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      Horizontal gene transfer of a functional cki homolog in the human pathogen Schistosoma mansoni

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      bioRxiv
      Cold Spring Harbor Laboratory

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          Abstract

          Schistosomes are parasitic flatworms responsible for the neglected tropical disease schistosomiasis, causing devastating morbidity and mortality in the developing world. The parasites are protected by a skin-like tegument, and maintenance of this tegument is controlled by a schistosome ortholog of the tumor suppressor TP53. To understand mechanistically how p53–1 controls tegument production, we identified a cyclin dependent kinase inhibitor homolog ( cki) that was co-expressed with p53–1. RNA interference of cki resulted in a hyperproliferation phenotype, that, in combination with p53–1 RNA interference yielded abundant tumor-like growths, indicating that cki and p53–1 are bona fide tumor suppressors in Schistosoma mansoni. Interestingly, cki homologs are widely present throughout parasitic flatworms but evidently absent from their free-living ancestors, suggesting this cki homolog came from an ancient horizontal gene transfer event. This in turn implies that the evolution of parasitism in flatworms may have been aided by a highly unusual means of metazoan genetic inheritance.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference

            Abstract Motivation Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets. Results We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric. Availability and implementation The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng . RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/ . Supplementary information Supplementary data are available at Bioinformatics online.
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              Search and sequence analysis tools services from EMBL-EBI in 2022

              The EMBL-EBI search and sequence analysis tools frameworks provide integrated access to EMBL-EBI’s data resources and core bioinformatics analytical tools. EBI Search ( https://www.ebi.ac.uk/ebisearch ) provides a full-text search engine across nearly 5 billion entries, while the Job Dispatcher tools framework ( https://www.ebi.ac.uk/services ) enables the scientific community to perform a diverse range of sequence analysis using popular bioinformatics applications. Both allow users to interact through user-friendly web applications, as well as via RESTful and SOAP-based APIs. Here, we describe recent improvements to these services and updates made to accommodate the increasing data requirements during the COVID-19 pandemic. Graphical Abstract Overview of the tools and data resources provided by EBI Search and Job Dispatcher services accessible via their webpage and programmatic interfaces.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                27 May 2024
                : 2024.05.27.596073
                Affiliations
                Department of Pharmacology, University of Texas Southwestern Medical Center
                Author notes
                [* ]To whom correspondence should be addressed
                Author information
                http://orcid.org/0000-0002-8302-079X
                Article
                10.1101/2024.05.27.596073
                11160599
                38853947
                8bc62125-0d49-40f0-86d0-fae814a79e9f

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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