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      Evolutionary History of the Galápagos Rail Revealed by Ancient Mitogenomes and Modern Samples

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      MDPI AG

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          Abstract

          The biotas of the Galápagos Islands are one of the best studied island systems and have provided a broad model for insular species’ origins and evolution. Nevertheless, some locally endemic taxa, such as the Galápagos Rail Laterallus spilonota, remain poorly characterized. Owing to its elusive behavior, cryptic plumage, and restricted distribution, the Galápagos Rail is one of the least studied endemic vertebrates of the Galapagos Islands. To date, there is no genetic data for this species, leaving its origins, relationships to other taxa, and levels of genetic diversity uncharacterized. This lack of information is critical given the adverse fate of island rail species around the world in the recent past. Here, we examine the genetics of Galápagos Rails using a combination of mitogenome de novo assembly with multilocus nuclear and mitochondrial sequencing from both modern and historical samples. We show that the Galápagos Rail is part of the “American black rail clade”, sister to the Black Rail L. jamaicensis, with a colonization of Galápagos dated to 1.2 million years ago. A separate analysis of one nuclear and two mitochondrial markers in the larger population samples demonstrates a shallow population structure across the islands, possibly due to elevated island connectivity. Additionally, birds from the island Pinta possessed the lowest levels of genetic diversity, possibly reflecting past population bottlenecks associated with overgrazing of their habitat by invasive goats. The modern and historical data presented here highlight the low genetic diversity in this endemic rail species and provide useful information to guide conservation efforts.

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          Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

          Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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            Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

            Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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              MultiQC: summarize analysis results for multiple tools and samples in a single report

              Motivation: Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis. Results: We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization. Availability and implementation: MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.info Contact: phil.ewels@scilifelab.se
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                Author and article information

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                Journal
                DIVEC6
                Diversity
                Diversity
                MDPI AG
                1424-2818
                November 2020
                November 12 2020
                : 12
                : 11
                : 425
                Article
                10.3390/d12110425
                3f2d2146-3ed7-48b7-bf07-00574e8581ea
                © 2020

                https://creativecommons.org/licenses/by/4.0/

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