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      Genetic consequences of long‐term small effective population size in the critically endangered pygmy hog

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          Abstract

          Increasing human disturbance and climate change have a major impact on habitat integrity and size, with far‐reaching consequences for wild fauna and flora. Specifically, population decline and habitat fragmentation result in small, isolated populations. To what extend different endangered species can cope with small population size is still largely unknown. Studies on the genomic landscape of these species can shed light on past demographic dynamics and current genetic load, thereby also providing guidance for conservation programs. The pygmy hog ( Porcula salvania) is the smallest and rarest wild pig in the world, with current estimation of only a few hundred living in the wild. Here, we analyzed whole‐genome sequencing data of six pygmy hogs, three from the wild and three from a captive population, along with 30 pigs representing six other Suidae. First, we show that the pygmy hog had a very small population size with low genetic diversity over the course of the past ~1 million years. One indication of historical small effective population size is the absence of mitochondrial variation in the six sequenced individuals. Second, we evaluated the impact of historical demography. Runs of homozygosity (ROH) analysis suggests that the pygmy hog population has gone through past but not recent inbreeding. Also, the long‐term, extremely small population size may have led to the accumulation of harmful mutations suggesting that the accumulation of deleterious mutations is exceeding purifying selection in this species. Thus, care has to be taken in the conservation program to avoid or minimize the potential for further inbreeding depression, and guard against environmental changes in the future.

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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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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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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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                Author and article information

                Contributors
                langqing.liu@wur.nl
                ole.madsen@wur.nl
                Journal
                Evol Appl
                Evol Appl
                10.1111/(ISSN)1752-4571
                EVA
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                1752-4571
                11 November 2020
                March 2021
                : 14
                : 3 ( doiID: 10.1111/eva.v14.3 )
                : 710-720
                Affiliations
                [ 1 ] Animal Breeding and Genomics Wageningen University & Research Wageningen the Netherlands
                Author notes
                [*] [* ] Correspondence

                Langqing Liu and Ole Madsen, Animal Breeding and Genomics, Wageningen University & Research, Wageningen, the Netherlands.

                Emails: langqing.liu@ 123456wur.nl (L. L.); ole.madsen@ 123456wur.nl (O. M.)

                Author information
                https://orcid.org/0000-0003-4868-087X
                https://orcid.org/0000-0003-2433-2483
                Article
                EVA13150
                10.1111/eva.13150
                7980308
                33767746
                54fcedde-62df-4939-9fb5-bd32d1fe83c9
                © 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 October 2020
                : 18 May 2020
                : 13 October 2020
                Page count
                Figures: 5, Tables: 0, Pages: 11, Words: 8154
                Funding
                Funded by: FP7 Ideas: European Research Council , open-funder-registry 10.13039/100011199;
                Award ID: ERC‐2009‐AdG: 249894
                Funded by: China Scholarship Council , open-funder-registry 10.13039/501100004543;
                Award ID: 201707720055
                Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek , open-funder-registry 10.13039/501100003246;
                Award ID: 016.Veni.181.050
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                March 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.0 mode:remove_FC converted:20.03.2021

                Evolutionary Biology
                conservation genomics,deleterious variants,inbreeding,population genomics
                Evolutionary Biology
                conservation genomics, deleterious variants, inbreeding, population genomics

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