Semiautomated improvement of RNA alignments
Author(s) -
Ebbe Sloth Andersen,
Allan Lind-Thomsen,
Bjarne Knudsen,
Susie E. Kristensen,
Jakob H. Havgaard,
Elfar Torarinsson,
Niels Larsen,
Christian Zwieb,
Peter Sestoft,
Jørgen Kjems,
Jan Gorodkin
Publication year - 2007
Publication title -
rna
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.037
H-Index - 171
eISSN - 1469-9001
pISSN - 1355-8382
DOI - 10.1261/rna.215407
Subject(s) - rna , biology , computational biology , nucleic acid secondary structure , base pair , rna editing , computer science , genetics , dna , gene
We have developed a semiautomated RNA sequence editor (SARSE) that integrates tools for analyzing RNA alignments. The editor highlights different properties of the alignment by color, and its integrated analysis tools prevent the introduction of errors when doing alignment editing. SARSE readily connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture of the SARSE editor makes it a flexible tool to improve all RNA alignments with relatively little human intervention. Online documentation and software are available at (http://sarse.ku.dk).
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