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      Male-Mediated Gene Flow in Patrilocal Primates

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          Abstract

          Background

          Many group–living species display strong sex biases in dispersal tendencies. However, gene flow mediated by apparently philopatric sex may still occur and potentially alters population structure. In our closest living evolutionary relatives, dispersal of adult males seems to be precluded by high levels of territoriality between males of different groups in chimpanzees, and has only been observed once in bonobos. Still, male–mediated gene flow might occur through rare events such as extra–group matings leading to extra–group paternity (EGP) and female secondary dispersal with offspring, but the extent of this gene flow has not yet been assessed.

          Methodology/Principal Findings

          Using autosomal microsatellite genotyping of samples from multiple groups of wild western chimpanzees ( Pan troglodytes verus) and bonobos ( Pan paniscus), we found low genetic differentiation among groups for both males and females. Characterization of Y–chromosome microsatellites revealed levels of genetic differentiation between groups in bonobos almost as high as those reported previously in eastern chimpanzees, but lower levels of differentiation in western chimpanzees. By using simulations to evaluate the patterns of Y–chromosomal variation expected under realistic assumptions of group size, mutation rate and reproductive skew, we demonstrate that the observed presence of multiple and highly divergent Y–haplotypes within western chimpanzee and bonobo groups is best explained by successful male–mediated gene flow.

          Conclusions/Significance

          The similarity of inferred rates of male–mediated gene flow and published rates of EGP in western chimpanzees suggests this is the most likely mechanism of male–mediated gene flow in this subspecies. In bonobos more data are needed to refine the estimated rate of gene flow. Our findings suggest that dispersal patterns in these closely related species, and particularly for the chimpanzee subspecies, are more variable than previously appreciated. This is consistent with growing recognition of extensive behavioral variation in chimpanzees and bonobos.

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          Most cited references144

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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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            Advances in our understanding of mammalian sex-biased dispersal.

            Sex-biased dispersal is an almost ubiquitous feature of mammalian life history, but the evolutionary causes behind these patterns still require much clarification. A quarter of a century since the publication of seminal papers describing general patterns of sex-biased dispersal in both mammals and birds, we review the advances in our theoretical understanding of the evolutionary causes of sex-biased dispersal, and those in statistical genetics that enable us to test hypotheses and measure dispersal in natural populations. We use mammalian examples to illustrate patterns and proximate causes of sex-biased dispersal, because by far the most data are available and because they exhibit an enormous diversity in terms of dispersal strategy, mating and social systems. Recent studies using molecular markers have helped to confirm that sex-biased dispersal is widespread among mammals and varies widely in direction and intensity, but there is a great need to bridge the gap between genetic information, observational data and theory. A review of mammalian data indicates that the relationship between direction of sex-bias and mating system is not a simple one. The role of social systems emerges as a key factor in determining intensity and direction of dispersal bias, but there is still need for a theoretical framework that can account for the complex interactions between inbreeding avoidance, kin competition and cooperation to explain the impressive diversity of patterns.
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              Using the AMOVA framework to estimate a standardized genetic differentiation measure.

              Comparison of population structure between studies can be difficult, because the value of the often-used FST-statistic depends on the amount of genetic variation within populations. Recently, a standardized measure of genetic differentiation was developed based on GST, which addressed this problem, though no method was provided to estimate this standardized measure without bias. Here I present a method to estimate a standardized measure of population differentiation based on the analysis of molecular variance framework. One advantage of the method is that it can be readily expanded to include different hierarchical levels in the tested population structure.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                1 July 2011
                : 6
                : 7
                : e21514
                Affiliations
                [1 ]Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
                [2 ]Junior Research Group Novel Zoonoses, Robert Koch Institute, Berlin, Germany
                [3 ]Emmanuel College, University of Cambridge, Cambridge, United Kingdom
                [4 ]Department of Anthropology, Boston University, Boston, Massachusetts, United States of America
                [5 ]Large Animal Research Group, Department of Zoology, University of Cambridge, Cambridge, United Kingdom
                Institut Pasteur, France
                Author notes

                Conceived and designed the experiments: GS LV. Performed the experiments: GS. Analyzed the data: GS CJS. Contributed reagents/materials/analysis tools: MA CB NE GH DL. Wrote the paper: GS LV KL.

                Article
                PONE-D-11-01066
                10.1371/journal.pone.0021514
                3128582
                21747938
                4de8cad7-6ede-42f9-9d99-1f6d3ffca695
                Schubert et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 11 January 2011
                : 2 June 2011
                Page count
                Pages: 10
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Population Genetics
                Gene Flow
                Genetic Polymorphism
                Haplotypes
                Animal Behavior
                Genetics
                Population Genetics
                Gene Flow
                Genetic Polymorphism
                Haplotypes
                Animal Genetics
                Population Biology
                Population Genetics
                Gene Flow
                Genetic Polymorphism
                Haplotypes

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                Uncategorized

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