Meeting report:Fungal genomics meets social media: Highlights of the 28th fungal genetics conference at asilomar

International audienc

Population Genetics, Evolutionary Genomics, and Genome-Wide Studies of Malaria: A View Across the International Centers of Excellence for Malaria Research.

The study of the three protagonists in malaria-the Plasmodium parasite, the Anopheles mosquito, and the human host-is key to developing methods to control and eventually eliminate the disease. Genomic technologies, including the recent development of next-generation sequencing, enable interrogation of this triangle to an unprecedented level of scrutiny, and promise exciting progress toward real-time epidemiology studies and the study of evolutionary adaptation. We discuss the use of genomics by the International Centers of Excellence for Malaria Research, a network of field sites and laboratories in malaria-endemic countries that undertake cutting-edge research, training, and technology transfer in malarious countries of the world

TriTrypDB: An integrated functional genomics resource for kinetoplastida.

Parasitic diseases caused by kinetoplastid parasites are a burden to public health throughout tropical and subtropical regions of the world. TriTrypDB (https://tritrypdb.org) is a free online resource for data mining of genomic and functional data from these kinetoplastid parasites and is part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org). As of release 59, TriTrypDB hosts 83 kinetoplastid genomes, nine of which, including Trypanosoma brucei brucei TREU927, Trypanosoma cruzi CL Brener and Leishmania major Friedlin, undergo manual curation by integrating information from scientific publications, high-throughput assays and user submitted comments. TriTrypDB also integrates transcriptomic, proteomic, epigenomic, population-level and isolate data, functional information from genome-wide RNAi knock-down and fluorescent tagging, and results from automated bioinformatics analysis pipelines. TriTrypDB offers a user-friendly web interface embedded with a genome browser, search strategy system and bioinformatics tools to support custom in silico experiments that leverage integrated data. A Galaxy workspace enables users to analyze their private data (e.g., RNA-sequencing, variant calling, etc.) and explore their results privately in the context of publicly available information in the database. The recent addition of an annotation platform based on Apollo enables users to provide both functional and structural changes that will appear as 'community annotations' immediately and, pending curatorial review, will be integrated into the official genome annotation

FungiDB: An Integrated Bioinformatic Resource for Fungi and Oomycetes

FungiDB (fungidb.org) is a free online resource for data mining and functional genomics analysis for fungal and oomycete species. FungiDB is part of the Eukaryotic Pathogen Genomics Database Resource (EuPathDB, eupathdb.org) platform that integrates genomic, transcriptomic, proteomic, and phenotypic datasets, and other types of data for pathogenic and non-pathogenic, free-living and parasitic organisms. FungiDB is one of the largest EuPathDB databases containing nearly 100 genomes obtained from GenBank, AspGD, The Broad Institute, JGI, Ensembl, and other sources. FungiDB offers a user-friendly web interface with embedded bioinformatics tools that support custom in silico experiments that leverage FungiDB-integrated data. In addition, a Galaxy-based workspace enables users to generate custom pipelines for large scale data analysis (e.g. RNA-Seq, variant calling, etc.). This review provides an introduction to the FungiDB resources and focuses on available features, tools and queries and how they can be used to mine data across a diverse range of integrated FungiDB datasets and records

EuPathDB: the eukaryotic pathogen genomics database resource

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions

What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species

GeneDB--an annotation database for pathogens.

GeneDB (http://www.genedb.org) is a genome database for prokaryotic and eukaryotic pathogens and closely related organisms. The resource provides a portal to genome sequence and annotation data, which is primarily generated by the Pathogen Genomics group at the Wellcome Trust Sanger Institute. It combines data from completed and ongoing genome projects with curated annotation, which is readily accessible from a web based resource. The development of the database in recent years has focused on providing database-driven annotation tools and pipelines, as well as catering for increasingly frequent assembly updates. The website has been significantly redesigned to take advantage of current web technologies, and improve usability. The current release stores 41 data sets, of which 17 are manually curated and maintained by biologists, who review and incorporate data from the scientific literature, as well as other sources. GeneDB is primarily a production and annotation database for the genomes of predominantly pathogenic organisms

Babesia duncani multi-omics identifies virulence factors and drug targets

Babesiosis is a malaria-like disease in humans and animals that is caused by Babesia species, which are tick-transmitted apicomplexan pathogens. Babesia duncani causes severe to lethal infection in humans, but despite the risk that this parasite poses as an emerging pathogen, little is known about its biology, metabolic requirements or pathogenesis. Unlike other apicomplexan parasites that infect red blood cells, B. duncani can be continuously cultured in vitro in human erythrocytes and can infect mice resulting in fulminant babesiosis and death. We report comprehensive, detailed molecular, genomic, transcriptomic and epigenetic analyses to gain insights into the biology of B. duncani. We completed the assembly, 3D structure and annotation of its nuclear genome, and analysed its transcriptomic and epigenetics profiles during its asexual life cycle stages in human erythrocytes. We used RNA-seq data to produce an atlas of parasite metabolism during its intraerythrocytic life cycle. Characterization of the B. duncani genome, epigenome and transcriptome identified classes of candidate virulence factors, antigens for diagnosis of active infection and several attractive drug targets. Furthermore, metabolic reconstitutions from genome annotation and in vitro efficacy studies identified antifolates, pyrimethamine and WR-99210 as potent inhibitors of B. duncani to establish a pipeline of small molecules that could be developed as effective therapies for the treatment of human babesiosis.We thank R. Gao for her contribution to the initial eforts to sequence the B. duncani genome. C.B.M.’s research was supported by grants from the National Institutes of Health (AI097218, GM110506, AI123321 and R43AI136118), the Steven and Alexandra Cohen Foundation (Lyme 62 2020), and the Global Lyme Alliance. S.L.’s research was supported by grants by the US National Science Foundation (IIS 1814359) and the National Institutes of Health (1R01AI169543-01). K.G.L.R.’s research was supported by the National Institutes of Allergy and Infectious Diseases (R01 AI136511, R01 AI142743-01 and R21 AI142506-01), the University of California, Riverside (NIFA-Hatch-225935) and the Health Institute Carlos III (PI20CIII/00037).S