Genome annotations are often published as plain text files describing genomic features and their subcomponents by an implicit annotation graph. In this paper, we present the GenomeTools, a convenient and efficient software library and associated software tools for developing bioinformatics software intended to create, process or convert annotation graphs. The GenomeTools strictly follow the annotation graph approach, offering a unified graph-based representation. This gives the developer intuitive and immediate access to genomic features and tools for their manipulation. To process large annotation sets with low memory overhead, we have designed and implemented an efficient pull-based approach for sequential processing of annotations. This allows to handle even the largest annotation sets, such as a complete catalogue of human variations. Our object-oriented C-based software library enables a developer to conveniently implement their own functionality on annotation graphs and to integrate it into larger workflows, simultaneously accessing compressed sequence data if required. The careful C implementation of the GenomeTools does not only ensure a light-weight memory footprint while allowing full sequential as well as random access to the annotation graph, but also facilitates the creation of bindings to a variety of script programming languages (like Python and Ruby) sharing the same interface.

Many evolutionarily distant pathogenic organisms have evolved similar survival strategies to evade the immune responses of their hosts. These include antigenic variation, through which an infecting organism prevents clearance by periodically altering the identity of proteins that are visible to the immune system of the host1. Antigenic variation requires large reservoirs of immunologically diverse antigen genes, which are often generated through homologous recombination, as well as mechanisms to ensure the expression of one or very few antigens at any given time. Both homologous recombination and gene expression are affected by three-dimensional genome architecture and local DNA accessibility2,3. Factors that link three-dimensional genome architecture, local chromatin conformation and antigenic variation have, to our knowledge, not yet been identified in any organism. One of the major obstacles to studying the role of genome architecture in antigenic variation has been the highly repetitive nature and heterozygosity of antigen-gene arrays, which has precluded complete genome assembly in many pathogens. Here we report the de novo haplotype-specific assembly and scaffolding of the long antigen-gene arrays of the model protozoan parasite Trypanosoma brucei, using long-read sequencing technology and conserved features of chromosome folding4. Genome-wide chromosome conformation capture (Hi-C) reveals a distinct partitioning of the genome, with antigen-encoding subtelomeric regions that are folded into distinct, highly compact compartments. In addition, we performed a range of analyses—Hi-C, fluorescence in situ hybridization, assays for transposase-accessible chromatin using sequencing and single-cell RNA sequencing—that showed that deletion of the histone variants H3.V and H4.V increases antigen-gene clustering, DNA accessibility across sites of antigen expression and switching of the expressed antigen isoform, via homologous recombination. Our analyses identify histone variants as a molecular link between global genome architecture, local chromatin conformation and antigenic variation.

Long terminal repeat (LTR) retrotransposons and endogenous retroviruses (ERVs) are transposable elements in eukaryotic genomes well suited for computational identification. De novo identification tools determine the position of potential LTR retrotransposon or ERV insertions in genomic sequences. For further analysis, it is desirable to obtain an annotation of the internal structure of such candidates. This article presents LTRdigest, a novel software tool for automated annotation of internal features of putative LTR retrotransposons. It uses local alignment and hidden Markov model-based algorithms to detect retrotransposon-associated protein domains as well as primer binding sites and polypurine tracts. As an example, we used LTRdigest results to identify 88 (near) full-length ERVs in the chromosome 4 sequence of Mus musculus, separating them from truncated insertions and other repeats. Furthermore, we propose a work flow for the use of LTRdigest in de novo LTR retrotransposon classification and perform an exemplary de novo analysis on the Drosophila melanogaster genome as a proof of concept. Using a new method solely based on the annotations generated by LTRdigest, 518 potential LTR retrotransposons were automatically assigned to 62 candidate groups. Representative sequences from 41 of these 62 groups were matched to reference sequences with >80% global sequence similarity.

Plasmodium vivax is now the predominant cause of malaria in the Asia-Pacific, South America and Horn of Africa. Laboratory studies of this species are constrained by the inability to maintain the parasite in continuous ex vivo culture, but genomic approaches provide an alternative and complementary avenue to investigate the parasite’s biology and epidemiology. To date, molecular studies of P. vivax have relied on the Salvador-I reference genome sequence, derived from a monkey-adapted strain from South America. However, the Salvador-I reference remains highly fragmented with over 2500 unassembled scaffolds.  Using high-depth Illumina sequence data, we assembled and annotated a new reference sequence, PvP01, sourced directly from a patient from Papua Indonesia. Draft assemblies of isolates from China (PvC01) and Thailand (PvT01) were also prepared for comparative purposes. The quality of the PvP01 assembly is improved greatly over Salvador-I, with fragmentation reduced to 226 scaffolds. Detailed manual curation has ensured highly comprehensive annotation, with functions attributed to 58% core genes in PvP01 versus 38% in Salvador-I. The assemblies of PvP01, PvC01 and PvT01 are larger than that of Salvador-I (28-30 versus 27 Mb), owing to improved assembly of the subtelomeres.  An extensive repertoire of over 1200 Plasmodium interspersed repeat (pir) genes were identified in PvP01 compared to 346 in Salvador-I, suggesting a vital role in parasite survival or development. The manually curated PvP01 reference and PvC01 and PvT01 draft assemblies are important new resources to study vivax malaria. PvP01 is maintained at GeneDB and ongoing curation will ensure continual improvements in assembly and annotation quality.

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.