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      The evolution of the huntingtin-associated protein 40 (HAP40) in conjunction with huntingtin

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          Abstract

          Background

          The huntingtin-associated protein 40 (HAP40) abundantly interacts with huntingtin (HTT), the protein that is altered in Huntington’s disease (HD). Therefore, we analysed the evolution of HAP40 and its interaction with HTT.

          Results

          We found that in amniotes HAP40 is encoded by a single-exon gene, whereas in all other organisms it is expressed from multi-exon genes. HAP40 co-occurs with HTT in unikonts, including filastereans such as Capsaspora owczarzaki and the amoebozoan Dictyostelium discoideum, but both proteins are absent from fungi . Outside unikonts, a few species, such as the free-living amoeboflagellate Naegleria gruberi, contain putative HTT and HAP40 orthologs.

          Biochemically we show that the interaction between HTT and HAP40 extends to fish, and bioinformatic analyses provide evidence for evolutionary conservation of this interaction. The closest homologue of HAP40 in current protein databases is the family of soluble N-ethylmaleimide-sensitive factor attachment proteins (SNAPs).

          Conclusion

          Our results indicate that the transition from a multi-exon to a single-exon gene appears to have taken place by retroposition during the divergence of amphibians and amniotes, followed by the loss of the parental multi-exon gene. Furthermore, it appears that the two proteins probably originated at the root of eukaryotes. Conservation of the interaction between HAP40 and HTT and their likely coevolution strongly indicate functional importance of this interaction.

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          Most cited references68

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            UCSF Chimera--a visualization system for exploratory research and analysis.

            The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Contributors
                andrei.lupas@tuebingen.mpg.de
                stefan.kochanek@uni-ulm.de
                Journal
                BMC Evol Biol
                BMC Evol Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                9 December 2020
                9 December 2020
                2020
                : 20
                : 162
                Affiliations
                [1 ]GRID grid.6582.9, ISNI 0000 0004 1936 9748, Department of Gene Therapy, , Ulm University, ; 89081 Ulm, Germany
                [2 ]GRID grid.419495.4, ISNI 0000 0001 1014 8330, Department of Protein Evolution, Max Planck Institute for Developmental Biology, ; Max-Planck-Ring 5, 72076 Tübingen, Germany
                [3 ]GRID grid.418615.f, ISNI 0000 0004 0491 845X, Department of Molecular Structural Biology, Max Planck Institute of Biochemistry, ; 82152 Martinsried, Germany
                [4 ]GRID grid.411984.1, ISNI 0000 0001 0482 5331, Institute of Neuropathology, , University Medical Center Göttingen, ; 37099 Göttingen, Germany
                [5 ]GRID grid.7450.6, ISNI 0000 0001 2364 4210, Cluster of Excellence “Multiscale Bioimaging: From Molecular Machines To Networks of Excitable Cells” (MBExC), , University of Göttingen, ; Göttingen, Germany
                [6 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Present Address: Peking-Tsinghua Joint Center for Life Sciences, School of Life Sciences, , Peking University, ; Beijing, 100871 China
                Author information
                http://orcid.org/0000-0001-7494-1602
                Article
                1705
                10.1186/s12862-020-01705-5
                7725122
                cb488113-c075-4269-8c60-8d1127dc60ed
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 2 March 2020
                : 20 October 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: 412854449
                Award ID: EXC 2067/1- 390729940
                Award Recipient :
                Funded by: European Commission ()
                Award ID: FP7 GA ERC-2012-SyG_318987-ToPAG
                Award Recipient :
                Funded by: Projekt DEAL
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Evolutionary Biology
                huntingtin,huntingtin-associated protein 40,soluble n-ethylmaleimide-sensitive factor attachment proteins,retroposition,single-exon gene,molecular evolution,protein coevolution

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