The pathogen and control management of rice blast disease

Zakaria, L.; Misman, N.

doi:10.21161/mjm.113717

Cited by 7 publications

(9 citation statements)

References 49 publications

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“…Interestingly, OsWRKY24 has been known as a blast disease responsive transcription factor, which positively regulates rice disease resistance [43]. This finding is consistent with the MR 297 (nonpigmented) variety which is resistant to blast disease caused by Pyricularia oryzae [55]. We also investigated the DEG encoding transcription factors in three distinct rice groups, namely, BR (black rice and red rice), BW (black rice and white rice), RW (red rice and white rice).…”

Section: Hub Genes Identificationsupporting

confidence: 67%

Mining of Stress-related Genes in Pigmented and Non-pigmented Rice using Gene Co-expression Network and Clustering Approaches

Zainal-Abidin

Aleng²,

Sew³

et al. 2023

Mal. J. Fund. Appl. Sci.

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Pigmented rice has been associated with stress-resistant traits, such as resistance to abiotic and biotic stresses, but the genes network that is responsible for such traits remains limited. Hence, this study aims to identify stress-related genes in the pigmented rice using computational approaches. The gene co-expression network was constructed using Pearson Correlation Coefficient (PCC) ≥ 0.9 among differentially expressed genes (DEGs) of trancriptomes between pigmented and non-pigmented rice. The gene co-expression network was clustered using Markov Cluster algorithm (MCL) to identify the functional modules and the hub genes for each module were determined. The functional analyses were performed to each module to determine the related gene ontology (GO) and pathway. Protein-protein interaction (PPI) from STRING database was used to validate the functional analyses. A total of 721 DEGs were used to construct the gene co-expression network of pigmented and non-pigmented rice varieties. Of these, 614 DEGs with 15,259 edges were identified by PCC. Using MCL, 10 clusters were identified in the gene co-expression network of pigmented and non-pigmented rice varieties. Three clusters were enriched with seven GO terms (i.e., response to stress, response to stimulus, transcription factor activity) that are related to stress-resistant traits, indicating the highly correlated genes were the stress-related genes. Interestingly, nine hub genes were found to be related to drought tolerance, disease resistance and hormone biosynthesis. Validation of hub genes using STRING database revealed that 48 hub genes were also connected in the PPI network, suggesting their potential as candidate proteins in stress-related traits. This study demonstrated that the molecular interaction network and the network clustering approach are efficient in identifying the stress-related genes, which could provide new insights in understanding plant responses to abiotic and biotic stresses.

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Section: Hub Genes Identificationsupporting

confidence: 67%

Mining of Stress-related Genes in Pigmented and Non-pigmented Rice using Gene Co-expression Network and Clustering Approaches

Zainal-Abidin

Aleng²,

Sew³

et al. 2023

Mal. J. Fund. Appl. Sci.

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“…This conveys a sense of continuing excitement in the field of molecular plant pathology to control bacterial rice pathogens. To date, the main approaches to control bacterial rice pathogens include the production of disease-resistant rice varieties [ 34 , 35 , 36 ]; modification in cultural practices [ 37 , 38 ]; use of natural products or botanical extracts [ 39 , 40 , 41 ]; use of conventional and non-conventional chemicals [ 42 , 43 ]; coevolution analysis of the pathogen virulence and the host resistance genes [ 44 , 45 ]; transcriptomic analysis of pathogen along rice development [ 46 , 47 ]; improvement of diagnostic tools in the field for early detection of infectious diseases [ 48 ].…”

Section: Bacterial Rice Pathogensmentioning

confidence: 99%

Plant Growth-Promoting Bacteria as an Emerging Tool to Manage Bacterial Rice Pathogens

et al. 2021

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As a major food crop, rice (Oryza sativa) is produced and consumed by nearly 90% of the population in Asia with less than 9% produced outside Asia. Hence, reports on large scale grain losses were alarming and resulted in a heightened awareness on the importance of rice plants’ health and increased interest against phytopathogens in rice. To serve this interest, this review will provide a summary on bacterial rice pathogens, which can potentially be controlled by plant growth-promoting bacteria (PGPB). Additionally, this review highlights PGPB-mediated functional traits, including biocontrol of bacterial rice pathogens and enhancement of rice plant’s growth. Currently, a plethora of recent studies address the use of PGPB to combat bacterial rice pathogens in an attempt to replace existing methods of chemical fertilizers and pesticides that often lead to environmental pollutions. As a tool to combat bacterial rice pathogens, PGPB presented itself as a promising alternative in improving rice plants’ health and simultaneously controlling bacterial rice pathogens in vitro and in the field/greenhouse studies. PGPB, such as Bacillus, Pseudomonas, Enterobacter, Streptomyces, are now very well-known. Applications of PGPB as bioformulations are found to be effective in improving rice productivity and provide an eco-friendly alternative to agroecosystems.

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“…Thus, it could be the reason insignificant for N, K, and Si on the number of spikelets per meter square (Figure 6). However, lower rice blast severity in the main-season 2021/2022 (31,408) could be the reason for the more significant spikelets number per meter square than in off-season 2021 (20,686).…”

Section: Effects Of N K and Si On Spikelet Per Meter Squarementioning

confidence: 99%

“…In Malaysia, blast outbreaks are sporadic and difficult to predict; thus, blast control in the field is difficult. Grain yield losses causing as much as 50-70% once being infected by rice blast in Malaysia are common [31,32], and 50-70% in the Philippines have been reported [33,34]. In Indonesia, about 12% of the total rice cultivation area was infected by rice blasts [35].…”

Section: Introductionmentioning

confidence: 99%

Nitrogen, Potassium, and Silicon Fertilization to Achieve Lower Panicle Blast Severity and Improve Yield Components of Rice Using Response Surface Methodology

Esa,

Misman,

Mohamad Saad

et al. 2023

Jurnal Teknologi

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Rice blast is one of the most critical limiting factors for rice plant growth performance, and it occurs in 85 countries, causing 10-35% grain yield losses. Several findings have indicated the positive benefits of nitrogen (N), potassium (K), and Silicon (Si) fertilization on plant development, yield, and biotic stress relief. However, due to rice blast attacks, its growth, development, and yield may be restricted or limited by insufficient or unbalanced N, K, and Si fertilizers. This study was conducted to optimize the fertilization strategies for rice panicle blast control and improve rice grain yield. The methods used were Central Composite Design and Response Surface Methodology. The application of N, K and Si did not influence the number of spikelets per meter square, filled grain (%) and 1000- grain weight (g). An increase in K and Si significantly reduced the rice blast severity in the off-season 2021 and the main-season 2021/2022. On the other hand, only Si had influenced rice grain yield production. An increase in Si showed a positive linear trend in rice grain yield. Based on these results, panicle blast disease is expected to be controlled with the recommended rate of 104 N kg/ha, 42 P2O5, 80 kg K2O, and an additional 200 Si kg/ha, which minimizes the rice blast severity (%) but at the same time maximizes the rice grain yield. The findings of this study provide a scientific base and technical advice for high-yield rice grain-growing under panicle blast disease hot spot areas.

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The pathogen and control management of rice blast disease

Cited by 7 publications

References 49 publications

Mining of Stress-related Genes in Pigmented and Non-pigmented Rice using Gene Co-expression Network and Clustering Approaches

Mining of Stress-related Genes in Pigmented and Non-pigmented Rice using Gene Co-expression Network and Clustering Approaches

Plant Growth-Promoting Bacteria as an Emerging Tool to Manage Bacterial Rice Pathogens

Nitrogen, Potassium, and Silicon Fertilization to Achieve Lower Panicle Blast Severity and Improve Yield Components of Rice Using Response Surface Methodology

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