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The widely used rice variety Lijiangxintuanheigu (LTH) shows a universal susceptibility to thousands of isolates, the causal agent of devastating rice blast, making LTH an ideal line in resistance () gene cloning. However, the underlying genetic mechanism of the universal susceptibility has not been fully revealed because of the lack of a high-quality genome. Here, we took a genomic approach together with experimental assays to investigate LTH's universal susceptibility to rice blast. Using Nanopore long reads, we assembled a chromosome-level genome. Millions of genomic variants were detected by comparing LTH with 10 other rice varieties, of which large-effect variants could affect plant immunity. Gene family analyses show that the number of genes and leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding genes decrease significantly in LTH. Rice blast resistance genes called genes are either absent or disrupted by genomic variations. Additionally, residual genes of LTH are likely under weak pathogen selection pressure, and other plant defense-related genes are weakly induced by rice blast. In contrast, the pattern-triggered immunity (PTI) of LTH is normal, as demonstrated by experimental assays. Therefore, we conclude that weak effector-trigger immunity (ETI)-mediated primarily by genes but not PTI results in the universal susceptibility of LTH to rice blast. The attenuated ETI of LTH may be also associated with reduced numbers of genes and LRR-RLKs, and minimally functional residual defense-related genes. Finally, we demonstrate the use of the LTH genome by rapid cloning of the gene from a resistant variety.
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http://dx.doi.org/10.1016/j.csbj.2022.01.030 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Hangzhou 311400, China.
As global climate change exacerbates extreme heat events, the interplay between heat stress and blast disease resistance in rice remains poorly understood. In this study, through integrated transcriptome profiling and systematic phenotyping of mutants in several thermosensory pathways, we identified HsfA1 as a positive regulator of heat priming-enhanced blast resistance in rice. Systematic analysis of microRNA (miRNA) dynamics, bioinformatics prediction, and RNA pull-down experiments revealed that , a temperature-responsive miRNA, directly suppresses the expression of by targeting the second exon of messenger RNA (mRNA).
View Article and Find Full Text PDFFront Plant Sci
August 2025
School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, China.
Rice leaf diseases significantly impact yield and quality. Traditional diagnostic methods rely on manual inspection and empirical knowledge, making them subjective and prone to errors. This study proposes an improved YOLOv8-based rice disease detection method (SSD-YOLO) to enhance diagnostic accuracy and efficiency.
View Article and Find Full Text PDFMol Plant
September 2025
Institute of Plant Science and Resources, Okayama University, Okayama 710-0046, Japan. Electronic address:
Breed Sci
April 2025
Institute of Agrobiological Sciences, NARO, Kan-nondai, Tsukuba, Ibaraki 305-8604, Japan.
Resistance breeding for rice blast is an economic strategy for protecting rice crops against this disease. Genes with nucleotide-binding site leucine-rich repeat (NBS-LRR) structures are known to contribute to disease resistance. Here, we identified a candidate resistance gene, named (t), associated with leaf and panicle blasts in an introgression line carrying the chromosome 4 segment of wild rice ( Griff.
View Article and Find Full Text PDFData Brief
October 2025
Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
This manuscript presents a comprehensive, expert-annotated dataset comprising 19,000 rice leaf images, including 2,753 original images and 16,247 augmented images, sourced from the Bangladesh Rice Research Institute (BRRI). The dataset includes seven disease classes: Healthy (603 original images), Rice Blast (696 original images), Scald (421 original images), Leaf-folder Injury (247 original images), Insect Infestation (281 original images), Rice Stripes (266 original images), and Tungro Disease (239 original images). These images, captured under varying environmental conditions using smartphone cameras, accurately reflect real-world conditions.
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