The number of distinct functional classes of single-stranded RNAs (ssRNAs) and the number of sequences representing them are substantial and continue to increase. Organizing this data in an evolutionary context is essential, yet traditional comparative sequence analyses require that homologous sites can be identified. This prevents comparative analysis between sequences of different functional classes that share no site-to-site sequence similarity. Analysis within a single evolutionary lineage also limits evolutionary inference because shared ancestry confounds properties of molecular structure and function that are historically contingent with those that are imposed for biophysical reasons. Here, we apply a method of comparative analysis to ssRNAs that is not restricted to homologous sequences, and therefore enables comparison between unrelated or distantly related sequences, minimizing the effects of shared ancestry. This method is based on statistical similarities in nucleotide base composition among different functional classes of ssRNAs. In order to denote base composition unambiguously, we have calculated the fraction G+A and G+U content in addition to the more commonly used fraction G+C content. These three parameters define RNA composition space which we have visualized using interactive graphics software. We have examined the distribution of nucleotide composition from 15 distinct functional classes of ssRNAs from organisms spanning the universal phylogenetic tree. Surprisingly, these distributions are highly constrained and consistently biased in G+A and G+U content both within and between functional classes regardless of the more variable G+C content. That RNA sequences sharing little or no sequence similarity should nonetheless exhibit similar patterns of base composition indicates that severe constraints, adaptive or otherwise, act to localize the evolutionary divergence of ssRNAs in ways that have not been obvious at the sequence level.
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Paper provided by Santa Fe Institute in its series Working Papers with number
96-12-090.