A data mining approach to dinoflagellate clustering according to sterol composition: correlations with evolutionary history

Authors:
Jeffrey D. Leblond;Andrew D. Lasiter;Cen Li;Ramiro Logares;Karin Rengefors;Terence J. Evens
Affiliations:
Department of Biology, Middle Tennessee State University, P.O. Box 60, Murfreesboro, TN 37132, USA.;Department of Biology, Middle Tennessee State University, P.O. Box 60, Murfreesboro, TN 37132, USA.;Department of Computer Science, Middle Tennessee State University, P.O. Box 48, Murfreesboro, TN 37132, USA.;Limnology Department, Uppsala University, Uppsala, SE-75123, Sweden.;Limnology Division, Department of Ecology, Lund University, Lund, SE-22362, Sweden.;USDA-ARS, United States Horticultural Research Laboratory, 2001 South Rock Rd., Ft. Pierce, FL 34945, USA
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2010

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Abstract

This study examined the sterol compositions of 102 dinoflagellates using clustering and cluster validation techniques, as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to 18S rDNA-based phylogenetic relationships using the Mantel test. Our results indicated that the examined dinoflagellates formed six clusters based on sterol composition and that several, but not all, dinoflagellate genera, which formed discrete clusters in the 18S rDNA-based phylogeny, shared similar sterol compositions. This and other correspondences suggest that the sterol compositions of dinoflagellates are explained, to a certain extent, by the evolutionary history of this lineage.