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      Genome-wide evidence for speciation with gene flow in Heliconius butterflies

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          Abstract

          Most speciation events probably occur gradually, without complete and immediate reproductive isolation, but the full extent of gene flow between diverging species has rarely been characterized on a genome-wide scale. Documenting the extent and timing of admixture between diverging species can clarify the role of geographic isolation in speciation. Here we use new methodology to quantify admixture at different stages of divergence in Heliconius butterflies, based on whole-genome sequences of 31 individuals. Comparisons between sympatric and allopatric populations of H. melpomene, H. cydno, and H. timareta revealed a genome-wide trend of increased shared variation in sympatry, indicative of pervasive interspecific gene flow. Up to 40% of 100-kb genomic windows clustered by geography rather than by species, demonstrating that a very substantial fraction of the genome has been shared between sympatric species. Analyses of genetic variation shared over different time intervals suggested that admixture between these species has continued since early in speciation. Alleles shared between species during recent time intervals displayed higher levels of linkage disequilibrium than those shared over longer time intervals, suggesting that this admixture took place at multiple points during divergence and is probably ongoing. The signal of admixture was significantly reduced around loci controlling divergent wing patterns, as well as throughout the Z chromosome, consistent with strong selection for Müllerian mimicry and with known Z-linked hybrid incompatibility. Overall these results show that species divergence can occur in the face of persistent and genome-wide admixture over long periods of time.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            A framework for variation discovery and genotyping using next-generation DNA sequencing data

            Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
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              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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                Author and article information

                Journal
                Genome Res
                Genome Res
                GENOME
                Genome Research
                Cold Spring Harbor Laboratory Press
                1088-9051
                1549-5469
                November 2013
                : 23
                : 11
                : 1817-1828
                Affiliations
                [1 ]Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom;
                [2 ]Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom;
                [3 ]Department of Biology, University of York, York YO10 5DD, United Kingdom;
                [4 ]Facultad de Ciencias Naturales y Matematicas, Universidad del Rosario, Bogota DC, Colombia;
                [5 ]Department of Biology, Stanford University, Stanford, California 94305, USA;
                [6 ]Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh EH9 3JT, United Kingdom;
                [7 ]Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA
                Author notes
                [8 ]Corresponding author E-mail shm45@ 123456cam.ac.uk
                Article
                9518021
                10.1101/gr.159426.113
                3814882
                24045163
                ffe5a5bf-16b6-45b2-b3a9-8eb6d8c3a10d
                © 2013 Martin et al.; Published by Cold Spring Harbor Laboratory Press

                This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.

                History
                : 23 April 2013
                : 15 August 2013
                Page count
                Pages: 12
                Categories
                Research

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