Similarity Analyses

The successful application of molecular techniques to population studies, particularly those based on the analysis of DNA or RNA in a gel matrix, relies heavily on the correct interpretation of the banding or spot patterns observed on elec-trophoretic gels. Gel images are typically digitized and band detection software is used to mark the band locations in the gel. The resulting band pattern is then exported to a statistical software package for analysis. Some analyses require that the fingerprint patterns obtained are first converted to presence/absence matrices; although average band density data are also used. The matrices generated are then compared using cluster analysis, multidimensional scaling, principal component analysis, redundancy analysis, canonical correspondence analysis, or additive main effects multiplicative interaction model, among others. Each analysis will allow community comparisons, yet each has associated strengths and weaknesses. There are a number of software packages available that will enable one to compare and score PCR fingerprints and produce similarity values for a given set of samples. Software packages, such as BioNumerics and GelCompar (Applied Maths, Kortrijk, Belgium), Canoco (Microcomputing, Ithaca, NY, USA), and PHYLIP (freeware via GenBank and the RDPII), among others, are used commonly.

level of resolution

Genes change as they acquire fixed mutations over time. The number of differences between two homologous sequences reflects both the evolutionary rate of the sequences and the time separating them, in other words—how long it has been since they had a common ancestor. Consequently, different sequences need to be selected to resolve variation at different taxonomic levels. In general, noncoding DNA evolves faster than transcribed DNA, since it is under no selection pressure to remain unchanged; therefore, intergenic spacer regions evolve more rapidly than other sequences. Next is the "wobble" position of protein-coding genes, and slowest to change are the structural rRNA genes. The information that can be obtained from the use of molecular approaches depends on the analysis technique chosen. The level of resolution required, coupled with study aims, will largely guide the choice of technique used for a given study (Fig. 4.3).

other factors that may affect molecular analyses

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