Full text in pdf format
Hierarquical versus nonhierarquical patterns of genetic distances among populations: a simulation study
José Alexandre Felizola Diniz-Filho
Departamento de Biologia, Instituto de Biociências, UNESP,Caixa Postal 199, 13506-900 Rio Claro, SP, Brasil
ABSTRACT
A simulation study was made of the effects of mixing two evolutionary forces (natural selection and random genetic drift), combined in a single data matrix of gene frequencies, on the resulting genetic distances among populations. Twenty-one kinds of simulated gene frequencies surfaces, for 15 populations linearly distributed over geographic space, were used to construct 21 data matrices, combining different proportions of two types of surfaces (gradients and random surfaces). These matrices were analysed by Unweighted Pair-Group Method- Arithmetic Averages (UPGMA), clustering and Principal Coordinate Analysis. The results obtained show that ordination is more accurate than UPGMA in revealing the spatial patterns in the genetic distances, in comparison with results obtained using the Mantel test comparing directly genetic and geographic distances.
Keywords: hierarquical patterns; nonhierarquical patterns; genetic distances.
REFERENCES
Barbujani, G. (1987). Autocorrelation of gene frequencies under isolation-by-distance. Genetics 177: 772-782.
Buth, D.G. (1984). The application of electrophoretic data in systematic studies. Ann. Rev. Ecol. Syst. 15: 501-522.
Farris, J. (1969). On the cophenetic correlation coefficient. Syst. Zool. 18: 279-285.
Gower, J.C. (1966). Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53: 325-338.
Manly, B.F.J. (1985). The Statistics of Natural Selection. Chapman & Hall, London.
Manly, B.F.J. (1991). Randomization and Monte Carlo Methods in Biology. Chapman & Hall, London.
Nei, M. (1972). Genetic distances among populations. Am. Nat. 106: 283-292.
Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89: 583-590.
Nei, M., Tajima, F. and Tateno, Y. (1983). Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J. Mol. Evol. 19: 153-170.
Rogers, J.S. (1972). Measures of genetic similarity and genetic distance. Univ. Tex. Publ. 7213: 145-153.
Rohlf, F.J.(1972). An empirical comparison of three ordination techniques in numerical taxonomy. Syst. Zool. 21: 271-280.
Rohlf, F.J. (1978). Methods of comparing classifications. Ann. Rev. Ecol. Syst. 5: 101-113.
Rohlf, F.J. (1989). NTSYS-Pc: Numerical Taxonomy and Multivariate Analysis System. Exeter, New York.
Rohlf, F.J. and Sokal, R.R. (1981). Comparing numerical taxonomic studies. Syst. Zool. 30: 459-490.
Romesburg, H.C. (1984). Cluster Analysis for Researchers. Wadsworth, London.
Smouse, P.E., Long, J.C. and Sokal, R.R. (1986). Multiple regression and correlation extensions of the Mantel test of matrix correspondence. Syst. Zool. 35: 627-632.
Sneath, P.H.A. and Sokal, R.R. (1973). Numerical Taxonomy. W.H. and Freeman, San Francisco.
Sokal, R.R. (1978). Population differentiation: Something new or more of the same? In: Genetics and Ecology (Brussard, P. and Solbrig, O., eds.). Academic Press, New York.
Sokal, R.R. (1979). Testing statistical significance of geographic variation patterns. Syst. Zool. 28: 227-232.
Sokal, R.R. (1986a). Phenetic taxonomy: theory and methods. Ann. Rev. Ecol. Syst. 17: 423-442.
Sokal, R.R. (1986b). Spatial data analysis and historical processes. In: Data Analysis and Informatics IV (Diday et al., eds.). Elsevier Science Publishers, Holland.
Sokal, R.R. and Oden, N.L. (1978a). Spatial autocorrelation in biology. 1. Methodology. Biol. J. Linn. Soc. 10: 199-228.
Sokal, R.R. and Oden, N.L. (1978b). Spatial autocorrelation in biology. 2. Some biological implications and four applications of evolutionary and ecological interest. Biol. J. Linn. Soc. 10: 229-249.
Sokal, R.R. and Rohlf, F.J. (1962). The comparison of dendrograms by objective methods. Taxon 9: 33-40.
Sokal, R.R. and Wartenberg, D. (1981). Space and population structure. In: Dynamic Spatial Models (Griffith, D. and McKinnon, R., eds.). Sijthoff and Noordhoff, Netherlands.
Sokal, R.R. and Wartenberg, D. (1983). A test of spatial autocorrelation using an isolation-by-distance model. Genetics 105: 219-237.
Sokal, R.R., Uytterschaut, H., Rosing, F. and Schwidetzky, I. (1987). A classification of European skulls from three time periods. Am. J. Phys. Anthr. 74: 1-20.
Sokal, R.R., Jacquez, G.M. and Wooten, M.C. (1989). Spatial autocorrelation analysis of migration and selection. Genetics 121: 845-855.