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      Mapping and validation of a major QTL affecting resistance to pancreas disease (salmonid alphavirus) in Atlantic salmon ( Salmo salar)

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          Abstract

          Pancreas disease (PD), caused by a salmonid alphavirus (SAV), has a large negative economic and animal welfare impact on Atlantic salmon aquaculture. Evidence for genetic variation in host resistance to this disease has been reported, suggesting that selective breeding may potentially form an important component of disease control. The aim of this study was to explore the genetic architecture of resistance to PD, using survival data collected from two unrelated populations of Atlantic salmon; one challenged with SAV as fry in freshwater (POP 1) and one challenged with SAV as post-smolts in sea water (POP 2). Analyses of the binary survival data revealed a moderate-to-high heritability for host resistance to PD in both populations (fry POP 1  h 2~0.5; post-smolt POP 2  h 2~0.4). Subsets of both populations were genotyped for single nucleotide polymorphism markers, and six putative resistance quantitative trait loci (QTL) were identified. One of these QTL was mapped to the same location on chromosome 3 in both populations, reaching chromosome-wide significance in both the sire- and dam-based analyses in POP 1, and genome-wide significance in a combined analysis in POP 2. This independently verified QTL explains a significant proportion of host genetic variation in resistance to PD in both populations, suggesting a common underlying mechanism for genetic resistance across lifecycle stages. Markers associated with this QTL are being incorporated into selective breeding programs to improve PD resistance.

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          Most cited references36

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          The investigation of linkage between a quantitative trait and a marker locus.

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            A Genomic Background Based Method for Association Analysis in Related Individuals

            Background Feasibility of genotyping of hundreds and thousands of single nucleotide polymorphisms (SNPs) in thousands of study subjects have triggered the need for fast, powerful, and reliable methods for genome-wide association analysis. Here we consider a situation when study participants are genetically related (e.g. due to systematic sampling of families or because a study was performed in a genetically isolated population). Of the available methods that account for relatedness, the Measured Genotype (MG) approach is considered the ‘gold standard’. However, MG is not efficient with respect to time taken for the analysis of genome-wide data. In this context we proposed a fast two-step method called Genome-wide Association using Mixed Model and Regression (GRAMMAR) for the analysis of pedigree-based quantitative traits. This method certainly overcomes the drawback of time limitation of the measured genotype (MG) approach, but pays in power. One of the major drawbacks of both MG and GRAMMAR, is that they crucially depend on the availability of complete and correct pedigree data, which is rarely available. Methodology In this study we first explore type 1 error and relative power of MG, GRAMMAR, and Genomic Control (GC) approaches for genetic association analysis. Secondly, we propose an extension to GRAMMAR i.e. GRAMMAR-GC. Finally, we propose application of GRAMMAR-GC using the kinship matrix estimated through genomic marker data, instead of (possibly missing and/or incorrect) genealogy. Conclusion Through simulations we show that MG approach maintains high power across a range of heritabilities and possible pedigree structures, and always outperforms other contemporary methods. We also show that the power of our proposed GRAMMAR-GC approaches to that of the ‘gold standard’ MG for all models and pedigrees studied. We show that this method is both feasible and powerful and has correct type 1 error in the context of genome-wide association analysis in related individuals.
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              A dense SNP-based linkage map for Atlantic salmon (Salmo salar) reveals extended chromosome homeologies and striking differences in sex-specific recombination patterns

              Background The Atlantic salmon genome is in the process of returning to a diploid state after undergoing a whole genome duplication (WGD) event between 25 and100 million years ago. Existing data on the proportion of paralogous sequence variants (PSVs), multisite variants (MSVs) and other types of complex sequence variation suggest that the rediplodization phase is far from over. The aims of this study were to construct a high density linkage map for Atlantic salmon, to characterize the extent of rediploidization and to improve our understanding of genetic differences between sexes in this species. Results A linkage map for Atlantic salmon comprising 29 chromosomes and 5650 single nucleotide polymorphisms (SNPs) was constructed using genotyping data from 3297 fish belonging to 143 families. Of these, 2696 SNPs were generated from ESTs or other gene associated sequences. Homeologous chromosomal regions were identified through the mapping of duplicated SNPs and through the investigation of syntenic relationships between Atlantic salmon and the reference genome sequence of the threespine stickleback (Gasterosteus aculeatus). The sex-specific linkage maps spanned a total of 2402.3 cM in females and 1746.2 cM in males, highlighting a difference in sex specific recombination rate (1.38:1) which is much lower than previously reported in Atlantic salmon. The sexes, however, displayed striking differences in the distribution of recombination sites within linkage groups, with males showing recombination strongly localized to telomeres. Conclusion The map presented here represents a valuable resource for addressing important questions of interest to evolution (the process of re-diploidization), aquaculture and salmonid life history biology and not least as a resource to aid the assembly of the forthcoming Atlantic salmon reference genome sequence.
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                Author and article information

                Journal
                Heredity (Edinb)
                Heredity (Edinb)
                Heredity
                Nature Publishing Group
                0018-067X
                1365-2540
                November 2015
                20 May 2015
                1 November 2015
                : 115
                : 5
                : 405-414
                Affiliations
                [1 ]The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh , Midlothian, UK
                [2 ]Nofima, Ås, Norway
                [3 ]Akvaforsk Genetics Center AS, Sunndalsøra, Norway
                [4 ]Marine Harvest, Bergen, Norway
                [5 ]Department of Animal and Aquacultural Sciences and Centre for Integrative Genetics, Norwegian University of Life Sciences, Ås, Norway
                [6 ]SalmoBreed AS, Bergen, Norway
                Author notes
                [* ]The Roslin Institute and R(D) School of Veterinary Studies, University of Edinburgh , Midlothian EH25 9RG, UK. E-mail: Serap.Gonen@ 123456roslin.ed.ac.uk or gonenserap@ 123456gmail.com
                [7]

                These authors contributed equally to this work.

                Article
                hdy201537
                10.1038/hdy.2015.37
                4611234
                25990876
                75283c88-442e-4600-a11a-16f8d87bff2d
                Copyright © 2015 The Genetics Society

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 21 October 2014
                : 22 February 2015
                : 23 March 2015
                Categories
                Original Article

                Human biology
                Human biology

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