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Variable regions within ribosomal RNAs frequently vary in length as a result of incorporating products of slippage. This makes constructing secondary structure models problematic because base homology is difficult or impossible to establish between species. Here, we model such a region by comparing the results of the MFOLD suboptimal folding algorithm for different species to identify conserved structures. Based on the reconstruction of base change on a phylogenetic tree of the species and comparison against null models of character change, we devise a statistical analysis to assess support of these structures from compensatory and semi-compensatory (i.e. G.C to G.U or A.U to G.U) mutations. As a model system we have used variable region V4 from cicindelid (tiger beetle) small subunit ribosomal RNAs (SSU rRNAs). This consists of a mixture of conserved and highly variable subregions and has been subject to extensive comparative analysis in the past. The model that results is similar to a previously described model of this variable region derived from a different set of species and contains a novel structure in the central, highly variable part. The method we describe may be useful in modelling other RNA regions that are subject to slippage.

Modelling the secondary structures of slippage-prone hypervariable RNA regions: the example of the tiger beetle 18S rRNA variable region V4