Comparison of similarity coefficients based on RAPD markers in the common bean

The alterations caused by eight different similarity coefficients were evaluated in the clustering and ordination of 27 common bean (Phaseolus vulgaris L.) cultivars analyzed by RAPD markers. The Anderberg, simple matching, Rogers and Tanimoto, Russel and Rao, Ochiai, Jaccard, Sorensen-Dice, and Ochiai II's coefficients were tested. Comparisons among the coefficients were made through correlation analysis of genetic distances obtained by the complement of these coefficients, dendrogram evaluation (visual inspection and consensus fork index - CIC), projection efficiency in a two-dimensional space, and groups formed by Tocher's optimization procedure. The employment of different similarity coefficients caused few alterations in cultivar classification, since correlations among genetic distances were larger than 0.86. Nevertheless, the different similarity coefficients altered the projection efficiency in a two-dimensional space and formed different numbers of groups by Tocher's optimization procedure. Among these coefficients, Russel and Rao's was the most discordant and the Sorensen-Dice was considered the most adequate due to a higher projection efficiency in a two-dimensional space. Even though few structural changes were suggested in the most different groups, these coefficients altered some relationships between cultivars with high genetic similarity.

[1]  P. Jaccard,et al.  Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .

[2]  P. F. Russell,et al.  On Habitat and Association of Species of Anopheline Larvae in South-eastern Madras. , 1940 .

[3]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[4]  T. Sørensen,et al.  A method of establishing group of equal amplitude in plant sociobiology based on similarity of species content and its application to analyses of the vegetation on Danish commons , 1948 .

[5]  Calyampudi R. Rao,et al.  Advanced Statistical Methods in Biometric Research. , 1953 .

[6]  A. Ochiai.  Zoogeographical Studies on the Soleoid Fishes Found in Japan and its Neighbouring Regions-III , 1957 .

[7]  Robert R. Sokal,et al.  A statistical method for evaluating systematic relationships , 1958 .

[8]  D J Rogers,et al.  A Computer Program for Classifying Plants. , 1960, Science.

[9]  J. Kruskal.  Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis , 1964 .

[10]  Calyampudi R. Rao,et al.  Advanced Statistical Methods in Biometric Research. , 1953 .

[11]  Michael R. Anderberg,et al.  Cluster Analysis for Applications , 1973 .

[12]  R. Sokal,et al.  Numerical Taxonomy: The Principles and Practice of Numerical Classification. , 1975 .

[13]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[14]  F. Rohlf.  Consensus indices for comparing classifications , 1982 .

[15]  J. Gower,et al.  Metric and Euclidean properties of dissimilarity coefficients , 1986 .

[16]  Donald A. Jackson,et al.  Similarity Coefficients: Measures of Co-Occurrence and Association or Simply Measures of Occurrence? , 1989, The American Naturalist.

[17]  K. Livak,et al.  DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. , 1990, Nucleic acids research.

[18]  F. Rohlf,et al.  NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, version 2.1: Owner manual , 1992 .

[19]  J. B. D. Santos,et al.  Genetic Relationships among Cultivars and Landraces of Lima Bean (Phaseolus lunatus L.) as Measured by RAPD Markers , 1995 .

[20]  M. Johns,et al.  Gene pool classification of common bean landraces from Chile based on RAPD and morphological data , 1997 .

[21]  C. D. Cruz.  Programa GENES: Aplicativo Computacional em Estatística Aplicada à Genética (GENES - Software for Experimental Statistics in Genetics) , 1998 .