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      Can balancing selection on MHC loci counteract genetic drift in small fragmented populations of black grouse?

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          Abstract

          The ability of natural populations to adapt to new environmental conditions is crucial for their survival and partly determined by the standing genetic variation in each population. Populations with higher genetic diversity are more likely to contain individuals that are better adapted to new circumstances than populations with lower genetic diversity. Here, we use both neutral and major histocompatibility complex (MHC) markers to test whether small and highly fragmented populations hold lower genetic diversity than large ones. We use black grouse as it is distributed across Europe and found in populations with varying degrees of isolation and size. We sampled 11 different populations; five continuous, three isolated, and three small and isolated. We tested patterns of genetic variation in these populations using three different types of genetic markers: nine microsatellites and 21 single nucleotide polymorphisms (SNPs) which both were found to be neutral, and two functional MHC genes that are presumably under selection. The small isolated populations displayed significantly lower neutral genetic diversity compared to continuous populations. A similar trend, but not as pronounced, was found for genotypes at MHC class II loci. Populations were less divergent at MHC genes compared to neutral markers. Measures of genetic diversity and population genetic structure were positively correlated among microsatellites and SNPs, but none of them were correlated to MHC when comparing all populations. Our results suggest that balancing selection at MHC loci does not counteract the power of genetic drift when populations get small and fragmented.

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          Most cited references78

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          Arlequin (version 3.0): An integrated software package for population genetics data analysis

          Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.
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            Directions in Conservation Biology

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              The neutral theory of molecular evolution.

              M. Kimura (1979)
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                Author and article information

                Journal
                Ecol Evol
                Ecol Evol
                ece3
                Ecology and Evolution
                Blackwell Publishing Ltd (Oxford, UK )
                2045-7758
                2045-7758
                February 2012
                : 2
                : 2
                : 341-353
                Affiliations
                [1 ]simplePopulation Biology and Conservation Biology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University Norbyvägen 18D, SE-752 36 Uppsala, Sweden
                [2 ]simpleDepartment Wildlife Ecology and Management, University Freiburg Tennenbacher Str. 4, D-79106 Freiburg, Germany
                [3 ]simpleFaculty of Science, Department of Animal Biology, Plant Biology and Ecology, University of A Coruña Campus da Zapateira, E-15171 A Coruña, Spain
                [4 ]simpleDepartment of Medical Sciences, Molecular Medicine, Uppsala University Akademiska sjukhuset ing. 70, SE-751 85 Uppsala, Sweden
                Author notes
                Tanja M Strand, Population Biology and Conservation Biology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden. Tel:+46 18 471 2671; Fax: +46 18 471 6424; E-mail: Tanja.Strand@ 123456ebc.uu.se .

                Funded by the Swedish Research Council (VR) to JH, Deutsche Wildtier Stiftung to GS, Helge Ax:son Johnssons stiftelse and Zoologiska stiftelsen to TS.

                Article
                10.1002/ece3.86
                3298947
                22423328
                2e6cbef8-cea4-43fa-8b9b-75a8ca4c76e0
                © 2012 The Authors. Published by Blackwell Publishing Ltd.

                This is an open access article under the terms of the Creative Commons Attribution Non Commercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 01 November 2011
                : 06 November 2011
                Categories
                Original Research

                Evolutionary Biology
                population isolation,snp,mhc,genetic drift,fragmentation
                Evolutionary Biology
                population isolation, snp, mhc, genetic drift, fragmentation

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