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      Genetic rescue increases fitness and aids rapid recovery of an endangered marsupial population

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          Abstract

          Genetic rescue has now been attempted in several threatened species, but the contribution of genetics per se to any increase in population health can be hard to identify. Rescue is expected to be particularly useful when individuals are introduced into small isolated populations with low levels of genetic variation. Here we consider such a situation by documenting genetic rescue in the mountain pygmy possum, Burramys parvus. Rapid population recovery occurred in the target population after the introduction of a small number of males from a large genetically diverged population. Initial hybrid fitness was more than two-fold higher than non-hybrids; hybrid animals had a larger body size, and female hybrids produced more pouch young and lived longer. Genetic rescue likely contributed to the largest population size ever being recorded at this site. These data point to genetic rescue as being a potentially useful option for the recovery of small threatened populations.

          Abstract

          Genetic rescue can be valuable for the conservation of small populations threatened by low genetic diversity, but it carries the perceived risk of outbreeding depression. Here, Weeks et al. report increased hybrid fitness in a rescued population of the mountain pygmy possum, which likely contributed to population growth following genetic rescue.

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          Inference of Population Structure Using Multilocus Genotype Data

          We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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            genalex 6: genetic analysis in Excel. Population genetic software for teaching and research

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              Program MARK: survival estimation from populations of marked animals

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                Author and article information

                Contributors
                aweeks@unimelb.edu.au
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 October 2017
                20 October 2017
                2017
                : 8
                : 1071
                Affiliations
                [1 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, School of BioSciences, , Bio21 Institute, The University of Melbourne, ; 30 Flemington Road, Parkville, VIC 3010 Australia
                [2 ]cesar Pty Ltd, 293 Royal Parade, Parkville, VIC 3052 Australia
                [3 ]ISNI 0000 0001 2342 0938, GRID grid.1018.8, Research Centre of Applied Alpine Ecology, , La Trobe University, ; Melbourne, 3086 VIC Australia
                [4 ]Mt Buller Mt Stirling Resort Management, Mt Buller, VIC 3723 Australia
                [5 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, School of Mathematics and Statistics and Evolution and Ecology Research Centre, , The University of New South Wales, ; Sydney, NSW 2052 Australia
                Author information
                http://orcid.org/0000-0003-3081-135X
                Article
                1182
                10.1038/s41467-017-01182-3
                5715156
                29057865
                382571b8-ff02-4ade-9485-27efdcb5da26
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 December 2016
                : 23 August 2017
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