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      Parallel evolution despite low genetic diversity in three-spined sticklebacks

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          Abstract

          When populations repeatedly adapt to similar environments they can evolve similar phenotypes based on shared genetic mechanisms (parallel evolution). The likelihood of parallel evolution is affected by demographic history, as it depends on the standing genetic variation of the source population. The three-spined stickleback ( Gasterosteus aculeatus) repeatedly colonized and adapted to brackish and freshwater. Most parallel evolution studies in G. aculeatus were conducted at high latitudes, where freshwater populations maintain connectivity to the source marine populations. Here, we analysed southern and northern European marine and freshwater populations to test two hypotheses. First, that southern European freshwater populations (which currently lack connection to marine populations) lost genetic diversity due to bottlenecks and inbreeding compared to their northern counterparts. Second, that the degree of genetic parallelism is higher among northern than southern European freshwater populations, as the latter have been subjected to strong drift due to isolation. The results show that southern populations exhibit lower genetic diversity but a higher degree of genetic parallelism than northern populations. Hence, they confirm the hypothesis that southern populations have lost genetic diversity, but this loss probably happened after they had already adapted to freshwater conditions, explaining the high degree of genetic parallelism in the south.

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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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            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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              PLINK: a tool set for whole-genome association and population-based linkage analyses.

              Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: Data curationRole: Formal analysis
                Role: Formal analysisRole: Methodology
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: ConceptualizationRole: Funding acquisitionRole: Supervision
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Journal
                Proc Biol Sci
                Proc Biol Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                April 10, 2024
                April 2024
                April 10, 2024
                : 291
                : 2020
                : 20232617
                Affiliations
                [ 1 ] Ecological Genetics Research Unit, Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, , Helsinki, FI-00014, Finland
                [ 2 ] School of Biological Sciences, Faculty of Science, The University of Hong Kong, , Hong Kong SAR, People's Republic of China
                [ 3 ] Swire Institute of Marine Science, Faculty of Science, The University of Hong Kong, , Hong Kong SAR, People's Republic of China
                [ 4 ] MARE—Marine and Environmental Sciences Centre, Universidade de Évora, , Évora, 7004-516, Portugal
                [ 5 ] MARE—Marine and Environmental Sciences Centre, Faculdade de Ciências, Universidade de Lisboa, , Campo Grande, 1749-016, Lisboa, Portugal
                [ 6 ] Department of Biology, Faculty of Science, University of Zagreb, , Rooseveltov trg 6, Zagreb, 10000, Croatia
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.7132044.

                Author information
                http://orcid.org/0000-0002-1407-0662
                https://orcid.org/0000-0001-9614-0072
                http://orcid.org/0000-0001-6390-6094
                Article
                rspb20232617
                10.1098/rspb.2023.2617
                11003780
                38593844
                298ac80d-7afb-47ff-a949-c548c95a7a29
                © 2024 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : November 20, 2023
                : March 8, 2024
                Funding
                Funded by: Centro de Ciências do Mar e do Ambiente, http://dx.doi.org/10.13039/501100019243;
                Award ID: CEECIND/02265/2018
                Award ID: UIDB/04292/2020
                Funded by: Research Council of Finland, http://dx.doi.org/10.13039/501100002341;
                Award ID: 129662,
                Award ID: 134728
                Award ID: 218343
                Award ID: 316294
                Categories
                1001
                70
                Evolution
                Research Articles

                Life sciences
                adaptation,gasterosteus aculeatus,genetic diversity,parallel evolution
                Life sciences
                adaptation, gasterosteus aculeatus, genetic diversity, parallel evolution

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