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      High Nucleotide Diversity Accompanies Differential DNA Methylation in Naturally Diverging Populations

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          Abstract

          Epigenetic mechanisms such as DNA methylation (DNAme) are thought to comprise an invaluable adaptive toolkit in the early stages of local adaptation, especially when genetic diversity is constrained. However, the link between genetic diversity and DNAme has been scarcely examined in natural populations, despite its potential to shed light on the evolutionary forces acting on methylation state. Here, we analyzed reduced-representation bisulfite sequencing and whole-genome pool-seq data from marine and freshwater stickleback populations to examine the relationship between DNAme variation (between- and within-population) and nucleotide diversity in the context of freshwater adaptation. We find that sites that are differentially methylated between populations have higher underlying standing genetic variation, with diversity higher among sites that gained methylation in freshwater than those that lost it. Strikingly, although nucleotide diversity is generally lower in the freshwater population as expected from a population bottleneck, this is not the case for sites that lost methylation, which instead have elevated nucleotide diversity in freshwater compared with marine. Subsequently, we show that nucleotide diversity is higher among sites with ancestrally variable methylation and also positively correlates with the sensitivity to environmentally induced methylation change. The results suggest that as selection on the control of methylation state becomes relaxed, so too does selection against mutations at the sites themselves. Increased epigenetic variance in a population is therefore likely to precede genetic diversification.

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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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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
                Role: Associate Editor
                Journal
                Mol Biol Evol
                Mol Biol Evol
                molbev
                Molecular Biology and Evolution
                Oxford University Press (US )
                0737-4038
                1537-1719
                April 2023
                22 March 2023
                22 March 2023
                : 40
                : 4
                : msad068
                Affiliations
                Institute for Fish and Wildlife Health, University of Bern , Bern, Switzerland
                Faculty of Biological and Environmental Sciences, University of Helsinki , Helsinki, Finland
                Computational Systems Biology, Faculty of Biochemical and Chemical Engineering, TU Dortmund University , Dortmund, Germany
                Institute for Fish and Wildlife Health, University of Bern , Bern, Switzerland
                Author notes
                Corresponding author: E-mail: jms.ord18@ 123456gmail.com .
                Author information
                https://orcid.org/0000-0001-6870-8927
                Article
                msad068
                10.1093/molbev/msad068
                10139703
                36947101
                f6339944-a2a7-4681-b41d-a8b417a605d8
                © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 16
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                dna methylation,stickleback,epigenetic,nucleotide diversity,local adaptation
                Molecular biology
                dna methylation, stickleback, epigenetic, nucleotide diversity, local adaptation

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