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      Extensive molecular tinkering in the evolution of the membrane attachment mode of the Rheb GTPase

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          Abstract

          Rheb is a conserved and widespread Ras-like GTPase involved in cell growth regulation mediated by the (m)TORC1 kinase complex and implicated in tumourigenesis in humans. Rheb function depends on its association with membranes via prenylated C-terminus, a mechanism shared with many other eukaryotic GTPases. Strikingly, our analysis of a phylogenetically rich sample of Rheb sequences revealed that in multiple lineages this canonical and ancestral membrane attachment mode has been variously altered. The modifications include: (1) accretion to the N-terminus of two different phosphatidylinositol 3-phosphate-binding domains, PX in Cryptista (the fusion being the first proposed synapomorphy of this clade), and FYVE in Euglenozoa and the related undescribed flagellate SRT308; (2) acquisition of lipidic modifications of the N-terminal region, namely myristoylation and/or S-palmitoylation in seven different protist lineages; (3) acquisition of S-palmitoylation in the hypervariable C-terminal region of Rheb in apusomonads, convergently to some other Ras family proteins; (4) replacement of the C-terminal prenylation motif with four transmembrane segments in a novel Rheb paralog in the SAR clade; (5) loss of an evident C-terminal membrane attachment mechanism in Tremellomycetes and some Rheb paralogs of Euglenozoa. Rheb evolution is thus surprisingly dynamic and presents a spectacular example of molecular tinkering.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

              S Altschul (1997)
              The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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                Author and article information

                Contributors
                marek.elias@osu.cz
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 March 2018
                27 March 2018
                2018
                : 8
                : 5239
                Affiliations
                [1 ]ISNI 0000 0001 2155 4545, GRID grid.412684.d, Department of Biology and Ecology & Institute of Environmental Technologies, Faculty of Science, , University of Ostrava, ; Ostrava, Czech Republic
                [2 ]ISNI 0000 0001 2292 3357, GRID grid.14848.31, Department of Biochemistry and Robert-Cedergren Centre for Bioinformatics and Genomics, , Université de Montréal, ; Montreal, Canada
                [3 ]ISNI 0000 0001 2369 4728, GRID grid.20515.33, Institute for Biological Sciences, University of Tsukuba, ; Tsukuba, Japan
                [4 ]ISNI 0000 0001 2192 9124, GRID grid.4886.2, Laboratory of Microbiology, Papanin Institute for Biology of Inland Waters, Russian Academy of Sciences, ; Borok, Russia
                [5 ]ISNI 0000000121901201, GRID grid.83440.3b, Department of Genetics, Evolution and Environment, , University College London, ; London, United Kingdom
                [6 ]ISNI 0000 0004 1937 116X, GRID grid.4491.8, Department of Parasitology, Faculty of Science, , Charles University, ; Prague, Czech Republic
                [7 ]ISNI 0000 0001 2369 4728, GRID grid.20515.33, Center for Computational Sciences, University of Tsukuba, ; Tsukuba, Japan
                [8 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Botany, , University of British Columbia, ; Vancouver, Canada
                Author information
                http://orcid.org/0000-0001-8689-0080
                http://orcid.org/0000-0002-8679-8812
                Article
                23575
                10.1038/s41598-018-23575-0
                5869587
                29588502
                0cdf6200-5f81-4403-ac96-3fc4e802284e
                © The Author(s) 2018

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 December 2017
                : 15 March 2018
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