A cause for consilience: Utilizing multiple genomic data types to resolve problematic nodes within Arthropoda and Ecdysozoa

A major turning point in the study of metazoan evolution was the recognition of the existence of the Ecdysozoa in 1997. This is a group of eight animal phyla (Nematoda, Nematomorpha, Loricifera, Kinorhyncha, Priapulida, Tardigrada, Onychophora and Arthropoda). Ecdysozoa is the most specious clade of animals to ever exist and the relationships among its eight phyla are still heatedly debated. Similarly also the relationships among the three sub-phyla (Chelicerata, Pancrustacea and Myriapoda) within the most important ecdysozoan phylum (the Arthropoda) are still debated. Indeed, the two major problems in ecdysozoan phylogeny refer to the relationships of Myriapoda within Arthropoda, and of Tardigrada within Ecdysozoa. Difficulties in ecdysozoan relationships resides in lineages characterized by rapid, deep divergences and subsequently long periods of divergent evolution. Phylogenetic signal to resolve the relationships of these lineages is diluted, increasing the likelihood of recovery of phylogenetic artifacts. In an attempt to resolve the relationships within Ecdysozoa, consilience of three independent phylogenetic data sets was investigated. EST and rRNA and microRNA (miRNA) data were sampled across all major ecdysozoan phyla. In particular, a major contribution of this thesis is the first time sequencing of miRNAs for all the panarthropod phyla. MicroRNAs are genome regulatory elements that recently emerged as a source of useful phylogenetic data (Sempere et al. 2006) because of their low homoplasy levels. The considered data sets were analysed under phylogenetic methods and models, implemented to minimize the occurrence of phylogenetic reconstruction artifacts to understand the evolution of Ecdysozoa. Analyses of independent data types recovered well supported and corroborating evidence for the monophyly of Panarthropoda (Arthropoda, Onychophora and Tardigrada), a sister group relationships between Myriapoda and Pancrustacea within Arthropoda, and the paraphyly of Cycloneuralia (Nematoda, Nematomorpha, Loricifera, Kinorhyncha and Priapulida).

A Polychaete’s Powerful Punch: Venom Gland Transcriptomics of Glycera Reveals a Complex Cocktail of Toxin Homologs

© The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. The article attached is the publisher's pdf

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

A cause for consilience: Utilizing multiple genomic data types to resolve problematic nodes within Arthropoda and Ecdysozoa

A major turning point in the study of metazoan evolution was the recognition of the existence of the Ecdysozoa in 1997. This is a group of eight animal phyla (Nematoda, Nematomorpha, Loricifera, Kinorhyncha, Priapulida, Tardigrada, Onychophora and Arthropoda). Ecdysozoa is the most specious clade of animals to ever exist and the relationships among its eight phyla are still heatedly debated. Similarly also the relationships among the three sub-phyla (Chelicerata, Pancrustacea and Myriapoda) within the most important ecdysozoan phylum (the Arthropoda) are still debated. Indeed, the two major problems in ecdysozoan phylogeny refer to the relationships of Myriapoda within Arthropoda, and of Tardigrada within Ecdysozoa. Difficulties in ecdysozoan relationships resides in lineages characterized by rapid, deep divergences and subsequently long periods of divergent evolution. Phylogenetic signal to resolve the relationships of these lineages is diluted, increasing the likelihood of recovery of phylogenetic artifacts. In an attempt to resolve the relationships within Ecdysozoa, consilience of three independent phylogenetic data sets was investigated. EST and rRNA and microRNA (miRNA) data were sampled across all major ecdysozoan phyla. In particular, a major contribution of this thesis is the first time sequencing of miRNAs for all the panarthropod phyla. MicroRNAs are genome regulatory elements that recently emerged as a source of useful phylogenetic data (Sempere et al. 2006) because of their low homoplasy levels. The considered data sets were analysed under phylogenetic methods and models, implemented to minimize the occurrence of phylogenetic reconstruction artifacts to understand the evolution of Ecdysozoa. Analyses of independent data types recovered well supported and corroborating evidence for the monophyly of Panarthropoda (Arthropoda, Onychophora and Tardigrada), a sister group relationships between Myriapoda and Pancrustacea within Arthropoda, and the paraphyly of Cycloneuralia (Nematoda, Nematomorpha, Loricifera, Kinorhyncha and Priapulida).

Comparative analyses of glycerotoxin expression unveil a novel structural organization of the bloodworm venom system

Background: We present the first molecular characterization of glycerotoxin (GLTx), a potent neurotoxin found in the venom of the bloodworm Glycera tridactyla (Glyceridae, Annelida). Within the animal kingdom, GLTx shows a unique mode of action as it can specifically up-regulate the activity of Cav2.2 channels (N-type) in a reversible manner. The lack of sequence information has so far hampered a detailed understanding of its mode of action. Results: Our analyses reveal three ~3.8 kb GLTx full-length transcripts, show that GLTx represents a multigene family, and suggest it functions as a dimer. An integrative approach using transcriptomics, quantitative real-time PCR, in situ hybridization, and immunocytochemistry shows that GLTx is highly expressed exclusively in four pharyngeal lobes, a previously unrecognized part of the venom apparatus. Conclusions: Our results overturn a century old textbook view on the glycerid venom system, suggesting that it is anatomically and functionally much more complex than previously thought. The herein presented GLTx sequence information constitutes an important step towards the establishment of GLTx as a versatile tool to understand the mechanism of synaptic function, as well as the mode of action of this novel neurotoxin.Copyright © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

MicroRNAs and phylogenomics resolve the relationships of Tardigrada and suggest that velvet worms are the sister group of Arthropoda

Morphological data traditionally group Tardigrada (water bears), Onychophora (velvet worms), and Arthropoda (e.g., spiders, insects, and their allies) into a monophyletic group of invertebrates with walking appendages known as the Panarthropoda. However, molecular data generally do not support the inclusion of tardigrades within the Panarthropoda, but instead place them closer to Nematoda (roundworms). Here we present results from the analyses of two independent genomic datasets, expressed sequence tags (ESTs) and microRNAs (miRNAs), which congruently resolve the phylogenetic relationships of Tardigrada. Our EST analyses, based on 49,023 amino acid sites from 255 proteins, significantly support a monophyletic Panarthropoda including Tardigrada and suggest a sister group relationship between Arthropoda and Onychophora. Using careful experimental manipulations—comparisons of model fit, signal dissection, and taxonomic pruning—we show that support for a Tardigrada + Nematoda group derives from the phylogenetic artifact of long-branch attraction. Our small RNA libraries fully support our EST results; no miRNAs were found to link Tardigrada and Nematoda, whereas all panarthropods were found to share one unique miRNA (miR-276). In addition, Onychophora and Arthropoda were found to share a second miRNA (miR-305). Our study confirms the monophyly of the legged ecdysozoans, shows that past support for a Tardigrada + Nematoda group was due to long-branch attraction, and suggests that the velvet worms are the sister group to the arthropods

Comparative evolutionary analyses of eight whitefly Bemisia tabaci sensu lato genomes: cryptic species, agricultural pests and plant-virus vectors

The genomes, transcriptomes, and predicted protein-coding sequences are available from Ensembl Metazoa (http://metazoa.ensembl.org) and are included within the references. Raw RNA-Seq datasets generated and/or analyzed during the current study are available from the European Nucleotide Archive database repository (https://www.ebi.ac.uk/ena) under the parent project accessions: PRJEB28507, PRJEB36965, PRJEB35304, PRJEB39408. All data generated during the analyses of these datasets are included in this published article, supplementary information files, and figshare repository (https://doi.org/10.6084/m9.figshare.23666799; https://doi.org/10.6084/m9.figshare.23666832.v4; https://doi.org/10.6084/m9.figshare.23666844).International audienceBackground: The group of > 40 cryptic whitefly species called Bemisia tabaci sensu lato are amongst the world's worst agricultural pests and plant-virus vectors. Outbreaks of B. tabaci s.l. and the associated plant-virus diseases continue to contribute to global food insecurity and social instability, particularly in sub-Saharan Africa and Asia. Published B. tabaci s.l. genomes have limited use for studying African cassava B. tabaci SSA1 species, due to the high genetic divergences between them. Genomic annotations presented here were performed using the 'Ensembl gene annotation system' , to ensure that comparative analyses and conclusions reflect biological differences, as opposed to arising from different methodologies underpinning transcript model identification. Results: We present here six new B. tabaci s.l. genomes from Africa and Asia, and two re-annotated previously published genomes, to provide evolutionary insights into these globally distributed pests. Genome sizes ranged between 616-658 Mb and exhibited some of the highest coverage of transposable elements reported within Arthropoda. Many fewer total protein coding genes (PCG) were recovered compared to the previously published B. tabaci s.l. genomes and structural annotations generated via the uniform methodology strongly supported a repertoire of between 12.8-13.2 × 10 3 PCG. An integrative systematics approach incorporating phylogenomic analysis of nuclear and mitochondrial markers supported a monophyletic Aleyrodidae and the basal positioning of B. tabaci Uganda-1 to the sub-Saharan group of species. Reciprocal cross-mating data and the co-cladogenesis pattern of the primary obligate endosymbiont 'Candidatus Portiera aleyrodidarum' from 11 Bemisia genomes further supported the phylogenetic reconstruction to show that African cassava B. tabaci populations consist of just three biological species. We include comparative analyses of gene families related to detoxification, sugar metabolism, vector competency and evaluate the presence and function of horizontally transferred genes, essential for understanding the evolution and unique biology of constituent B. tabaci. s.l species.Conclusions: These genomic resources have provided new and critical insights into the genetics underlying B. tabaci s.l. biology. They also provide a rich foundation for post-genomic research, including the selection of candidate gene-targets for innovative whitefly and virus-control strategies

Ensembl Genomes 2022: an expanding genome resource for non-vertebrates.

Ensembl Genomes (https://www.ensemblgenomes.org) provides access to non-vertebrate genomes and analysis complementing vertebrate resources developed by the Ensembl project (https://www.ensembl.org). The two resources collectively present genome annotation through a consistent set of interfaces spanning the tree of life presenting genome sequence, annotation, variation, transcriptomic data and comparative analysis. Here, we present our largest increase in plant, metazoan and fungal genomes since the project's inception creating one of the world's most comprehensive genomic resources and describe our efforts to reduce genome redundancy in our Bacteria portal. We detail our new efforts in gene annotation, our emerging support for pangenome analysis, our efforts to accelerate data dissemination through the Ensembl Rapid Release resource and our new AlphaFold visualization. Finally, we present details of our future plans including updates on our integration with Ensembl, and how we plan to improve our support for the microbial research community. Software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license). Data updates are synchronised with Ensembl's release cycle