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Measuring genetic distances between breeds: use of some distances in various short term evolution models

  • Guillaume Laval
  • Magali SanCristobalEmail author
  • Claude Chevalet
Open Access
Research

Abstract

Many works demonstrate the benefits of using highly polymorphic markers such as microsatellites in order to measure the genetic diversity between closely related breeds. But it is sometimes difficult to decide which genetic distance should be used. In this paper we review the behaviour of the main distances encountered in the literature in various divergence models. In the first part, we consider that breeds are populations in which the assumption of equilibrium between drift and mutation is verified. In this case some interesting distances can be expressed as a function of divergence time, t, and therefore can be used to construct phylogenies. Distances based on allele size distribution (such as (δμ)2 and derived distances), taking a mutation model of microsatellites, the Stepwise Mutation Model, specifically into account, exhibit large variance and therefore should not be used to accurately infer phylogeny of closely related breeds. In the last section, we will consider that breeds are small populations and that the divergence times between them are too small to consider that the observed diversity is due to mutations: divergence is mainly due to genetic drift. Expectation and variance of distances were calculated as a function of the Wright-Malécot inbreeding coefficient, F. Computer simulations performed under this divergence model show that the Reynolds distance [57]is the best method for very closely related breeds.

Keywords

microsatellites breeds divergence mutation genetic drift 

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Copyright information

© INRA, EDP Sciences 2002

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Guillaume Laval
    • 1
    • 2
  • Magali SanCristobal
    • 1
    Email author
  • Claude Chevalet
    • 1
  1. 1.Laboratoire de génétique cellulaireInstitut national de la recherche agronomiqueCastanet-Tolosan cedexFrance
  2. 2.Computational and Molecular Population Genetics LaboratoryZoologisches InstitutBernSwitzerland

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