Marcus C. Chibucos

Genome sequence and analysis of the Irish potato famine pathogen Phytophthora infestans

Phytophthora infestans is the most destructive pathogen of potato and a model organism for the oomycetes, a distinct lineage of fungus-like eukaryotes that are related to organisms such as brown algae and diatoms. As the agent of the Irish potato famine in the mid-nineteenth century, P. infestans has had a tremendous effect on human history, resulting in famine and population displacement. To this day, it affects world agriculture by causing the most destructive disease of potato, the fourth largest food crop and a critical alternative to the major cereal crops for feeding the world’s population. Current annual worldwide potato crop losses due to late blight are conservatively estimated at

Signatures of adaptation to obligate biotrophy in the Hyaloperonospora arabidopsidis genome.

6.7 billion. Management of this devastating pathogen is challenged by its remarkable speed of adaptation to control strategies such as genetically resistant cultivars. Here we report the sequence of the P. infestans genome, which at ∼240 megabases (Mb) is by far the largest and most complex genome sequenced so far in the chromalveolates. Its expansion results from a proliferation of repetitive DNA accounting for ∼74% of the genome. Comparison with two other Phytophthora genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection or are predicted to have activities that alter host physiology. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the P. infestans genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential.

The Aspergillus Genome Database (AspGD): recent developments in comprehensive multispecies curation, comparative genomics and community resources

From Blight to Powdery Mildew Pathogenic effects of microbes on plants have widespread consequences. Witness, for example, the cultural upheavals driven by potato blight in the 1800s. A variety of microbial pathogens continue to afflict crop plants today, driving both loss of yield and incurring the increased costs of control mechanisms. Now, four reports analyze microbial genomes in order to understand better how plant pathogens function (see the Perspective by Dodds). Raffaele et al. (p. 1540) describe how the genome of the potato blight pathogen accommodates transfer to different hosts. Spanu et al. (p. 1543) analyze what it takes to be an obligate biotroph in barley powdery mildew, and Baxter et al. (p. 1549) ask a similar question for a natural pathogen of Arabidopsis. Schirawski et al. (p. 1546) compared genomes of maize pathogens to identify virulence determinants. Better knowledge of what in a genome makes a pathogen efficient and deadly is likely to be useful for improving agricultural crop management and breeding. A group of papers analyzes pathogen genomes to find the roots of virulence, opportunism, and life-style determinants. Many oomycete and fungal plant pathogens are obligate biotrophs, which extract nutrients only from living plant tissue and cannot grow apart from their hosts. Although these pathogens cause substantial crop losses, little is known about the molecular basis or evolution of obligate biotrophy. Here, we report the genome sequence of the oomycete Hyaloperonospora arabidopsidis (Hpa), an obligate biotroph and natural pathogen of Arabidopsis thaliana. In comparison with genomes of related, hemibiotrophic Phytophthora species, the Hpa genome exhibits dramatic reductions in genes encoding (i) RXLR effectors and other secreted pathogenicity proteins, (ii) enzymes for assimilation of inorganic nitrogen and sulfur, and (iii) proteins associated with zoospore formation and motility. These attributes comprise a genomic signature of evolution toward obligate biotrophy.

The Aspergillus Genome Database, a curated comparative genomics resource for gene, protein and sequence information for the Aspergillus research community

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available, web-based resource for researchers studying fungi of the genus Aspergillus, which includes organisms of clinical, agricultural and industrial importance. AspGD curators have now completed comprehensive review of the entire published literature about Aspergillus nidulans and Aspergillus fumigatus, and this annotation is provided with streamlined, ortholog-based navigation of the multispecies information. AspGD facilitates comparative genomics by providing a full-featured genomics viewer, as well as matched and standardized sets of genomic information for the sequenced aspergilli. AspGD also provides resources to foster interaction and dissemination of community information and resources. We welcome and encourage feedback at aspergillus-curator@lists.stanford.edu.

Simultaneous Transcriptional Profiling of Bacteria and Their Host Cells

The Aspergillus Genome Database (AspGD) is an online genomics resource for researchers studying the genetics and molecular biology of the Aspergilli. AspGD combines high-quality manual curation of the experimental scientific literature examining the genetics and molecular biology of Aspergilli, cutting-edge comparative genomics approaches to iteratively refine and improve structural gene annotations across multiple Aspergillus species, and web-based research tools for accessing and exploring the data. All of these data are freely available at http://www.aspgd.org. We welcome feedback from users and the research community at aspergillus-curator@genome.stanford.edu.

Expressed Sequence Tags from Phytophthora sojae Reveal Genes Specific to Development and Infection

We developed an RNA-Seq-based method to simultaneously capture prokaryotic and eukaryotic expression profiles of cells infected with intracellular bacteria. As proof of principle, this method was applied to Chlamydia trachomatis-infected epithelial cell monolayers in vitro, successfully obtaining transcriptomes of both C. trachomatis and the host cells at 1 and 24 hours post-infection. Chlamydiae are obligate intracellular bacterial pathogens that cause a range of mammalian diseases. In humans chlamydiae are responsible for the most common sexually transmitted bacterial infections and trachoma (infectious blindness). Disease arises by adverse host inflammatory reactions that induce tissue damage & scarring. However, little is known about the mechanisms underlying these outcomes. Chlamydia are genetically intractable as replication outside of the host cell is not yet possible and there are no practical tools for routine genetic manipulation, making genome-scale approaches critical. The early timeframe of infection is poorly understood and the host transcriptional response to chlamydial infection is not well defined. Our simultaneous RNA-Seq method was applied to a simplified in vitro model of chlamydial infection. We discovered a possible chlamydial strategy for early iron acquisition, putative immune dampening effects of chlamydial infection on the host cell, and present a hypothesis for Chlamydia-induced fibrotic scarring through runaway positive feedback loops. In general, simultaneous RNA-Seq helps to reveal the complex interplay between invading bacterial pathogens and their host mammalian cells and is immediately applicable to any bacteria/host cell interaction.

Standardized description of scientific evidence using the Evidence Ontology (ECO).

Six unique expressed sequence tag (EST) libraries were generated from four developmental stages of Phytophthora sojae P6497. RNA was extracted from mycelia, swimming zoospores, germinating cysts, and soybean (Glycine max (L.) Merr.) cv. Harosoy tissues heavily infected with P. sojae. Three libraries were created from mycelia growing on defined medium, complex medium, and nutrient-limited medium. The 26,943 high-quality sequences obtained clustered into 7,863 unigenes composed of 2,845 contigs and 5,018 singletons. The total number of P. sojae unigenes matching sequences in the genome assembly was 7,412 (94%). Of these unigenes, 7,088 (90%) matched gene models predicted from the P. sojae sequence assembly, but only 2,047 (26%) matched P. ramorum gene models. Analysis of EST frequency from different growth conditions and morphological stages revealed genes that were specific to or highly represented in particular growth conditions and life stages. Additionally, our results indicate that, during infection, the pathogen derives most of its carbon and energy via glycolysis of sugars in the plant. Sequences identified with putative roles in pathogenesis included avirulence homologs possessing the RxLR motif, elicitins, and hydrolytic enzymes. This large collection of P. sojae ESTs will serve as a valuable public genomic resource.

The Ontology for Biomedical Investigations

The Evidence Ontology (ECO) is a structured, controlled vocabulary for capturing evidence in biological research. ECO includes diverse terms for categorizing evidence that supports annotation assertions including experimental types, computational methods, author statements and curator inferences. Using ECO, annotation assertions can be distinguished according to the evidence they are based on such as those made by curators versus those automatically computed or those made via high-throughput data review versus single test experiments. Originally created for capturing evidence associated with Gene Ontology annotations, ECO is now used in other capacities by many additional annotation resources including UniProt, Mouse Genome Informatics, Saccharomyces Genome Database, PomBase, the Protein Information Resource and others. Information on the development and use of ECO can be found at http://evidenceontology.org. The ontology is freely available under Creative Commons license (CC BY-SA 3.0), and can be downloaded in both Open Biological Ontologies and Web Ontology Language formats at http://code.google.com/p/evidenceontology. Also at this site is a tracker for user submission of term requests and questions. ECO remains under active development in response to user-requested terms and in collaborations with other ontologies and database resources. Database URL: Evidence Ontology Web site: http://evidenceontology.org

The Confidence Information Ontology: A Step Towards a Standard for Asserting Confidence in Annotations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Programmed cell death in host-symbiont associations, viewed through the Gene Ontology

Biocuration has become a cornerstone for analyses in biology, and to meet needs, the amount of annotations has considerably grown in recent years. However, the reliability of these annotations varies; it has thus become necessary to be able to assess the confidence in annotations. Although several resources already provide confidence information about the annotations that they produce, a standard way of providing such information has yet to be defined. This lack of standardization undermines the propagation of knowledge across resources, as well as the credibility of results from high-throughput analyses. Seeded at a workshop during the Biocuration 2012 conference, a working group has been created to address this problem. We present here the elements that were identified as essential for assessing confidence in annotations, as well as a draft ontology—the Confidence Information Ontology—to illustrate how the problems identified could be addressed. We hope that this effort will provide a home for discussing this major issue among the biocuration community. Tracker URL: https://github.com/BgeeDB/confidence-information-ontology Ontology URL: https://raw.githubusercontent.com/BgeeDB/confidence-information-ontology/master/src/ontology/cio-simple.obo