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United States Department of Agriculture

Agricultural Research Service

Title: Similarity Coefficients for Molecular Markers in Studies of Genetic Relationships Between Individuals for Haploid, Diploid, and Polyploid Species

Authors
item Kosman, Esvey - TEL AVIV UNIV., ISRAEL
item Leonard, Kurt

Submitted to: Molecular Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 20, 2004
Publication Date: February 1, 2005
Citation: Kosman, E., Leonard, K.J. 2005. Similarity coefficients for molecular markers in studies of genetic relationships between individuals for haploid, diploid, and polyploid species. Molecular Ecology. 14:415-424.

Interpretive Summary: Knowledge of genetic diversity within and between populations of animals, plants, or microorganisms gives useful information about the populations including their origins and extent of mixture with other populations through migration and interbreeding. Genetic information from molecular markers is especially useful for anticipating genetic changes in microorganisms that cause diseases in animals or crops that are essential food sources. Several measures of genetic distance have been developed to determine degrees of genetic difference between organisms, but the commonly used measures do not necessarily agree. Moreover, the commonly used measures were intended for typical plants and animals that have two sets of chromosomes and reproduce by random, sexual mating. Disease-causing microorganisms usually have just one, not two, sets of chromosomes and they reproduce asexually most, if not all, of the time. We determined which of the commonly used measures of genetic distance is most appropriate for measuring genetic differences based on several categories of molecular markers in cases of organisms that have one, two, or more sets of chromosomes. In cases in which no commonly used measures was satisfactory, we developed new measures that will provide accurate assessments of genetic differences in each type of organism. Our methods will provide more accurate determinations of genetic diversity than have been obtained in previously published research on most disease-causing microorganisms. This will lead to more accurate assessments of the potential for populations of these organisms to overcome resistance of their host plants or animals or to circumvent existing pesticides or other disease control options.

Technical Abstract: Determining true genetic dissimilarity between individuals is an important and decisive point for clustering and analyzing diversity within and among populations because different dissimilarity indices may yield contrary outcomes. We show that there are no acceptable universal approaches for assessing dissimilarity between individuals with molecular markers. Different measures are relevant to dominant and codominant DNA markers depending on ploidy of organisms. The Dice (Nei and Li) coefficient is the suitable measure for haploids with codominant markers, and it can be applied directly to {0,1}-vectors representing banding profiles of individuals. None of the common measures, Dice, Jaccard, simple mismatch coefficient (or the squared Euclidean distance), is appropriate for diploids with codominant markers. By transforming multiallelic banding patterns at each locus into the corresponding homozygous or heterozygous states, a new measure of dissimilarity within locus was developed and expanded to assess dissimilarity between multilocus states of two individuals by averaging across all codominant loci tested. There is no rigorous well-founded solution in the case of dominant markers. The simple mismatch coefficient is the most suitable measure of dissimilarity between banding patterns of closely related haploid forms. For distantly related haploid individuals, the Jaccard dissimilarity is recommended. In general, no suitable method for measuring genetic dissimilarity between diploids with dominant markers can be proposed. Banding patterns of diploids with dominant markers and polyploids with codominant markers represent individuals’ phenotypes rather than genotypes. All dissimilarity measures proposed and developed herein are metrics.

Last Modified: 4/17/2014
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