Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package

Motivation: Aligning RNAs is useful to search for homologous genes, study evolutionary relationships, detect conserved regions and identify any patterns that may be of biological relevance. Poor levels of conservation among homologs, however, make it difficult to compare RNA sequences, even when considering closely evolutionary related sequences. Results: We describe SARA-Coffee, a tertiary structure-based multiple RNA aligner, which has been validated using BRAliDARTS, a new benchmark framework designed for evaluating tertiary structure-based multiple RNA aligners. We provide two methods to measure the capacity of alignments to match corresponding secondary and tertiary structure features. On this benchmark, SARA-Coffee outperforms both regular aligners and those using secondary structure information. Furthermore, we show that on sequences in which <60% of the nucleotides form base pairs, primary sequence methods usually perform better than secondary-structure aware aligners.