VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023.

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes.

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center.

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports >500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate >1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial & Viral BRC.

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.

Subtelomeric CTCF and cohesin binding site organization using improved subtelomere assemblies and a novel annotation pipeline.

Mapping genome-wide data to human subtelomeres has been problematic due to the incomplete assembly and challenges of low-copy repetitive DNA elements. Here, we provide updated human subtelomere sequence assemblies that were extended by filling telomere-adjacent gaps using clone-based resources. A bioinformatic pipeline incorporating multiread mapping for annotation of the updated assemblies using short-read data sets was developed and implemented. Annotation of subtelomeric sequence features as well as mapping of CTCF and cohesin binding sites using ChIP-seq data sets from multiple human cell types confirmed that CTCF and cohesin bind within 3 kb of the start of terminal repeat tracts at many, but not all, subtelomeres. CTCF and cohesin co-occupancy were also enriched near internal telomere-like sequence (ITS) islands and the nonterminal boundaries of subtelomere repeat elements (SREs) in transformed lymphoblastoid cell lines (LCLs) and human embryonic stem cell (ES) lines, but were not significantly enriched in the primary fibroblast IMR90 cell line. Subtelomeric CTCF and cohesin sites predicted by ChIP-seq using our bioinformatics pipeline (but not predicted when only uniquely mapping reads were considered) were consistently validated by ChIP-qPCR. The colocalized CTCF and cohesin sites in SRE regions are candidates for mediating long-range chromatin interactions in the transcript-rich SRE region. A public browser for the integrated display of short-read sequence-based annotations relative to key subtelomere features such as the start of each terminal repeat tract, SRE identity and organization, and subtelomeric gene models was established.

EuPathDB: the eukaryotic pathogen database.

EuPathDB (http://eupathdb.org) resources include 11 databases supporting eukaryotic pathogen genomic and functional genomic data, isolate data and phylogenomics. EuPathDB resources are built using the same infrastructure and provide a sophisticated search strategy system enabling complex interrogations of underlying data. Recent advances in EuPathDB resources include the design and implementation of a new data loading workflow, a new database supporting Piroplasmida (i.e. Babesia and Theileria), the addition of large amounts of new data and data types and the incorporation of new analysis tools. New data include genome sequences and annotation, strand-specific RNA-seq data, splice junction predictions (based on RNA-seq), phosphoproteomic data, high-throughput phenotyping data, single nucleotide polymorphism data based on high-throughput sequencing (HTS) and expression quantitative trait loci data. New analysis tools enable users to search for DNA motifs and define genes based on their genomic colocation, view results from searches graphically (i.e. genes mapped to chromosomes or isolates displayed on a map) and analyze data from columns in result tables (word cloud and histogram summaries of column content). The manuscript herein describes updates to EuPathDB since the previous report published in NAR in 2010.

Comparative sequence analyses reveal sites of ancestral chromosomal fusions in the Indian muntjac genome.

BACKGROUND: Indian muntjac (Muntiacus muntjak vaginalis) has an extreme mammalian karyotype, with only six and seven chromosomes in the female and male, respectively. Chinese muntjac (Muntiacus reevesi) has a more typical mammalian karyotype, with 46 chromosomes in both sexes. Despite this disparity, the two muntjac species are morphologically similar and can even interbreed to produce viable (albeit sterile) offspring. Previous studies have suggested that a series of telocentric chromosome fusion events involving telomeric and/or satellite repeats led to the extant Indian muntjac karyotype. RESULTS: We used a comparative mapping and sequencing approach to characterize the sites of ancestral chromosomal fusions in the Indian muntjac genome. Specifically, we screened an Indian muntjac bacterial artificial-chromosome library with a telomere repeat-specific probe. Isolated clones found by fluorescence in situ hybridization to map to interstitial regions on Indian muntjac chromosomes were further characterized, with a subset then subjected to shotgun sequencing. Subsequently, we isolated and sequenced overlapping clones extending from the ends of some of these initial clones; we also generated orthologous sequence from isolated Chinese muntjac clones. The generated Indian muntjac sequence has been analyzed for the juxtaposition of telomeric and satellite repeats and for synteny relationships relative to other mammalian genomes, including the Chinese muntjac. CONCLUSIONS: The generated sequence data and comparative analyses provide a detailed genomic context for seven ancestral chromosome fusion sites in the Indian muntjac genome, which further supports the telocentric fusion model for the events leading to the unusual karyotypic differences among muntjac species.

Fine-mapping subtelomeric deletions and duplications by comparative genomic hybridization in 42 individuals.

Human subtelomere regions contain numerous gene-rich segments and are susceptible to germline rearrangements. The availability of diagnostic test kits to detect subtelomeric rearrangements has resulted in the diagnosis of numerous abnormalities with clinical implications including congenital heart abnormalities and mental retardation. Several of these have been described as clinically recognizable syndromes (e.g., deletion of 1p, 3p, 5q, 6p, 9q, and 22q). Given this, fine-mapping of subtelomeric breakpoints is of increasing importance to the assessment of genotype-phenotype correlations in these recognized syndromes as well as to the identification of additional syndromes. We developed a BAC and cosmid-based DNA array (TEL array) with high-resolution coverage of 10 Mb-sized subtelomeric regions, and used it to analyze 42 samples from unrelated patients with subtelomeric rearrangements whose breakpoints were previously either unmapped or mapped at a lower resolution than that achievable with the TEL array. Six apparently recurrent subtelomeric breakpoint loci were localized to genomic regions containing segmental duplication, copy number variation, and sequence gaps. Small (1 Mb or less) candidate gene regions for clinical phenotypes in separate patients were identified for 3p, 6q, 9q, and 10p deletions as well as for a 19q duplication. In addition to fine-mapping nearly all of the expected breakpoints, several previously unidentified rearrangements were detected.

Human subtelomeric duplicon structure and organization.

BACKGROUND: Human subtelomeric segmental duplications ('subtelomeric repeats') comprise about 25% of the most distal 500 kb and 80% of the most distal 100 kb in human DNA. A systematic analysis of the duplication substructure of human subtelomeric regions was done in order to develop a detailed understanding of subtelomeric sequence organization and a nucleotide sequence-level characterization of subtelomeric duplicon families. RESULTS: The extent of nucleotide sequence divergence within subtelomeric duplicon families varies considerably, as does the organization of duplicon blocks at subtelomere alleles. Subtelomeric internal (TTAGGG)n-like tracts occur at duplicon boundaries, suggesting their involvement in the generation of the complex sequence organization. Most duplicons have copies at both subtelomere and non-subtelomere locations, but a class of duplicon blocks is identified that are subtelomere-specific. In addition, a group of six subterminal duplicon families are identified that, together with six single-copy telomere-adjacent segments, include all of the (TTAGGG)n-adjacent sequence identified so far in the human genome. CONCLUSION: Identification of a class of duplicon blocks that is subtelomere-specific will facilitate high-resolution analysis of subtelomere repeat copy number variation as well as studies involving somatic subtelomere rearrangements. The significant levels of nucleotide sequence divergence within many duplicon families as well as the differential organization of duplicon blocks on subtelomere alleles may provide opportunities for allele-specific subtelomere marker development; this is especially true for subterminal regions, where divergence and organizational differences are the greatest. These subterminal sequence families comprise the immediate cis-elements for (TTAGGG)n tracts, and are prime candidates for subtelomeric sequences regulating telomere-specific (TTAGGG)n tract length in humans.