Search

Background: Rice blast caused by the fungus Magnaporthe oryzae is an important disease in virtually every rice growing region of the world, which leads to significant annual decreases of grain quality and yield. To prevent disease, resistance genes in rice have been cloned and introduced into susceptible cultivars. However, introduced resistance can often be broken within few years of release, often due to mutation of cognate avirulence genes in fungal field populations., Results: To better understand the pattern of mutation of M. oryzae field isolates under natural selection forces, we used a next generation sequencing approach to analyze the genomes of two field isolates FJ81278 and HN19311, as well as the transcriptome of FJ81278. By comparing the de novo genome assemblies of the two isolates against the finished reference strain 70-15, we identified extensive polymorphisms including unique genes, SNPs (single nucleotide polymorphism) and indels, structural variations, copy number variations, and loci under strong positive selection. The 1.75 MB of isolate-specific genome content carrying 118 novel genes from FJ81278, and 0.83 MB from HN19311 were also identified. By analyzing secreted proteins carrying polymorphisms, in total 256 candidate virulence effectors were found and 6 were chosen for functional characterization., Conclusions: We provide results from genome comparison analysis showing extensive genome variation, and generated a list of M. oryzae candidate virulence effectors for functional characterization.

Interactions between rice and Magnaporthe oryzae involve the recognition of cellular components and the exchange of complex molecular signals from both partners. How these interactions occur in rice cells is still elusive. We employed robust-long serial analysis of gene expression, massively parallel signature sequencing, and sequencing by synthesis to examine transcriptome profiles of infected rice leaves. A total of 6,413 in planta-expressed fungal genes, including 851 genes encoding predicted effector proteins, were identified. We used a protoplast transient expression system to assess 42 of the predicted effector proteins for the ability to induce plant cell death. Ectopic expression assays identified five novel effectors that induced host cell death only when they contained the signal peptide for secretion to the extracellular space. Four of them induced cell death in Nicotiana benthamiana. Although the five effectors are highly diverse in their sequences, the physiological basis of cell death induced by each was similar. This study demonstrates that our integrative genomic approach is effective for the identification of in planta-expressed cell death-inducing effectors from M. oryzae that may play an important role facilitating colonization and fungal growth during infection.

Rice blast disease, caused by the fungal pathogen Magnaporthe grisea, is an excellent model system to study plant-fungal interactions and host defense responses. In this study, comprehensive analysis of the rice (Oryza sativa) transcriptome after M. grisea infection was conducted using robust-long serial analysis of gene expression. A total of 83,382 distinct 21-bp robust-long serial analysis of gene expression tags were identified from 627,262 individual tags isolated from the resistant (R), susceptible (S), and control (C) libraries. Sequence analysis revealed that the tags in the R and S libraries had a significant reduced matching rate to the rice genomic and expressed sequences in comparison to the C library. The high level of one-nucleotide mismatches of the R and S library tags was due to nucleotide conversions. The A-to-G and U-to-C nucleotide conversions were the most predominant types, which were induced in the M. grisea-infected plants. Reverse transcription-polymerase chain reaction analysis showed that expression of the adenine deaminase and cytidine deaminase genes was highly induced after inoculation. In addition, many antisense transcripts were induced in infected plants and expression of four antisense transcripts was confirmed by strand-specific reverse transcription-polymerase chain reaction. These results demonstrate that there is a series of dynamic and complex transcript modifications and changes in the rice transcriptome at the M. grisea early infection stages.

Identification of important transcripts from fungal pathogens and host plants is indispensable for full understanding the molecular events occurring during fungal-plant interactions. Recently, we developed an improved LongSAGE method called robust-long serial analysis of gene expression (RL-SAGE) for deep transcriptome analysis of fungal and plant genomes. Using this method, we made 10 RL-SAGE libraries from two plant species (Oryza sativa and Zea maize) and one fungal pathogen (Magnaporthe grisea). Many of the transcripts identified from these libraries were novel in comparison with their corresponding EST collections. Bioinformatic tools and databases for analyzing the RL-SAGE data were developed. Our results demonstrate that RL-SAGE is an effective approach for large-scale identification of expressed genes in fungal and plant genomes.

Background: Rice blast, caused by the fungal pathogen Magnaporthe grisea, is a devastating disease causing tremendous yield loss in rice production. The public availability of the complete genome sequence of M. grisea provides ample opportunities to understand the molecular mechanism of its pathogenesis on rice plants at the transcriptome level. To identify all the expressed genes encoded in the fungal genome, we have analyzed the mycelium and appressorium transcriptomes using massively parallel signature sequencing (MPSS), robust-long serial analysis of gene expression (RL-SAGE) and oligoarray methods., Results: The MPSS analyses identified 12,531 and 12,927 distinct significant tags from mycelia and appressoria, respectively, while the RL-SAGE analysis identified 16,580 distinct significant tags from the mycelial library. When matching these 12,531 mycelial and 12,927 appressorial significant tags to the annotated CDS, 500 bp upstream and 500 bp downstream of CDS, 6,735 unique genes in mycelia and 7,686 unique genes in appressoria were identified. A total of 7,135 mycelium-specific and 7,531 appressorium-specific significant MPSS tags were identified, which correspond to 2,088 and 1,784 annotated genes, respectively, when matching to the same set of reference sequences. Nearly 85% of the significant MPSS tags from mycelia and appressoria and 65% of the significant tags from the RL-SAGE mycelium library matched to the M. grisea genome. MPSS and RL-SAGE methods supported the expression of more than 9,000 genes, representing over 80% of the predicted genes in M. grisea. About 40% of the MPSS tags and 55% of the RL-SAGE tags represent novel transcripts since they had no matches in the existing M. grisea EST collections. Over 19% of the annotated genes were found to produce both sense and antisense tags in the protein-coding region. The oligoarray analysis identified the expression of 3,793 mycelium-specific and 4,652 appressorium-specific genes. A total of 2,430 mycelial genes and 1,886 appressorial genes were identified by both MPSS and oligoarray., Conclusion: The comprehensive and deep transcriptome analysis by MPSS and RL-SAGE methods identified many novel sense and antisense transcripts in the M. grisea genome at two important growth stages. The differentially expressed transcripts that were identified, especially those specifically expressed in appressoria, represent a genomic resource useful for gaining a better understanding of the molecular basis of M. grisea pathogenicity. Further analysis of the novel antisense transcripts will provide new insights into the regulation and function of these genes in fungal growth, development and pathogenesis in the host plants.