Ulrike Böhme

We present Apollo 3, a new manual genome annotation tool that integrates with the JBrowse 2 genome browser. Its functionality is inspired by existing manual genome annotation tools such as Apollo, Artemis, and Otter, but uses an updated and more scalable architecture and technology stack. It allows the simultaneous editing of multiple genomes, including the visualization of synteny to inform those annotations. Apollo 3 can be used as a standalone annotation editor, or it can be installed on a server and used collaboratively. We describe the application’s design, features, and use cases.

Background: As sequencing technology improves, more genomes become available. Most lack annotation, automated methods are error prone, and few genomes are ever manually curated due to time and cost. Protein structure prediction software may provide new angles for assessing and improving gene models without requiring experimental data. In this paper, we explore whether scores from protein structure prediction can aid in scoring gene model quality. We chose three species ( Fusarium graminearum , Toxoplasma gondii , and Aspergillus fumigatus ) from the VEuPathDB database which have collectively undergone more than 1000 manual curation events. We modelled translations of the gene models with AlphaFold 3, before and after curation, collecting various scores. Then we carried out structure searching of the PDB with Foldseek and sequence-based domain identification using InterProScan. We profiled the scores produced by these methods to identify those best for gene model assessment. Results: AlphaFold 3 scores strongly favoured manually improved over pre-improvement models, supporting 75% of manually-curated changes in F. graminearum , 65% in T. gondii , and 84% in A. fumigatus (the lower percentage in T. gondii attributed to a high level of disorder). Further, combining scores across multiple tools (AlphaFold 3, Foldseek and InterProScan) provided additional improvements in model scoring. Conclusion: Overall, the most discriminative scores combined outputs of AlphaFold 3 and Foldseek. Our results therefore highlight the potential of scores derived from deep learning-based protein structure prediction for scoring gene models in the absence of experimental data. Future work should focus on intrinsically disordered regions and developing integrated tools to apply this approach.

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.

We present a genome assembly from a clonal population of Eimeria tenella Houghton parasites (Apicomplexa; Conoidasida; Eucoccidiorida; Eimeriidae). The genome sequence is 53.25 megabases in span. The entire assembly is scaffolded into 15 chromosomal pseudomolecules, with complete mitochondrion and apicoplast organellar genomes also present.

Background: Schistosoma mansoni is a flatworm that causes a neglected tropical disease affecting millions worldwide. Most flatworms are hermaphrodites but schistosomes have genotypically determined male (ZZ) and female (ZW) sexes. Sex is essential for pathology and transmission, however, the molecular determinants of sex remain unknown and is limited by poorly resolved sex chromosomes in previous genome assemblies. Results: We assembled the 391.4 Mb S. mansoni genome into individual, single-scaffold chromosomes, including Z and W. Manual curation resulted in a vastly improved gene annotation, resolved gene and repeat arrays, trans-splicing, and almost all UTRs. The sex chromosomes each comprise pseudoautosomal regions and single sex-specific regions. The Z-specific region contains 932 genes, but on W all but 29 of these genes have been lost and the presence of five pseudogenes indicates that degeneration of W is ongoing. Synteny analysis reveals an ancient chromosomal fusion corresponding to the oldest part of Z, where only a single gene—encoding the large subunit of pre-mRNA splicing factor U2AF—has retained an intact copy on W. The sex-specific copies of U2AF have divergent N-termini and show sex-biased gene expression. Conclusion: Our assembly with fully resolved chromosomes provides evidence of an evolutionary path taken to create the Z and W sex chromosomes of schistosomes. Sex-linked divergence of the single U2AF gene, which has been present in the sex-specific regions longer than any other extant gene with distinct male and female specific copies and expression, may have been a pivotal step in the evolution of gonorchorism and genotypic sex determination of schistosomes.

Hepatocystis is a genus of single-celled parasites infecting, amongst other hosts, monkeys, bats and squirrels. Although thought to have descended from malaria parasites (Plasmodium spp.), Hepatocystis spp. are thought not to undergo replication in the blood–the part of the Plasmodium life cycle which causes the symptoms of malaria. Furthermore, Hepatocystis is transmitted by biting midges, not mosquitoes. Comparative genomics of Hepatocystis and Plasmodium species therefore presents an opportunity to better understand some of the most important aspects of malaria parasite biology. We were able to generate a draft genome for Hepatocystis sp. using DNA sequencing reads from the blood of a naturally infected red colobus monkey. We provide robust phylogenetic support for Hepatocystis sp. as a sister group to Plasmodium parasites infecting rodents. We show transcriptomic support for a lack of replication in the blood and genomic support for a complete loss of a family of genes involved in red blood cell invasion. Our analyses highlight the rapid evolution of genes involved in parasite vector stages, revealing genes that may be critical for interactions between malaria parasites and mosquitoes. Hepatocystis parasites are single-celled organisms, closely related to the Plasmodium species which cause malaria. But Hepatocystis are distinct–unlike Plasmodium they are thought not to replicate in the blood and cause little or no disease in their mammalian hosts. They are transmitted from one host to the next, not by mosquitoes, but by biting midges. In this study we generated a genome sequence for Hepatocystis–the first time this data has ever been produced and analysed for this species. We compared genome sequences of Hepatocystis and Plasmodium, confirming that Hepatocystis is descended from Plasmodium. We strengthened support for the absence of replication in the blood and, in line with this finding, discovered that genes involved in interaction with red blood cells have been lost in Hepatocystis. Our analyses revealed rapid evolution of genes which are active when the parasite is in the insect vector, highlighting those which might be important for understanding interaction between malaria parasites and mosquitoes. Hepatocystis has a fascinating evolutionary story and is a powerful comparator for understanding malaria parasite biology.

Plasmodium vivax gene regulation remains difficult to study due to the lack of a robust in vitro culture method, low parasite densities in peripheral circulation and asynchronous parasite development. We adapted an RNA-seq protocol “DAFT-seq” to sequence the transcriptome of four P. vivax field isolates that were cultured for a short period ex vivo before using a density gradient for schizont enrichment. Transcription was detected from 78% of the PvP01 reference genome, despite being schizont-enriched samples. This extensive data was used to define thousands of 5’ and 3’ untranslated regions (UTRs), some of which overlapped with neighbouring transcripts, and to improve the gene models of 352 genes, including identifying 20 novel gene transcripts. This dataset has also significantly increased the known amount of heterogeneity between P. vivax schizont transcriptomes from individual patients. The majority of genes found to be differentially expressed between the isolates lack Plasmodium falciparum homologs and are predicted to be involved in host-parasite interactions, with an enrichment in reticulocyte binding proteins, merozoite surface proteins and exported proteins with unknown function. An improved understanding of the diversity within P. vivax transcriptomes will be essential for the prioritisation of novel vaccine targets.

Hepatocystis is a genus of single-celled parasites infecting monkeys, bats and squirrels. Although thought to descend from malaria parasites ( Plasmodium spp. ), Hepatocystis spp. are thought not to undergo replication in the blood – the part of the Plasmodium life cycle which causes the symptoms of malaria. Furthermore, Hepatocystis is transmitted by midges, not mosquitoes. Comparative genomics of Hepatocystis and Plasmodium species therefore presents an opportunity to better understand some of the most important aspects of malaria parasite biology. We were able to generate a draft genome for Hepatocystis using DNA sequencing reads from the blood of a naturally infected red colobus monkey. We provide robust phylogenetic support for Hepatocystis as a sister group to Plasmodium parasites infecting rodents. We show transcriptomic support for a lack of replication in the blood and genomic support for a complete loss of a family of genes involved in red blood cell invasion. Our analyses highlight the rapid evolution of genes involved in parasite vector stages, revealing genes that may be critical for interactions between malaria parasites and mosquitoes.

The var gene family of the human malaria parasite Plasmodium falciparum encode proteins that are crucial determinants of both pathogenesis and immune evasion and are highly polymorphic. Here we have assembled nearly complete var gene repertoires from 2398 field isolates and analysed a normalised set of 714 from across 12 countries. This therefore represents the first large scale attempt to catalogue the worldwide distribution of var gene sequences We confirm the extreme polymorphism of this gene family but also demonstrate an unexpected level of sequence sharing both within and between continents. We show that this is likely due to both the remnants of selective sweeps as well as a worrying degree of recent gene flow across continents with implications for the spread of drug resistance. We also address the evolution of the var repertoire with respect to the ancestral genes within the Laverania and show that diversity generated by recombination is concentrated in a number of hotspots. An analysis of the subdomain structure indicates that some existing definitions may need to be revised From the analysis of this data, we can now understand the way in which the family has evolved and how the diversity is continuously being generated. Finally, we demonstrate that because the genes are distributed across the genome, sequence sharing between genotypes acts as a useful population genetic marker.

Publishing authoritative genomic annotation data, keeping it up to date, linking it to related information, and allowing community annotation is difficult and hard to support with limited resources. Here, we show how importing GeneDB annotation data into Wikidata allows for leveraging existing resources, integrating volunteer and scientific communities, and enriching the original information.