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      Multiple Selection Signatures in Farmed Atlantic Salmon Adapted to Different Environments Across Hemispheres

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          Domestication of Atlantic salmon started approximately 40 years ago, using artificial selection through genetic improvement programs. Selection is likely to have imposed distinctive signatures on the salmon genome, which are often characterized by high genetic differentiation across population and/or reduction in genetic diversity in regions associated to traits under selection. The identification of such selection signatures may give insights into the candidate genomic regions of biological and commercial interest. Here, we used three complementary statistics to detect selection signatures, two haplotype-based (iHS and XP-EHH), and one F ST-based method (BayeScan) among four populations of Atlantic salmon with a common genetic origin. Several regions were identified for these techniques that harbored genes, such as kind1 and chp2, which have been associated with growth-related traits or the kcnb2 gene related to immune system in Atlantic salmon, making them particularly relevant in the context of aquaculture. Our results provide candidate genes to inform the evolutionary and biological mechanisms controlling complex selected traits in Atlantic salmon.

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          Most cited references 68

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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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.

                Author and article information

                URI :
                URI :
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                01 October 2019
                : 10
                1Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile , Santiago, Chile
                2Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences , Uppsala, Sweden
                3Department of Integrative Biology, University of California , Berkeley, CA, United States
                4Marine Harvest, Kindrum, Fanad, C. Donegal, Ireland
                5Benchmark Genetics Chile , Puerto Montt, Chile
                6Facultad de Ciencias Agronómicas, Universidad de Chile , Santiago, Chile
                7Núcleo Milenio INVASAL , Concepción, Chile
                Author notes

                Edited by: Maria Saura, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Spain

                Reviewed by: Roger Vallejo, Cool and Cold Water Aquaculture Research (USDA-ARS), United States; Andrés Pérez-Figueroa, University of Porto, Portugal

                *Correspondence: José Manuel Yañez, jmayanez@

                This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics

                †Present address: Department of Genetics, University of Cambridge, Cambridge, United Kingdom

                Copyright © 2019 López, Linderoth, Norris, Lhorente, Neira and Yáñez

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 7, Tables: 6, Equations: 0, References: 73, Pages: 15, Words: 7101
                Original Research


                artificial selection, selection signatures, snp data, domestication, salmo salar


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