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DNA Surveillance

Species identification with DNA

Inspector Foode Home About How to Use The Science Links and Publications Data Ownership
Search Cluster (Simple) Cluster (Advanced) Maximum Likelihood Example Data

Identification using Phylogenetic Analyses

The general principles involved in the identification of species using phylogenetic analyses are described in Inspector Foode's Home Page .

The following describes some technical aspects of this particular implementation.

Sequence Alignment

The sequence input by the user is aligned with the chosen reference set of sequences by a simple profile alignment (Gribskov et al. 1987, 1990, Gribskov and Veretnik 1996). Clustal X implements a more sophisticated method which allows the user to specify local gap costs and other parameter values (Thompson et al. 1997). To optimize system performance, the reference sequences have been prealigned.

The parameters used in the alignment are displayed with the dataset information.
DomainCytochrome B = CytB
MeatsLink

Calculation of Evolutionary Distances

The evolutionary distances among all of the aligned sequences, reference and submitted, are then calculated using the F84 model (Felsenstein 1984; Kishino and Hasegawa 1989). The parameter values used are those displayed with the dataset information.
DomainCytochrome B = CytB
MeatsLink

Building the Phylogenetic Tree

A phylogenetic tree is build to include the members of the reference set of sequences chosen by the user and the sequence that the user has submitted. The tree is built using the Neighbor-Joining (NJ) algorithm (Saitou and Nei 1987) and rooted using an outgroup appropriate for each data set.

References

  1. Felsenstein, J. 1984 Distance methods forinferring phylogenies: A justification. Evolution 38, 16-24.
  2. Guindon S, Gascuel O (2003) A simple,fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Systematic Biology 52, 696-704.
  3. Gribskov, M. Luthy, R. Eisenberg, D. (1990) Profile analysis. Methods in Enzymology 183, 146-159.
  4. Gribskov, M., McLachlan, A. D. Eisenberg,D. (1987) Profile analysis: detection of distantly related proteins. Proceedings of the National Academy of Science of the USA 84, 4355-4358.
  5. Kishino, H. and Hasegawa, M. 1989 Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. Journal of Molecular Evolution 29, 170-179.
  6. Posada D, Crandall K (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14, 817-818.
  7. Saitou, N. and Nei, M. 1987 The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution 4, 406-425.
  8. Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: a laboratory manual, 2nd edn., Cold Spring Harbour Laboratory, Cold Spring Harbor.
  9. Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F. Higgins, D. G. (1997) The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research 24, 4876-4882.