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      Six reference-quality genomes reveal evolution of bat adaptations

      research-article
      1 , 2 , 3 , 4 , 1 , 3 , 4 , 5 , 5 , 1 , 4 , 6 , 7 , 8 , 8 , 9 , 10 , 10 , 1 , 2 , 3 , 1 , 2 , 3 , 11 , 12 , 13 , 4 , 14 , 14 , 15 , 16 , 17 , 4 , 18 , 19 , 20 , 20 , 21 , 22 , 1 , 2 , 3 , , 5 , 23 , , 1 , 3 , 24 , , 4 ,
      Nature
      Nature Publishing Group UK
      Phylogenetics, Evolutionary biology, Genomics, Virology

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          Abstract

          Bats possess extraordinary adaptations, including flight, echolocation, extreme longevity and unique immunity. High-quality genomes are crucial for understanding the molecular basis and evolution of these traits. Here we incorporated long-read sequencing and state-of-the-art scaffolding protocols 1 to generate, to our knowledge, the first reference-quality genomes of six bat species ( Rhinolophus ferrumequinum, Rousettus aegyptiacus, Phyllostomus discolor, Myotis myotis, Pipistrellus kuhlii and Molossus molossus). We integrated gene projections from our ‘Tool to infer Orthologs from Genome Alignments’ (TOGA) software with de novo and homology gene predictions as well as short- and long-read transcriptomics to generate highly complete gene annotations. To resolve the phylogenetic position of bats within Laurasiatheria, we applied several phylogenetic methods to comprehensive sets of orthologous protein-coding and noncoding regions of the genome, and identified a basal origin for bats within Scrotifera. Our genome-wide screens revealed positive selection on hearing-related genes in the ancestral branch of bats, which is indicative of laryngeal echolocation being an ancestral trait in this clade. We found selection and loss of immunity-related genes (including pro-inflammatory NF-κB regulators) and expansions of anti-viral APOBEC3 genes, which highlights molecular mechanisms that may contribute to the exceptional immunity of bats. Genomic integrations of diverse viruses provide a genomic record of historical tolerance to viral infection in bats. Finally, we found and experimentally validated bat-specific variation in microRNAs, which may regulate bat-specific gene-expression programs. Our reference-quality bat genomes provide the resources required to uncover and validate the genomic basis of adaptations of bats, and stimulate new avenues of research that are directly relevant to human health and disease 1 .

          Abstract

          Reference-quality genomes for six bat species shed light on the phylogenetic position of Chiroptera, and provide insight into the genetic underpinnings of the unique adaptations of this clade.

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          Most cited references93

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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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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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                hiller@mpi-cbg.de
                sonja.vernes@mpi.nl
                gene@mpi-cbg.de
                emma.teeling@ucd.ie
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                22 July 2020
                22 July 2020
                2020
                : 583
                : 7817
                : 578-584
                Affiliations
                [1 ]ISNI 0000 0001 2113 4567, GRID grid.419537.d, Max Planck Institute of Molecular Cell Biology and Genetics, ; Dresden, Germany
                [2 ]ISNI 0000 0001 2154 3117, GRID grid.419560.f, Max Planck Institute for the Physics of Complex Systems, ; Dresden, Germany
                [3 ]GRID grid.495510.c, Center for Systems Biology Dresden, ; Dresden, Germany
                [4 ]ISNI 0000 0001 0768 2743, GRID grid.7886.1, School of Biology and Environmental Science, , University College Dublin, ; Dublin, Ireland
                [5 ]ISNI 0000 0004 0501 3839, GRID grid.419550.c, Neurogenetics of Vocal Communication Group, , Max Planck Institute for Psycholinguistics, ; Nijmegen, The Netherlands
                [6 ]ISNI 0000 0001 2180 7477, GRID grid.1001.0, Research School of Biology, , Australian National University, ; Canberra, Australian Capital Territory Australia
                [7 ]ISNI 0000 0001 0768 2743, GRID grid.7886.1, Earth Institute, , University College Dublin, ; Dublin, Ireland
                [8 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Peter Medawar Building for Pathogen Research, Department of Zoology, , University of Oxford, ; Oxford, UK
                [9 ]ISNI 0000 0001 0768 2743, GRID grid.7886.1, Conway Institute of Biomolecular and Biomedical Science, , University College Dublin, ; Dublin, Ireland
                [10 ]ISNI 0000 0001 2186 7496, GRID grid.264784.b, Department of Biological Sciences, , Texas Tech University, ; Lubbock, TX USA
                [11 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Department of Ecology and Evolution, , Stony Brook University, ; Stony Brook, NY USA
                [12 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Consortium for Inter-Disciplinary Environmental Research, , Stony Brook University, ; Stony Brook, NY USA
                [13 ]ISNI 0000 0004 1937 0116, GRID grid.258202.f, Department of Sciences, , John Jay College of Criminal Justice, ; New York, NY USA
                [14 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, School of Biological Sciences, , University of Bristol, ; Bristol, UK
                [15 ]ISNI 0000 0004 7661 536X, GRID grid.507516.0, Department of Migration, , Max Planck Institute of Animal Behavior, ; Radolfzell, Germany
                [16 ]ISNI 0000 0001 0658 7699, GRID grid.9811.1, Department of Biology, , University of Konstanz, ; Konstanz, Germany
                [17 ]ISNI 0000 0001 2296 9689, GRID grid.438006.9, Smithsonian Tropical Research Institute, ; Panama City, Panama
                [18 ]ISNI 0000 0001 2188 7059, GRID grid.462058.d, ISEM, University of Montpellier, ; Montpellier, France
                [19 ]GRID grid.5603.0, Zoological Institute and Museum, , University of Greifswald, ; Greifswald, Germany
                [20 ]ISNI 0000 0001 2166 1519, GRID grid.134907.8, Vertebrate Genomes Laboratory, , The Rockefeller University, ; New York, NY USA
                [21 ]ISNI 0000 0001 2166 1519, GRID grid.134907.8, Laboratory of Neurogenetics of Language, , The Rockefeller University, ; New York, NY USA
                [22 ]ISNI 0000 0001 2167 1581, GRID grid.413575.1, Howard Hughes Medical Institute, ; Chevy Chase, MD USA
                [23 ]Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
                [24 ]ISNI 0000 0001 2111 7257, GRID grid.4488.0, Faculty of Computer Science, , Technical University Dresden, ; Dresden, Germany
                Author information
                http://orcid.org/0000-0002-1298-0486
                http://orcid.org/0000-0002-8134-5929
                http://orcid.org/0000-0002-9619-3809
                http://orcid.org/0000-0002-4327-7697
                http://orcid.org/0000-0002-5610-2992
                http://orcid.org/0000-0002-1904-3735
                http://orcid.org/0000-0003-0043-8267
                http://orcid.org/0000-0002-3763-7967
                http://orcid.org/0000-0001-9517-5775
                http://orcid.org/0000-0002-6450-7551
                http://orcid.org/0000-0001-8931-5049
                http://orcid.org/0000-0003-3024-1449
                http://orcid.org/0000-0003-0305-4584
                http://orcid.org/0000-0002-6580-7839
                http://orcid.org/0000-0002-3309-1346
                Article
                2486
                10.1038/s41586-020-2486-3
                8075899
                32699395
                bdd5a711-8d04-408c-b72d-5737de2f0926
                © The Author(s) 2020

                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 October 2019
                : 9 June 2020
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                © The Author(s), under exclusive licence to Springer Nature Limited 2020

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                phylogenetics,evolutionary biology,genomics,virology
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                phylogenetics, evolutionary biology, genomics, virology

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