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Population genetics on islands connected by an arbitrary network: an analytic approach.
Constable, George W A; McKane, Alan J.
Afiliación
  • Constable GW; Theoretical Physics Division, School of Physics and Astronomy, The University of Manchester, Manchester M13 9PL, UK. Electronic address: george.constable@postgrad.manchester.ac.uk.
  • McKane AJ; Theoretical Physics Division, School of Physics and Astronomy, The University of Manchester, Manchester M13 9PL, UK. Electronic address: alan.mckane@manchester.ac.uk.
J Theor Biol ; 358: 149-65, 2014 Oct 07.
Article en En | MEDLINE | ID: mdl-24882790
We analyse a model consisting of a population of individuals which is subdivided into a finite set of demes, each of which has a fixed but differing number of individuals. The individuals can reproduce, die and migrate between the demes according to an arbitrary migration network. They are haploid, with two alleles present in the population; frequency-independent selection is also incorporated, where the strength and direction of selection can vary from deme to deme. The system is formulated as an individual-based model and the diffusion approximation systematically applied to express it as a set of nonlinear coupled stochastic differential equations. These can be made amenable to analysis through the elimination of fast-time variables. The resulting reduced model is analysed in a number of situations, including migration-selection balance leading to a polymorphic equilibrium of the two alleles and an illustration of how the subdivision of the population can lead to non-trivial behaviour in the case where the network is a simple hub. The method we develop is systematic, may be applied to any network, and agrees well with the results of simulations in all cases studied and across a wide range of parameter values.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genética de Población Tipo de estudio: Prognostic_studies Idioma: En Revista: J Theor Biol Año: 2014 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genética de Población Tipo de estudio: Prognostic_studies Idioma: En Revista: J Theor Biol Año: 2014 Tipo del documento: Article Pais de publicación: Reino Unido