u0026rdquo;, with a score of 3.60%. The accessions \u0026ldquo;Hongdo(ja127)\u0026rdquo;, \u0026ldquo;Annamjo(ja253)\u0026rdquo; and \u0026ldquo;Gangweondo(ja177)\u0026rdquo; were the most resistant, with resistance score percentages greater than 92%. (Fig. 1B)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of the genetic diversity and population structure of 169 rice accessions\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003cp\u003eThe natural population contained 164 japonica and 5 indica accessions was used in this study. After the elimination of the monomorphic loci and loci with minor allele frequencies (MAFs)\u0026thinsp;\u0026lt;\u0026thinsp;0.03, 74,111 SNPs were retained from a total of 266,042 SNPs for association analysis. The SNPs number of each chromosome was 2699 to 15515, in which the chromosome 1 had the highest SNPs and the chromosome 9 had the lowest SNPs. (Supplementary Fig. 2A). The structure output and the information taken from the literature were also compared with results from a principal component analysis (PCA) (Supplementary Fig. 2B). The first, second, and third components accounted for 78.59%, 10.99%, and 10.41% of the variation, respectively. Model-based analysis of the panel structure was performed with Admixture, and the cross-validation (CV) error score indicated that K\u0026thinsp;=\u0026thinsp;3 was the most likely value (Supplementary Fig. 2C). At K\u0026thinsp;=\u0026thinsp;3, 14.79% of the accessions were classified as admixed, whereas at higher K values, the percentage increased to over 44.68% (Supplementary Fig. 2D). The structure analysis at K\u0026thinsp;=\u0026thinsp;3 identified a subpopulation with 63 accessions, a second group with 62 accessions, a third group with 19 accessions, and an admixture subpopulation with 25 accessions (Supplementary Fig. 2D). PCA1 separated the varieties into 3 subpopulations, mainly corresponding to subpopulations 1 and 2, as defined by the structure analysis at K\u0026thinsp;=\u0026thinsp;3. Phylogenetic tree analysis revealed that these 169 rice accessions formed four clades, with Clade 1 containing 16 accessions, clade 2 containing 19 accessions, clade 3 containing 22 accessions, and Clade 4 containing 112 accessions (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Clades 1, 2, and 3 comprised Subgroup 2, whereas clade 4 contained mainly Subgroups 1 and 3 (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). based on the results of the structural and phylogenetic analyses, we divided the 169 rice accessions into four groups (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). The group1 mainly contained the varieties from Clade 1, Clade 2 and Clade 3, while the varieties from Clade 4 divided into group2, group3, and group4 (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). We further analyzed the changes in the percentages of \u003cem\u003ebakanae\u003c/em\u003e resistance scores in the different groups. Group 1 changed from 5.6 to 91.4, group 2 changed from 3.7 to 87.9, group 3 changed from 0 to 94.6, and group 4 changed from 0 to 92.6(Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). The average percentages of \u003cem\u003ebakanae\u003c/em\u003e resistance in Group 1 to Group 4 were 46.3, 51.5, 47.0, and 37.98, respectively. Statistical analysis using ANOVA showed differences among the groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean \u003cem\u003ebakanae\u003c/em\u003e resistance score percentage of group 4 was significantly lower than that of the other groups (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLoci associated with\u003c/strong\u003e \u003cstrong\u003ebakanae\u003c/strong\u003e \u003cstrong\u003eresistance according to GWAS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTo identify the genetic loci responsible for the variation in \u003cem\u003ebakanae\u003c/em\u003e resistance in rice accessions, an association analysis was performed using the FarmCPU, CMLM, GLM, and MLM methods, with a significance threshold of \u0026ndash;log\u003csub\u003e10\u003c/sub\u003eP\u0026thinsp;\u0026ge;\u0026thinsp;4.8(Table S3). Finally, we selected the QTLs that overlapped in all models (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). For the FarmCPU model, we detected two loci located on chromosome 9 and 6. For the CMLM model, we only detected one loci located on chromosome 9. For the GLM model, we detected five loci that are very near located on chromosome 9. For the MLM model, we also detected one loci located on chromosome 9. One QTL (\u003cem\u003eqBK9\u003c/em\u003e) on chromosome 9 was identified in a Korean landrace accession under \u003cem\u003ebakanae\u003c/em\u003e inoculation. The \u003cem\u003eqBK9\u003c/em\u003e showed an effect size of about 1.5 in association with resistance to \u003cem\u003ebakanae\u003c/em\u003e. Twenty-five of the 169 accessions (14.79%) carried the resistance \u0026ldquo;C\u0026rdquo; allele at position 6,944,283 and presented an average \u003cem\u003ebakanae\u003c/em\u003e resistance score of 72.30%. The accessions carrying the alternative \u0026ldquo;T\u0026rdquo; allele had an average \u003cem\u003ebakanae\u003c/em\u003e resistance score of 41.71%.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eIdentification of candidate genes colocalized with significant SNPs\u003c/h2\u003e\n \u003cp\u003eThe LD decay of chromosome 9 across the 169 rice varieties was 280 kb (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.38) (Supplementary Fig. S3). Thus, the areas 280 kb upstream and downstream of the lead SNPs were considered candidate regions. Thus, we obtained 38 candidate genes corresponding to the identified QTLs for \u003cem\u003ebakanae\u003c/em\u003e resistance via Ensemble Plants (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plants.ensembl.org/\u003c/span\u003e\u003c/span\u003e) (Table S5). Within this region, 13 associated SNPs were detected; however, all the SNPs were located in the intergenic regions between the 7 genes (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB). Using these significant SNPs, all the accessions were divided into eight haplotypes (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). Most accessions (83) contained hap2. The accessions in group 1 and group 2 contained hap1 and hap2, whereas the group 3 and group 4 accessions contained hap3, hap4, and hap5, respectively. In combination with the \u003cem\u003ebakanae\u003c/em\u003e resistance score percentage, the average score percentage in hap3 was significantly greater than that in the other haplotypes (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eIdentification of candidate genes with public RNA-seq data and qPCR\u003c/h2\u003e\n \u003cp\u003eTo identify 38 candidate genes associated with \u003cem\u003ebakanae\u003c/em\u003e resistance, we integrated public RNA-seq data with our qPCR analysis. We first examined the expression patterns via public RNA-seq data from \u003cem\u003ebakanae\u003c/em\u003e-inoculated plants within the candidate region. We identified five genes (\u003cem\u003eOsUBC18(Os09g0293400)\u003c/em\u003e, \u003cem\u003eOs09g0293900\u003c/em\u003e, \u003cem\u003eOs09g0294000\u003c/em\u003e, \u003cem\u003eOs09g0294300\u003c/em\u003e, and \u003cem\u003eOs09g0295300\u003c/em\u003e) expressed in both \u003cem\u003ebakanae\u003c/em\u003e-susceptible and \u003cem\u003ebakanae\u003c/em\u003e-resistant varieties (Supplementary Fig. 4). Among these genes, \u003cem\u003eOsUBC18(Os09g0293400)\u003c/em\u003e and \u003cem\u003eOs09g0295300\u003c/em\u003e had downregulated in the \u003cem\u003ebakanae\u003c/em\u003e-resistant variety but upregulated expression in the susceptible variety. For gene \u003cem\u003eOs09g0293900, it was upregulated\u003c/em\u003e in both the resistant and susceptible varieties. \u003cem\u003eOs09g0294000\u003c/em\u003e and \u003cem\u003eOs09g0294300\u003c/em\u003e were both downregulated in the resistant and susceptible varieties. \u003cem\u003eOs09g0295300\u003c/em\u003e, which contains 384 codons and encodes an expressed protein, was predicted to encode a hypothetical protein whose function is unknown.\u003c/p\u003e\n \u003cp\u003eWe then analyzed the expression patterns of 7 genes that were near to significant SNP and 5 genes selected from public RNA-seq data by qPCR (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Among those genes, \u003cem\u003eOs09g0293400(OsUBC18)\u003c/em\u003e was overlapped.\u003c/p\u003e\n \u003cp\u003eAmong the 7 genes related to significant SNP, the expression of two genes (\u003cem\u003eOs09g0292900\u003c/em\u003e and \u003cem\u003eOs09g0293400(OsUBC18))\u003c/em\u003e was detected by qPCR. The expression of \u003cem\u003eOs09g0292900\u003c/em\u003e was similar in all the accessions at 2 wpi. The expression of \u003cem\u003eOs09g0293400(OsUBC18)\u003c/em\u003e was downregulated in the resistant group but upregulated in the susceptible group at 1, 2, and 3 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eD-F).\u003c/p\u003e\n \u003cp\u003eFor the 4 genes selected from RNA-seq data, all genes were detected expression patterns by qPCR. The expression of \u003cem\u003eOs09g0293900\u003c/em\u003e was upregulated at 1 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA) and downregulated at 2 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB) in both groups but upregulated in the resistant group and downregulated in the susceptible group at 3 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC). For the \u003cem\u003eOs09g0294000\u003c/em\u003e gene, the expression levels were low in all the varieties at 1 wpi except S2(Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eD). At 2 wpi, \u003cem\u003eOs09g0294000\u003c/em\u003e expression was significantly upregulated in S2 after \u003cem\u003ebakanae\u003c/em\u003e inoculation (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eE). At 3 wpi, expression was upregulated in all varieties (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eF). \u003cem\u003eOs09g0294300\u003c/em\u003e expression was downregulated in the resistant group but upregulated only in S2 at 1 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eG). At 2 wpi, \u003cem\u003eOs09g0294300\u003c/em\u003e expression was downregulated in R1 and S1(Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eH). At 3 wpi, \u003cem\u003eOs09g0294300\u003c/em\u003e expression was downregulated in R1 and S2 but upregulated in S1 (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eI). \u003cem\u003eOs09g0295300\u003c/em\u003e expression was downregulated in the resistant group and upregulated in the susceptible group at 1 wpi (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eJ). At 2 and 3 wpi, it was downregulated in all the varieties (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eK, L). Among those results, genes \u003cem\u003eOs09g0293900\u003c/em\u003e and \u003cem\u003eOs09g0295300\u003c/em\u003e show a similar expression pattern in the resistance group (R1, R2) or susceptible group (S1, S2). For gene \u003cem\u003eOs09g0293900\u003c/em\u003e, it was upregulated in the resistance group and downregulated in the susceptible group at 1 and 3 wpi. For gene \u003cem\u003eOs09g0295300\u003c/em\u003e, it was downregulated in the resistance group and downregulated in the susceptible group at 1 wpi\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOsUBC18\u003c/strong\u003e \u003cstrong\u003eexpression negatively regulates resistance to bakanae disease.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTo investigate whether \u003cem\u003eOsUBC18\u003c/em\u003e is involved in rice \u003cem\u003ebakanae\u003c/em\u003e resistance, we obtained T-DNA insertion lines from the Salk Institute Genomic Analysis Laboratory (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA). The expression levels of \u003cem\u003eOsUBC18\u003c/em\u003e in the T-DNA mutants were lower than those in the wild type (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eB). We then inoculated both mutant and wild-type \u0026ldquo;Dongjin\u0026rdquo;. Two days postinoculation, the plant root length of both the wild-type and mutant plants was significantly affected (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eC, D), and the shoot length of the wild-type plants also significantly decreased (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eE). After one week post-inoculation, the root length significantly decreased in both the wild-type and mutant plants (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eG). The wild-type plant heights significantly decreased, whereas the heights of the two T-DNA mutants slightly decreased (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eH). After three weeks, the \u003cem\u003ebakanae\u003c/em\u003e resistance score percentage of the T-DNA mutant was significantly greater than that of the wild type (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eI, J). The Dongjin, \u003cem\u003eOsUBC18-1\u003c/em\u003e, and OsUBC18-2 received resistance scores of 28.5%, 80%, and 80.7%, respectively. Notably, the root length and plant height of the T-DNA mutant and the two mutants decreased after \u003cem\u003ebakanae\u003c/em\u003e inoculation (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eK, L). Based on these observations, the T-DNA mutant line presented greater resistance to \u003cem\u003ebakanae\u003c/em\u003e disease than did the wild type.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eInhibited GA signaling observed in the T-DNA OsUBC18 mutant\u003c/h2\u003e\n \u003cp\u003eGibberellin (GA) plays a central role in plant growth and development \u003csup\u003e23\u003c/sup\u003e. We found that the height of the T-DNA \u003cem\u003eOsUBC18\u003c/em\u003e mutant was significantly shorter than that of the wild-type plants (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). Song et al. reported that the resistant gene OsWRKY114 represses GA signaling [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. Based on this observation, we hypothesized that \u003cem\u003eOsUBC18\u003c/em\u003e expression may repress GA signaling. To test this hypothesis, we analyzed the expression pattern of \u003cem\u003eOsGID1\u003c/em\u003e, \u003cem\u003eOsXTH8\u003c/em\u003e, \u003cem\u003eGA20\u003c/em\u003e\u003csub\u003e\u003cem\u003eOX\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e2\u003c/em\u003e, and \u003cem\u003eGA3\u003c/em\u003e\u003csub\u003e\u003cem\u003eOX\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e1\u003c/em\u003e which were related to the GA pathway in the \u003cem\u003eOsUBC18\u003c/em\u003e T-DNA mutant lines (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). The expression level of that gene in wild type were all lower than in the \u003cem\u003eOsUBC18\u003c/em\u003e T-DNA mutant lines. The downregulation of \u003cem\u003eOsGID1\u003c/em\u003e and \u003cem\u003eOsXTH8\u003c/em\u003e expression, which are GA receptor- and GA response-specific markers of GA signaling, respectively, suggests that \u003cem\u003eOsUBC18\u003c/em\u003e expression suppresses GA signaling in rice (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA, B). Furthermore, \u003cem\u003eGA20\u003c/em\u003e\u003csub\u003e\u003cem\u003eOX\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e2\u003c/em\u003e and \u003cem\u003eGA3\u003c/em\u003e\u003csub\u003e\u003cem\u003eOX\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e1\u003c/em\u003e are key enzymes that regulate GA biosynthesis. These results confirm our hypothesis that the \u003cem\u003ebakanae\u003c/em\u003e resistance mutant line of \u003cem\u003eOsUBC18\u003c/em\u003e represses the GA pathway (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eC, D).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNatural allelic variations in\u003c/strong\u003e \u003cstrong\u003eOsUBC18\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOsUBC18\u003c/em\u003e encodes a conserved\u0026thinsp;~\u0026thinsp;150-residue ubiquitin-conjugating domain. There are LTR, MYB, WRE3, CAT-box, Box4, CGTCA-motif, W box, TAT-box, CAAT-Box, and STRE binding motifs for transcription factors in the 2-kb \u003cem\u003eOsUBC18\u003c/em\u003e promoter region (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). A comparison of the \u003cem\u003eOsUBC18\u003c/em\u003e promoter and genomic region from our landrace SNP genotype dataset revealed one SNP (snp_6945916) in the 2.0 kb region upstream of the translation start site, representing two haplotypes (landrace_hap1 and landrace_hap2) in \u003cem\u003eOsUBC18\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eA). Notably, in combination with the \u003cem\u003ebakanae\u003c/em\u003e resistance phenotype, landrace_hap2 was significantly more resistant to \u003cem\u003ebakanae\u003c/em\u003e disease than landrace_hap1 was (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eB). Then we compared the expression levels of two haplotypes (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eC). The expression level of \u0026ldquo;C\u0026rdquo; haplotype (landrace_hap1) was higher than the \u0026ldquo;T\u0026rdquo; haplotype (landrace_hap2). Those indicate that the expression level of \u003cem\u003eOsUBC18\u003c/em\u003e may influenced by the snp_6945916 SNP in the promoter.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCis element information for the OsUBC18 promoter region\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStart Position\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAnnotation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCGAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInducible expression by powdery mildew and brown spot\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMYB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTAACTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eplant growth and development, stress responses, hormone signal regulation, and pathogen defense in plants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWRE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCACCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eresponse to biotic stresses and, interact with WRKY transcription\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAT-box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGCCACT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ea handful of sugar-regulated genes such as sporamine and amylase genes in sweet potato and rice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBox4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATTAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elight-responsive elements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCGTCA-motif\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCGTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe cis-acting-regulatory element involved in the MeJA responsiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMYB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCGTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecombining with MYB transcription factors, Water response, Drought response, salt response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAT-box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommon cis-acting elements in promoter and enhancer regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eW box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTTGACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFungal elicitor, oomycetes, fungi, bacteria, positive regulators of senescence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAT-box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommon cis-acting elements in promoter and enhancer regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCGTCA-motif\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCGTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe cis-acting-regulatory element involved in the MeJA responsiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTATA-box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATATAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCore promoter/enhancer element\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAT-box\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommon cis-acting elements in promoter and enhancer regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003estresses response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eWe then performed haplotype analysis using the promoter and genomic sequences of \u003cem\u003eOsUBC18\u003c/em\u003e from 5,459 rice accessions publicly available from the Molecular Breeding Knowledgebase (MBKbase). There were 90 SNPs and 4 indels, which consisted of 120 haplotypes. Regarding snp_6945916, we measured its frequency among 5,429 rice accessions and reported that 68.35% of the accessions carried the snp_6945916_C allele, whereas 31.65% of the accessions carried the snp_6945916_T allele. Most accessions belonging to the indica subpopulation carried the snp_6945916_T allele (65.98%), indicating that snp_6945916_T arose after differentiation of the indica subpopulation.\u003c/p\u003e\n \u003cp\u003eAnalysis of the dominant haplotypes (hap1-hap4) in \u003cem\u003eOsUBC18\u003c/em\u003e from the MBKbase genotype revealed that they are strongly associated with either japonica or indica accessions. For example, hap1 was present mainly in japonica (69.3% of temperate japonica, 13.8% of tropical japonica, and 6% of japonica). Furthermore, hap2, hap3, and hap4 were the major haplotypes of the indica accessions (89.9% of hap2 in indica; 91.1% of hap3 in indica; 91.0% of hap4 in indica) (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eD).\u003c/p\u003e\n \u003cp\u003eWe further analyze the nucleotide diversity (\u0026pi; value) on chromosome 9 to study the genetic diversity of \u003cem\u003eOsUBC18.\u003c/em\u003e The \u0026pi; value of chromosome 9 was 0.000055 which was higher than \u003cem\u003eOsUBC18\u003c/em\u003e (0.000038) These results illustrate the sequence of \u003cem\u003eOsUBC18\u003c/em\u003e in landrace populations was conserved (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eE).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this study, we used F. \u003cem\u003efujimura\u003c/em\u003e grown on PDA as inoculum and tissue-embedding cassettes used as large-scale infection. This method provided the reproducible infection necessary to assay disease for large-scale screening and uniform disease development. However, harvesting bacterial culture from PDA is time-consuming. Based on this reason, we lack the experimental replicates in this study. Lee et al.[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] used F. \u003cem\u003efujimura\u003c/em\u003e grown on PDB and cultured for one week to save time in harvesting fungi. The concentration was adjusted to 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e spores/mL. We plan to include replicates in further studies to validate these findings.\u003c/p\u003e \u003cp\u003eA genome-wide association study (GWAS) revealed the \u003cem\u003eqBK9\u003c/em\u003e QTL on chromosome 9, which is highly associated with the observed phenotypic variation in response to \u003cem\u003ebakanae\u003c/em\u003e infection in 169 Korean landrace accessions. In addition to \u003cem\u003eqBK9\u003c/em\u003e, other QTLs have been identified on chromosomes 1, 3, 4, 9, and 10. \u003cem\u003eqBK9\u003c/em\u003e is close to \u003cem\u003eqFfR9\u003c/em\u003e, as reported by Kang et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who used F2 and F3 plants derived from crossing the \u003cem\u003ebakanae\u003c/em\u003e-resistant Korean japonica rice variety \u0026ldquo;Samgwang\u0026rdquo; with the susceptible variety \u0026ldquo;Junam\u0026rdquo;. They reported a major QTL at 30.1 centimorgan (cM) on chromosome 9 with a logarithm of the odds score of 60.3. Previous studies have reported that landraces are defined as dynamic populations of cultivated plants with historical origins and distinct identities, lack formal crop improvement, and are often genetically diverse, locally adapted, and associated with traditional farming systems [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Lee et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] showed that the Korean rice landrace has high genetic diversity compared with the Korean japonica cultivar and that this result highlights the potential value of landraces. It may be inferred that \u003cem\u003eqBK9\u003c/em\u003e is a new QTL related to \u003cem\u003ebakanae\u003c/em\u003e resistance.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eqBK9\u003c/em\u003e locus associated with the 280 kb upstream and downstream regions included 38 genes. Within this region, thirteen associated SNPs were detected, all of which were located in intergenic regions close to genes such as \u003cem\u003eOs09g0290900\u003c/em\u003e, \u003cem\u003eOs09g0291500\u003c/em\u003e, \u003cem\u003eOs09g0291700\u003c/em\u003e, \u003cem\u003eOs09g0292101\u003c/em\u003e, \u003cem\u003eOs09g0292400\u003c/em\u003e, \u003cem\u003eOs09g0292900\u003c/em\u003e and \u003cem\u003eOs09g0293400(OsUBC18)\u003c/em\u003e. A public RNA-seq dataset related to \u003cem\u003ebakanae\u003c/em\u003e disease revealed another five genes (\u003cem\u003eOs09g0293400(OsUBC18)\u003c/em\u003e, \u003cem\u003eOs09g0293900\u003c/em\u003e, \u003cem\u003eOs09g0294000\u003c/em\u003e, \u003cem\u003eOs09g0294300\u003c/em\u003e, and \u003cem\u003eOs09g0295300\u003c/em\u003e) were related to \u003cem\u003ebakanae\u003c/em\u003e disease. Among those genes, \u003cem\u003eOs09g0293400(OsUBC18)\u003c/em\u003e was not only related to significant SNP but also detected in RNA-seq data. Then we verified the gene expression pattern between bakanae resistance (R1, R2) and susceptible (S1, S2) groups after \u003cem\u003ebakanae\u003c/em\u003e inoculation 1, 2, and 3 wpi by qPCR. As a result, \u003cem\u003eOs09g0293900\u003c/em\u003e and \u003cem\u003eOs09g0295300\u003c/em\u003e show a similar expression pattern in the resistance group (R1, R2) or susceptible group (S1, S2). For gene \u003cem\u003eOs09g0293900\u003c/em\u003e, it was upregulated in the resistance group and downregulated in the susceptible group at 1 and 3 wpi. For gene \u003cem\u003eOs09g0295300\u003c/em\u003e, it was downregulated in the resistance group and downregulated in the susceptible group at 1 wpi. For gene \u003cem\u003eOs09g0293900\u003c/em\u003e, also called OsFKBP53, it was encoding a member of the FK506-binding proteins (FKBP)-type immunophilin family protein. In rice, there are 29 FKBPs gene family members[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The FKBPs join the cyclophilins (CYPs) under the umbrella term \u0026lsquo;immunophilin\u0026rsquo; due to their discovery as cellular receptors for immunosuppressant drug ligands FK506 and rapamycin[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Studies on maize, Chlamydomonas, and Arabidopsis showed that one of the FKBPs, FKBP12, plays a regulator of plant germination, development, and mRNA splicing[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. However, no evidence related to rice diseases was found for gene \u003cem\u003eOs09g0293900. OsUBC18\u003c/em\u003e is predicted to be a member of the ubiquitin-conjugating enzyme-encoding gene family. In plants, ubiquitination plays an important role in response to biotic and abiotic stresses [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Liu et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] reported that \u003cem\u003eOsUBC26\u003c/em\u003e is involved in the defense against blast (\u003cem\u003eMagnaporthe oryzae\u003c/em\u003e). Liu et al. [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] revealed that OsUBC13-RNAi lines presented a significant increase in resistance to rice blast and rice bacterial blight (\u003cem\u003eXanthomonas oryzae pv oryzae\u003c/em\u003e). The gene function of \u003cem\u003eOs09g0295300\u003c/em\u003e was unknown. Based on the GWAS study, RNA-seq analysis, and expression pattern, we consider \u003cem\u003eOs09g0293400\u003c/em\u003e (\u003cem\u003eOsUBC18\u003c/em\u003e) to be a potential \u003cem\u003ebakanae\u003c/em\u003e disease resistance-related gene at this locus.\u003c/p\u003e \u003cp\u003eWe found that the T-DNA mutation of \u003cem\u003eOsUBC18\u003c/em\u003e significantly increased \u003cem\u003ebakanae\u003c/em\u003e resistance. Additionally, the GA signaling-related genes that will repress the GA pathway were downregulated after bakanae inoculated in the T-DNA mutant of \u003cem\u003eOsUBC18.\u003c/em\u003e Bakanae disease of rice is because by the GAs produced by the fungus F.\u003cem\u003efujikuroi\u003c/em\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Kim et al. reported that GA3-treated and \u003cem\u003ebakanae\u003c/em\u003e-affected seedlings showed similar phenotypes[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These findings potentially indicate that the T-DNA mutant of \u003cem\u003eOsUBC18\u003c/em\u003e improved innate immunity against bakanae via the inhibition of GA signaling. To further validate the involvement of GA signaling in the observed phenotypes, we aim to test GA levels and enzyme activity in T-DNA mutant of \u003cem\u003eOsUBC18\u003c/em\u003e as well as additional genetic backgrounds. Natural allelic variation in \u003cem\u003eOsUBC18\u003c/em\u003e revealed that an SNP (snp_6945916) in the promoter region is important for its expression at the transcript level and leads to \u003cem\u003ebakanae\u003c/em\u003e resistance. The expression level of the \u0026ldquo;C\u0026rdquo; haplotype (landrace_hap1) was higher than the \u0026ldquo;T\u0026rdquo; haplotype (landrace_hap2) which has higher \u003cem\u003ebakanae\u003c/em\u003e disease than landrace_hap1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB, C). Allele frequency among 5,429 rice accessions revealed that 68.35% of the accessions carried the snp_6945916_C allele, whereas 31.65% of the accessions carried the snp_6945916_T allele (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eD). Nucleotide diversity (π value) on chromosome 9 the π value of \u003cem\u003eOsUBC18\u003c/em\u003e(0.000038) was lower than the average π value on chromosome 9 (0.000055). Those results illustrate the sequence of \u003cem\u003eOsUBC18\u003c/em\u003e in landrace populations was conserved and it was controlled by artificial selection. To clarify this, it might be necessary to further investigate the detailed genomic diversity among cultivated rice and wild rice.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, through GWAS, we identified a novel \u003cem\u003ebakanae\u003c/em\u003e resistance gene, \u003cem\u003eOsUBC18\u003c/em\u003e, which belongs to the ubiquitin-conjugating enzyme-encoding gene family. In this study, we performed a GWAS to quickly and accurately identify the \u003cem\u003ebakanae\u003c/em\u003e resistance-related genes in rice.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. \u003cstrong\u003eRS-2024-00391988\u003c/strong\u003e) and supported by the New Breeding Technologies Development Program (\u003cstrong\u003eNo. RS-2024-00322502\u003c/strong\u003e), Rural Development Administration, Korea.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Authors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZeng Y:\u003c/strong\u003e\u0026nbsp; Data curation, Methodology, Investigation, Validation, Writing \u0026ndash; original draft. \u003cstrong\u003eCao FY:\u0026nbsp;\u003c/strong\u003eInvestigation, Data curation, \u003cstrong\u003eLee AR:\u003c/strong\u003e Investigation, Data curation, \u003cstrong\u003eLee D:\u003c/strong\u003e data curation and reviewing. \u003cstrong\u003eKim B:\u003c/strong\u003e data curation and reviewing. \u003cstrong\u003eKwon SW:\u003c/strong\u003e Conceptualization, Project administration, Supervision, Fund acquisition, Supervision, Validation, Resources, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the reviewers for their helpful suggestions. We thank the editors very much for their efficient work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePark W-S, Choi H-W, Han S-S, Shin D-B, Shim H-K, Jung E-S, Lee S-W, Lim C-K, Lee Y-H: \u003cstrong\u003eControl of bakanae disease of rice by seed soaking into the mixed solution of procholraz and fludioxnil\u003c/strong\u003e. \u003cem\u003eResearch in Plant Disease \u003c/em\u003e2009, \u003cstrong\u003e15\u003c/strong\u003e(2):94-100.\u003c/li\u003e\n\u003cli\u003ePr\u0026agrave; Md, Tonti S, Pancaldi D, Nipoti P, Alberti I: \u003cstrong\u003eFirst report of Fusarium andiyazi associated with rice bakanae in Italy\u003c/strong\u003e. \u003cem\u003ePlant Disease \u003c/em\u003e2010, \u003cstrong\u003e94\u003c/strong\u003e(8):1070-1070.\u003c/li\u003e\n\u003cli\u003eGupta A, Solanki IS, Bashyal B, Singh Y, Srivastava K: \u003cstrong\u003eBakanae of rice-an emerging disease in Asia\u003c/strong\u003e. \u003cem\u003eThe Journal of Animal \u0026amp; Plant Sciences \u003c/em\u003e2015, \u003cstrong\u003e25\u003c/strong\u003e(6):1499-1514.\u003c/li\u003e\n\u003cli\u003eDesjardins A, Manandhar H, Plattner R, Manandhar G, Poling S, Maragos C: \u003cstrong\u003eFusarium species from Nepalese rice and production of mycotoxins and gibberellic acid by selected species\u003c/strong\u003e. \u003cem\u003eApplied and Environmental Microbiology \u003c/em\u003e2000, \u003cstrong\u003e66\u003c/strong\u003e(3):1020-1025.\u003c/li\u003e\n\u003cli\u003eAmatulli MT, Spadaro D, Gullino ML, Garibaldi A: \u003cstrong\u003eMolecular identification of Fusarium spp. associated with bakanae disease of rice in Italy and assessment of their pathogenicity\u003c/strong\u003e. \u003cem\u003ePlant Pathology \u003c/em\u003e2010, \u003cstrong\u003e59\u003c/strong\u003e(5):839-844.\u003c/li\u003e\n\u003cli\u003eCheon K-S, Jeong Y-M, Lee Y-Y, Oh J, Kang D-Y, Oh H, Kim SL, Kim N, Lee E, Baek J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eKompetitive Allele-Specific PCR Marker Development and Quantitative Trait Locus Mapping for Bakanae Disease Resistance in Korean Japonica Rice Varieties\u003c/strong\u003e. \u003cem\u003ePlant Breeding and Biotechnology \u003c/em\u003e2019, \u003cstrong\u003e7\u003c/strong\u003e(3):208-219.\u003c/li\u003e\n\u003cli\u003eLee S-B, Hur Y-J, Cho J-H, Lee J-H, Kim T-H, Cho S-M, Song Y-C, Seo Y-S, Lee J, Kim T-s: \u003cstrong\u003eMolecular mapping of qBK1 WD, a major QTL for bakanae disease resistance in rice\u003c/strong\u003e. \u003cem\u003eRice \u003c/em\u003e2018, \u003cstrong\u003e11\u003c/strong\u003e(1):1-8.\u003c/li\u003e\n\u003cli\u003eHayasaka T, Ishiguro K, Shibutani K, Namai T: \u003cstrong\u003eSeed disinfection using hot water immersion to control several seed-borne diseases of rice plants\u003c/strong\u003e. \u003cem\u003eJapanese Journal of Phytopathology \u003c/em\u003e2001, \u003cstrong\u003e67\u003c/strong\u003e(1):26-32.\u003c/li\u003e\n\u003cli\u003eKim J-M, Hong S-K, Kim W-G, Lee Y-K, Yu S-H, Choi H-W: \u003cstrong\u003eFungicide resistance of Gibberella fujikuroi isolates causing rice bakanae disease and their progeny isolates\u003c/strong\u003e. \u003cem\u003eThe Korean Journal of Mycology \u003c/em\u003e2010, \u003cstrong\u003e38\u003c/strong\u003e(1):75-79.\u003c/li\u003e\n\u003cli\u003eHur Y-J, Lee SB, Kim TH, Kwon T, Lee J-H, Shin D-J, Park S-K, Hwang U-H, Cho JH, Yoon Y-N: \u003cstrong\u003eMapping of qBK1, a major QTL for bakanae disease resistance in rice\u003c/strong\u003e. \u003cem\u003eMolecular Breeding \u003c/em\u003e2015, \u003cstrong\u003e35\u003c/strong\u003e:1-9.\u003c/li\u003e\n\u003cli\u003eFiyaz RA, Yadav AK, Krishnan SG, Ellur RK, Bashyal BM, Grover N, Bhowmick PK, Nagarajan M, Vinod K, Singh NK: \u003cstrong\u003eMapping quantitative trait loci responsible for resistance to Bakanae disease in rice\u003c/strong\u003e. \u003cem\u003eRice \u003c/em\u003e2016, \u003cstrong\u003e9\u003c/strong\u003e:1-10.\u003c/li\u003e\n\u003cli\u003eCheon K-S, Jeong Y-M, Lee Y-Y, Oh J, Kang D-Y, Oh H, Kim SL, Kim N, Lee E, Baek J: \u003cstrong\u003eKompetitive allele-specific PCR marker development and quantitative trait locus mapping for bakanae disease resistance in Korean japonica rice varieties\u003c/strong\u003e. \u003cem\u003ePlant breeding and biotechnology \u003c/em\u003e2019, \u003cstrong\u003e7\u003c/strong\u003e(3):208-219.\u003c/li\u003e\n\u003cli\u003eLee S-B, Hur Y-J, Cho J-H, Lee J-H, Kim T-H, Cho S-M, Song Y-C, Seo Y-S, Lee J, Kim T-s: \u003cstrong\u003eMolecular mapping of qBK1 WD, a major QTL for bakanae disease resistance in rice\u003c/strong\u003e. \u003cem\u003eRice \u003c/em\u003e2018, \u003cstrong\u003e11\u003c/strong\u003e:1-8.\u003c/li\u003e\n\u003cli\u003eLee S-B, Kim T-H, Kang J-W, Jo S-M, Cho J-H, Lee J-Y, Lee J-H, Kwon Y-H, Song Y-C, Ko J-M: \u003cstrong\u003eQTL Analysis of the qBK1 Z, a Major QTL for Bakanae Disease Resistance in Rice\u003c/strong\u003e. 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In this study, \u003cem\u003eqBK9 \u003c/em\u003ewas identified via GWASs based on 169 Korean landrace accessions. Furthermore, 5 genes in the qBK9 region were identified as potential candidates, which demonstrated notable expression differences between resistant and susceptible accessions. Finally, \u003cem\u003eOsUBC18\u003c/em\u003eencoded a ubiquitin-conjugating enzyme significantly downregulated in the resistant rice cultivars. Os\u003cem\u003eUBC18 \u003c/em\u003eT-DNA insertion mutants presented significantly reduced \u003cem\u003ebakanae\u003c/em\u003eresistance. A single nucleotide polymorphism (SNP) in the promoter region of \u003cem\u003eOsUBC18\u003c/em\u003e is responsible for its differential expression, leading to alterations in rice \u003cem\u003ebakanae\u003c/em\u003eresistance. Moreover, genes associated with the gibberellin (GA) pathway, which plays a role in bakanae disease, were down-regulated in \u003cem\u003eOsUBC18\u003c/em\u003e T-DNA mutant lines.\u003cem\u003e \u003c/em\u003eThese findings suggest that OsUBC18 is a gene associated with bakanae resistance, and its expression enhances rice immunity via reduced GA-related genes.\u003c/p\u003e","manuscriptTitle":"Genome-Wide Association Study to Identify Bakanae Disease Resistance- Related QTLs Carrying Novel Candidate Genes in Rice (Oryza sativa L.)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-25 10:57:47","doi":"10.21203/rs.3.rs-6309254/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-13T09:05:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T19:33:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-17T12:58:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329979608208447697174866333421194958031","date":"2025-04-17T00:46:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300788480376244918890759355838772384595","date":"2025-04-04T07:31:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-04T06:28:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-01T15:32:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-31T08:13:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Science of Plants","date":"2025-03-26T06:29:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-science-of-plants","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Science of Plants](https://www.nature.com/npjsciplants)","snPcode":"44383","submissionUrl":"https://submission.springernature.com/new-submission/44383/3","title":"npj Science of Plants","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"35ffaa6c-359d-4643-a3f2-025a0416f98d","owner":[],"postedDate":"April 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":47559241,"name":"Biological sciences/Genetics/Agricultural genetics"},{"id":47559242,"name":"Biological sciences/Plant sciences/Plant breeding"},{"id":47559243,"name":"Biological sciences/Plant sciences/Plant genetics"}],"tags":[],"updatedAt":"2025-08-25T09:53:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-25 10:57:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6309254","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6309254","identity":"rs-6309254","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}