A Correction to this paper has been published: https://doi.org/10.1038/s41551-020-00677-7

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.

Small RNAs are well described in higher eukaryotes such as mammals and plants; however, knowledge in simple eukaryotes such as filamentous fungi is limited. In this study, we discovered and characterized methylguanosine-capped and polyadenylated small RNAs (CPA-sRNAs) by using differential RNA selection, full-length cDNA cloning and 454 transcriptome sequencing of the rice blast fungus Magnaporthe oryzae. This fungus causes blast, a devastating disease on rice, the principle food staple for over half the world's population. CPA-sRNAs mapped primarily to the transcription initiation and termination sites of protein-coding genes and were positively correlated with gene expression, particularly for highly expressed genes including those encoding ribosomal proteins. Numerous CPA-sRNAs also mapped to rRNAs, tRNAs, snRNAs, transposable elements and intergenic regions. Many other 454 sequence reads could not be mapped to the genome; however, inspection revealed evidence for non-template additions and chimeric sequences. CPA-sRNAs were independently confirmed using a high affinity variant of eIF-4E to capture 5'-methylguanosine-capped RNA followed by 3'-RACE sequencing. These results expand the repertoire of small RNAs in filamentous fungi.

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 annotationof 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.

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.

Background Rice blast disease is caused by the filamentous Ascomycetous fungus Magnaporthe oryzae and results in significant annual rice yield losses worldwide. Infection by this and many other fungal plant pathogens requires the development of a specialized infection cell called an appressorium. The molecular processes regulating appressorium formation are incompletely understood. Results We analyzed genome-wide gene expression changes during spore germination and appressorium formation on a hydrophobic surface compared to induction by cAMP. During spore germination, 2,154 (approximately 21%) genes showed differential expression, with the majority being up-regulated. During appressorium formation, 357 genes were differentially expressed in response to both stimuli. These genes, which we refer to as appressorium consensus genes, were functionally grouped into Gene Ontology categories. Overall, we found a significant decrease in expression of genes involved in protein synthesis. Conversely, expression of genes associated with protein and amino acid degradation, lipid metabolism, secondary metabolism and cellular transportation exhibited a dramatic increase. We functionally characterized several differentially regulated genes, including a subtilisin protease ( SPM1 ) and a NAD specific glutamate dehydrogenase ( Mgd1 ), by targeted gene disruption. These studies revealed hitherto unknown findings that protein degradation and amino acid metabolism are essential for appressorium formation and subsequent infection. Conclusion We present the first comprehensive genome-wide transcript profile study and functional analysis of infection structure formation by a fungal plant pathogen. Our data provide novel insight into the underlying molecular mechanisms that will directly benefit efforts to identify fungal pathogenicity factors and aid the development of new disease management strategies.

A collaboration is a collection of services that work together to achieve a common goal. Although collaborations help when tackling difficult problems, they lead to security issues. First, a collaboration is often performed by services that are drawn from different security domains. Second, a service interacts with multiple peer services during the collaboration. These interactions are not isolated from one another - e.g., data may flow through a sequence of different services. As a result, a service is exposed to multiple peer services in varying degrees, leading to different security threats. We identify the types of interactions that can be present in collaborations, and discuss the security threats due to each type. We propose a model for representing the collaboration context so that a service can be made aware of the existing interactions. We provide an access control model for a service participating in a collaboration. We couple our access control model with a policy model, so that the access requirements from collaborations can be expressed and evaluated.

Inexpensive computational power combined with high-throughput experimental platforms has created a wealth of biological information requiring analytical tools and techniques for interpretation. Graph-theoretic concepts and tools have provided an important foundation for information visualization, integration, and analysis of datasets, but they have often been relegated to background analysis tasks. GT-Miner is designed for visual data analysis and mining operations, interacts with other software, including databases, and works with diverse data types. It facilitates a discovery-oriented approach to data mining wherein exploration of alterations of the data and variations of the visualization is encouraged. The user is presented with a basic iterative process, consisting of loading, visualizing, transforming, and then storing the resultant information. Complex analyses are built-up through repeated iterations and user interactions. The iterative process is optimized by automatic layout following transformations and by maintaining a current selection set of interest for elements modified by the transformations. Multiple visualizations are supported including hierarchical, spring, and force-directed self-organizing layouts. Graphs can be transformed with an extensible set of algorithms or manually with an integral visual editor. GT-Miner is intended to allow easier access to visual data mining for the non-expert.

Service-oriented computing promotes collaboration by defining the standards layer that allows compatibility between disparate domains. Workflows, by taking advantage of the service oriented framework, provide the necessary tools to harness services in order to tackle complicated problems. As a result, a service is no longer exposed to a small pre-determined homogeneous pool of users; instead it has a large, undefined, and heterogeneous pool of users. This paradigm shift in computing results in increased service exposure. The interactions among the services of a workflow must be carefully evaluated against the security risks associated with them. Classical security problems, such as delegation of rights, conflict of interest, and access control in general, become more complicated due to multiple autonomous security domains and the absence of pre- established trust relationships among the domains. Our work tackles these problems in two aspects: it provides a service owner with the necessary means to express and evaluate its trust requirements from a workflow (collaboration policies), and it incorporates these trust requirements into the workflow-planning framework (workflow authorization framework). Our policy-based framework allows bilateral peer-level trust evaluations that are based on each peer’s collaboration policies, and incorporates the outcome of these evaluations into the workflow planning logic. As a result, our work provides the necessary tools for promoting multi-party ad-hoc collaborations, and aims to reduce the reluctance and hesitation towards these collaborations by attacking the security risks associated with them.

An international consortium is sequencing the euchromatic genespace of Medicago truncatula. Extensive bioinformatic and database resources support the marker-anchored bacterial artificial chromosome (BAC) sequencing strategy. Existing physical and genetic maps and deep BAC-end sequencing help to guide the sequencing effort, while EST databases provide essential resources for genome annotation as well as transcriptome characterization and microarray design. Finished BAC sequences are joined into overlapping sequence assemblies and undergo an automated annotation process that integrates ab initio predictions with EST, protein, and other recognizable features. Because of the sequencing project's international and collaborative nature, data production, storage, and visualization tools are broadly distributed. This paper describes databases and Web resources for the project, which provide support for physical and genetic maps, genome sequence assembly, gene prediction, and integration of EST data. A central project Web site at medicago.org/genome provides access to genome viewers and other resources project-wide, including an Ensembl implementation at medicago.org, physical map and marker resources at mtgenome.ucdavis.edu, and genome viewers at the University of Oklahoma (www.genome.ou.edu), the Institute for Genomic Research (www.tigr.org), and Munich Information for Protein Sequences Center (mips.gsf.de).

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.

We have created a federated database for genome studies of Magnaporthe grisea, the causal agent of rice blast disease, by integrating end sequence data from BAC clones, genetic marker data and BAC contig assembly data. A library of 9216 BAC clones providing >25-fold coverage of the entire genome was end sequenced and fingerprinted by HindIII digestion. The Image/FPC software package was then used to generate an assembly of 188 contigs covering >95% of the genome. The database contains the results of this assembly integrated with hybridization data of genetic markers to the BAC library. AceDB was used for the core database engine and a MySQL relational database, populated with numerical representations of BAC clones within FPC contigs, was used to create appropriately scaled images. The database is being used to facilitate sequencing efforts. The database also allows researchers mapping known genes or other sequences of interest, rapid and easy access to the fundamental organization of the M.grisea genome. This database, MagnaportheDB, can be accessed on the web at http://www.cals.ncsu.edu/fungal_genomics/mgdatabase/int.htm.