Bioinformatics Advance Access originally published online on January 24, 2008
Bioinformatics 2008 24(4):579-580; doi:10.1093/bioinformatics/btm635
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Colorstock, SScolor, Ratón: RNA alignment visualization tools
Department of Bioengineering, UC Berkeley, Berkeley, CA, USA
*To whom correspondence should be addressed.
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ABSTRACT |
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 TOP ABSTRACT 1 Introduction2 DesignACKNOWLEDGEMENTSREFERENCES |
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Summary: Interactive examination of RNA multiple alignments for covariant mutations is a useful step in non-coding RNA sequence analysis. We present three parallel implementations of an RNA visualization metaphor: Colorstock, a command-line script using ANSI terminal color; SScolor, a Perl script that generates static HTML pages; and Ratón, an AJAX web application generating dynamic HTML. Each tool can be used to color RNA alignments by secondary structure and to visually highlight compensatory mutations in stems.
Availability: All source code is freely available under the GPL. The source code can be downloaded and a prototype of Ratón can be accessed at http://biowiki.org/RnaAlignmentViewers
Contact: ihh{at}berkeley.edu
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1 Introduction |
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TOPABSTRACT1 Introduction2 DesignACKNOWLEDGEMENTSREFERENCES |
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Non-coding RNA (ncRNA) is an important part of the cis-regulatory picture (Ambros and Chen, 2007; Pheasant and Mattick, 2007) and has a broad chemical repertoire of great potential value (Breaker, 2004). Several ‘pipelines’ for discovery of novel ncRNA motifs by comparative genomics have been described (Pedersen et al., 2006; Rivas et al., 2001; Bradley et al., 2007; Washietl et al., 2005) adding to a comprehensive database of known ncRNA alignments (Griffiths-Jones et al., 2003). Visual inspection of alignments is an important quality control step in such pipelines.
Generally, in comparative genomics, alignments of sequences from related species are used to look for evidence of conservation of genomic features through evolution. Non-coding RNAs in particular, however, often do not exhibit conservation at the sequence level but do display conservation at the structural level. Compensatory mutations of the bases in an RNA alignment are a signature of this structural-level conservation. (By ‘compensatory mutations’ we mean substitutions of both the sites involved in a base-pair, such that canonical Watson-Crick or wobble base-pairing is maintained: although we do not know in which order the two substitutions occurred, we presume that the second substitution ‘compensated’ for the first.) When eyballing an RNA alignment to determine if it includes a structural ncRNA, it is extremely helpful to have a visual indicator of such mutations.
Using color to denote basepairing patterns in RNA alignments has been common and, workers place for a while. To our knowledge, the idea of specifically highlighting compensatory mutations was introduced by Pedersen in the EVOFOLD track of the UCSC Genome Browser, and by Griffiths-Jones in RALEE, the RNA alignment mode for Emacs (Griffiths-Jones, 2005). In the EVOFOLD track, rendered HTML pages show the colorized alignment for a predicted ncRNA feature on clickthrough from the corresponding browser track (Pedersen et al., 2006).
We found this visual paradigm to be useful enough to warrant a standalone implementation. We observe, however, that bioinformatics workflow often goes beyond static HTML. Experienced analysts spend a lot of time at the command line in an X11, VT100 or other terminal window, which (for an expert) is usually the most interactive way to work. However, extra interactivity is also starting to show up in ‘Web 2.0’ applications via dynamic HTML technologies such as Javascript/AJAX. An example of this migration of command-line workflow to a Javascript-led interface is the heavily Unix-influenced web application ‘Yahoo Pipes’: http://pipes.yahoo.com/
To analyze RNA effectively we needed visualization tools that matched all three parts of our workflow: command-line terminal hackery, static HTML page browsing and smart AJAX components. We also found that a variety of coloring paradigms is effective. Here, we describe three tools—Colorstock, SScolor and Ratón—that grew from these needs.
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2 Design |
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TOPABSTRACT1 Introduction2 DesignACKNOWLEDGEMENTSREFERENCES |
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All three scripts take a Stockholm format alignment as input (see biowiki.org/StockholmFormat). The alignment should include a line beginning ‘#=GC SS_cons’ that describes the consensus secondary structure, as per the Stockholm format spec. A colorized, annotated alignment is produced as output. Optionally, compensatory mutations are shown relative to a designated reference sequence.
The visual outputs of the three tools are compared in Figure 1. The coloring scheme used by Colorstock is slightly different than the scheme used by the other two programs. In Colorstock, coloration is per-column and by stem; the number of compensatory mutations is indicated above each stem. In SScolor and Ratón, coloration is per-basepair and depends on whether the bases (i) are complementary and (ii) display mutations relative to a reference sequence.
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2.1 Colorstock
The Perl script colorstock.pl renders a colorized RNA alignment in ANSI terminal color. Optionally, a reference sequence can be highlighted. Colorstock also outputs a summary line counting total paired columns, the number of these paired columns which display compensatory mutations and the number of distinct stems. Output is piped through less or another Unix pager. Optionally, the output can be rendered in HTML using the ANSI terminal color scheme. Extensive documentation is available by typing ‘perldoc colorstock.pl’.
2.2 SScolor
The sscolor.pl script outputs static HTML without Javascript, with a color scheme similar to Ratón's (described below). The accompanying sscolorMult.pl script calls sscolor.pl repeatedly, generating a family of interlinked HTML pages where each page has a different row of the alignment designated as the reference sequence. Extensive documentation of both tools is available by typing ‘perldoc sscolor.pl’.
2.3 Ratón
Ratón is an AJAX web application created to make the sscolor.pl alignment coloring function more interactive. At the beginning of a session, the user first uploads an RNA alignment in Stockholm format to the server. If the alignment contains a consensus secondary structure, the user is then able to select one of the sequences in the alignment to be the reference sequence. If there is more than one consensus secondary structure, the user can also select which one will be used for coloring.
The Ratón program acts as an interface to the xrate phylogrammar engine (Klosterman et al., 2006), so that the user can also request that a consensus structure to be computed by an xrate server.While this is processing, the user can (asynchronously) perform interactive coloring operations on the alignment, selecting any sequence to be the ‘reference’ and observing the mutations in the other sequences relative to this reference. With the graphical interface, the user is quickly able to see how basepairing covariation changes with respect to a given sequence in the alignment and consensus secondary structure.
The coloring scheme was inspired by the UCSC Genome Browser Evofold track, which uses color to distinguish Watson-Crick/wobble base-pairs from non-canonical base-pairs and to indicate compensatory mutations. Complementary basepairs are colored black if both are identical to the reference sequence, blue if one is different and green if both are different. Non-complementary basepairs are colored red. Unpaired bases are colored gray if they are identical to the reference sequence or purple if they are different.
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ACKNOWLEDGEMENTS |
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TOPABSTRACT1 Introduction2 DesignACKNOWLEDGEMENTSREFERENCES |
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YRB was funded in part by a Berkeley EDGE scholarship. IH was funded in part by NIH/NHGRI grant 1R01GM076705-01. The authors thank Mitch Skinner, Andrew Uzilov and Robert Bradley.
Conflict of Interest: none declared.
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FOOTNOTES |
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Associate Editor: Limsoon Wong
Received on October 22, 2007; revised on December 11, 2007; accepted on December 22, 2007
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REFERENCES |
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TOPABSTRACT1 Introduction2 DesignACKNOWLEDGEMENTSREFERENCES |
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Ambros V, Chen X. The regulation of genes and genomes by small RNAs. Development (2007) 134:1635–1641.
Bradley, et al. An XRATE ncRNA pipeline. (2007) In preparation.
Breaker RR. Natural and engineered nucleic acids as tools to explore biology. Nature (2004) 432:838–845.[CrossRef][Medline]
Griffiths-Jones S. RALEE–RNA ALignment editor in Emacs. Bioinformatics (2005) 21:257–9.
Griffiths-Jones S, et al. Rfam: an RNA family database. Nucleic Acids Res (2003) 31:439–441.
Klosterman PS, et al. XRate: a fast prototyping, training and annotation tool for phylo-grammars. BMC Bioinformatics (2006) 7:428.[CrossRef][Medline]
Pedersen JS, et al. Identification and classification of conserved RNA secondary structures in the human genome. PLoS Computational Biology (2007) 2:e33.
Pheasant M, Mattick JS. Raising the estimate of functional human sequences. Genome Res (2007) 17:1245–1253.
Rivas E, Klein RJ, Jones TA, Eddy SR. Computational identification of noncoding RNAs in E. coli by comparative genomics. Curr. Biol (2001) 11:1369–1373.[CrossRef][Web of Science][Medline]
Washietl S, et al. Fast and reliable prediction of noncoding RNAs. Proc. Nat. Acad. Sci. USA (2005) 102:2454–2459.
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