Skyline-plot methods for estimating demographic history from nucleotide sequences

Authors

  • SIMON Y. W. HO,

    1. Centre for Macroevolution and Macroecology, Research School of Biology, Australian National University, ACT 0200, Australia
    2. School of Biological Sciences, University of Sydney, NSW 2006, Australia
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  • BETH SHAPIRO

    1. Department of Biology, The Pennsylvania State University, University Park, PA 16802–5301, USA
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Simon Ho, Fax: +61 2 91140979; E-mail: simon.ho@sydney.edu.au

Abstract

Estimation of demographic history from nucleotide sequences represents an important component of many studies in molecular ecology. For example, knowledge of a population’s history can allow us to test hypotheses about the impact of climatic and anthropogenic factors. In the past, demographic analysis was typically limited to relatively simple population models, such as exponential or logistic growth. More flexible approaches are now available, including skyline-plot methods that are able to reconstruct changes in population sizes through time. This technical review focuses on these skyline-plot methods. We describe some general principles relating to sampling design and data collection. We then provide an outline of the methodological framework, which is based on coalescent theory, before tracing the development of the various skyline-plot methods and describing their key features. The performance and properties of the methods are illustrated using two simulated data sets.

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