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      A genomic glance through the fog of plasticity and diversification in Pocillopora

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          Abstract

          Scleractinian corals of the genus Pocillopora (Lamarck, 1816) are notoriously difficult to identify morphologically with considerable debate on the degree to which phenotypic plasticity, introgressive hybridization and incomplete lineage sorting obscure well-defined taxonomic lineages. Here, we used RAD-seq to resolve the phylogenetic relationships among seven species of Pocillopora represented by 15 coral holobiont metagenomic libraries. We found strong concordance between the coral holobiont datasets, reads that mapped to the Pocillopora damicornis (Linnaeus, 1758) transcriptome, nearly complete mitochondrial genomes, 430 unlinked high-quality SNPs shared across all Pocillopora taxa, and a conspecificity matrix of the holobiont dataset. These datasets also show strong concordance with previously published clustering of the mitochondrial clades based on the mtDNA open reading frame (ORF). We resolve seven clear monophyletic groups, with no evidence for introgressive hybridization among any but the most recently derived sister species. In contrast, ribosomal and histone datasets, which are most commonly used in coral phylogenies to date, were less informative and contradictory to these other datasets. These data indicate that extant Pocillopora species diversified from a common ancestral lineage within the last ~3 million years. Key to this evolutionary success story may be the high phenotypic plasticity exhibited by Pocillopora species.

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          PEAR: a fast and accurate Illumina Paired-End reAd mergeR

          Motivation: The Illumina paired-end sequencing technology can generate reads from both ends of target DNA fragments, which can subsequently be merged to increase the overall read length. There already exist tools for merging these paired-end reads when the target fragments are equally long. However, when fragment lengths vary and, in particular, when either the fragment size is shorter than a single-end read, or longer than twice the size of a single-end read, most state-of-the-art mergers fail to generate reliable results. Therefore, a robust tool is needed to merge paired-end reads that exhibit varying overlap lengths because of varying target fragment lengths. Results: We present the PEAR software for merging raw Illumina paired-end reads from target fragments of varying length. The program evaluates all possible paired-end read overlaps and does not require the target fragment size as input. It also implements a statistical test for minimizing false-positive results. Tests on simulated and empirical data show that PEAR consistently generates highly accurate merged paired-end reads. A highly optimized implementation allows for merging millions of paired-end reads within a few minutes on a standard desktop computer. On multi-core architectures, the parallel version of PEAR shows linear speedups compared with the sequential version of PEAR. Availability and implementation: PEAR is implemented in C and uses POSIX threads. It is freely available at http://www.exelixis-lab.org/web/software/pear. Contact: Tomas.Flouri@h-its.org
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            Phenotypic plasticity's impacts on diversification and speciation.

            Phenotypic plasticity (the ability of a single genotype to produce multiple phenotypes in response to variation in the environment) is commonplace. Yet its evolutionary significance remains controversial, especially in regard to whether and how it impacts diversification and speciation. Here, we review recent theory on how plasticity promotes: (i) the origin of novel phenotypes, (ii) divergence among populations and species, (iii) the formation of new species and (iv) adaptive radiation. We also discuss the latest empirical support for each of these evolutionary pathways to diversification and identify potentially profitable areas for future research. Generally, phenotypic plasticity can play a largely underappreciated role in driving diversification and speciation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
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              ExaBayes: Massively Parallel Bayesian Tree Inference for the Whole-Genome Era

              Modern sequencing technology now allows biologists to collect the entirety of molecular evidence for reconstructing evolutionary trees. We introduce a novel, user-friendly software package engineered for conducting state-of-the-art Bayesian tree inferences on data sets of arbitrary size. Our software introduces a nonblocking parallelization of Metropolis-coupled chains, modifications for efficient analyses of data sets comprising thousands of partitions and memory saving techniques. We report on first experiences with Bayesian inferences at the whole-genome level using the SuperMUC supercomputer and simulated data.
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                Author and article information

                Contributors
                erikacj@hawaii.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 July 2017
                20 July 2017
                2017
                : 7
                : 5991
                Affiliations
                [1 ]ISNI 0000 0001 2188 0957, GRID grid.410445.0, Hawai‘i Institute of Marine Biology, , University of Hawai‘i at Mānoa, ; Kāne‘ohe, HI 96744 USA
                [2 ]ISNI 0000 0001 2348 0746, GRID grid.4989.c, , Université libre de Bruxelles (ULB), ; Avenue F.D. Roosevelt 50, B-1050 Bruxelles, Belgium
                [3 ]ISNI 0000 0001 0328 1619, GRID grid.1046.3, , Australian Institute of Marine Science, ; 4810 Townsville, Australia
                [4 ]ISNI 0000 0001 1009 3608, GRID grid.5560.6, , Carl von Ossietzky University of Oldenburg, ; 26129 Oldenburg, Germany
                [5 ]ISNI 0000 0000 9482 7121, GRID grid.267313.2, Department of Psychiatry, , UT Southwestern Medical Center, ; Dallas, TX USA
                Author information
                http://orcid.org/0000-0002-3330-8226
                Article
                6085
                10.1038/s41598-017-06085-3
                5519588
                28127051
                c7f9ebaa-e9b2-4d87-9124-eab78010d235
                © The Author(s) 2017

                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
                : 31 January 2017
                : 7 June 2017
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