Nucleic Acids Research Advance Access published online on September 25, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp788
© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Recode-2: new design, new search tools, and many more genes
Michaël Bekaert1,
Andrew E. Firth2,
Yan Zhang3,
Vadim N. Gladyshev3,
John F. Atkins2,4 and
Pavel V. Baranov5,*
1School of Biology and Environmental Science, University College Dublin, 2BioSciences Institute, University College Cork, Ireland, 3Division of Genetics, Department of Medicine, Brigham & Womens Hospital and Harvard Medical School, Boston, MA 02115, USA, 4Human Genetics Department, University of Utah, UT 84112 USA and 5Biochemistry Department, University College Cork, Ireland
*To whom correspondence should be addressed. Tel: +353 (0) 21 4904212; Fax: +353 (0) 21 4904259; Email: p.baranov{at}ucc.ie
Received August 15, 2009. Accepted September 4, 2009.
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ABSTRACT
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Recoding is a term used to describe non-standard
read-out of the genetic code, and encompasses such phenomena
as programmed ribosomal frameshifting, stop codon readthrough,
selenocysteine insertion and translational bypassing. Although
only a small proportion of genes utilize recoding in protein
synthesis, accurate annotation of recoded genes
lags far behind annotation of standard genes.
In order to address this issue, provide a service to researchers
in the field, and offer training data for developers of gene-annotation
software, we have gathered together known cases of recoding
within the Recode database. Recode-2 is an improved and updated
version of the database. It provides access to detailed information
on genes known to utilize translational recoding and allows
complex search queries, browsing of recoding data and enhanced
visualization of annotated sequence elements. At present, the
Recode-2 database stores information on approximately 1500 genes
that are known to utilize recoding in their expression—a
factor of approximately three increase over the previous version
of the database. Recode-2 is available at
http://recode.ucc.ie
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INTRODUCTION
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The term translational recoding describes the
utilization of non-standard decoding during protein synthesis
and encompasses such processes as ribosomal frameshifting, codon
redefinition, translational bypassing and StopGo (
1–7).
What is often considered as a decoding error—e.g. a frameshifting
error or mistranslation of a particular codon—may occasionally
benefit the organism by increasing its fitness and survival.
In such instances the propensity for the decoding error
may be selected for during evolution, leading to the formation
of a particular sequence context that elevates the frequency
of the error. To discriminate such cases of programmed
decoding misbehaviour from promiscuous translational
errors or translational noise, the term recoding is used. The
position within an mRNA where a recoding event takes place is
termed the recoding site. Sequence elements responsible
for increasing the efficiency of recoding events are termed
recoding stimulatory signals, and a minimal sequence
fragment that allows recoding to take place at the natural efficiency
(i.e. relative to the level of standard decoding at the recoding
site) is termed a recoding cassette.
Recoding can benefit gene expression in a number of ways. It can regulate gene expression by being part of a sensor for particular cellular conditions. Prominent examples include ribosomal frameshifting in bacterial release factor 2 (RF2) and eukaryotic antizyme mRNAs. In both instances, ribosomal frameshifting is required for the production of the corresponding active full-length protein products. In the RF2 mRNA, the efficiency of frameshifting is negatively regulated by the cellular concentration of its product, RF2, providing an auto-regulatory circuit for its biosynthesis (8–10). In the antizyme mRNA, the efficiency of frameshifting is modulated by cellular levels of polyamines, whose concentration in turn is controlled by antizyme (11,12). Thus, this mechanism ensures the maintenance of antizyme production at the levels required to support physiologically appropriate concentrations of polyamines. Recoding can also be used for the diversification of protein products encoded by a single gene. An illustrative example is in bacterial dnaX mRNA, where frameshifting allows synthesis of two different protein subunits—sharing the same N-terminal part—from a single open reading frame (ORF) in its mRNA (13–15). A presumed constant ratio of frameshifting in dnaX ensures a fixed stoichiometric balance between these two subunits (16). This balance, then, is independent of the absolute levels of dnaX transcription and translational initiation on its mRNA. Similarly, in many viruses recoding is responsible for setting a ratio between protein products (such as those encoded by gag–pro–pol genes in retroviruses) produced from a single mRNA (17). Recoding also provides RNA viruses with a mechanism for the translation of downstream ORFs on polycistronic RNAs [other mechanisms include leaky scanning, shunting, reinitiation, IRESs and the production of subgenomic RNAs (18)] and may also be involved in global regulation mechanisms, such as mediating the switch between translation and replication on the same genomic RNA (19). Finally, recoding provides a way for the incorporation of non-standard amino acids—e.g. amino acids that share their codons with termination signals (the most prominent example of which is selenocysteine, encoded by UGA) (20–22). For further information on the diverse variety of recoding functions, see recent reviews (1,3,7,23,24).
Recoding cassettes may be composed of a variety of diverse sequence elements. For example, primary nucleotide sequences may promote re-arrangements of tRNA molecules relative to their codons in mRNA inside the ribosome or affect recognition of tRNAs or release factors in the ribosomal A-site. On the other hand, many recoding signals act in the form of RNA secondary structures, such as simple stem-loops, or more complex pseudoknots, kissing stem-loops and other structures that involve interactions between considerably distant RNA regions (19,25–28). Trans-acting RNA signals affecting ribosomal decoding through complementary interactions with ribosomal RNA (29–32), or through the nascent peptide acting within the ribosome exit tunnel (6,33,34), are also known. Some recoding events—such as selenocysteine insertion—require the presence of additional specialized machinery such as selenocysteine tRNAs, selenocysteine-specific translation factors and several other components of the selenocysteine biosynthesis and insertion pathway (20,35–37). Recent reviews on stimulatory signals involved in the modulation of recoding events and molecular mechanisms of recoding provide further details (7,25,27,38,39).
Despite considerable progress in the development of computational tools for the prediction of protein coding genes in sequenced genomes, the identification and annotation of recoded genes lags far behind. The hurdle lies not so much in the fact that recoded genes do not obey standard rules of genetic readout but, rather, in the considerable diversity of recoded genes and sequence elements responsible for recoding. Even among evolutionarily related genes, all utilizing recoding, the diversity of recoding signals can be considerable. An extreme example is when orthologous genes utilize recoding at different stages of gene expression to achieve the same goal. An example is in dnaX, where ribosomal frameshifting is employed by enterobacteria, but transcriptional slippage is used in Thermus thermophilus (40). A similar situation occurs in bacterial insertion sequence (IS) elements, where a certain group of IS elements utilizes transcriptional slippage to produce ORFA–ORFB fusions, while many other IS elements utilize ribosomal frameshifting for the same purpose (41). The diversity of recoding functions, combined with the wide spectrum of unrelated sequence elements involved in recoding, makes the design of a uniform model of recoding intractable. Nonetheless, in recent years, we have witnessed the development of specialized models and computational tools for the identification of particular subsets of recoding cassettes, or tools that are specific to recoding events in particular groups of homologous genes (42–45).
These developments, at least partially, were facilitated by the availability of a compiled dataset of known recoded genes collected together in the Recode database (http://recode.genetics.utah.edu), which was initially launched 9 years ago (46,47). To facilitate further development of computational tools for the prediction of recoded genes in the ever faster growing body of sequence data, as well as to provide bench researchers with up-to-date information on recoding, an efficient means of Recode database population and annotation are now required. In this article, we describe the incarnation of the database, Recode-2. The major advances of Recode-2 (hosted in a new location http://recode.ucc.ie) over previous versions include a new web design allowing enhanced visualization of stimulatory signals, a uniform RecodeML format for the annotation of recoded genes, and a significantly larger number of entries—including many recently identified cases—that altogether have more than doubled the size of the database since its last published update.
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DATABASE ORGANIZATION AND USAGE
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The data are stored in a local PostgreSQL database that is queried
by PHP scripts embedded in the web interface. The schema of
the PostgreSQL database is shown in
Figure 1. The database stores
information on individual genes that utilize recoding, the mechanisms
and stimulatory signals involved, and references to the original
literature sources that describe the recoding events. In order
to facilitate the uniform annotation of recoding events, we
have designed an XML-based format for the annotation of recoded
genes, RecodeML. The document type definition for RecodeML is
available at the Recode-2 web site at
http://recode.ucc.ie/dtd
The extensibility of the RecodeML format will allow incorporation
of new annotation, if required, for newly discovered types of
recoding, and the associated features, as they are being discovered.
The database handles batch importation of properly designed
RecodeML entries into the PostgreSQL database, thus facilitating
rapid population of the database with new data.

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Figure 1. Entity-Relationship diagram for the Recode-2 database. The database schematic shows the relationships between the database tables. Each Recode-2 entry is composed of one entry in the Recode-2 table and a variable number of entries in related tables. PK (Primary Key) indicates the row selected as the unique identifier for a table. FK (Foreign Key) indicates rows of a table whose values match those in the primary key of a related table. (This ensures the constancy of the database.) The arrows show the connection relationships between the various tables (PK to FK).
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The data in the database may be explored in two ways. They may
be browsed by one of the three categories: kingdom (archaea,
bacteria, eukaryotes and viruses), organism and type of recoding.
The data may also be searched directly by key words that can
be inserted into the search field. Searches that use regular
expressions are allowed. The output of a database search is
a list of Recode-2 entries in a short format that includes organism
name, kingdom, genus, type of recoding event, status of the
entry in the database and a link to the full database entry.
The full description includes the following additional information:
(i) the common name of the gene and the validation status of
the recoding event; (ii) the organism description, giving the
organism name and a link to the NCBI Taxonomy Browser (
48);
(iii) the sequence description, giving the Genbank (
49) accession
numbers for matching sequences (with links to Genbank) and links
to detailed annotations of the sequences and to diagrams of
RNA secondary structures involved in stimulation of the recoding
event; (iv) information on the protein sequence generated as
a result of recoding; (v) comments on the function of the recoding
event and any additional notes and (vi) references to relevant
literature (with links to corresponding abstracts in PubMed).
The detailed sequence annotation appears in the form of text
decorations that are described in the Help page of the database
and are also illustrated within the Recode-1 logo itself (which
can be used for rapid intuitive decoding of the text decorations
and their associations with the mechanistic ways by which different
sequences affect ribosome functions). To generate RNA secondary
structure diagrams, PseudoViewer3 (
50) is used, since it can
handle complex pseudoknot RNA structures correctly.
Figure 2 shows an example of sequence annotation for the human oaz1 gene,
alongside a diagram of a stimulatory RNA secondary structure,
and the Recode-1 logo.

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Figure 2. Screenshots from the Recode-2 database for the entry describing +1 frameshifting in human antizyme 1. (A) Annotated sequence of the human antizyme 1 gene. Colouring and formatting of the text highlights functional elements according to a scheme described on the Help page of the Recode-2 database and within the Recode-1 logo. (B) Structure of the stimulatory RNA pseudoknot. (C) The Recode1 logo.
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NOVEL DATA
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Unlike Recode-1, where all data on recoding events were introduced
manually, Recode-2 also utilizes automated identification of
recoding events by the recently developed computer programs
ARFA (
43) and OAF (
44), that are able to identify and annotate
+1 frameshifting events in mRNAs of bacterial RF2s and eukaryotic
antizyme (OAZs), respectively. However, a significant source
of recoding events remains to be serendipitous discoveries by
experimental studies that sometimes are complemented by more
systematic studies of large groups of similar genes (
51,
52).
Therefore, a large proportion of new data are still populated
manually or semi-manually. To ease manual population of recoding
events, a special form has been designed that is available in
the database upon user registration. User registration needs
to be approved by one of the database contributors. The novel
data in the database include 249 RF2 mRNAs identified by ARFA,
152 events identified by OAF, 200 new selenoprotein genes (
53–56)
and

200 new viral annotations (
57) including the newly discovered
frameshift cassettes in potyviruses (
58), alphaviruses (
59)
and the Japanese encephalitis group of flaviviruses (
60).
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FUTURE DEVELOPMENT
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The database will expand in accordance with the growth of available
sequence information that will be scanned by one of the existing
programs for recode annotation. We also plan to continue developing
tools for the automatic identification of recoding events from
nucleotide sequences. As the field grows and the number of recoded
genes progressively increases, it becomes harder to extract
data from the relevant literature and a number of novel recoded
genes may escape the database. Therefore, we encourage users
and researchers in the field to submit their data directly to
the Recode-2 database. We are also willing to provide help with
the analysis of potential new recoding events.
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FUNDING
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Science Foundation Ireland (SFI) grants (to P.V.B. and J.F.A.);
National Institutes of Health grants (to J.F.A. and V.N.G.).
Funding for open access charge: Science Foundation Ireland.
Conflict of interest statement. None declared.
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ACKNOWLEDGEMENTS
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We would like to express our appreciation to the colleagues
who have contributed data for the previous versions of the database.
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