Reconstruction of ancestral RNA sequences under multiple structural constraints

Abstract

BackgroundSecondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors.MethodsIn this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families.ResultsWe test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database.ConclusionsOur results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3105-4) contains supplementary material, which is available to authorized users.

Median and small parsimony problems on RNA trees

“…We could not compare the results of our method to the two existing approaches cited in the introduction, namely Bradley and Holmes (2009) and Tremblay-Savard et al (2016) . Unfortunately, the source code for Bradley and Holmes (2009) is no longer available at the time of writing this paper.…”

“…Unfortunately, the source code for Bradley and Holmes (2009) is no longer available at the time of writing this paper. As for Tremblay-Savard et al (2016) , the method computes ancestral sequences while our methods compute ancestral structures.…”

“…In future extensions, the RNA sequences can be involved either by considering a distance metric that incorporates both the sequence and the structure to reconstruct parsimonious ancestral sequences and structures, or by using the resulting parsimonious ancestral structures as a constraint to subsequently compute parsimonious ancestral RNA sequences under a structurally constrained sequence evolution model. This will allow us to compare the results of our methods against ancestral RNA sequence reconstruction methods such as achARNement ( Tremblay-Savard et al 2016 ). Moreover, we have studied the restricted version of the problems where RNA structures are not subject to nucleotide indel events, thus considering RNA sequences of the same length.…”

“…The structure of RNA molecules is closely linked to their function ( Mattick 2005 ). Inferring ancestral RNA sequences and structures aims to understand how these structures have adapted and evolved over time, leading to the diversity of RNA observed today ( Holmes 2004 , Gruber et al 2008 , Tremblay-Savard et al 2016 ). It can provide information about the RNA World hypothesis and the roles played by RNA in early biological processes by revealing patterns of conservation and providing insights into functional adaptations of RNA structures.…”

“…However, the computational burden involved in the inference algorithm makes it prohibitive in practice. Then, Tremblay-Savard et al (2016) developed a maximum parsimony method to compute the ancestral RNA sequences under a structurally constrained nucleotide substitution model, given an alignment of input sequences. The model allows only single nucleotide substitutions, and the method uses secondary structures as constraints.…”