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SnOPY: A small nucleolar RNA orthological gene database

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Small nucleolar RNAs (snoRNAs) are a class of non-coding RNAs that guide the modification of specific nucleotides in ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). Although most non-coding RNAs undergo post-transcriptional modifications prior to maturation, the functional significance of these modifications remains unknown. Here, we introduce the snoRNA orthological gene database (snOPY) as a tool for studying RNA modifications. snOPY provides comprehensive information about snoRNAs, snoRNA gene loci, and target RNAs. It also contains data for orthologues from various species, which enables users to analyze the evolution of snoRNA genes. In total, 13,770 snoRNA genes, 10,345 snoRNA gene loci, and 133 target RNAs have been registered. Users can search and access the data efficiently using a simple web interface with a series of internal links. snOPY is freely available on the web at http://snoopy.med.miyazaki-u.ac.jp. snOPY is the database that provides information about the small nucleolar RNAs and their orthologues. It will help users to study RNA modifications and snoRNA gene evolution.
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DATA NOTE Open Access
snOPY: a small nucleolar RNA orthological gene
database
Maki Yoshihama
1
, Akihiro Nakao
1,2
and Naoya Kenmochi
1*
Abstract
Background: Small nucleolar RNAs (snoRNAs) are a class of non-coding RNAs that guide the modification of
specific nucleotides in ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). Although most non-coding RNAs
undergo post-transcriptional modifications prior to maturation, the functional significance of these modifications
remains unknown. Here, we introduce the snoRNA ortho logical gene database (snOPY) as a tool for studying RNA
modifications.
Findings: snOPY provides comprehensive information about snoRNAs, snoRNA gene loci, and target RNAs. It also
contains data for orthologues from various species, which enables users to analyze the evolution of snoRNA genes.
In total, 13,770 snoRNA genes, 10,345 snoRNA gene loci, and 133 target RNAs have been registered. Users can
search and access the data efficiently using a simple web interface with a series of internal links. snOPY is freely
available on the web at http://snoopy.med.miyazaki-u.ac.jp.
Conclusions: snOPY is the database that provides information about the small nucleolar RNAs and their
orthologues. It will help users to study RNA modifications and snoRNA gene evolution.
Keywords: snoRNA, RNA modification, Intron
Findings
Background
Large-scale sequencing and transcriptome analyses have
revealed that most of the genome is transcribed and that
there are a large number of non-protein-coding tran-
scripts present in the cell [1]. Functional non-coding
RNAs (ncRNAs) include micro RNAs (miRNAs), short
interfering RNAs (siRNAs), and Piwi-interacting RNAs
(piRNAs), which play important roles in biological pro-
cesses such as gene expression, gene silencing, and RNA
processing [2]. In addition, there are many classical es-
sential ncRNAs, including ribosomal RNAs (rRNAs),
small nuclear RNAs (snRNAs), and tRNAs. Some of
these RNAs are known to undergo post-transcriptional
modifications [3-5]. Experimental results have shown
that deficiencies in RNA-modifying enzymes lead to em-
bryonic death in mice, and the loss of rRNA modifica-
tion leads to developmental defects in zebrafish, which
signifies the importance of RNA modifications for the
proper functioning of ncRNAs [6,7]. Alth ough many
modification sites have been identified [8], the functions
of these modifications remain unknown.
Small nucleolar RNAs (snoRNAs) play key roles in the
RNA modification process. These RNAs function as
guide RNAs for the site-specific modification of target
RNAs such as rRNAs and snRNAs [9]. Over the last
decade, a large number of snoRNAs have been identified
experimentally or computationally in various species
[10,11]. These RNAs are encoded by three types of gen-
omic loci, i.e., intronic gene loci, polycistronic gene loci
(clusters), and monocistronic gene loci (independent)
[9]. The snoRNA genes of different loci must be
expressed in different ways but in a coordinated manner.
For example, for the maturation of human 28S rRNA,
98 distinct snoRNA genes need to be expressed simul-
taneously from 65 independent loci. It is still unclear
how the expression of these snoRNAs is regulated in a
synchronized manner.
We have constructed the snoRNA orthological gene
database (snOPY) as a tool for studying RNA modifica-
tions and snoRNA gene evolution. This database provides
comprehensive information about snoRNAs, snoRNA
* Correspondence: kenmochi@med.miyazaki-u.ac.jp
1
Frontier Science Research Center, University of Miyazaki, 5200 Kihara,
Kiyotake, Miyazaki 889-1692, Japan
Full list of author information is available at the end of the article
© 2013 Yoshihama et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the
Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
Yoshihama et al. BMC Research Notes 2013, 6:426
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gene loci, and target RNAs. In addition, it includes manu-
ally curated orthologous gene data for each gene. This
unique database enables users to analyze not only
snoRNAs but also their targets and gene organization in
various species.
Database content
snOPY provides three main types of information:
snoRNA, snoRNA gene locus, and target RNA (Table 1).
As of October 2013, it contains 13,770, 10,345, and 133
records of snoRNAs, snoRNA gene loci, and target RNAs,
respectively.
snoRNA
The major function of snoRNAs is to guide the modifi-
cation of rRNAs or snRNAs via antisense RNA:RNA
interactions with their target RNAs (Figure 1). snoRNAs
are divided into two major classes based on highly con-
served motifs, i.e., the C/D and H/ACA boxes [9]. The
C/D box snoRNAs contain two sequence motifs (C box:
TGATGA; D box: CTGA) and dire ct the 2-O-methyla-
tion of their target RNAs. In these snoRNAs, a region
upstream of the D or D box is complementary to the
target RNA, and the modification occurs 5 nt upstream
of these boxes (Figures 1 and 2) [12]. The H/ACA box
snoRNAs also contain two sequence motifs (H box:
ANANNA; ACA: ACA box) and guide the pseudo-
uridylation (conversion of uridine to pseudouridine) of
the target RNA. The modification site is located at the
pseudouridylation pocket, which is formed by an RNA:
RNA antisense interaction betw een complementar y se-
quences of the snoRNA and target RNA (Figure 1) [13].
The snoRNA data were collected from public databases
according to the sequence annotation and manually
curated.
Gene locus
There are three types of snoRNA gene loci: intronic,
polycistronic, and monocistronic [9,14]. In intronic loci,
the snoRNA gene is located within the intron of protein-
coding or non-protein-coding genes (host gene) and
transcribed simultaneously with its host gene under the
control of the host gene promoter. The maturation of
snoRNA transcripts is achieved via the splicing and sub-
sequent processing of the host gene. In the animal king-
dom, most snoRNA genes are expressed from introns
[14]. The polycistronic loci contain multiple snoRNA
genes that are organized into a cluste r and transcribed
from a single promoter, whereas the monocistronic loci
contain a single snoRNA gene that is expres sed from its
own promoter. In plants and yeast, most of the snoRNA
genes exhibit either polycistronic or monocistronic
expression [15,16].
Target RNA
rRNAs and snRNAs are the major targets of snoRNAs.
In general, the number of modified nucleotides depends
on the length of the target RNA. For example, human
28S rRNA and U2 snRNA contain 119 and 13 mod ifica-
tion sites, respectively. However, there are many orphan
snoRNAs whose targets remain to be determined.
Orthologue
snOPY also contains information about snoRNA ortho-
logues. The identification of the orthologues using com-
mon homology search techniques such as BLAST is
difficult because the sequence conservation between
snoRNAs from different species is very low (Figure 2).
Although there are some short conserved motifs, BLAST
often fails to identify the correct counterparts. There-
fore, we focused on the sequence conservation between
the target RNAs such as rRNAs rather than the snoRNA
sequences themselves to identify the orthologues. We
performed sequence alignment of the target RNAs from
different species using ClustalW [17], then mapped the
modification sites on that alignment. If the modified nu-
cleotide is aligned at the same position, we assumed the
snoRNA that guides this modification as an orthologue.
Utility and discussion
snOPY provides several search parameters, including
species, box motif, target RNA, gene organization, cur-
ation status, and keywords. Users can also perform a
Table 1 snOPY statistics
Classification No.
Records
Species 34
snoRNA gene 13,770
Gene locus 10,345
Target RNA 133
Box type
C/D 4,795
H/ACA 7,913
H/ACA, C/D 2
Unclassified 1,060
Gene locus
Intronic 2,539
Polycistronic 473
Monocistronic 7,333
Target RNA
Ribosomal RNA (rRNA) 101
Small nuclear RNA (snRNA) 32
Numbers include both curated and noncurated data. As of October 2013, the
number of curated snoRNA gene entries is 2,024.
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BLAST search for the gene sequences, gene loci, and tar-
get RNAs (Figure 3A, 3B). In addition, search results are
visualized using Locus View, which enables users to
compare the snoRNA locus directly between various
species (Figure 3C).
Each snoRNA entry page provides ba sic information
about the locus, including the snoRNA gene sequence,
type of box motif, and genomic position (Figure 3D). In-
formation relating to the gene locus and target RNA is
also provided, and these items are linked to more de-
tailed descriptions (Figure 3E). Users can retrieve
orthologues and perform multiple sequence alignments
via this page (Figure 3F). The locus entry pages show
schematics of the locus structure and sequence, as well
as other information about the locus (Figure 3G). The
target RNA entry pages show complete RNA sequences
and modification sites (Figure 3H). When available, the
snoRNAs involved in these modifications are also
Figure 2 A multiple sequence alignment of snoRNAs (SNORD38) from 25 species. Part of the target RNA sequence (H. sapiens) and
modification site are also included. Box motifs and complementary sequences are highlighted in red and blue, respectively. The multiple
alignment was generated by ClustalW [17].
Figure 1 Secondary structure of snoRNAs and genomic loci. Three types of snoRNA gene loci (top), intermediate transcripts (middle), and
mature box C/D and box H/ACA snoRNAs associated with target RNAs (bottom) are shown. Circles indicate modification sites for methylation (m)
and pseudouridylation (Ψ). snoRNAs, snoRNA gene loci, and target RNAs are shown in red, gray, and blue, respectively.
Yoshihama et al. BMC Research Notes 2013, 6:426 Page 3 of 5
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shown, with links to the individual snoRNA entry page.
Users can access a list of all target RNAs via the Target
RNA link at the top of each page (Figure 3A).
The orthologues table page shows the orthologous re-
lationships between snoRNA genes from various species
(Figure 3I). The default setting includes four selected
species, Homo sapiens, Caenorhabditis elegans, Drosophila
melanogaster,andSaccharomyces cerevisiae, which are
well studied and widely referenced species. Users can
select any species for comparison and readily access the
reference data from the default setting.
At present, there exist several other databases for
snoRNAs, including snoRNA-LBME-db [18], Yeast
snoRNA Database [16], Plant snoRNA Database [19],
and the sno/scaRNAba se [20]. These databases provide
very useful information about the snoRNAs from par-
ticular organisms. However, users are unable to compare
the snoRNAs from various species. On the other hand,
Figure 3 Representative snapshots of snOPY pages. A, search form; B, search results selected with Homo sapiens; C, results retrieved from
Locus View using RPL4 as a keyword; D, individual snoRNA entry page for H. sapiens SNORD18A, with box motifs and complementary
sequences highlighted in red and green, respectively; E, orthologues retrieved using list in the human SNORD18A page; F, multiple sequence
alignment for SNORD18A; G, snoRNA gene locus of the human RPL4 gene for SNORD18A; H, target RNA and modification sites for human 28S
rRNA; I, an orthologue table for four representative species. With the exception of A and C, only a part of each page is shown in the snapshot.
Yoshihama et al. BMC Research Notes 2013, 6:426 Page 4 of 5
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snOPY provides data from a wide variety of species,
which enables users to perform comparative analysis
very efficiently.
Availability and requirements
snOPY is freely available on the web at http://snoopy.
med.miyazaki-u.ac.jp.
Competing interests
The authors declare that they have no competing interests.
Authors contributions
MY designed and implemented the database. AN designed and developed
the web server. NK designed and developed the database and wrote the
manuscript. All authors read and approved the final manuscript.
Acknowledgements
We thank Dr. Jun-ichi Iwakiri and Dr. Sayomi Higa (University of the Ryukyus)
for help and advice with the database development and Ms. Mariko
Nagatomo and Ms. Shiori Yasukawa for their help in collecting the data. This
work was supported by JSPS KAKENHI Grant Numbers 22370065, 238043,
248045, and 24659476.
Author details
1
Frontier Science Research Center, University of Miyazaki, 5200 Kihara,
Kiyotake, Miyazaki 889-1692, Japan.
2
Hymena & Co., 1-21-3 Ebisu, Shibuya, 4-1-
10 Kounan, Minato, Tokyo 108-0075, Japan.
Received: 26 August 2013 Accepted: 21 October 2013
Published: 23 October 2013
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doi:10.1186/1756-0500-6-426
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The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.
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Despite the accumulating research on noncoding RNAs (ncRNAs), it is likely that we are seeing only the tip of the iceberg regarding our understanding of the functions and the regulatory roles served by ncRNAs in cellular metabolism, pathogenesis and host-pathogen interactions. Therefore, more powerful computational and experimental tools for analyzing ncRNAs need to be developed. To this end, we propose novel kernel functions, called base-pairing profile local alignment (BPLA) kernels, for analyzing functional ncRNA sequences using support vector machines (SVMs). We extend the local alignment kernels for amino acid sequences in order to handle RNA sequences by using STRAL's; scoring function, which takes into account sequence similarities as well as upstream and downstream base-pairing probabilities, thus enabling us to model secondary structures of RNA sequences. As a test of the performance of BPLA kernels, we applied our kernels to the problem of discriminating members of an RNA family from nonmembers using SVMs. The results indicated that the discrimination ability of our kernels is stronger than that of other existing methods. Furthermore, we demonstrated the applicability of our kernels to the problem of genome-wide search of snoRNA families in the Caenorhabditis elegans genome, and confirmed that the expression is valid in 14 out of 48 of our predicted candidates by using qRT-PCR. Finally, highly expressed six candidates were identified as the original target regions by DNA sequencing.
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The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.
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Transfer RNAs are adaptor molecules, which decode mRNA into protein and, thereby, play a central role in gene expression. During the maturation of a primary tRNA transcript, specific subsets of the four normal nucleosides adenosine, cytidine, guanosine, and uridine are modified. The formation of a modified nucleoside can require more than one gene product and may involve several enzymatic steps. In the last few years, the identification of gene products required for formation of modified nucleosides in tRNA has dramatically increased. In this review, proteins involved in modification of cytoplasmic tRNAs in Saccharomyces cerevisiae are described, emphasizing phenotypic characteristics of modification deficient strains and genetic approaches used to determine the in vivo role of modified nucleosides/modifying enzymes.