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      Historical population declines prompted significant genomic erosion in the northern and southern white rhinoceros ( Ceratotherium simum)

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          Abstract

          Large vertebrates are extremely sensitive to anthropogenic pressure, and their populations are declining fast. The white rhinoceros ( Ceratotherium simum) is a paradigmatic case: this African megaherbivore has suffered a remarkable decline in the last 150 years due to human activities. Its subspecies, the northern (NWR) and the southern white rhinoceros (SWR), however, underwent opposite fates: the NWR vanished quickly, while the SWR recovered after the severe decline. Such demographic events are predicted to have an erosive effect at the genomic level, linked to the extirpation of diversity, and increased genetic drift and inbreeding. However, there is little empirical data available to directly reconstruct the subtleties of such processes in light of distinct demographic histories. Therefore, we generated a whole‐genome, temporal data set consisting of 52 resequenced white rhinoceros genomes, representing both subspecies at two time windows: before and during/after the bottleneck. Our data reveal previously unknown population structure within both subspecies, as well as quantifiable genomic erosion. Genome‐wide heterozygosity decreased significantly by 10% in the NWR and 36% in the SWR, and inbreeding coefficients rose significantly by 11% and 39%, respectively. Despite the remarkable loss of genomic diversity and recent inbreeding it suffered, the only surviving subspecies, the SWR, does not show a significant accumulation of genetic load compared to its historical counterpart. Our data provide empirical support for predictions about the genomic consequences of shrinking populations, and our findings have the potential to inform the conservation efforts of the remaining white rhinoceroses.

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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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            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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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Contributors
                fatima@palaeome.org
                tgilbert@sund.ku.dk
                Journal
                Mol Ecol
                Mol Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                07 July 2021
                December 2021
                : 30
                : 23 , WHOLE GENOME SEQUENCING IN MOLECULAR ECOLOGY ( doiID: 10.1111/mec.v30.23 )
                : 6355-6369
                Affiliations
                [ 1 ] GLOBE Institute University of Copenhagen Copenhagen Denmark
                [ 2 ] DTU Bioinformatics Kongens Lyngby Hovedstaden Denmark
                [ 3 ] Center for Evolutionary Hologenomics University of Copenhagen Copenhagen Denmark
                [ 4 ] Institut de Biologia Evolutiva (Consejo Superior de Investigaciones Científicas–Universitat Pompeu Fabra) Barcelona Biomedical Research Park Barcelona Spain
                [ 5 ] Department of Zoology Swedish Museum of Natural History Stockholm Sweden
                [ 6 ] Department of Natural Sciences National Museums Scotland Edinburgh UK
                [ 7 ] Centre of Excellence for Omics‐Driven Computational Biodiscovery (COMBio) Faculty of Applied Sciences AIMST University Kedah Malaysia
                [ 8 ] Centre for Palaeogenetics Stockholm Sweden
                [ 9 ] Department of Bioinformatics and Genetics Swedish Museum of Natural History Stockholm Sweden
                [ 10 ] San Diego Zoo Institute for Conservation Research Escondido CA USA
                [ 11 ] Section for Ecology and Evolution Department of Biology University of Copenhagen Copenhagen Denmark
                [ 12 ] State Key Laboratory of Genetic Resources and Evolution Kunming Institute of Zoology Chinese Academy of Sciences Kunming China
                [ 13 ] Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China
                [ 14 ] BGI‐Shenzhen Shenzhen China
                [ 15 ] National Centre for Genomic Analysis–Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain
                [ 16 ] Institucio Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain
                [ 17 ] Department of Zoology University of Venda Thohoyandou South Africa
                [ 18 ] Norwegian University of Science and Technology University Museum Trondheim Norway
                Author notes
                [*] [* ] Correspondence

                Fátima Sánchez‐Barreiro and M. Thomas P. Gilbert, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.

                Emails: fatima@ 123456palaeome.org (F.S.‐B.); tgilbert@ 123456sund.ku.dk (M.T.P.G.)

                Author information
                https://orcid.org/0000-0002-5902-0052
                https://orcid.org/0000-0002-2004-6810
                https://orcid.org/0000-0003-0478-3930
                https://orcid.org/0000-0002-5597-3075
                Article
                MEC16043
                10.1111/mec.16043
                9291831
                34176179
                8712e2ee-f682-4007-8ecd-1208c866fc04
                © 2021 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 11 June 2021
                : 27 November 2020
                : 21 June 2021
                Page count
                Figures: 5, Tables: 1, Pages: 0, Words: 10163
                Funding
                Funded by: H2020 European Research Council , doi 10.13039/100010663;
                Award ID: 681396
                Funded by: European Molecular Biology Organization , doi 10.13039/100004410;
                Award ID: 7578
                Categories
                Special Issue
                Conservation
                Custom metadata
                2.0
                December 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:18.07.2022

                Ecology
                conservation genomics,genomic erosion,northern white rhinoceros,population decline,southern white rhinoceros

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