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      Genomic insight into “sky island” species diversification in a mountainous biodiversity hotspot

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          Abstract

          “Sky island” species diversification contributes greatly to mountainous biodiversity. However, the underlying genomic divergence and the inferred drivers remain largely unknown. In this study, we examined the diversification history of five diploid species with three exclusively endemic to the sky islands (mountains) of the Himalaya–Hengduan Mountains biodiversity hotspot. All of them together comprise a clade of the genus Eutrema (Brassicaceae). We resequenced genomes of multiple individuals of the found populations for each species. We recovered the inconsistent phylogenetic relationships between plastome and nuclear‐genome trees for one species. Based on nuclear population genomic data, we detected high genetic divergence between five species with limited gene flow. Four species seemed to diverge mainly through geographical isolation, whereas one arose through hybrid origin. The origins of the sampled five species were dated to within the late Miocene when mountains were uplifted and climates oscillated. All species decreased their population sizes since the inferred origin of each species initially, but only two of them expanded after the Last Glacial Maximum. Together, these findings suggest that geographic isolation plays an important role in driving the sky island species diversification of the sampled species in addition to the occasional gene flow that might have led to the hybrid origin of some sky island species, similar to the species diversification of sea islands.

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          Most cited references64

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              Is Open Access

              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
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Journal of Systematics and Evolution
                J of Sytematics Evolution
                Wiley
                1674-4918
                1759-6831
                November 2019
                November 03 2019
                November 2019
                : 57
                : 6
                : 633-645
                Affiliations
                [1 ] Key Laboratory of Bio‐Resource and Eco‐Environment, College of Life Sciences and State Key Laboratory of Hydraulics & Mountain River Engineering, Ministry of Education Sichuan University Chengdu 610065 China
                [2 ] Biodiversity Institute of Mount Emei Mount Emei Scenic Area Management Committee Leshan 614000 Sichua China
                [3 ] CEITEC—Central European Institute of Technology Masaryk University 625 00 Brno Czech Republic
                [4 ] State Key Laboratory of Grassland Agro‐Ecosystem, Institute of Innovation Ecology Lanzhou University Lanzhou 730000 China
                Article
                10.1111/jse.12543
                bd3f2e75-1b5c-411f-a63b-6938f696ed47
                © 2019

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