Research Status and Prospect on the Interaction Between Magnaporthe oryzae Effector Protein and Rice
Bibliographic record
Abstract
Rice is one of the most important crops in the world, and safe production of rice is related to food safety issues. Rice blast, caused by Magnaporthe oryzae, is a worldwide fungal disease that causes serious losses to rice production. Compared with chemical pesticides control, the breeding and application of disease-resistant cultivars is the most economical and effective way to control the disease. However, the complex and diverse population of blast fungus in the field, excessive use of chemical pesticides, change of temperature environment and other factors cause rapid evolution of M. oryzae isolates, and the resistance of cultivars can only last for 3-5 years. Magnaporthe oryzae generates new races through the mutation of avirulent genes, which can escape or suppress the immune system of rice, causing infection and disease. At present, 26 avirulent genes in blast fungus have been identified, and 14 of them have been cloned, which plays an important role in the infection and colonization of pathogens and in interfering with the immune response of host plants. Further studies on the interaction mechanism of M. oryzae effector protein and rice resistance protein have also been conducted. Understanding the pathogenic mechanism of blast fungus and molecular mechanism of its interaction with rice will help to better understand the pathway of pathogens and the immune response of plant disease resistance genes, to formulate more efficient and green control measures. This review summarized the process of M. oryzae effector protein translocation and secretion in rice cells, the research advances in the interaction between effector proteins and disease-resistance proteins and the regional distribution of effector proteins. And the opportunities and challenges in current researches were discussed and prospected, with an aim to provide references for the molecular mechanism of the interaction between rice and blast fungus, disease-resistance breeding and disease prevention and control strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".