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.