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Abstract Background Magnaporthe oryzae, the causal agent of blast disease of rice, is the most destructive disease of rice worldwide. The genome of this fungal pathogen has been sequenced and an automated annotation has recently been updated to Version 6 http://www.broad.mit.edu/annotation/genome/magnaporthe_grisea/MultiDownloads.html. However, a comprehensive manual curation remains to be performed. Gene Ontology (GO) annotation is a valuable means of assigning functional information using standardized vocabulary. We report an overview of the GO annotation for Version 5 of M. oryzae genome assembly. Methods A similarity-based (i.e., computational) GO annotation with manual review was conducted, which was then integrated with a literature-based GO annotation with computational assistance. For similarity-based GO annotation a stringent reciprocal best hits method was used to identify similarity between predicted proteins of M. oryzae and GO proteins from multiple organisms with published associations to GO terms. Significant alignment pairs were manually reviewed. Functional assignments were further cross-validated with manually reviewed data, conserved domains, or data determined by wet lab experiments. Additionally, biological appropriateness of the functional assignments was manually checked. Results In total, 6,286 proteins received GO term assignment via the homology-based annotation, including 2,870 hypothetical proteins. Literature-based experimental evidence, such as microarray, MPSS, T-DNA insertion mutation, or gene knockout mutation, resulted in 2,810 proteins being annotated with GO terms. Of these, 1,673 proteins were annotated with new terms developed for Plant-Associated Microbe Gene Ontology (PAMGO). In addition, 67 experiment-determined secreted proteins were annotated with PAMGO terms. Integration of the two data sets resulted in 7,412 proteins (57%) being annotated with 1,957 distinct and specific GO terms. Unannotated proteins were assigned to the 3 root terms. The Version 5 GO annotation is publically queryable via the GO site http://amigo.geneontology.org/cgi-bin/amigo/go.cgi. Additionally, the genome of M. oryzae is constantly being refined and updated as new information is incorporated. For the latest GO annotation of Version 6 genome, please visit our website http://scotland.fgl.ncsu.edu/smeng/GoAnnotationMagnaporthegrisea.html. The preliminary GO annotation of Version 6 genome is placed at a local MySql database that is publically queryable via a user-friendly interface Adhoc Query System. Conclusion Our analysis provides comprehensive and robust GO annotations of the M. oryzae genome assemblies that will be solid foundations for further functional interrogation of M. oryzae.

Abstract Background The highly conserved bHLH (basic Helix-Loop-Helix) domain, found in many transcription factors, has been well characterized separately in Plants, Animals, and Fungi. While conserved, even functionally constrained sites have varied since the Eukarya split. Our research identifies those slightly variable sites that were highly characteristic of Plants, Animals, or Fungi. Results Through discriminant analysis, we identified five highly discerning DNA-binding amino acid sites. Additionally, by incorporating Kingdom specific HMMs, we were able to construct a tool to quickly and accurately identify and classify bHLH sequences using these sites. Conclusions We conclude that highly discerning sites identified through our analysis were likely under functional constraints specific to each Kingdom. We also demonstrated the utility of our tool by identifying and classifying previously unknown bHLH domains in both characterized genomes and from sequences in a large environmental sample.

Abstract Background Emerging knowledge of the impact of small RNAs as important cellular regulators has prompted an explosion of small transcriptome sequencing projects. Although significant progress has been made towards small RNA discovery and biogenesis in higher eukaryotes and other model organisms, knowledge in simple eukaryotes such as filamentous fungi remains limited. Results Here, we used 454 pyrosequencing to present a detailed analysis of the small RNA transcriptome (~ 15 - 40 nucleotides in length) from mycelia and appressoria tissues of the rice blast fungal pathogen, Magnaporthe oryzae. Small RNAs mapped to numerous nuclear and mitochondrial genomic features including repetitive elements, tRNA loci, rRNAs, protein coding genes, snRNAs and intergenic regions. For most elements, small RNAs mapped primarily to the sense strand with the exception of repetitive elements to which small RNAs mapped in the sense and antisense orientation in near equal proportions. Inspection of the small RNAs revealed a preference for U and suppression of C at position 1, particularly for antisense mapping small RNAs. In the mycelia library, small RNAs of the size 18 - 23 nt were enriched for intergenic regions and repetitive elements. Small RNAs mapping to LTR retrotransposons were classified as LTR retrotransposon-siRNAs (LTR-siRNAs). Conversely, the appressoria library had a greater proportion of 28 - 35 nt small RNAs mapping to tRNA loci, and were classified as tRNA-derived RNA fragments (tRFs). LTR-siRNAs and tRFs were independently validated by 3' RACE PCR and northern blots, respectively. Conclusions Our findings suggest M. oryzae small RNAs differentially accumulate in vegetative and specialized-infection tissues and may play an active role in genome integrity and regulating growth and development.

Abstract Background Rice blast is the most threatening disease to cultivated rice. Magnaporthe oryzae, its causal agent, is likely to encounter environmental challenges during invasive growth in its host plants that require shifts in gene expression to establish a compatible interaction. Here, we tested the hypothesis that gene expression patterns during in planta invasive growth are similar to in vitro stress conditions, such as nutrient limitation, temperature up shift and oxidative stress, and determined which condition most closely mimicked that of in planta invasive growth. Gene expression data were collected from these in vitro experiments and compared to fungal gene expression during the invasive growth phase at 72 hours post-inoculation in compatible interactions on two grass hosts, rice and barley. Results We identified 4,973 genes that were differentially expressed in at least one of the in planta and in vitro stress conditions when compared to fungal mycelia grown in complete medium, which was used as reference. From those genes, 1,909 showed similar expression patterns between at least one of the in vitro stresses and rice and/or barley. Hierarchical clustering of these 1,909 genes showed three major clusters in which in planta conditions closely grouped with the nutrient starvation conditions. Out of these 1,909 genes, 55 genes and 129 genes were induced and repressed in all treatments, respectively. Functional categorization of the 55 induced genes revealed that most were either related to carbon metabolism, membrane proteins, or were involved in oxidoreduction reactions. The 129 repressed genes showed putative roles in vesicle trafficking, signal transduction, nitrogen metabolism, or molecular transport. Conclusions These findings suggest that M. oryzae is likely primarily coping with nutrient-limited environments at the invasive growth stage 72 hours post-inoculation, and not with oxidative or temperature stresses.

Abstract Background Duplication, followed by fixation or random loss of novel genes, contributes to genome evolution. Particular outcomes of duplication events are possibly associated with pathogenic life histories in fungi. To date, differential gene gain and loss have not been studied at genomic scales in fungal pathogens, despite this phenomenon's known importance in virulence in bacteria and viruses. Results To determine if patterns of gene duplication differed between pathogens and non-pathogens, we identified gene families across nine euascomycete and two basidiomycete species. Gene family size distributions were fit to power laws to compare gene duplication trends in pathogens versus non-pathogens. Fungal phytopathogens showed globally altered patterns of gene duplication, as indicated by differences in gene family size distribution. We also identified sixteen examples of gene family expansion and five instances of gene family contraction in pathogenic lineages. Expanded gene families included those predicted to be important in melanin biosynthesis, host cell wall degradation and transport functions. Contracted families included those encoding genes involved in toxin production, genes with oxidoreductase activity, as well as subunits of the vacuolar ATPase complex. Surveys of the functional distribution of gene duplicates indicated that pathogens show enrichment for gene duplicates associated with receptor and hydrolase activities, while euascomycete pathogens appeared to have not only these differences, but also significantly more duplicates associated with regulatory and carbohydrate binding functions. Conclusion Differences in the overall levels of gene duplication in phytopathogenic species versus non-pathogenic relatives implicate gene inventory flux as an important virulence-associated process in fungi. We hypothesize that the observed patterns of gene duplicate enrichment, gene family expansion and contraction reflect adaptation within pathogenic life histories. These adaptations were likely shaped by ancient, as well as contemporary, intimate associations with monocot hosts.

Abstract Background The Cytochrome P450 system is important in fungal evolution for adapting to novel ecological niches. To elucidate the evolutionary process of cytochrome P450 genes in fungi with different life styles, we studied the patterns of gene gains and losses in the genomes of four filamentous Ascomycetes, including two saprotrophs (Aspergillus nidulans (AN) and Neurospora crassa (NC)) and two plant pathogens (Fusarium graminearum (FG) and Magnaporthe grisea (MG)). Results A total of 376 P450 genes were assigned to 168 families according to standard nomenclature. On average, only 1 to 2 genes per family were in each genome. To resolve conflicting results between different clustering analyses and standard family designation, a higher order relationship was formulated. 376 genes were clustered into 115 clans. Subsequently a novel approach based on parsimony was developed to build the evolutionary models. Based on these analyses, a core of 30 distinct clans of P450s was defined. The core clans experienced contraction in all four fungal lineages while new clans expanded in all with exception of NC. MG experienced more genes and clans gains compared to the other fungi. Parsimonious analyses unanimously supported one species topology for the four fungi. Conclusion The four studied fungi exhibit unprecedented diversity in their P450omes in terms of coding sequence, intron-exon structures and genome locations, suggesting a complicated evolutionary history of P450s in filamentous Ascomycetes. Clan classification and a novel strategy were developed to study evolutionary history. Contraction of core clans and expansion of novel clans were identified. The exception was the NC lineage, which exhibited pure P450 gene loss.

Abstract Background - Sequencing of EST and BAC end datasets is no longer limited to large research groups. Drops in per-base pricing have made high throughput sequencing accessible to individual investigators. However, there are few options available which provide a free and user-friendly solution to the BLAST result storage and data mining needs of biologists. Results - Here we describe NuclearBLAST, a batch BLAST analysis, storage and management system designed for the biologist. It is a wrapper for NCBI BLAST which provides a user-friendly web interface which includes a request wizard and the ability to view and mine the results. All BLAST results are stored in a MySQL database which allows for more advanced data-mining through supplied command-line utilities or direct database access. NuclearBLAST can be installed on a single machine or clustered amongst a number of machines to improve analysis throughput. NuclearBLAST provides a platform which eases data-mining of multiple BLAST results. With the supplied scripts, the program can export data into a spreadsheet-friendly format, automatically assign Gene Ontology terms to sequences and provide bi-directional best hits between two datasets. Users with SQL experience can use the database to ask even more complex questions and extract any subset of data they require. Conclusion - This tool provides a user-friendly interface for requesting, viewing and mining of BLAST results which makes the management and data-mining of large sets of BLAST analyses tractable to biologists.

Abstract Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

The common rust disease of maize is caused by the obligate biotrophic fungus Puccinia sorghi. The maize Rp1-D allele imparts resistance against the P. sorghi IN2 isolate by initiating a defense response that includes a rapid localized programmed cell death process, the hypersensitive response (HR). In this study, to identify AvrRp1-D from P. sorghi IN2, we employed the isolation of haustoria, facilitated by a biotin-streptavidin interaction, as a powerful approach. This method proves particularly advantageous in cases where the genome information for the fungal pathogen is unavailable, enhancing our ability to explore and understand the molecular interactions between maize and P. sorghi. The haustorial transcriptome generated through this technique, in combination with bioinformatic analyses such as SignalP and TMHMM, enabled the identification of 251 candidate effectors. We ultimately identified two closely related genes, AvrRp1-D.1 and AvrRp1-D.2, which triggered an Rp1-D-dependent defense response in Nicotiana benthamiana. AvrRp1-D-induced Rp1-D-dependent HR was further confirmed in maize protoplasts. We demonstrated that AvrRp1-D.1 interacts directly and specifically with the leucine-rich repeat (LRR) domain of Rp1-D through yeast two-hybrid assay. We also provide evidence that, in the absence of Rp1-D, AvrRp1-D.1 plays a role in suppressing the plant immune response. Our research provides valuable insights into the molecular interactions driving resistance against common rust in maize. Author summary: The common rust disease of maize is caused by the obligate biotrophic fungus Puccinia sorghi. Resistance to common rust is controlled by race-specific dominant NLR (nucleotide-binding domain and leucine-rich repeats) genes and by a variety of non-race-specific quantitative trait loci. The maize Rp1-D is a coiled-coil-NLR protein conferring race-specific resistance that includes a rapid localized programmed cell death, hypersensitive response (HR). In this study, to identify AvrRp1-D from an avirulent P. sorghi IN2, we employed the isolation of haustoria, facilitated by a biotin-streptavidin interaction, as a powerful approach. This method proves particularly advantageous in cases where the genome information for the fungal pathogen is unavailable, enhancing our ability to explore and understand the molecular interactions between maize and P. sorghi. The haustorial transcriptome is generated through this technique in combination with bioinformatic analyses. We identified two closely related genes, AvrRp1-D.1 and AvrRp1-D.2, which triggered an Rp1-D-dependent defense response in Nicotiana benthamiana. AvrRp1-D-induced Rp1-D-dependent HR was further confirmed in maize protoplasts. We demonstrated that AvrRp1-D.1 interacts directly and specifically with the leucine-rich repeat domain of Rp1-D through yeast two-hybrid assay. Our research provides valuable insights into the molecular interactions driving resistance against common rust in maize. [ABSTRACT FROM AUTHOR]

Numerous experimental strategies exist for relative protein quantification, one of the primary objectives of mass spectrometry based proteomics analysis. These strategies mostly involve the incorporation of a stable isotope label via either metabolic incorporation in cell or tissue culture ([sup.15]N/[sup.14]N metabolic labeling, stable isotope labeling by amino acids in cell culture (SILAC)), chemical derivatization (ICAT, iTRAQ, TMT), or enzymatically catalyzed incorporation ([sup.18]O labeling). Also, these techniques can be cost or time prohibitive or not amenable to the biological system of interest (i.e., metabolic labeling of clinical samples, most animals, or fungi). This is the case with the quantification of fungal proteomes, which often require auxotroph mutants to fully metabolically label. Alternatively, label-free strategies for protein quantification such as using integrated ion abundance and spectral counting have been demonstrated for quantification affording over 2 orders of magnitude of dynamic range which is comparable to metabolic labeling strategies. Direct comparisons of these quantitative techniques are largely lacking in the literature but are highly warranted in order to evaluate the capabilities, limitations, and analytical variability of available quantitative strategies. Here, we present the direct comparison of SILAC to label-free quantification by spectral counting of an identical set of data from the bottom-up proteomic analysis of human embryonic stem cells, which are readily able to be quantified using both strategies, finding that both strategies result in a similar number of protein identifications. We also discuss necessary constraints for accurate quantification using spectral counting and assess the potential of this label-free strategy as a viable alternative for quantitative proteomics. 10.1021/ac101978b

Rice blast disease caused by the hemi-biotrophic fungus Magnaporthe oryzae is the most destructive disease of rice world-wide. Traditional disease resistance strategies for the control of rice blast disease have not proved durable. HIGS (host induced gene silencing) is being developed as an alternative strategy. Six genes (CRZ1, PMC1, MAGB, LHS1, CYP51A, CYP51B) that play important roles in pathogenicity and development of M. oryzae were chosen for HIGS. HIGS vectors were transformed into rice calli through Agrobacterium-mediated transformation and T0, T1 and T2 generations of transgenic rice plants were generated. Except for PMC1 and LHS1, HIGS transgenic rice plants challenged with M. oryzae showed significantly reduced disease compared with non-silenced control plants. Following infection with M. oryzae of HIGS transgenic plants, expression levels of target genes were reduced as demonstrated by Quantitative RT-PCR. In addition, treating M. oryzae with small RNA derived from the target genes inhibited fungal growth. These findings suggest RNA silencing signals can be transferred from host to an invasive fungus and that HIGS has potential to generate resistant rice against M. oryzae. [ABSTRACT FROM AUTHOR]