In autumn 2020, leaf blight was observed on rice (Oryza sativa L., variety Zhongzao39, Yongyou9, Yongyou12, Yongyou15, Yongyou18, Yongyou1540, Zhongzheyou8, Jiafengyou2, Xiangliangyou900 and Jiyou351) in the fields of 17 towns in Zhejiang and Jiangxi Provinces, China. The disease incidence was 45%-60%. Initially, water-soaked, linear, light brown lesions emerged in the upper blades of the leaves, and then spread down to leaf margins, which ultimately caused leaf curling and blight during the booting-harvest stage (Fig. S1). The disease symptoms were assumed to be caused by Xanthomonas oryzae pv. oryzae (Xoo), the pathogen of rice bacterial blight. 63 isolates were obtained from the collected diseased leaves as previously described (Hou et al. 2020). All isolates showed circular, smooth-margined, yellow colonies when cultured on peptone sugar agar (PSA) medium for 24h at 28℃. The cells were all gram-negative and rod-shaped with three to six peritrichous flagella; positive for catalase, indole, glucose fermentation and citrate utilization, while negative for oxidase, alkaline, phenylalanine deaminase, urease, and nitrate reductase reactions. 16S rRNA gene sequence analysis from the 6 isolates (FY43, JH31, JH99, TZ20, TZ39 and TZ68) revealed that the amplified fragments shared 98% similarity with Pantoea ananatis type strain LMG 2665T (GenBank JFZU01) (Table S3). To further verify P. ananatis identity of these isolates, fragments of three housekeeping genes including gyrB, leuS and rpoB from the 6 isolates were amplified and sequenced, which showed highest homology to LMG 2665T with a sequence similarity of 95%-100% (Table S3). Primers (Brady et al. 2008) and GenBank accession numbers of gene sequences from the 6 isolates are listed in Table S1 and Table S2. Phylogenetic analysis of gyrB, leuS and rpoB concatenated sequences indicated that the 6 isolates were clustered in a stable branch with P. ananatis (Fig. S2). Based on the above morphological, physiological, biochemical and molecular data, the isolates are identified as P. ananatis. For pathogenicity tests, bacterial suspension at 108 CFU/mL was inoculated into flag leaves of rice (cv. Zhongzao39) at the late booting stage using clipping method. Water was used as a negative control. The clipped leaves displayed water-soaked lesions at 3 to 5 days after inoculation (DAI); then the lesion spread downward and turned light brown. At about 14 DAI, blight was shown with similar symptoms to those samples collected from the rice field of Zhejiang and Jiangxi provinces (Fig. S1). In contrast, the control plants remained healthy and symptomless. The same P. ananatis was re-isolated in the inoculated rice plants, fulfilling Koch's postulates. In the past decade, P. ananatis has been reported to cause grain discoloration in Hangzhou, China (Yan et al. 2010) and induce leaf blight as a companion of Enterobacter asburiae in Sichuan province, China (Xue et al. 2020). Nevertheless, to the best of our knowledge, this is the first report of P. ananatis as the causative agent of rice leaf blight in southeast China. This study raises the alarm that the emerging rice bacterial leaf blight in southeast China might be caused by a new pathogen P. ananatis, instead of Xoo as traditionally assumed. Further, the differences of occurrence, spread and control between two rice bacterial leaf blight diseases caused by P. ananatis and Xoo, respectively need to be determined in the future.

Bakanae disease, caused by the fungus Fusarium fujikuroi, occurs widely throughout Asia and Europe and sporadically in other rice production areas. Recent changes in climate and cropping patterns have aggravated this disease. To gain a better understanding of the molecular mechanisms of rice bakanae disease resistance, we employed a 6-plex tandem mass tag approach for relative quantitative proteomic comparison of infected and uninfected rice seedlings 7 days post-inoculation with two genotypes: the resistant genotype 93–11 and the susceptible genotype Nipponbare. In total, 123 (77.2% up-regulated, 22.8% down-regulated) and 91 (94.5% up-regulated, 5.5% down-regulated) differentially expressed proteins (DEPs) accumulated in 93–11 and Nipponbare, respectively. Only 11 DEPs were both shared by the two genotypes. Clustering results showed that the protein regulation trends for the two genotypes were highly contrasting, which suggested obviously different interaction mechanisms of the host and the pathogen between 93 and 11 and Nipponbare. Further analysis showed that a noticeable aquaporin, PIP2–2, was sharply upregulated with a fold change (FC) of 109.2 in 93–11, which might be related to pathogen defense and the execution of bakanae disease resistance. Certain antifungal proteins were regulated in both 93–11 and Nipponbare with moderate FCs. These proteins might participate in protecting the cellular integrity required for basic growth of the susceptible genotype. Correlation analysis between the transcriptome and proteome revealed that Pearson correlation coefficients of R = 0.677 (P = 0.0005) and R = − 0.097 (P = 0.702) were obtained for 93–11 and Nipponbare, respectively. Our findings raised an intriguing result that a significant positive correlation only in the resistant genotype, while no correlation was found in the susceptible genotype. The differences in codon usage was hypothesized for the cause of the result. Quantitative proteomic analysis of the rice genotypes 93-11and Nipponbare after F. fujikuroi infection revealed that the aquaporin protein PIP2–2 might execute bakanae disease resistance. The difference in the correlation between the transcriptome and proteome might be due to the differences in codon usage between 93-11and Nipponbare. Overall, the protein regulation trends observed under bakanae disease stress are highly contrasting, and the molecular mechanisms of disease defense are obviously different between 93 and 11 and Nipponbare. In summary, these findings deepen our understanding of the functions of proteins induced by bakanae disease and the mechanisms of rice bakanae disease resistance.

Bakanae disease is mainly caused by Fusarium fujikuroi and is a significant fungal disease with a number of disastrous consequences. It causes great losses in rice production. However, few studies have focused on the details of bakanae disease resistance in rice. Here, we summarize and discuss the progress of bakanae disease resistance in rice. Besides rice germplasm screening and resistance-related gene/quantitative trait locus (QTL) exploration, the route of pathogen invasion in rice plants was determined. We further discussed the regulation of phytohormone-related genes and changes in endogenous phytohormones in rice plants that are induced by the pathogen. To achieve better control of bakanae disease, the use of natural fungicides was assessed in this review. During rice—F. fujikuroi interactions, the infection processes and spatial distribution of F. fujikuroi in infected seedlings and adult plants exhibit different trends. Fungal growth normally occurs both in resistant and susceptible cultivars, with less abundance in the former. Generally, bakanae disease is seed-borne, and seed disinfection using effective fungicides should always be the first and main option to better control the disease. Besides the friendly and effective measure of using natural fungicides, breeding and utilization of resistant rice cultivars is also an effective control method. To some extent, rice cultivars with low grain quality, indica subspecies, and some dwarf or semi-dwarf rice germplasms are more resistant to bakanae disease. Although no highly resistant germplasms were obtained, 37 QTLs were located, with almost half of the QTLs being located on chromosome 1. Using omics methods, WRKYs and MAPKs were usually found to be regulated during rice—F. fujikuroi interactions. The regulation of certain phytohormone-related genes and changes in some endogenous phytohormones induced by the pathogen were clear, i.e., it downregulated gibberellin-related genes and repressed endogenous gibberellins in resistant genotypes, but the opposite results were noted in susceptible rice genotypes. Overall, exploring resistant germplasms or resistance-related genes/QTLs for the breeding of rice with bakanae disease resistance, expanding research on the complex mechanism of rice—F. fujikuroi interactions, and using cost-effective and eco-friendly innovative control methods against the disease are necessary for present and future bakanae disease management.

Xanthomonas oryzae pv. oryzae (Xoo) is a causative agent of rice bacterial blight (BB). In 2020–2022, BB re-emerged, and there was a break out in the Yangtze River area, China. The pandemic Xoo strain, LA20, was isolated and identified from cultivar Quanyou1606 and demonstrated to be the Chinese R9 Xoo strain, which is able to override the widely adopted xa5-, Xa7- and xa13-mediated resistance in rice varieties in Yangtze River. Here, we report the complete genome of LA20 by PacBio and Illumina sequencing. The assembled genome consists of one circular chromosome of 4,960,087 bp, sharing 99.65% sequence identity with the traditional representative strain, YC11 (R5), in the Yangtze River. Comparative genome analysis of LA20 and YC11 revealed the obvious variability in Tal genes (the uppermost virulence determinants) in numbers and sequences. Particularly, six Tal genes were only found in LA20, but not in YC11, among which Tal1b (pthXo1)/Tal4 (pthXo6), along with the lost one, pthXo3 (avrXa7), might be the major factors for LA20 to overcome xa5-, Xa7- and xa13-mediated resistance, thus, leading to the resurgence of BB. This complete genome of the new pandemic Xoo strain will provide novel insights into pathogen evolution, the traits of pathogenicity on genomic level and the epidemic disease status in China.

Rice sheath blight (SB) disease is a global issue that causes great yield losses each year. To explore whether SB field resistance can be predicted, 273 rice genotypes were inoculated and evaluated for SB field resistance across nine environments from 2012 to 2019 to identify loci associated with SB resistance by association mapping. A total of 80 significant marker–trait associations were detected in nine environments, among which six loci (D130B, D230A, D304B, D309, D427A, and RM409) were repeatedly detected in at least two environments. A linear regression model for predicting SB lesion length was developed using genotypic data of these six loci and SB field resistance data of the 273 rice genotypes: y = 34.44 – 0.56x, where y is the predicted value of lesion length, and x is the total genotypic value of the six loci. A recombinant inbred line (RIL) population consisting of 219 lines that was grown in six environments (from 2013 to 2018) for evaluation of SB field resistance was used to check the prediction accuracy of the prediction model. The average absolute error between the predicted lesion length and real lesion length for the RIL population was 6.67 cm. The absolute errors between predicted and real lesion lengths were <6 cm for 51.22% of the lines and <9 cm for 71.22% of the lines. An SB visual rating prediction model was also developed, and the average absolute error between the predicted visual rating and real visual rating for the RIL population was 0.94. These results indicated that the rice SB lesion length can be predicted by the development of a linear regression model using both genotypic and phenotypic data.