Reconstruction of ancestral RNA sequences under multiple structural constraints

Abstract Background Secondary 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...

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Main Authors: Olivier Tremblay-Savard, Vladimir Reinharz, Jérôme Waldispühl
Format: Article
Language:English
Published: BMC 2016-11-01
Series:BMC Genomics
Subjects:
RNA
Online Access:http://link.springer.com/article/10.1186/s12864-016-3105-4
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spelling doaj-1f49b4a2f930420893e73c6b2220e4342020-11-24T22:18:12ZengBMCBMC Genomics1471-21642016-11-0117S1017518610.1186/s12864-016-3105-4Reconstruction of ancestral RNA sequences under multiple structural constraintsOlivier Tremblay-Savard0Vladimir Reinharz1Jérôme Waldispühl2School of Computer Science, McGill UniversitySchool of Computer Science, McGill UniversitySchool of Computer Science, McGill UniversityAbstract Background Secondary 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. Methods In 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. Results We 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. Conclusions Our 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 .http://link.springer.com/article/10.1186/s12864-016-3105-4RNASecondary structureAncestor reconstructionEvolutionPhylogenyAlgorithm
collection DOAJ
language English
format Article
sources DOAJ
author Olivier Tremblay-Savard
Vladimir Reinharz
Jérôme Waldispühl
spellingShingle Olivier Tremblay-Savard
Vladimir Reinharz
Jérôme Waldispühl
Reconstruction of ancestral RNA sequences under multiple structural constraints
BMC Genomics
RNA
Secondary structure
Ancestor reconstruction
Evolution
Phylogeny
Algorithm
author_facet Olivier Tremblay-Savard
Vladimir Reinharz
Jérôme Waldispühl
author_sort Olivier Tremblay-Savard
title Reconstruction of ancestral RNA sequences under multiple structural constraints
title_short Reconstruction of ancestral RNA sequences under multiple structural constraints
title_full Reconstruction of ancestral RNA sequences under multiple structural constraints
title_fullStr Reconstruction of ancestral RNA sequences under multiple structural constraints
title_full_unstemmed Reconstruction of ancestral RNA sequences under multiple structural constraints
title_sort reconstruction of ancestral rna sequences under multiple structural constraints
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2016-11-01
description Abstract Background Secondary 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. Methods In 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. Results We 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. Conclusions Our 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 .
topic RNA
Secondary structure
Ancestor reconstruction
Evolution
Phylogeny
Algorithm
url http://link.springer.com/article/10.1186/s12864-016-3105-4
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AT vladimirreinharz reconstructionofancestralrnasequencesundermultiplestructuralconstraints
AT jeromewaldispuhl reconstructionofancestralrnasequencesundermultiplestructuralconstraints
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