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      Genomic signatures in the coral holobiont reveal host adaptations driven by Holocene climate change and reef specific symbionts

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          Abstract

          Genomes of 150 coral colonies reveal evolutionary processes related to past climatic change on the Great Barrier Reef.

          Abstract

          Genetic signatures caused by demographic and adaptive processes during past climatic shifts can inform predictions of species’ responses to anthropogenic climate change. To identify these signatures in Acropora tenuis, a reef-building coral threatened by global warming, we first assembled the genome from long reads and then used shallow whole-genome resequencing of 150 colonies from the central inshore Great Barrier Reef to inform population genomic analyses. We identify population structure in the host that reflects a Pleistocene split, whereas photosymbiont differences between reefs most likely reflect contemporary (Holocene) conditions. Signatures of selection in the host were associated with genes linked to diverse processes including osmotic regulation, skeletal development, and the establishment and maintenance of symbiosis. Our results suggest that adaptation to post-glacial climate change in A. tenuis has involved selection on many genes, while differences in symbiont specificity between reefs appear to be unrelated to host population structure.

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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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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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                November 2020
                27 November 2020
                : 6
                : 48
                : eabc6318
                Affiliations
                [1 ]College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia.
                [2 ]Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia.
                [3 ]Research School of Biology, Australian National University, Canberra, ACT, Australia.
                [4 ]ARC Centre of Excellence for Coral Reef Studies, Australian National University, Canberra, ACT, Australia.
                [5 ]California Academy of Sciences, Golden Gate Park, San Francisco, CA, USA.
                [6 ]Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, Queensland, Australia.
                [7 ]Department of Ecology, Environment and Evolution, School of Life Sciences, La Trobe University, Melbourne, Australia
                [8 ]College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
                [9 ]Department of Molecular Evolution and Development, University of Vienna, Austria.
                [10 ]ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia.
                [11 ]Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Queensland, Australia.
                [12 ]Institute of Environment and Department of Biological Sciences, Florida International University, Miami, Fl 33199, USA.
                [13 ]Australian Institute of Marine Science, Townsville, Queensland, Australia.
                [14 ]School of BioSciences, University of Melbourne, Melbourne, Australia.
                [15 ]Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
                Author notes
                [* ]Corresponding author. Email: ira.cooke@ 123456jcu.edu.au (I.C.); david.miller@ 123456jcu.edu.au (D.J.M.)
                Author information
                http://orcid.org/0000-0001-6520-1397
                http://orcid.org/0000-0002-6723-2733
                http://orcid.org/0000-0001-6747-6044
                http://orcid.org/0000-0003-2994-637X
                http://orcid.org/0000-0002-3585-4511
                http://orcid.org/0000-0003-1161-4836
                http://orcid.org/0000-0003-0788-6513
                http://orcid.org/0000-0003-3007-2841
                http://orcid.org/0000-0003-1327-0360
                http://orcid.org/0000-0002-1492-8710
                http://orcid.org/0000-0003-4607-0744
                http://orcid.org/0000-0003-1672-7020
                http://orcid.org/0000-0003-0291-9531
                Article
                abc6318
                10.1126/sciadv.abc6318
                7695477
                33246955
                c53e3b18-98b0-4fbd-928f-720316b7d9ff
                Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 09 May 2020
                : 15 October 2020
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Evolutionary Biology
                Genetics
                Evolutionary Biology
                Custom metadata
                Karla Peñamante

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