Computational prediction of telomerase RNAs in yeast genomes
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Telomerase RNA (TR) is a vital component of the telomerase enzyme which ensures the complete replication of chromosome ends. Experimental identification of TRs is expensive and lacks a general approach due to the divergent TR sequences across many eukaryotes. Computational prediction of TRs can help narrow down the number of plausible candidates for further experimental validations. The common core structure found in all known TRs may form the basis for a prediction. However, the structure contains a recently identified triple helix as well as structural elements divergent across many eukaryotes, beyond the capability of existing RNA structure profiling techniques. The structure-based prediction of TRs thus remains challenging. I introduce a pseudoknot-prediction-capable utility computer program, called TRFolder. Unlike existing general purpose structure prediction programs, TRFolder is effective in predicting core TR elements including pseudoknots, triple helices, template-boundary elements and core-closing stems that occur in yeast TRs.