A Genome-wide association study of panicle blast resistance (PBR) to Magnaporthe Oryzae in Rice

A Genome-wide association study of panicle blast resistance (PBR) to Magnaporthe Oryzae in Rice | 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 A Genome-wide association study of panicle blast resistance (PBR) to Magnaporthe Oryzae in Rice Hu Jinlong, Zhang Yu, Wang Ruizhi, Wang Xiaoyu, Feng Zhiming, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4255607/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2024 Read the published version in Molecular Breeding → Version 1 posted 4 You are reading this latest preprint version Abstract Rice blast, caused by Magnaporthe Oryzae ( M. oryzae ), is one of the most serious diseases all over the world. Development of blast-resistant rice varieties can effectively control the damage of rice blast and reduce the application of chemical pesticides. In this study, 477 sequenced rice germplasms from 48 countries were inoculated and identified at booting stage. We found that 23 germplasms displayed high panicle blast resistance against M. oryzae. 43 quantitative trait loci (QTLs) significantly ( P < 10 − 4 ) associated with rice panicle blast resistance were identified by genome-wide association analysis (GWAS). These QTL intervals contain four genes ( OsAKT1 , OsRACK1A , Bsr-k1 and Pi25 / Pid3 ) have been reported to be involved in rice blast resistance. We select QTLs with -Log10(Pvalue) higher than 6.0 or those detected in two-year replicates, totaling 12 QTLs, for candidate gene analysis. We identified three blast resistance candidate genes ( Os06g0316800 , Os06g0320000 , Pi25 / Pid3 ) based on the significant SNP distribution of annotated gene sequences in these 12 QTL and the difference of expression levels among blast resistant varieties after 72h inoculation. Os06g0316800 encodes a protein similar to Glycine-rich protein, an important component of plant cell walls involved in cellular stress responses and signaling, named as OsGrp6 . Os06g0320000 encodes a protein of unknown function DUF953, belonging to the thioredoxin-like family, crucial for maintaining reactive oxygen species (ROS) homeostasis in vivo, named as OsTrxl1 . Lastly, Pi25 / Pid3 encodes a disease resistance protein, emphasizing its potential significance in plant biology. By analyzing the haplotypes of these 3 genes, we identified the favorable haplotypes with blast resistance, which will provide genetic resources for future rice blast resistance breeding. panicle blast resistance Rice (Oryza sativa L.) genome-wide association study (GWAS) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Rice ( Oryza sativa L.) stands as one of the paramount crops globally; nonetheless, its production is besieged by an array of diseases and pests (Li et al. 2020 ). Chief among these maladies is rice blast, instigated by the ascomycete fungus M. oryzae , which inflicts profound devastation (Deng and Naqvi 2019 ). The peril lies in M. oryzae ability to assail rice plants across all developmental stages, precipitating yield reductions ranging from 10–35% and consequent escalation the costs associated with chemical control. (Fisher et al. 2012 ; Nalley et al., 2016). Furthermore, the M. oryzae population exhibits variability and complexity, categorizing into distinct physiological races based on varying pathogenicity, thereby exacerbating the challenge of disease management (Zhang et al. 2017 ; Yin et al. 2021 ). Hence, effective control of rice blast assumes paramount importance in safeguarding global food security. Breeding blast-resistant cultivars harboring resistance genes emerges as the most economical and efficacious strategy for rice blast control (Li et al. 2019 ). R genes, owing to their potent resistance effect and ease of selection, have been instrumental in blast resistance breeding efforts (Li et al. 2020 ). However, R genes frequently succumb to breakdown under the selection pressure engendered by the high variability of rice blast pathogens and the protracted cultivation of a single resistant variety over extensive areas (Wang et al. 2017 ; Zhang et al. 2017 ; Ning et al. 2020 ). Despite endeavors to mitigate this issue by pyramiding multiple R genes or QTL through marker-assisted selection to achieve broad-spectrum resistance, such approaches entail prolonged durations and elevated costs for breeders, as well as the risk of negative effects after the pyramiding of different R genes (Jiang et al. 2019 ; Wu et al. 2019 ). Hence, the exploration and exploitation of broad-spectrum resistance genes represent a viable avenue for enhancing the efficacy of rice blast control. Recent studies have demonstrated the involvement of certain R and defense-regulator (DR) genes in conferring broad-spectrum resistance to M. oryzae (Li et al. 2019 ). Among these genes, PigmR , an R gene, has been found to interact with the RNA recognition motif (RRM) domain-containing transcription factor PIBP1 (PigmR-INTERACTING and BLAST RESISTANCE PROTEIN 1). This interaction facilitates the nuclear translocation of PigmR-PIBP1 complex, subsequently activating the expression of downstream defense genes such as OsWAK14 and OsPAL1 . This coordinated activation leads to enhanced resistance against various strains of blast in rice (Deng et al. 2017 ; Zhai et al. 2019 ). Another notable gene, Bsr-d1 , encodes a C2H2 transcription factor responsible for promoting the expression of catalase. Interestingly, loss-of-function mutations in bsr-d1 result in heightened blast resistance attributed to the accumulation of hydrogen peroxide within cells, achieved by the downregulation of catalase expression (Li et al. 2017 ). Similarly, the gene bsr-k1 encodes a protein rich in tetratricopeptide repeats (TPRs) and exhibits RNA-binding activity. Bsr-k1 functions by binding to and promoting the degradation of OsPAL1-7 mRNAs, consequently inhibiting lignin synthesis. Loss-of-function mutations in bsr-k1 lead to enhanced blast resistance due to increased lignin accumulation in plants (Zhou et al. 2018 ). Due to the trade-off between growth and resistance, plant defense activation often causes growth inhibition and yield reduction. Among those cloned R genes, Pigm locus confers durable resistance to M. oryzae without yield penalty due to tight epigenetic regulation of paired antagonistic nucleotide-binding site leucine-rich repeat (NLR) receptors ( PigmR and PigmS ) (Deng et al. 2017 ). IPA1 promotes both yield and disease resistance through the strict phosphorylated state transform during rice blast infected (Wang et al. 2018a ). Therefore, the precise regulation of gene expression and protein modification can achieve the balancing between high resistance and yield, providing a theoretical guidance to develop elite crop varieties. Amidst the wealth of genetic diversity within rice resource varieties lies a treasure trove for both breeding endeavors and genomics research (Wang et al. 2018b ). Advancements in sequencing technologies have enabled the comprehensive resequencing of numerous rice varieties, resulting in the identification of a plethora of genetic variants (Zhao et al. 2015 ; Zheng et al. 2015 ). Genome-wide association studies (GWAS) harnessing these abundant genetic variants have led to the identification of numerous genes governing complex and pivotal agronomic traits (Kang et al. 2016 ; Zhu et al. 2016 ; Tang et al. 2019 ; Xiao et al. 2019 ). Notably, the 3000 Rice Genome Project (3K RGP) has emerged as an invaluable resource, offering extensive data for the mapping and cloning of key agronomic trait genes in rice (Li et al. 2014 ; Science and World 2014 ; Alexandrov et al. 2015 ; Sun et al. 2017 ; Wang et al. 2018b ). Given the significant yield losses attributed to panicle blast epidemics, particularly during the critical period of rice yield formation (Deng and Naqvi 2019 ), the mapping and cloning of blast broad-spectrum resistance genes hold immense potential for accelerating the development of disease-resistant, high-yielding rice varieties (Yin et al. 2021 ). Notably, certain cloned R genes, such as Pi2 and Pizt , have demonstrated markedly lower resistance against panicle blast compared to foliar blast in rice (Wu et al. 2016 , 2017 ; Ning et al. 2020 ). In this study, we conducted a genome-wide association study (GWAS) employing a panel comprising 477 accessions sourced from the 3000 rice germplasms. These accessions were subjected to infection by a combination of five representative M. oryzae isolates in the years 2020 and 2022. Through this approach, we successfully identified 18 quantitative trait loci (QTLs) associated with panicle blast resistance. Additionally, through sequence analysis of select candidate genes within these identified QTLs, we unearthed promising candidates for utilization in rice blast disease resistance breeding programs. Results Characterization and evaluation of panicle blast resistance in 477 sequenced rice accessions There exists a rich reservoir of genetic diversity within the natural rice population. A comprehensive evaluation of rice panicle blast resistance was conducted on a total of 477 rice varieties sourced from 48 countries or regions as part of the 3000 Rice Genome Project (3K RGP). These 477 accessions were classified into five subspecies: Xian / indica , Geng / japonica , circum-Aus, circum-Basmati, and admixed. Further sub-grouping identified 12 distinct subgroups ( XI-1A , XI-1B , XI-2 , XI-3 , XI-adm , GJ-tmp , GJ-sbtrp , GJ-trp , GJ-adm , cA , cB , Admix ) based on previous research findings. This comprehensive categorization facilitated a detailed examination of the panicle blast resistance across various genetic backgrounds and geographical origins (Table S1 ). In 2020, a total of 374 rice accessions were subjected to inoculation with a mixture of five M. oryzae isolates (2020 − 110, 2020 − 183, 2020 − 321, 2020 − 113, and 2020 − 353) at the booting stage, while 410 rice accessions underwent inoculation with a blend of five M. oryzae isolates (2022 − 113, 2022 − 313, 2022 − 406, 2022 − 417, 2022 − 556, and 2022 − 586) at the booting stage in 2022. The average scale of rice panicle blast resistance (PBR) was measured at 3.1 and 5.7, ranging from 0 (no disease) to 9 (highly susceptible) in 2020 and 2022, respectively (Fig. 1 A and 1 C). The wide spectrum of resistance variations observed across these rice germplasm accessions suggests significant genetic diversity associated with rice panicle blast resistance. Comparative analysis among different subspecies revealed that XI-1A and XI-1B exhibited higher blast resistance against the disease (Fig. 1 B; Table S2). The average blast resistance scales in XI-1A and XI-1B were 1.68 and 1.72, respectively, significantly lower than those observed in the GJ-tmp (5.3), GJ-trp (3.0), and GJ-adm (4.5) subspecies in 2020 (Fig. 1 B; Table S2). Conversely, the average incidence of blast in the GJ-tmp subspecies reached 5.28, significantly higher than that observed in XI-1A and XI-1B in 2020 (Fig. 1 B; Table S2). In the subsequent inoculation of 410 rice resources in 2022, the mean blast resistance value increased to 5.7 compared to 2020, potentially due to differences in virulence between the two years. Consistent with the findings of 2020, XI-1A and XI-1B exhibited higher blast resistance in 2022 compared to other subspecies. The average blast resistance scales in XI-1A and XI-1B were 5.7 and 3.5, respectively, significantly lower than those observed in the GJ-tmp (7.2), GJ-trp (5.8), and GJ-adm (7.2) subspecies in 2022 (Fig. 1 D; Table S3). These results highlight the significant divergence in rice panicle blast resistance among different subspecies, with GJ-tmp demonstrating increased susceptibility compared to others. Among the 477 rice accessions, 23 were identified as possessing stably high resistance (rice panicle blast resistance scale ≤ 1 in both 2020 and 2022) (Table S4). These 23 rice accessions represent promising germplasm resources for blast resistance breeding efforts. GWAS analysis of QTLs for rice panicle blast resistance A total of 2,918,100 and 2,914,029 single nucleotide polymorphisms (SNPs) distributed across the entire rice genome were selected for the genome-wide association study (GWAS) analysis of quantitative trait loci (QTLs) associated with rice panicle blast resistance in 2020 and 2022, respectively. In 2020, 27 QTLs encompassing 993 SNPs were identified as significantly associated ( P < 1.0 × 10 − 4 ) with rice panicle blast resistance in the 374 rice accessions (Table S5). Similarly, in 2022, 19 QTLs comprising 1,284 SNPs were significantly associated ( P < 1.0 × 10 − 4 ) with rice panicle blast resistance in the 410 rice accessions (Table S5). Notably, when P < 1.0 × 10 − 4 , a rapid deviation between observed and predicted SNP values was observed (Fig. 2 B and 2 D), suggesting that the significant correlation between genotype and phenotype was likely due to natural selection rather than genetic drift. These QTLs were distributed across chromosomes 1, 3, 4, 5, 6, 8, 9, 10, and 11 (Table S5). Among them, four QTL regions ( qPBR1-10 , qPBR1-11 , qPBR6-6 , qPBR10-2 ) contained four reported blast resistance genes ( OsAKT1 , OsRACK1A , Pi25 / Pid3 , Bsr-k1 ) (Table S5 and Fig. 2 A and 2 C). Only five QTLs ( qPBR1-5 , qPBR1-6 , qPBR6-4 , qPBR6-5 , qPBR6-6 ) exhibited stability across both 2020 and 2022, suggesting the presence of genes conferring broad-spectrum resistance to blast (Table S6 and Fig. 2 A, 2 C). Additionally, five QTLs ( qPBR6-3 , qPBR6-6 , qPBR8-1 , qPBR11-4 , qPBR11-6 ) exhibited -log10( p ) exceeding 6.0, indicating a significant correlation with rice blast resistance and warranting further investigation (Table S6). Hence, qPBR1-10 , qPBR1-11, qPBR1-5 , qPBR1-6 , qPBR6-3 , qPBR6-4 , qPBR6-5 , qPBR6-6 , qPBR8-1 , qPBR10-2 , qPBR11-4 , and qPBR11-6 were identified as more significant targets for candidate panicle blast resistance gene discovery. Putative candidate genes for twelve QTL intervals The twelve blast resistance QTL intervals obtained from the above analysis were further screened, resulting in a total of 277 annotated genes are found (Table S7). After screening non-synonymous SNP, 67 genes exhibit non-synonymous SNP sites in exon or within the up/downstream regions of 3 kb, which P -values less than 3.16 × 10 − 4 (Table S8). Among them, 2 genes were obtained on PBR1-5 , 1 gene were obtained on PBR1-6 , 2 genes were obtained on PBR1-10 , 2 genes were obtained on PBR1-11 , 3 genes were obtained on PBR6-3 , 46 genes were obtained on PBR6-6 , 9 genes were obtained on PBR8-1 , 1 gene were obtained on PBR10-2 , 1 gene were obtained on PBR11-6 (Table S8). The twelve blast resistance QTL intervals identified in the preceding analysis were further scrutinized, leading to the identification of a total of 277 annotated genes (Table S7). Subsequent screening for non-synonymous single nucleotide polymorphisms (SNPs) revealed 67 genes harboring non-synonymous SNP sites within exons or within the up/downstream regions of 3 kb, with P -values less than 3.16 × 10 − 4 (Table S8). Among these, 2 genes were identified within the PBR1-5 interval, 1 gene within PBR1-6 , 2 genes within PBR1-10 , 2 genes within PBR1-11 , 3 genes within PBR6-3 , 46 genes within PBR6-6 , 9 genes within PBR8-1 , 1 gene within PBR10-2 , and 1 gene within PBR11-6 (Table S8). Only one significant SNP locus is found upstream of the ATG of Pi25 / Pid3 among the four rice blast resistance genes detected within the identified QTL intervals. The coding, upstream, and downstream regions of OsAKT1 , OsRACK1A , and Bsr-k1 do not contain significant SNP loci. Expression patterns of rice panicle blast resistance Genes Rice blast resistance genes demonstrate significant differential expression between resistant and susceptible varieties following rice blast infection. Thus, we selected five highly resistant rice varieties (IRIS_313–8067, IRIS_313–8148, IRIS_313–9925, CX393, and IRIS_313-11538) alongside five highly susceptible rice varieties (IRIS_313–8039, IRIS_313-10430, IRIS_313-10642, B154, and IRIS_313–8204) for rice blast inoculation at the seedling stage. Tissue samples were collected 72 hours post-inoculation, with tissues pooled from both highly susceptible and highly resistant varieties for RNA-seq analysis. A total of 24,891 differentially expressed genes were identified, with 1,510 genes showing significantly higher expression levels in the mixed pool of resistant varieties compared to the mixed pool of susceptible varieties, and 2,681 genes exhibiting significantly lower expression levels in the mixed pool of resistant varieties compared to the mixed pool of susceptible varieties (Table S9). Additionally, among the 67 candidate genes identified in the GWAS analysis, 14 genes demonstrated significant differential expression in the pooled sequencing of disease-resistant and susceptible samples. These genes were Os01g0686100 , Os06g0306600 , Os06g0316800 , Os06g0318533 , Os06g0320000 , Os06g0320500 , Os06g0321700 , Os06g0323100 , Os06g0324000 , Os06g0325602 , Os06g0326400 , Os06g0329350 , Os06g0330100 and Os08g0135500 (Table 1 ). Table 1 Functional annotation of 14 candidate genes QTL Locus ID Description log2(foldchange) for HR VS HS padj direction PBR1-11 Os01g0686100 Conserved hypothetical protein -2.53 1.39E-03 down PBR6-3 Os06g0306600 Esterase/lipase/thioesterase domain containing protein -1.70 7.91E-04 down PBR6-6 Os06g0316800 Similar to Glycine-rich protein (Fragment) 0.97 3.31E-02 up PBR6-6 Os06g0318533 expressed protein -9.28 4.06E-11 down PBR6-6 Os06g0320000 Protein of unknown function DUF953, thioredoxin-like family protein 0.95 7.09E-03 up PBR6-6 Os06g0320500 Similar to Light-harvesting complex I (Fragment) 1.30 2.62E-10 up PBR6-6 Os06g0321700 Conserved hypothetical protein -1.20 4.25E-02 down PBR6-6 Os06g0323100 indole-3-acetate O-methyltransferase 1-like -8.61 1.23E-09 down PBR6-6 Os06g0324000 Conserved hypothetical protein -5.99 1.84E-03 down PBR6-6 Os06g0325602 Hypothetical gene. (Os06t0325602-00) -5.20 7.09E-04 down PBR6-6 Os06g0326400 Pyrophosphate-dependent phosphofructokinase PfpB family protein. 1.38 4.76E-03 up PBR6-6 Os06g0329350 expressed protein -10.20 4.94E-14 down PBR8-1 Os08g0135500 X8 domain containing protein -5.82 6.59E-04 down PBR6-6 Os06g0330100 Disease resistance protein family protein. 5.96 0.00 up OsGrp6/Os06g0316800 encodes a protein similar to Glycine-rich protein, an important component of plant cell walls involved in cellular stress responses and signaling (Ringli et al. 2001 ; Czolpinska and Rurek 2018 ). OsTrxl1 / Os06g0320000 encodes a protein of unknown function DUF953, belonging to the thioredoxin-like family, crucial for maintaining reactive oxygen species (ROS) homeostasis in vivo (Hu et al. 2021 ). Lastly, Pi25 / Pid3 / Os06g0330100 encodes a disease resistance protein, emphasizing its potential significance in plant biology (Zhou et al. 2019 ). These five genes warrant further exploration and attention due to their potential importance in plant biology. Analysis of three Candidate Gene Haplotype by RFGB Database In the upstream region of the ATG start codon of the OsGrp6 gene, a notable SNP locus at 555 bp (Chr6_12253876, A/C) has been identified (Fig. 3 A). Utilizing this SNP variant information, haplotype analysis of the OsGrp6 gene was conducted on the RFGB Database website. The analysis revealed two distinct haplotypes for OsGrp6 , with resistance levels to rice blast observed as 2.11 and 4.77 in 2020, and 4.79 and 7.27 in 2022, displaying statistically significant differences (Fig. 3 A- 3 C). The expression level of OsGrp6 was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation(Fig. 3 D). Among the 23 identified high-resistant germplasm resources, 21 were found to carry the Hap1 haplotype (Table S4), indicating potential involvement in rice blast resistance. In the upstream or downstream region of the ATG start codon of the OsTrxl1 gene, six notable SNP loci at 555 bp to 1375 bp (Chr6_12433018, C/T; Chr6_ 12433210, T/C; Chr6_ 12433295, G/A; Chr6_ 12433438, C/T; Chr6_ 12433662, G/A; Chr6_12433816, C/T) have been identified (Fig. 4 A). In the downstream region of the ATG stop codon of the OsTrxl1 gene, one notable SNP locus at 1633 bp (Chr6_ 12430293, T/C) has been identified (Fig. 4 A). Utilizing this SNP variant information, haplotype analysis of the OsTrxl1 gene was conducted on the RFGB Database website. The analysis indicated three haplotypes for OsTrxl1 Hap1 and Hap3 with resistance levels to rice blast observed as 2.09 and 2.94 in 2020, and 4.84 and 6.64 in 2022, and Hap2 with resistance levels to rice blast observed as 5.38 in 2020, and 7.47 in 2022, displaying statistically significant differences (Fig. 4 A- 4 C). The expression level of OsTrxl1 was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation (Fig. 4 D). Among the 23 identified high-resistant germplasm resources, 17 were found to carry the Hap1 haplotype (Table S4), suggesting potential involvement in rice blast resistance. In the upstream region of the ATG start codon of the Pi25 / Pid3 gene, a notable SNP locus at 152 bp (Chr6_13058179, A/C) has been identified (Fig. 5 A). Utilizing this SNP variant information, haplotype analysis of the Pi25 / Pid3 gene was conducted on the RFGB Database website. The analysis revealed two distinct haplotypes for Pi25 / Pid3 , with resistance levels to rice blast observed as 2.11 and 4.65 in 2020, and 4.80 and 7.18 in 2022, showing statistically significant differences (Fig. 5 A- 5 C). The expression level of Pi25 / Pid3 was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation (Fig. 5 D). Among the 23 identified high-resistant germplasm resources, 21 were found to carry the Hap1 haplotype (Table S4), suggesting potential involvement in rice blast resistance. Discussion Rice blast is a serious threat to the yield and quality of rice, especially at heading stage. However, most of the rice varieties with high yield and good quality are highly susceptible to blast (Xiao et al. 2021 ). Therefore, explore blast resistance genes and introduce them into susceptible varieties by marker-assisted selection method is an economical and effective strategy to develop blast resistant varieties. In this study, 477 sequenced rice germplasm resources were used to identify panicle blast resistance, and 23 rice materials with high blast resistance were screened (Table S1 and Table S4). These 23 rice blast resistant materials consisted of different genetic backgrounds, including 4 XI-1A , 9 XI-1B , 1 XI-2, 4 XI-adm , 3 GJ-tmp , 2 cA and 1 Admix (Table S4), which could provide rich genetic materials for blast resistance breeding. Rice blast poses a significant threat to both the yield and quality of rice, particularly during the heading stage. However, many rice varieties known for their high yield and quality are highly susceptible to blast (Xiao et al. 2021 ). Therefore, employing the marker-assisted selection method to explore blast resistance genes and introduce them into susceptible varieties proves to be an economical and effective strategy for developing blast-resistant varieties. In this study, 477 sequenced rice germplasm resources were utilized to identify panicle blast resistance, resulting in the screening of 23 rice materials exhibiting high blast resistance (refer to Table S1 and Table S4). These 23 rice blast-resistant materials encompass various genetic backgrounds, including 4 XI-1A , 9 XI-1B , 1 XI-2 , 4 XI-adm , 3 GJ-tmp , 2 cA , and 1 Admix (Table S4), thus providing diverse genetic materials for blast resistance breeding. Under the strong selection pressure of disease-resistant host, pathogenic virulent races will evolve the ability to suppress host immunity by multiple pathogen effectors, and the host resistance loss will further evolve new resistance response to resist the invasion of pathogenic bacteria (Shi et al. 2018 ; Wang et al. 2021 ; Zhai et al. 2021 ). Because of the arms race between plants and pathogens, rice varieties with a single resistance gene planted on a large scale over a long period of time will run the risk of resistance broken-down (Kou and Wang 2010 ; Peñalver Cruz et al. 2011 ). Therefore, exploring rich and diverse blast resistance gene resources and using them in breeding will contribute to develop rice varieties with durable and broad-spectrum blast resistance. This study screened 23 highly resistant germplasm resources after two years of mixed inoculation with various physiological races of rice blast, offering a diverse array of resources for rice blast resistance breeding. Among the 43 identified QTLs, qPBR6-4/5/6 appeared in GWAS analyses for both years and contained numerous significant SNP loci. This suggests that the qPBR6-4/5/6 rice blast resistance loci merit further gene cloning and utilization in breeding programs. We combined gene expression data obtained after inoculating resistant and susceptible rice varieties with the rice blast pathogen, and identified four target candidate genes. These four genes exhibited significant differences in rice blast resistance among different haplotypes. Molecular markers can be developed based on SNP sites on these three genes for molecular marker-assisted selection in breeding. During rice blast infection, the fungus typically invades surface cells by penetrating appressoria and releases effectors to suppress the host resistance response (Yan et al. 2023 ). Further investigation is warranted to determine whether the glycine-rich protein encoded by OsGrp6 interacts with effectors released during rice blast infection and triggers resistance responses in host cells. After successful invasion of host cells by the rice blast pathogen, it induces the accumulation of reactive oxygen species (ROS) in host cells and triggers programmed cell death to control fungal growth (Liu et al. 2015 ; Sha et al. 2023 ). The thioredoxin-like protein encoded by OsTrxl1 is involved in regulating the ROS homeostasis in cells, potentially promoting the accumulation of ROS during pathogen infection and enhancing rice blast resistance. Pi25 / Pid3 , as a typical R gene, encodes an NBS-LRR protein capable of recognizing effectors released by the rice blast pathogen, triggering downstream resistance responses (Zhou et al. 2019 ). Through genome-wide association analysis, we identified an SNP site upstream of Pi25 / Pid3 ATG that enhances gene transcription levels, thereby improving resistance to rice blast. This new allele genotype of Pi25 / Pid3 can be utilized in rice blast resistance breeding. Rice R genes usually encodes nucleotide-binding site leucine-rich repeat (NLR) proteins, which can recognized specific avirulence (AVR) protein of specific blast race, leading to a particularly strong immune response (Yin et al. 2021 ). Compared to the R gene, defense-regulator (DR) genes often confer partial but durable resistance to a broad spectrum of pathogen races (Li et al. 2019 ). In order to identify new DR genes with broad-spectrum resistance, 477 rice varieties were inoculated with a mixture of 5 blast races in this study. OsTrxl1 may through regulate ROS homeostasis to confer blast resistance, so whether it has broad-spectrum blast resistance is worth for further study. In conclusion, the high blast resistance rice varieties identified in this study, as well as associated SNPs and favorable haplotypes, should be contribute to the development of blast resistance rice varieties through molecular marker-assisted selection. Materials and methods Plant materials and growth conditions A total of 477 rice accessions collected from 48 countries or regions in The 3000 Rice Genomes Project (3K RGP) were selected to evaluate panicle blast resistance to Magnaporthe Oryzae (Li et al. 2014 ; Science and World 2014 ; Sun et al. 2017 ; Wang et al. 2018b ). Rice plants were cultivated one line for each accession, 10 plants in each line, conventional water and fertilizer management. All seeds in 3K RGP were provided by the Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China (Zhen et al. 2015). Fungal materials and inoculation The five representative M. oryzae isolates (2020 − 110, 2020 − 183, 2020 − 321, 2020 − 113, 2020 − 353) were identified by 31 near-monogenic lines in 2020, that provided by Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences (Qi et al. 2021 ). The six representative M. oryzae isolates (2022 − 113、2022 − 313、2022 − 406、2022 − 417、2022 − 556 and 2022 − 586) were identified by 24 near-monogenic lines in 2022, that provided by Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences (Qi et al. 2021 ). Method of spore culture and inoculation was performed as previously described (Wang et al. 2016 ). Briefly, the tested strains were transplanted into solid medium (corn powder 40 g, rice stalk powder 50 g, agar powder 20 g) and cultured in darkness at 28 ℃ for 7 days. Then, treated with black light lamp (λ = 330-400nm) for 72 h, spores of M. oryzae isolate were produced and washed with sterile water. The spores of each M. oryzae isolates were dilute into a suspension of 10 5 /mL. At the early stage of rice booting, 1 mL mixed suspension spores of 5 representative M. oryzae isolates were injected into each rice panicle, and the inoculation time was after 5 PM every day. Each rice accession was inoculated with 5 panicles/accession. Evaluation of Blast Resistance After inoculation, the blast resistance was investigated according to the 0–9 score classification standard of single panicle loss rate of rice panicle blast, which in the mature stage of rice. The classification standard refer to the technical regulations for identification and evaluation of blast resistance in rice variety test issued by ministry of Agriculture (NY/T2646-2014). Detailed description is as follows: 0, no disease. 1, the incidence of branchlets, loss per panicle < = 5.0%. 3, spindle or panicle disease, loss per panicle 5.1%-20.0%. 5, spindle or panicle disease, grain half deflated, loss of 20.1%-50.0% per panicle. 7, panicle disease, most deflated grain, loss of 50.1%-70.0% per panicle. 9, panicle disease, loss per panicle > 70.0%. Three main panicles with similar resistance performance were selected to average the score of each accession. Genome-wide association analysis The GWAS SNP Dataset of the 477 rice accessions were downloaded from the Rice SNP-Seek Database ( http://snp-seek.irri.org/ ). These SNP variations and positions were identified based on the assembly Os-Nipponbare-Reference-IRGSP-1.0 (Alexandrov et al. 2015 ). Then, the data was filtered by plink 1.90 (Chang et al. 2015 ), according to minor allele frequency (MAF) > 0.1 and missing call rate < 0.1. We used EMMAX software (Kang et al. 2010 ) to detect the SNPs associated with rice panicle blast resistance. The Manhattan and Quantile-Quantile (Q-Q) plots were drawn by R package CMplot. P < 1×10 − 4 was used as the threshold to screen the marker significantly associated with resistance of rice panicle blast. A QTL was declared if a region has two or more than two significant SNPs within a 200 kb interval. The candidate genes were searched from 200 kb upstream and downstream of the most significant SNP in each QTL, which using the reference Nipponbare genome ( http://rice.uga.edu/cgi-bin/gbrowse/rice/ ). Gene haplotype analysis OsGrp6 , OsTrxl1 and Pi25 / Pid3 haplotype analysis was performed on the www.rmbreeding.cn/Index/(Wang et al. 2020) .The base sequence of OsGrp6 , OsTrxl1 and Pi25 / Pid3 mutation locus was downloaded from the http://ricevarmap.ncpgr.cn/(Zhao et al. 2021) and analyzed. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Not applicable. Competing interests The authors declare that they have no conflict of interest. Funding This work was supported by the Project funded by China Postdoctoral Science Foundation (2021M702767), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Authors’ Contributions HJL, ZJY and FZM conceived and designed the experiments. HJL, ZY, WRZ, WXY, XQQ, ZNB and ZJY performed the experiments and analyzed the data. HJL and ZJY was responsible for material plant and field management. HJL wrote the manuscript. WHY, ZY, FZM and ZHC revised the manuscript. All authors read and approved the manuscript. Acknowledgments We owe special thanks to Professor Jianlong Xu (Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China) for providing the seeds in 3K RGP, to Professor Yongfeng Liu (Institute of Plant Protection, Jiangsu Academy of Agricultural Science, Nanjing, China) for providing the M. oryzae isolates (2020-110, 2020-183, 2020-321, 2020-113, 2020-353). References Alexandrov N, Tai S, Wang W, et al (2015) SNP-Seek database of SNPs derived from 3000 rice genomes. Nucleic Acids Research 43:D1023–D1027. https://doi.org/10.1093/nar/gku1039 Chang CC, Chow CC, Tellier LCAM, et al (2015) Second-generation PLINK: Rising to the challenge of larger and richer datasets. 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Rice 9:. https://doi.org/10.1186/s12284-016-0116-3 Supplementary Files Supplementarymolecularbreeding.xlsx Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2024 Read the published version in Molecular Breeding → Version 1 posted Reviewers agreed at journal 25 Apr, 2024 Reviewers invited by journal 15 Apr, 2024 Editor assigned by journal 14 Apr, 2024 First submitted to journal 11 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4255607","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291613564,"identity":"6a91012d-0583-4697-98d0-90bfe2c417be","order_by":0,"name":"Hu Jinlong","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hu","middleName":"","lastName":"Jinlong","suffix":""},{"id":291613565,"identity":"b5e175b6-0321-44e5-aa7d-33dafad4d3b8","order_by":1,"name":"Zhang Yu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhang","middleName":"","lastName":"Yu","suffix":""},{"id":291613566,"identity":"71ababff-8c2a-4624-b6fc-87562095b2fd","order_by":2,"name":"Wang Ruizhi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"Ruizhi","suffix":""},{"id":291613567,"identity":"17a95195-5651-42cc-8df0-baf862ae3b9b","order_by":3,"name":"Wang Xiaoyu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"Xiaoyu","suffix":""},{"id":291613568,"identity":"22998de0-a38f-4dca-9197-5b92bef780b3","order_by":4,"name":"Feng Zhiming","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Zhiming","suffix":""},{"id":291613569,"identity":"deeeb6f7-3e25-49df-bab0-f52852af0131","order_by":5,"name":"Xiong Qiangqiang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiong","middleName":"","lastName":"Qiangqiang","suffix":""},{"id":291613570,"identity":"3f2d93e0-52a5-425a-89b5-73a7186b7cba","order_by":6,"name":"Zhou Nianbing","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhou","middleName":"","lastName":"Nianbing","suffix":""},{"id":291613571,"identity":"408c5534-0cae-44c8-8ac5-1a0c60ea648f","order_by":7,"name":"Zhou Yong","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhou","middleName":"","lastName":"Yong","suffix":""},{"id":291613572,"identity":"f7f3f559-573c-43e0-9945-b3640e5ea63d","order_by":8,"name":"Wei Haiyan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Haiyan","suffix":""},{"id":291613573,"identity":"a08679d3-0216-461f-8906-362765777d24","order_by":9,"name":"Zhang Hongcheng","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhang","middleName":"","lastName":"Hongcheng","suffix":""},{"id":291613574,"identity":"3bb01ae8-0810-442f-8d05-5e53f5e1e8a2","order_by":10,"name":"Jinyan Zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYDACCQYGgwQo+wBDhYScPIlazlgYGzYQoQUBGNsqEoEa8QP52T0GBQ93HJY3lz788HDhPIkExgbmh49u4NHCOOeMgUHimcOGO/vSDA7P3CaRx87AZmycg0cLs0QOUEvbYcYNZxgMDvNukyhmbOBhk8anhQ2qxX7DGfYPh3nnSCQ2HCCghQeqJXHDGR6gLQ1EaJGQSCsAaklPBmopOMxzTMLYsJmAX+RnJG8z/NlmbQt02ObPPDV1cvLszQ8f49MC8o4BA0MzEp8Zv3KwkgcMDHWElY2CUTAKRsHIBQDKv0sEy2/mUAAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Jinyan","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2024-04-12 05:55:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4255607/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4255607/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11032-024-01486-5","type":"published","date":"2024-07-01T12:10:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54992790,"identity":"61189184-e360-42a5-9146-27e48cd3ae77","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":166380,"visible":true,"origin":"","legend":"\u003cp\u003ePhenotypic variation of 477 rice accessions for panicle blast resistance to \u003cem\u003eM. Oryzae \u003c/em\u003ein rice.\u003c/p\u003e\n\u003cp\u003eA and C, Frequency distribution of panicle blast disease resistance scores of 374 rice accessions in 2020 (A) and 410 rice accessions 2022 (C). B and D, Distribution of panicle blast resistance scale to \u003cem\u003eM. Oryzae\u003c/em\u003e in the 12 subgroups. The area of the black circle represents the number of accessions. \u003cem\u003eXI-1A\u003c/em\u003e, \u003cem\u003eXian\u003c/em\u003e/Indica 1A. \u003cem\u003eXI-1B\u003c/em\u003e, \u003cem\u003eXian\u003c/em\u003e/Indica 1B. \u003cem\u003eXI-2\u003c/em\u003e, \u003cem\u003eXian\u003c/em\u003e/Indica 2. \u003cem\u003eXI-3\u003c/em\u003e, \u003cem\u003eXian\u003c/em\u003e/Indica 3. \u003cem\u003eXI-adm\u003c/em\u003e, \u003cem\u003eXian\u003c/em\u003e/Indica admixture. \u003cem\u003eGJ-tmp\u003c/em\u003e, \u003cem\u003eGeng\u003c/em\u003e/Japonica temperate. \u003cem\u003eGJ-sbtrp\u003c/em\u003e, \u003cem\u003eGeng\u003c/em\u003e/\u003cem\u003eJaponica \u003c/em\u003esubtropical. \u003cem\u003eGJ-trp\u003c/em\u003e, \u003cem\u003eGeng\u003c/em\u003e/Japonica tropical. \u003cem\u003eGJ-adm\u003c/em\u003e, \u003cem\u003eGeng\u003c/em\u003e/Japonica admixture. \u003cem\u003ecA\u003c/em\u003e, circum-Aus group. \u003cem\u003ecB\u003c/em\u003e, circum-Basmati group. Admix, admixed.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/98f04b95f03a349fcca0c179.jpeg"},{"id":54992792,"identity":"53f096bb-bf95-40dc-9e8e-f83e8c5e38b3","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":270375,"visible":true,"origin":"","legend":"\u003cp\u003eGenome-wide association scan for loci associated with panicle blast resistance to \u003cem\u003eM. oryzae\u003c/em\u003e in rice. A and C, Manhattan plots of panicle blast resistance on 12 rice chromosomes at 2020 (A) and 2022 (C). Red horizontal lines indicate genome-wide significance threshold -log10(\u003cem\u003ep\u003c/em\u003e) = 4.5. B and D, Quantile-quantile (Q-Q) plot for panicle blast disease resistance scores at 2020 (B) and 2022 (D). The vertical axis represents the observed probability value of SNP loci. The horizontal axis represents the expected probability of uniform distribution of SNP loci.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/5caa0fc13eb2c70c41f19899.jpeg"},{"id":54992788,"identity":"1fdeb8e9-2a56-4a5e-b593-b34b0c134b03","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":77047,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype and expression analysis of \u003cem\u003eOsGrp6\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA, Haplotype analysis of \u003cem\u003eOsGrp6\u003c/em\u003e. B and C, Rice blast resistance of \u003cem\u003eOsGrp6 \u003c/em\u003ehaplotype in 2020 (B) and 2022 (C). D, The gene expression of \u003cem\u003eOsGrp6\u003c/em\u003e in the pooled sequencing of disease-resistant and susceptible samples.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/fd61dea64bd1513dc194195b.jpeg"},{"id":54992789,"identity":"edf883e4-1f21-4419-bd59-58d322a50d45","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":89723,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype and expression analysis of \u003cem\u003eOsTrxl1\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA, Haplotype analysis of \u003cem\u003eOsTrxl1\u003c/em\u003e. B and C, Rice blast resistance of \u003cem\u003eOsTrxl1 \u003c/em\u003ehaplotype in 2020 (B) and 2022 (C). D, The gene expression of \u003cem\u003eOsTrxl1 \u003c/em\u003ein the pooled sequencing of disease-resistant and susceptible samples.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/40cee8e01f7f50552eb70da6.jpeg"},{"id":54992791,"identity":"87e8f2f7-795c-457e-abf2-1e33fac21239","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":88668,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype and expression analysis of \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA, Haplotype analysis of \u003cem\u003ePi25/Pid3\u003c/em\u003e. B and C, Rice blast resistance of \u003cem\u003ePi25/Pid3 \u003c/em\u003ehaplotype in 2020 (B) and 2022 (C). D, The gene expression of \u003cem\u003ePi25/Pid3\u003c/em\u003e in the pooled sequencing of disease-resistant and susceptible samples.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/158147beca9b7e8324e95ef2.jpeg"},{"id":60581789,"identity":"d3d60024-ed2d-445b-8c4a-d621939bb0e7","added_by":"auto","created_at":"2024-07-18 12:11:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1429621,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/c50e9593-cd15-422a-afcb-e240737af2c0.pdf"},{"id":54992794,"identity":"17031930-d0d3-40e6-87a4-a84a864d4a24","added_by":"auto","created_at":"2024-04-19 17:28:39","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3585965,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymolecularbreeding.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4255607/v1/967cc3fdf66b0ae5883635fa.xlsx"}],"financialInterests":"","formattedTitle":"A Genome-wide association study of panicle blast resistance (PBR) to Magnaporthe Oryzae in Rice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRice (\u003cem\u003eOryza sativa\u003c/em\u003e L.) stands as one of the paramount crops globally; nonetheless, its production is besieged by an array of diseases and pests (Li et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Chief among these maladies is rice blast, instigated by the ascomycete fungus \u003cem\u003eM. oryzae\u003c/em\u003e, which inflicts profound devastation (Deng and Naqvi \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The peril lies in \u003cem\u003eM. oryzae\u003c/em\u003e ability to assail rice plants across all developmental stages, precipitating yield reductions ranging from 10\u0026ndash;35% and consequent escalation the costs associated with chemical control. (Fisher et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nalley et al., 2016). Furthermore, the \u003cem\u003eM. oryzae\u003c/em\u003e population exhibits variability and complexity, categorizing into distinct physiological races based on varying pathogenicity, thereby exacerbating the challenge of disease management (Zhang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yin et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Hence, effective control of rice blast assumes paramount importance in safeguarding global food security.\u003c/p\u003e \u003cp\u003eBreeding blast-resistant cultivars harboring resistance genes emerges as the most economical and efficacious strategy for rice blast control (Li et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). \u003cem\u003eR\u003c/em\u003e genes, owing to their potent resistance effect and ease of selection, have been instrumental in blast resistance breeding efforts (Li et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, R genes frequently succumb to breakdown under the selection pressure engendered by the high variability of rice blast pathogens and the protracted cultivation of a single resistant variety over extensive areas (Wang et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ning et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Despite endeavors to mitigate this issue by pyramiding multiple R genes or QTL through marker-assisted selection to achieve broad-spectrum resistance, such approaches entail prolonged durations and elevated costs for breeders, as well as the risk of negative effects after the pyramiding of different R genes (Jiang et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hence, the exploration and exploitation of broad-spectrum resistance genes represent a viable avenue for enhancing the efficacy of rice blast control.\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated the involvement of certain R and defense-regulator (DR) genes in conferring broad-spectrum resistance to \u003cem\u003eM. oryzae\u003c/em\u003e (Li et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among these genes, \u003cem\u003ePigmR\u003c/em\u003e, an R gene, has been found to interact with the RNA recognition motif (RRM) domain-containing transcription factor PIBP1 (PigmR-INTERACTING and BLAST RESISTANCE PROTEIN 1). This interaction facilitates the nuclear translocation of PigmR-PIBP1 complex, subsequently activating the expression of downstream defense genes such as \u003cem\u003eOsWAK14\u003c/em\u003e and \u003cem\u003eOsPAL1\u003c/em\u003e. This coordinated activation leads to enhanced resistance against various strains of blast in rice (Deng et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhai et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Another notable gene, \u003cem\u003eBsr-d1\u003c/em\u003e, encodes a C2H2 transcription factor responsible for promoting the expression of catalase. Interestingly, loss-of-function mutations in \u003cem\u003ebsr-d1\u003c/em\u003e result in heightened blast resistance attributed to the accumulation of hydrogen peroxide within cells, achieved by the downregulation of catalase expression (Li et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, the gene \u003cem\u003ebsr-k1\u003c/em\u003e encodes a protein rich in tetratricopeptide repeats (TPRs) and exhibits RNA-binding activity. Bsr-k1 functions by binding to and promoting the degradation of \u003cem\u003eOsPAL1-7\u003c/em\u003e mRNAs, consequently inhibiting lignin synthesis. Loss-of-function mutations in \u003cem\u003ebsr-k1\u003c/em\u003e lead to enhanced blast resistance due to increased lignin accumulation in plants (Zhou et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDue to the trade-off between growth and resistance, plant defense activation often causes growth inhibition and yield reduction. Among those cloned \u003cem\u003eR\u003c/em\u003e genes, \u003cem\u003ePigm\u003c/em\u003e locus confers durable resistance to \u003cem\u003eM. oryzae\u003c/em\u003e without yield penalty due to tight epigenetic regulation of paired antagonistic nucleotide-binding site leucine-rich repeat (NLR) receptors (\u003cem\u003ePigmR\u003c/em\u003e and \u003cem\u003ePigmS\u003c/em\u003e) (Deng et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eIPA1\u003c/em\u003e promotes both yield and disease resistance through the strict phosphorylated state transform during rice blast infected (Wang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Therefore, the precise regulation of gene expression and protein modification can achieve the balancing between high resistance and yield, providing a theoretical guidance to develop elite crop varieties.\u003c/p\u003e \u003cp\u003eAmidst the wealth of genetic diversity within rice resource varieties lies a treasure trove for both breeding endeavors and genomics research (Wang et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e). Advancements in sequencing technologies have enabled the comprehensive resequencing of numerous rice varieties, resulting in the identification of a plethora of genetic variants (Zhao et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zheng et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Genome-wide association studies (GWAS) harnessing these abundant genetic variants have led to the identification of numerous genes governing complex and pivotal agronomic traits (Kang et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zhu et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xiao et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Notably, the 3000 Rice Genome Project (3K RGP) has emerged as an invaluable resource, offering extensive data for the mapping and cloning of key agronomic trait genes in rice (Li et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Science and World \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Alexandrov et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the significant yield losses attributed to panicle blast epidemics, particularly during the critical period of rice yield formation (Deng and Naqvi \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the mapping and cloning of blast broad-spectrum resistance genes hold immense potential for accelerating the development of disease-resistant, high-yielding rice varieties (Yin et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Notably, certain cloned R genes, such as \u003cem\u003ePi2\u003c/em\u003e and \u003cem\u003ePizt\u003c/em\u003e, have demonstrated markedly lower resistance against panicle blast compared to foliar blast in rice (Wu et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ning et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we conducted a genome-wide association study (GWAS) employing a panel comprising 477 accessions sourced from the 3000 rice germplasms. These accessions were subjected to infection by a combination of five representative \u003cem\u003eM. oryzae\u003c/em\u003e isolates in the years 2020 and 2022. Through this approach, we successfully identified 18 quantitative trait loci (QTLs) associated with panicle blast resistance. Additionally, through sequence analysis of select candidate genes within these identified QTLs, we unearthed promising candidates for utilization in rice blast disease resistance breeding programs.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eCharacterization and evaluation of panicle blast resistance in 477 sequenced rice accessions\u003c/h2\u003e\n\u003cp\u003eThere exists a rich reservoir of genetic diversity within the natural rice population. A comprehensive evaluation of rice panicle blast resistance was conducted on a total of 477 rice varieties sourced from 48 countries or regions as part of the 3000 Rice Genome Project (3K RGP). These 477 accessions were classified into five subspecies: \u003cem\u003eXian\u003c/em\u003e/\u003cem\u003eindica\u003c/em\u003e, \u003cem\u003eGeng\u003c/em\u003e/\u003cem\u003ejaponica\u003c/em\u003e, circum-Aus, circum-Basmati, and admixed. Further sub-grouping identified 12 distinct subgroups (\u003cem\u003eXI-1A\u003c/em\u003e, \u003cem\u003eXI-1B\u003c/em\u003e, \u003cem\u003eXI-2\u003c/em\u003e, \u003cem\u003eXI-3\u003c/em\u003e, \u003cem\u003eXI-adm\u003c/em\u003e, \u003cem\u003eGJ-tmp\u003c/em\u003e, \u003cem\u003eGJ-sbtrp\u003c/em\u003e, \u003cem\u003eGJ-trp\u003c/em\u003e, \u003cem\u003eGJ-adm\u003c/em\u003e, \u003cem\u003ecA\u003c/em\u003e, \u003cem\u003ecB\u003c/em\u003e, \u003cem\u003eAdmix\u003c/em\u003e) based on previous research findings. This comprehensive categorization facilitated a detailed examination of the panicle blast resistance across various genetic backgrounds and geographical origins (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). In 2020, a total of 374 rice accessions were subjected to inoculation with a mixture of five \u003cem\u003eM. oryzae\u003c/em\u003e isolates (2020\u0026thinsp;\u0026minus;\u0026thinsp;110, 2020\u0026thinsp;\u0026minus;\u0026thinsp;183, 2020\u0026thinsp;\u0026minus;\u0026thinsp;321, 2020\u0026thinsp;\u0026minus;\u0026thinsp;113, and 2020\u0026thinsp;\u0026minus;\u0026thinsp;353) at the booting stage, while 410 rice accessions underwent inoculation with a blend of five \u003cem\u003eM. oryzae\u003c/em\u003e isolates (2022\u0026thinsp;\u0026minus;\u0026thinsp;113, 2022\u0026thinsp;\u0026minus;\u0026thinsp;313, 2022\u0026thinsp;\u0026minus;\u0026thinsp;406, 2022\u0026thinsp;\u0026minus;\u0026thinsp;417, 2022\u0026thinsp;\u0026minus;\u0026thinsp;556, and 2022\u0026thinsp;\u0026minus;\u0026thinsp;586) at the booting stage in 2022. The average scale of rice panicle blast resistance (PBR) was measured at 3.1 and 5.7, ranging from 0 (no disease) to 9 (highly susceptible) in 2020 and 2022, respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). The wide spectrum of resistance variations observed across these rice germplasm accessions suggests significant genetic diversity associated with rice panicle blast resistance.\u003c/p\u003e\n\u003cp\u003eComparative analysis among different subspecies revealed that \u003cem\u003eXI-1A\u003c/em\u003e and \u003cem\u003eXI-1B\u003c/em\u003e exhibited higher blast resistance against the disease (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB; Table S2). The average blast resistance scales in \u003cem\u003eXI-1A\u003c/em\u003e and \u003cem\u003eXI-1B\u003c/em\u003e were 1.68 and 1.72, respectively, significantly lower than those observed in the GJ-tmp (5.3), GJ-trp (3.0), and GJ-adm (4.5) subspecies in 2020 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB; Table S2). Conversely, the average incidence of blast in the GJ-tmp subspecies reached 5.28, significantly higher than that observed in XI-1A and XI-1B in 2020 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB; Table S2).\u003c/p\u003e\n\u003cp\u003eIn the subsequent inoculation of 410 rice resources in 2022, the mean blast resistance value increased to 5.7 compared to 2020, potentially due to differences in virulence between the two years. Consistent with the findings of 2020, \u003cem\u003eXI-1A\u003c/em\u003e and \u003cem\u003eXI-1B\u003c/em\u003e exhibited higher blast resistance in 2022 compared to other subspecies. The average blast resistance scales in \u003cem\u003eXI-1A\u003c/em\u003e and \u003cem\u003eXI-1B\u003c/em\u003e were 5.7 and 3.5, respectively, significantly lower than those observed in the \u003cem\u003eGJ-tmp\u003c/em\u003e (7.2), \u003cem\u003eGJ-trp\u003c/em\u003e (5.8), and \u003cem\u003eGJ-adm\u003c/em\u003e (7.2) subspecies in 2022 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD; Table S3).\u003c/p\u003e\n\u003cp\u003eThese results highlight the significant divergence in rice panicle blast resistance among different subspecies, with \u003cem\u003eGJ-tmp\u003c/em\u003e demonstrating increased susceptibility compared to others. Among the 477 rice accessions, 23 were identified as possessing stably high resistance (rice panicle blast resistance scale\u0026thinsp;\u0026le;\u0026thinsp;1 in both 2020 and 2022) (Table S4). These 23 rice accessions represent promising germplasm resources for blast resistance breeding efforts.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eGWAS analysis of QTLs for rice panicle blast resistance\u003c/h2\u003e\n\u003cp\u003eA total of 2,918,100 and 2,914,029 single nucleotide polymorphisms (SNPs) distributed across the entire rice genome were selected for the genome-wide association study (GWAS) analysis of quantitative trait loci (QTLs) associated with rice panicle blast resistance in 2020 and 2022, respectively. In 2020, 27 QTLs encompassing 993 SNPs were identified as significantly associated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1.0 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) with rice panicle blast resistance in the 374 rice accessions (Table S5). Similarly, in 2022, 19 QTLs comprising 1,284 SNPs were significantly associated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1.0 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) with rice panicle blast resistance in the 410 rice accessions (Table S5). Notably, when \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1.0 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e, a rapid deviation between observed and predicted SNP values was observed (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD), suggesting that the significant correlation between genotype and phenotype was likely due to natural selection rather than genetic drift.\u003c/p\u003e\n\u003cp\u003eThese QTLs were distributed across chromosomes 1, 3, 4, 5, 6, 8, 9, 10, and 11 (Table S5). Among them, four QTL regions (\u003cem\u003eqPBR1-10\u003c/em\u003e, \u003cem\u003eqPBR1-11\u003c/em\u003e, \u003cem\u003eqPBR6-6\u003c/em\u003e, \u003cem\u003eqPBR10-2\u003c/em\u003e) contained four reported blast resistance genes (\u003cem\u003eOsAKT1\u003c/em\u003e, \u003cem\u003eOsRACK1A\u003c/em\u003e, \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e, \u003cem\u003eBsr-k1\u003c/em\u003e) (Table S5 and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). Only five QTLs (\u003cem\u003eqPBR1-5\u003c/em\u003e, \u003cem\u003eqPBR1-6\u003c/em\u003e, \u003cem\u003eqPBR6-4\u003c/em\u003e, \u003cem\u003eqPBR6-5\u003c/em\u003e, \u003cem\u003eqPBR6-6\u003c/em\u003e) exhibited stability across both 2020 and 2022, suggesting the presence of genes conferring broad-spectrum resistance to blast (Table S6 and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). Additionally, five QTLs (\u003cem\u003eqPBR6-3\u003c/em\u003e, \u003cem\u003eqPBR6-6\u003c/em\u003e, \u003cem\u003eqPBR8-1\u003c/em\u003e, \u003cem\u003eqPBR11-4\u003c/em\u003e, \u003cem\u003eqPBR11-6\u003c/em\u003e) exhibited -log10(\u003cem\u003ep\u003c/em\u003e) exceeding 6.0, indicating a significant correlation with rice blast resistance and warranting further investigation (Table S6). Hence, \u003cem\u003eqPBR1-10\u003c/em\u003e, \u003cem\u003eqPBR1-11, qPBR1-5\u003c/em\u003e, \u003cem\u003eqPBR1-6\u003c/em\u003e, \u003cem\u003eqPBR6-3\u003c/em\u003e, \u003cem\u003eqPBR6-4\u003c/em\u003e, \u003cem\u003eqPBR6-5\u003c/em\u003e, \u003cem\u003eqPBR6-6\u003c/em\u003e, \u003cem\u003eqPBR8-1\u003c/em\u003e, \u003cem\u003eqPBR10-2\u003c/em\u003e, \u003cem\u003eqPBR11-4\u003c/em\u003e, and \u003cem\u003eqPBR11-6\u003c/em\u003e were identified as more significant targets for candidate panicle blast resistance gene discovery.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003ePutative candidate genes for twelve QTL intervals\u003c/h2\u003e\n\u003cp\u003eThe twelve blast resistance QTL intervals obtained from the above analysis were further screened, resulting in a total of 277 annotated genes are found (Table S7). After screening non-synonymous SNP, 67 genes exhibit non-synonymous SNP sites in exon or within the up/downstream regions of 3 kb, which \u003cem\u003eP\u003c/em\u003e-values less than 3.16 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e (Table S8). Among them, 2 genes were obtained on \u003cem\u003ePBR1-5\u003c/em\u003e, 1 gene were obtained on \u003cem\u003ePBR1-6\u003c/em\u003e, 2 genes were obtained on \u003cem\u003ePBR1-10\u003c/em\u003e, 2 genes were obtained on \u003cem\u003ePBR1-11\u003c/em\u003e, 3 genes were obtained on \u003cem\u003ePBR6-3\u003c/em\u003e, 46 genes were obtained on \u003cem\u003ePBR6-6\u003c/em\u003e, 9 genes were obtained on \u003cem\u003ePBR8-1\u003c/em\u003e, 1 gene were obtained on \u003cem\u003ePBR10-2\u003c/em\u003e, 1 gene were obtained on \u003cem\u003ePBR11-6\u003c/em\u003e (Table S8).\u003c/p\u003e\n\u003cp\u003eThe twelve blast resistance QTL intervals identified in the preceding analysis were further scrutinized, leading to the identification of a total of 277 annotated genes (Table S7). Subsequent screening for non-synonymous single nucleotide polymorphisms (SNPs) revealed 67 genes harboring non-synonymous SNP sites within exons or within the up/downstream regions of 3 kb, with \u003cem\u003eP\u003c/em\u003e-values less than 3.16 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e (Table S8). Among these, 2 genes were identified within the \u003cem\u003ePBR1-5\u003c/em\u003e interval, 1 gene within \u003cem\u003ePBR1-6\u003c/em\u003e, 2 genes within \u003cem\u003ePBR1-10\u003c/em\u003e, 2 genes within \u003cem\u003ePBR1-11\u003c/em\u003e, 3 genes within \u003cem\u003ePBR6-3\u003c/em\u003e, 46 genes within \u003cem\u003ePBR6-6\u003c/em\u003e, 9 genes within \u003cem\u003ePBR8-1\u003c/em\u003e, 1 gene within \u003cem\u003ePBR10-2\u003c/em\u003e, and 1 gene within \u003cem\u003ePBR11-6\u003c/em\u003e (Table S8). Only one significant SNP locus is found upstream of the ATG of \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e among the four rice blast resistance genes detected within the identified QTL intervals. The coding, upstream, and downstream regions of \u003cem\u003eOsAKT1\u003c/em\u003e, \u003cem\u003eOsRACK1A\u003c/em\u003e, and \u003cem\u003eBsr-k1\u003c/em\u003e do not contain significant SNP loci.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eExpression patterns of rice panicle blast resistance Genes\u003c/h2\u003e\n\u003cp\u003eRice blast resistance genes demonstrate significant differential expression between resistant and susceptible varieties following rice blast infection. Thus, we selected five highly resistant rice varieties (IRIS_313\u0026ndash;8067, IRIS_313\u0026ndash;8148, IRIS_313\u0026ndash;9925, CX393, and IRIS_313-11538) alongside five highly susceptible rice varieties (IRIS_313\u0026ndash;8039, IRIS_313-10430, IRIS_313-10642, B154, and IRIS_313\u0026ndash;8204) for rice blast inoculation at the seedling stage. Tissue samples were collected 72 hours post-inoculation, with tissues pooled from both highly susceptible and highly resistant varieties for RNA-seq analysis. A total of 24,891 differentially expressed genes were identified, with 1,510 genes showing significantly higher expression levels in the mixed pool of resistant varieties compared to the mixed pool of susceptible varieties, and 2,681 genes exhibiting significantly lower expression levels in the mixed pool of resistant varieties compared to the mixed pool of susceptible varieties (Table S9). Additionally, among the 67 candidate genes identified in the GWAS analysis, 14 genes demonstrated significant differential expression in the pooled sequencing of disease-resistant and susceptible samples. These genes were \u003cem\u003eOs01g0686100\u003c/em\u003e, \u003cem\u003eOs06g0306600\u003c/em\u003e, \u003cem\u003eOs06g0316800\u003c/em\u003e, \u003cem\u003eOs06g0318533\u003c/em\u003e, \u003cem\u003eOs06g0320000\u003c/em\u003e, \u003cem\u003eOs06g0320500\u003c/em\u003e, \u003cem\u003eOs06g0321700\u003c/em\u003e, \u003cem\u003eOs06g0323100\u003c/em\u003e, \u003cem\u003eOs06g0324000\u003c/em\u003e, \u003cem\u003eOs06g0325602\u003c/em\u003e, \u003cem\u003eOs06g0326400\u003c/em\u003e, \u003cem\u003eOs06g0329350\u003c/em\u003e, \u003cem\u003eOs06g0330100\u003c/em\u003e and \u003cem\u003eOs08g0135500\u003c/em\u003e (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eFunctional annotation of 14 candidate genes\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eQTL\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eLocus ID\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDescription\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elog2(foldchange) for HR VS HS\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003epadj\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edirection\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\u003ePBR1-11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs01g0686100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConserved hypothetical protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-2.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.39E-03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0306600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEsterase/lipase/thioesterase domain containing protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.91E-04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0316800\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSimilar to Glycine-rich protein (Fragment)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.31E-02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eup\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0318533\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eexpressed protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-9.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.06E-11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0320000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eProtein of unknown function DUF953, thioredoxin-like family protein\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.09E-03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eup\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0320500\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSimilar to Light-harvesting complex I (Fragment)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.62E-10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eup\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0321700\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConserved hypothetical protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-1.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.25E-02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0323100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eindole-3-acetate O-methyltransferase 1-like\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-8.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.23E-09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0324000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConserved hypothetical protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-5.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.84E-03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0325602\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypothetical gene. (Os06t0325602-00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-5.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.09E-04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0326400\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePyrophosphate-dependent phosphofructokinase PfpB family protein.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.76E-03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eup\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0329350\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eexpressed protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-10.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.94E-14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR8-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs08g0135500\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX8 domain containing protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e-5.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.59E-04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edown\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBR6-6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOs06g0330100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDisease resistance protein family protein.\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eup\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\u003e\u003cem\u003eOsGrp6/Os06g0316800\u003c/em\u003e encodes a protein similar to Glycine-rich protein, an important component of plant cell walls involved in cellular stress responses and signaling (Ringli et al. \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; Czolpinska and Rurek \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eOsTrxl1\u003c/em\u003e/\u003cem\u003eOs06g0320000\u003c/em\u003e encodes a protein of unknown function DUF953, belonging to the thioredoxin-like family, crucial for maintaining reactive oxygen species (ROS) homeostasis in vivo (Hu et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Lastly, \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e/\u003cem\u003eOs06g0330100\u003c/em\u003e encodes a disease resistance protein, emphasizing its potential significance in plant biology (Zhou et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). These five genes warrant further exploration and attention due to their potential importance in plant biology.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eAnalysis of three Candidate Gene Haplotype by RFGB Database\u003c/h2\u003e\n\u003cp\u003eIn the upstream region of the ATG start codon of the \u003cem\u003eOsGrp6\u003c/em\u003e gene, a notable SNP locus at 555 bp (Chr6_12253876, A/C) has been identified (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). Utilizing this SNP variant information, haplotype analysis of the \u003cem\u003eOsGrp6\u003c/em\u003e gene was conducted on the RFGB Database website. The analysis revealed two distinct haplotypes for \u003cem\u003eOsGrp6\u003c/em\u003e, with resistance levels to rice blast observed as 2.11 and 4.77 in 2020, and 4.79 and 7.27 in 2022, displaying statistically significant differences (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA-\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC). The expression level of \u003cem\u003eOsGrp6\u003c/em\u003e was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation(Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD). Among the 23 identified high-resistant germplasm resources, 21 were found to carry the Hap1 haplotype (Table S4), indicating potential involvement in rice blast resistance.\u003c/p\u003e\n\u003cp\u003eIn the upstream or downstream region of the ATG start codon of the \u003cem\u003eOsTrxl1\u003c/em\u003e gene, six notable SNP loci at 555 bp to 1375 bp (Chr6_12433018, C/T; Chr6_ 12433210, T/C; Chr6_ 12433295, G/A; Chr6_ 12433438, C/T; Chr6_ 12433662, G/A; Chr6_12433816, C/T) have been identified (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). In the downstream region of the ATG stop codon of the \u003cem\u003eOsTrxl1\u003c/em\u003e gene, one notable SNP locus at 1633 bp (Chr6_ 12430293, T/C) has been identified (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). Utilizing this SNP variant information, haplotype analysis of the \u003cem\u003eOsTrxl1\u003c/em\u003e gene was conducted on the RFGB Database website. The analysis indicated three haplotypes for \u003cem\u003eOsTrxl1\u003c/em\u003e Hap1 and Hap3 with resistance levels to rice blast observed as 2.09 and 2.94 in 2020, and 4.84 and 6.64 in 2022, and Hap2 with resistance levels to rice blast observed as 5.38 in 2020, and 7.47 in 2022, displaying statistically significant differences (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA-\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). The expression level of \u003cem\u003eOsTrxl1\u003c/em\u003e was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD). Among the 23 identified high-resistant germplasm resources, 17 were found to carry the Hap1 haplotype (Table S4), suggesting potential involvement in rice blast resistance.\u003c/p\u003e\n\u003cp\u003eIn the upstream region of the ATG start codon of the \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e gene, a notable SNP locus at 152 bp (Chr6_13058179, A/C) has been identified (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA). Utilizing this SNP variant information, haplotype analysis of the \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e gene was conducted on the RFGB Database website. The analysis revealed two distinct haplotypes for \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e, with resistance levels to rice blast observed as 2.11 and 4.65 in 2020, and 4.80 and 7.18 in 2022, showing statistically significant differences (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA-\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC). The expression level of \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e was significantly higher in resistant samples compared to susceptible samples after 48h of inoculation (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eD). Among the 23 identified high-resistant germplasm resources, 21 were found to carry the Hap1 haplotype (Table S4), suggesting potential involvement in rice blast resistance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eRice blast is a serious threat to the yield and quality of rice, especially at heading stage. However, most of the rice varieties with high yield and good quality are highly susceptible to blast (Xiao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, explore blast resistance genes and introduce them into susceptible varieties by marker-assisted selection method is an economical and effective strategy to develop blast resistant varieties. In this study, 477 sequenced rice germplasm resources were used to identify panicle blast resistance, and 23 rice materials with high blast resistance were screened (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table S4). These 23 rice blast resistant materials consisted of different genetic backgrounds, including 4 \u003cem\u003eXI-1A\u003c/em\u003e, 9 \u003cem\u003eXI-1B\u003c/em\u003e, 1 XI-2, 4 \u003cem\u003eXI-adm\u003c/em\u003e, 3 \u003cem\u003eGJ-tmp\u003c/em\u003e, 2 cA and 1 Admix (Table S4), which could provide rich genetic materials for blast resistance breeding.\u003c/p\u003e \u003cp\u003eRice blast poses a significant threat to both the yield and quality of rice, particularly during the heading stage. However, many rice varieties known for their high yield and quality are highly susceptible to blast (Xiao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, employing the marker-assisted selection method to explore blast resistance genes and introduce them into susceptible varieties proves to be an economical and effective strategy for developing blast-resistant varieties. In this study, 477 sequenced rice germplasm resources were utilized to identify panicle blast resistance, resulting in the screening of 23 rice materials exhibiting high blast resistance (refer to Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table S4). These 23 rice blast-resistant materials encompass various genetic backgrounds, including 4 \u003cem\u003eXI-1A\u003c/em\u003e, 9 \u003cem\u003eXI-1B\u003c/em\u003e, 1 \u003cem\u003eXI-2\u003c/em\u003e, 4 \u003cem\u003eXI-adm\u003c/em\u003e, 3 \u003cem\u003eGJ-tmp\u003c/em\u003e, 2 \u003cem\u003ecA\u003c/em\u003e, and 1 \u003cem\u003eAdmix\u003c/em\u003e (Table S4), thus providing diverse genetic materials for blast resistance breeding.\u003c/p\u003e \u003cp\u003eUnder the strong selection pressure of disease-resistant host, pathogenic virulent races will evolve the ability to suppress host immunity by multiple pathogen effectors, and the host resistance loss will further evolve new resistance response to resist the invasion of pathogenic bacteria (Shi et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhai et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Because of the arms race between plants and pathogens, rice varieties with a single resistance gene planted on a large scale over a long period of time will run the risk of resistance broken-down (Kou and Wang \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pe\u0026ntilde;alver Cruz et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, exploring rich and diverse blast resistance gene resources and using them in breeding will contribute to develop rice varieties with durable and broad-spectrum blast resistance. This study screened 23 highly resistant germplasm resources after two years of mixed inoculation with various physiological races of rice blast, offering a diverse array of resources for rice blast resistance breeding. Among the 43 identified QTLs, \u003cem\u003eqPBR6-4/5/6\u003c/em\u003e appeared in GWAS analyses for both years and contained numerous significant SNP loci. This suggests that the \u003cem\u003eqPBR6-4/5/6\u003c/em\u003e rice blast resistance loci merit further gene cloning and utilization in breeding programs.\u003c/p\u003e \u003cp\u003eWe combined gene expression data obtained after inoculating resistant and susceptible rice varieties with the rice blast pathogen, and identified four target candidate genes. These four genes exhibited significant differences in rice blast resistance among different haplotypes. Molecular markers can be developed based on SNP sites on these three genes for molecular marker-assisted selection in breeding. During rice blast infection, the fungus typically invades surface cells by penetrating appressoria and releases effectors to suppress the host resistance response (Yan et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Further investigation is warranted to determine whether the glycine-rich protein encoded by \u003cem\u003eOsGrp6\u003c/em\u003e interacts with effectors released during rice blast infection and triggers resistance responses in host cells. After successful invasion of host cells by the rice blast pathogen, it induces the accumulation of reactive oxygen species (ROS) in host cells and triggers programmed cell death to control fungal growth (Liu et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sha et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The thioredoxin-like protein encoded by \u003cem\u003eOsTrxl1\u003c/em\u003e is involved in regulating the ROS homeostasis in cells, potentially promoting the accumulation of ROS during pathogen infection and enhancing rice blast resistance. \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e, as a typical \u003cem\u003eR\u003c/em\u003e gene, encodes an NBS-LRR protein capable of recognizing effectors released by the rice blast pathogen, triggering downstream resistance responses (Zhou et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Through genome-wide association analysis, we identified an SNP site upstream of \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e ATG that enhances gene transcription levels, thereby improving resistance to rice blast. This new allele genotype of \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e can be utilized in rice blast resistance breeding.\u003c/p\u003e \u003cp\u003eRice \u003cem\u003eR\u003c/em\u003e genes usually encodes nucleotide-binding site leucine-rich repeat (NLR) proteins, which can recognized specific avirulence (AVR) protein of specific blast race, leading to a particularly strong immune response (Yin et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Compared to the \u003cem\u003eR\u003c/em\u003e gene, defense-regulator (DR) genes often confer partial but durable resistance to a broad spectrum of pathogen races (Li et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In order to identify new DR genes with broad-spectrum resistance, 477 rice varieties were inoculated with a mixture of 5 blast races in this study. \u003cem\u003eOsTrxl1\u003c/em\u003e may through regulate ROS homeostasis to confer blast resistance, so whether it has broad-spectrum blast resistance is worth for further study.\u003c/p\u003e \u003cp\u003eIn conclusion, the high blast resistance rice varieties identified in this study, as well as associated SNPs and favorable haplotypes, should be contribute to the development of blast resistance rice varieties through molecular marker-assisted selection.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and growth conditions\u003c/h2\u003e \u003cp\u003eA total of 477 rice accessions collected from 48 countries or regions in The 3000 Rice Genomes Project (3K RGP) were selected to evaluate panicle blast resistance to \u003cem\u003eMagnaporthe Oryzae\u003c/em\u003e (Li et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Science and World \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRice plants were cultivated one line for each accession, 10 plants in each line, conventional water and fertilizer management. All seeds in 3K RGP were provided by the Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China (Zhen et al. 2015).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFungal materials and inoculation\u003c/h2\u003e \u003cp\u003eThe five representative \u003cem\u003eM. oryzae\u003c/em\u003e isolates (2020\u0026thinsp;\u0026minus;\u0026thinsp;110, 2020\u0026thinsp;\u0026minus;\u0026thinsp;183, 2020\u0026thinsp;\u0026minus;\u0026thinsp;321, 2020\u0026thinsp;\u0026minus;\u0026thinsp;113, 2020\u0026thinsp;\u0026minus;\u0026thinsp;353) were identified by 31 near-monogenic lines in 2020, that provided by Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences (Qi et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The six representative \u003cem\u003eM. oryzae\u003c/em\u003e isolates (2022\u0026thinsp;\u0026minus;\u0026thinsp;113、2022\u0026thinsp;\u0026minus;\u0026thinsp;313、2022\u0026thinsp;\u0026minus;\u0026thinsp;406、2022\u0026thinsp;\u0026minus;\u0026thinsp;417、2022\u0026thinsp;\u0026minus;\u0026thinsp;556 and 2022\u0026thinsp;\u0026minus;\u0026thinsp;586) were identified by 24 near-monogenic lines in 2022, that provided by Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences (Qi et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Method of spore culture and inoculation was performed as previously described (Wang et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Briefly, the tested strains were transplanted into solid medium (corn powder 40 g, rice stalk powder 50 g, agar powder 20 g) and cultured in darkness at 28 ℃ for 7 days. Then, treated with black light lamp (λ\u0026thinsp;=\u0026thinsp;330-400nm) for 72 h, spores of \u003cem\u003eM. oryzae\u003c/em\u003e isolate were produced and washed with sterile water. The spores of each \u003cem\u003eM. oryzae\u003c/em\u003e isolates were dilute into a suspension of 10\u003csup\u003e5\u003c/sup\u003e/mL. At the early stage of rice booting, 1 mL mixed suspension spores of 5 representative \u003cem\u003eM. oryzae\u003c/em\u003e isolates were injected into each rice panicle, and the inoculation time was after 5 PM every day. Each rice accession was inoculated with 5 panicles/accession.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of Blast Resistance\u003c/h2\u003e \u003cp\u003eAfter inoculation, the blast resistance was investigated according to the 0\u0026ndash;9 score classification standard of single panicle loss rate of rice panicle blast, which in the mature stage of rice. The classification standard refer to the technical regulations for identification and evaluation of blast resistance in rice variety test issued by ministry of Agriculture (NY/T2646-2014). Detailed description is as follows: 0, no disease. 1, the incidence of branchlets, loss per panicle\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;5.0%. 3, spindle or panicle disease, loss per panicle 5.1%-20.0%. 5, spindle or panicle disease, grain half deflated, loss of 20.1%-50.0% per panicle. 7, panicle disease, most deflated grain, loss of 50.1%-70.0% per panicle. 9, panicle disease, loss per panicle\u0026thinsp;\u0026gt;\u0026thinsp;70.0%. Three main panicles with similar resistance performance were selected to average the score of each accession.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGenome-wide association analysis\u003c/h2\u003e \u003cp\u003eThe GWAS SNP Dataset of the 477 rice accessions were downloaded from the Rice SNP-Seek Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://snp-seek.irri.org/\u003c/span\u003e\u003cspan address=\"http://snp-seek.irri.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). These SNP variations and positions were identified based on the assembly Os-Nipponbare-Reference-IRGSP-1.0 (Alexandrov et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Then, the data was filtered by plink 1.90 (Chang et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), according to minor allele frequency (MAF)\u0026thinsp;\u0026gt;\u0026thinsp;0.1 and missing call rate\u0026thinsp;\u0026lt;\u0026thinsp;0.1. We used EMMAX software (Kang et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) to detect the SNPs associated with rice panicle blast resistance. The Manhattan and Quantile-Quantile (Q-Q) plots were drawn by R package CMplot. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e was used as the threshold to screen the marker significantly associated with resistance of rice panicle blast. A QTL was declared if a region has two or more than two significant SNPs within a 200 kb interval. The candidate genes were searched from 200 kb upstream and downstream of the most significant SNP in each QTL, which using the reference Nipponbare genome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rice.uga.edu/cgi-bin/gbrowse/rice/\u003c/span\u003e\u003cspan address=\"http://rice.uga.edu/cgi-bin/gbrowse/rice/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGene haplotype analysis\u003c/h2\u003e \u003cp\u003e \u003cem\u003eOsGrp6\u003c/em\u003e, \u003cem\u003eOsTrxl1\u003c/em\u003e and \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e haplotype analysis was performed on the \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://snp-seek.irri.org/\" target=\"_blank\"\u003ewww.rmbreeding.cn/Index/(Wang et al. 2020)\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.rmbreeding.cn/Index/(Wang et al. 2020)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e .The base sequence of \u003cem\u003eOsGrp6\u003c/em\u003e, \u003cem\u003eOsTrxl1\u003c/em\u003e and \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e mutation locus was downloaded from the \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ricevarmap.ncpgr.cn/(Zhao et al. 2021)\u003c/span\u003e\u003cspan address=\"http://ricevarmap.ncpgr.cn/(Zhao et al. 2021)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e and analyzed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Project funded by China Postdoctoral Science Foundation (2021M702767), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHJL, ZJY and FZM conceived and designed the experiments. HJL, ZY, WRZ, WXY, XQQ, ZNB and ZJY performed the experiments and analyzed the data. HJL and ZJY was responsible for material plant and field management. HJL wrote the manuscript. WHY, ZY, FZM and ZHC revised the manuscript. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe owe special thanks to Professor Jianlong Xu (Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China) for providing the seeds in 3K RGP, to Professor Yongfeng Liu (Institute of Plant Protection, Jiangsu Academy of Agricultural Science, Nanjing, China) for providing the \u003cem\u003eM. oryzae\u003c/em\u003e isolates (2020-110, 2020-183, 2020-321, 2020-113, 2020-353).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlexandrov N, Tai S, Wang W, et al (2015) SNP-Seek database of SNPs derived from 3000 rice genomes. 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Rice 9:. https://doi.org/10.1186/s12284-016-0116-3\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-breeding","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"molb","sideBox":"Learn more about [Molecular Breeding](https://www.springer.com/journal/11032)","snPcode":"11032","submissionUrl":"https://submission.nature.com/new-submission/11032/3","title":"Molecular Breeding","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"panicle blast resistance, Rice (Oryza sativa L.), genome-wide association study (GWAS)","lastPublishedDoi":"10.21203/rs.3.rs-4255607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4255607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRice blast, caused by \u003cem\u003eMagnaporthe Oryzae\u003c/em\u003e (\u003cem\u003eM. oryzae\u003c/em\u003e), is one of the most serious diseases all over the world. Development of blast-resistant rice varieties can effectively control the damage of rice blast and reduce the application of chemical pesticides. In this study, 477 sequenced rice germplasms from 48 countries were inoculated and identified at booting stage. We found that 23 germplasms displayed high panicle blast resistance against \u003cem\u003eM. oryzae.\u003c/em\u003e 43 quantitative trait loci (QTLs) significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) associated with rice panicle blast resistance were identified by genome-wide association analysis (GWAS). These QTL intervals contain four genes (\u003cem\u003eOsAKT1\u003c/em\u003e, \u003cem\u003eOsRACK1A\u003c/em\u003e, \u003cem\u003eBsr-k1\u003c/em\u003e and \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e) have been reported to be involved in rice blast resistance. We select QTLs with -Log10(Pvalue) higher than 6.0 or those detected in two-year replicates, totaling 12 QTLs, for candidate gene analysis. We identified three blast resistance candidate genes (\u003cem\u003eOs06g0316800\u003c/em\u003e, \u003cem\u003eOs06g0320000\u003c/em\u003e, \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e) based on the significant SNP distribution of annotated gene sequences in these 12 QTL and the difference of expression levels among blast resistant varieties after 72h inoculation. \u003cem\u003eOs06g0316800\u003c/em\u003e encodes a protein similar to Glycine-rich protein, an important component of plant cell walls involved in cellular stress responses and signaling, named as \u003cem\u003eOsGrp6\u003c/em\u003e. \u003cem\u003eOs06g0320000\u003c/em\u003e encodes a protein of unknown function DUF953, belonging to the thioredoxin-like family, crucial for maintaining reactive oxygen species (ROS) homeostasis in vivo, named as \u003cem\u003eOsTrxl1\u003c/em\u003e. Lastly, \u003cem\u003ePi25\u003c/em\u003e/\u003cem\u003ePid3\u003c/em\u003e encodes a disease resistance protein, emphasizing its potential significance in plant biology. By analyzing the haplotypes of these 3 genes, we identified the favorable haplotypes with blast resistance, which will provide genetic resources for future rice blast resistance breeding.\u003c/p\u003e","manuscriptTitle":"A Genome-wide association study of panicle blast resistance (PBR) to Magnaporthe Oryzae in Rice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-19 17:28:34","doi":"10.21203/rs.3.rs-4255607/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-04-26T01:47:05+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-16T00:53:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-14T23:08:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Breeding","date":"2024-04-12T01:54:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-breeding","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"molb","sideBox":"Learn more about [Molecular Breeding](https://www.springer.com/journal/11032)","snPcode":"11032","submissionUrl":"https://submission.nature.com/new-submission/11032/3","title":"Molecular Breeding","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0ae4373d-70c8-4053-91b0-6e827909af37","owner":[],"postedDate":"April 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-07-18T12:10:54+00:00","versionOfRecord":{"articleIdentity":"rs-4255607","link":"https://doi.org/10.1007/s11032-024-01486-5","journal":{"identity":"molecular-breeding","isVorOnly":false,"title":"Molecular Breeding"},"publishedOn":"2024-07-01 12:10:54","publishedOnDateReadable":"July 1st, 2024"},"versionCreatedAt":"2024-04-19 17:28:34","video":"","vorDoi":"10.1007/s11032-024-01486-5","vorDoiUrl":"https://doi.org/10.1007/s11032-024-01486-5","workflowStages":[]},"version":"v1","identity":"rs-4255607","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4255607","identity":"rs-4255607","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}