243
which minimizes the difference between the distance values in the branch lengths of the tree,
to those distance values of the original data set (Olsen, 1988). Parsimony methods compare
sequences on a nucleotide per nucleotide basis. Parsimony analysis seeks a phylogenetic tree
topology which minimizes the number of postulated base changes. The best tree in parsimony
analysis is that which requires the fewest number of nucleotide substitutions. Likelihood
methods essentially work backwards, and estimate the likelihood of a given data set occurring,
given a specific phylogenetic tree topology. The best tree is that which maximizes the
likelihood of observing the actual data set, given a specific tree topology. Of the three
approaches, likelihood methods are the most computationally intense. A more detailed
discussion of the methods of phylogenetic inference is beyond the scope of this chapter. The
interested reader is referred to several excellent articles on the methods and assumptions of
molecular phylogenetics (Felsenstein, 1982; Felsenstein, 1988; Olsen, 1987; Swofford and
Olsen, 1990).
RmOSOMAL RNA AND MOLECULAR ECOLOGY
The application of molecular techniques to ecological and oceanographic studies is still in its
infancy. Nonetheless, several studies have recently demonstrated that a molecular approach
can help resolve some recurring difficulties in analyses of the diversity and variability of
mixed microbial populations. With reference to ecological studies, ribosomal RNA sequence
comparisons are particularly useful. This is largely due to their universal distribution, utility
in nucleic acid hybridization assays, and the growing data base of reference rRNA sequences.
The following section will focus on the development of rRNA cloning, sequencing and
hybridization techniques for ecological applications.
Ribosomal RNAs contain a wealth of evolutionary information, which can be extracted by the
process of comparative sequence analysis. This process relies only on our ability to isolate and
analyze individual rRNA sequences. Pace et al. (1986a) first suggested that this approach can
remove a major stumbling block to gaining information about naturally occurring microbes,
many of which are recalcitrant to cultivation. These workers realized that by recovering
nucleic acids from complex microbial assemblages, and clonally retrieving individual rRNA
genes from mixed population DNA, it is possible to extract information about the phylogenetic
which minimizes the difference between the distance values in the branch lengths of the tree,
to those distance values of the original data set (Olsen, 1988). Parsimony methods compare
sequences on a nucleotide per nucleotide basis. Parsimony analysis seeks a phylogenetic tree
topology which minimizes the number of postulated base changes. The best tree in parsimony
analysis is that which requires the fewest number of nucleotide substitutions. Likelihood
methods essentially work backwards, and estimate the likelihood of a given data set occurring,
given a specific phylogenetic tree topology. The best tree is that which maximizes the
likelihood of observing the actual data set, given a specific tree topology. Of the three
approaches, likelihood methods are the most computationally intense. A more detailed
discussion of the methods of phylogenetic inference is beyond the scope of this chapter. The
interested reader is referred to several excellent articles on the methods and assumptions of
molecular phylogenetics (Felsenstein, 1982; Felsenstein, 1988; Olsen, 1987; Swofford and
Olsen, 1990).
RmOSOMAL RNA AND MOLECULAR ECOLOGY
The application of molecular techniques to ecological and oceanographic studies is still in its
infancy. Nonetheless, several studies have recently demonstrated that a molecular approach
can help resolve some recurring difficulties in analyses of the diversity and variability of
mixed microbial populations. With reference to ecological studies, ribosomal RNA sequence
comparisons are particularly useful. This is largely due to their universal distribution, utility
in nucleic acid hybridization assays, and the growing data base of reference rRNA sequences.
The following section will focus on the development of rRNA cloning, sequencing and
hybridization techniques for ecological applications.
Ribosomal RNAs contain a wealth of evolutionary information, which can be extracted by the
process of comparative sequence analysis. This process relies only on our ability to isolate and
analyze individual rRNA sequences. Pace et al. (1986a) first suggested that this approach can
remove a major stumbling block to gaining information about naturally occurring microbes,
many of which are recalcitrant to cultivation. These workers realized that by recovering
nucleic acids from complex microbial assemblages, and clonally retrieving individual rRNA
genes from mixed population DNA, it is possible to extract information about the phylogenetic