Publications
2005
Lescoute A, Leontis N B, Massire C, Westhof E
Recurrent structural RNA motifs, Isostericity Matrices and sequence alignments Journal Article
In: Nucleic Acids Res, vol. 33, no. 8, pp. 2395-2409, 2005, ISBN: 15860776, (1362-4962 Journal Article).
Abstract | Links | BibTeX | Tags: Base Pairing Models, Molecular Nucleic Acid Conformation RNA, Non-U.S. Gov't Research Support, Nucleic Acid, P.H.S. *Sequence Alignment Sequence Analysis, Ribosomal/*chemistry Research Support, RNA/*methods Sequence Homology, U.S. Gov't, Unité ARN, WESTHOF
@article{,
title = {Recurrent structural RNA motifs, Isostericity Matrices and sequence alignments},
author = {A Lescoute and N B Leontis and C Massire and E Westhof},
url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15860776},
isbn = {15860776},
year = {2005},
date = {2005-01-01},
journal = {Nucleic Acids Res},
volume = {33},
number = {8},
pages = {2395-2409},
abstract = {The occurrences of two recurrent motifs in ribosomal RNA sequences, the Kink-turn and the C-loop, are examined in crystal structures and systematically compared with sequence alignments of rRNAs from the three kingdoms of life in order to identify the range of the structural and sequence variations. Isostericity Matrices are used to analyze structurally the sequence variations of the characteristic non-Watson-Crick base pairs for each motif. We show that Isostericity Matrices for non-Watson-Crick base pairs provide important tools for deriving the sequence signatures of recurrent motifs, for scoring and refining sequence alignments, and for determining whether motifs are conserved throughout evolution. The systematic use of Isostericity Matrices identifies the positions of the insertion or deletion of one or more nucleotides relative to the structurally characterized examples of motifs and, most importantly, specifies whether these changes result in new motifs. Thus, comparative analysis coupled with Isostericity Matrices allows one to produce and refine structural sequence alignments. The analysis, based on both sequence and structure, permits therefore the evaluation of the conservation of motifs across phylogeny and the derivation of rules of equivalence between structural motifs. The conservations observed in Isostericity Matrices form a predictive basis for identifying motifs in sequences.},
note = {1362-4962
Journal Article},
keywords = {Base Pairing Models, Molecular Nucleic Acid Conformation RNA, Non-U.S. Gov't Research Support, Nucleic Acid, P.H.S. *Sequence Alignment Sequence Analysis, Ribosomal/*chemistry Research Support, RNA/*methods Sequence Homology, U.S. Gov't, Unité ARN, WESTHOF},
pubstate = {published},
tppubtype = {article}
}
The occurrences of two recurrent motifs in ribosomal RNA sequences, the Kink-turn and the C-loop, are examined in crystal structures and systematically compared with sequence alignments of rRNAs from the three kingdoms of life in order to identify the range of the structural and sequence variations. Isostericity Matrices are used to analyze structurally the sequence variations of the characteristic non-Watson-Crick base pairs for each motif. We show that Isostericity Matrices for non-Watson-Crick base pairs provide important tools for deriving the sequence signatures of recurrent motifs, for scoring and refining sequence alignments, and for determining whether motifs are conserved throughout evolution. The systematic use of Isostericity Matrices identifies the positions of the insertion or deletion of one or more nucleotides relative to the structurally characterized examples of motifs and, most importantly, specifies whether these changes result in new motifs. Thus, comparative analysis coupled with Isostericity Matrices allows one to produce and refine structural sequence alignments. The analysis, based on both sequence and structure, permits therefore the evaluation of the conservation of motifs across phylogeny and the derivation of rules of equivalence between structural motifs. The conservations observed in Isostericity Matrices form a predictive basis for identifying motifs in sequences.