Literature DB >> 9691051

Analysis of genetic structure and dispersal patterns in a population of sea beet.

J Tufto1, A F Raybould, K Hindar, S Engen.   

Abstract

A model of the migration pattern in a metapopulation of sea beet (Beta vulgaris L. ssp. maritima), based on the continuous distributions of seed and pollen movements, is fitted to gene frequency data at 12 isozyme and RFLP loci by maximum likelihood by using an approximation of the simultaneous equilibrium distribution of the gene frequencies generated by the underlying multivariate stochastic process of genetic drift in the population. Several alternative restrictions of the general model are fitted to the data, including the island model, a model of complete isolation, and a model in which the seed and pollen dispersal variances are equal. Several likelihood ratio tests between these alternatives are performed, and median bias in the estimated parameters is corrected by using parametric bootstrapping. To assess the fit of the selected model, the predicted covariances are compared with covariances computed from the data directly. The dependency of estimated parameters on the ratio between effective and absolute subpopulation sizes, which is treated as a known parameter in the analysis, is also examined. Finally, we note that the data also appear to contain some information about this ratio.

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Year:  1998        PMID: 9691051      PMCID: PMC1460291     

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  5 in total

1.  The Stepping Stone Model of Population Structure and the Decrease of Genetic Correlation with Distance.

Authors:  M Kimura; G H Weiss
Journal:  Genetics       Date:  1964-04       Impact factor: 4.562

2.  Isolation by Distance.

Authors:  S Wright
Journal:  Genetics       Date:  1943-03       Impact factor: 4.562

3.  Stochastic Dispersal Processes in Plant Populations

Authors: 
Journal:  Theor Popul Biol       Date:  1997-08       Impact factor: 1.570

4.  A migration matrix model for the study of random genetic drift.

Authors:  W F Bodmer; L L Cavalli-Sforza
Journal:  Genetics       Date:  1968-08       Impact factor: 4.562

5.  How can we infer geography and history from gene frequencies?

Authors:  J Felsenstein
Journal:  J Theor Biol       Date:  1982-05-07       Impact factor: 2.691

  5 in total

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