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      Whole-genome phylogeography of the intertidal snail Littorina saxatilis

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          Abstract

          Understanding the factors that have shaped the current distributions and diversity of species is a central and longstanding aim of evolutionary biology. The recent inclusion of genomic data into phylogeographic studies has dramatically improved our understanding in organisms where evolutionary relationships have been challenging to infer. We used whole-genome sequences to study the phylogeography of the intertidal snail Littorina saxatilis, which has successfully colonized and diversified across a broad range of coastal environments in the Northern Hemisphere amid repeated cycles of glaciation. Building on past studies based on short DNA sequences, we used genome-wide data to provide a clearer picture of the relationships among samples spanning most of the species natural range. Our results confirm the trans-Atlantic colonization of North America from Europe, and have allowed us to identify rough locations of glacial refugia and to infer likely routes of colonization within Europe. We also investigated the signals in different datasets to account for the effects of genomic architecture and non-neutral evolution, which provides new insights about diversification of four ecotypes of L. saxatilis (the crab, wave, barnacle, and brackish ecotypes) at different spatial scales. Overall, we provide a much clearer picture of the biogeography of L. saxatilis, providing a foundation for more detailed phylogenomic and demographic studies.

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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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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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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

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                Journal
                Evolutionary Journal of the Linnean Society
                Oxford University Press (OUP)
                2752-938X
                January 01 2023
                January 01 2023
                January 01 2023
                January 01 2023
                August 17 2023
                : 2
                : 1
                Article
                10.1093/evolinnean/kzad002
                453b2d90-2ef6-4583-bc7d-58ecd6dc2e29
                © 2023

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

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