Finding consensus stable local optimal structures for aligned RNA sequences

Many non-coding RNAs (ncRNAs), such as riboswitches, can fold into alternate native structures and perform different biological functions. The computational prediction of an ncRNA's alternate native structures can be conducted by analyzing the ncRNA's energy landscape. Previously, we have developed a computational approach, RNASLOpt, to predict alternate native structures for a single ncRNA by generating all possible stable local optimal (SLOpt) stack configurations on the ncRNA's energy landscape. In this paper, in order to improve the accuracy of the prediction, we incorporate structural conservation information among a family of related ncRNA sequences to the prediction. We propose a comparative approach, RNAConSLOpt, to produce all possible consensus SLOpt stack configurations that are conserved on the consensus energy landscape of a family of related ncRNAs. Benchmarking tests show that RNAConSLOpt can reduce the number of candidate structures considered compared with RNASLOpt, and can predict ncRNAs' alternate native structures accurately. Availability: Source code and benchmark tests for RNACon-SLOpt are available at http://genome.ucf.edu/RNAConSLOpt.