UTRdb and UTRsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs (original) (raw)
Journal Article
,
* To whom correspondence should be addressed. Tel: +39 02 50314915; Fax: +39 02 50314912; Email: graziano.pesole@unimi.it
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
,
Search for other works by this author on:
Search for other works by this author on:
Published:
01 January 2005
Cite
Flavio Mignone, Giorgio Grillo, Flavio Licciulli, Michele Iacono, Sabino Liuni, Paul J. Kersey, Jorge Duarte, Cecilia Saccone, Graziano Pesole, UTRdb and UTRsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs, Nucleic Acids Research, Volume 33, Issue suppl_1, 1 January 2005, Pages D141–D146, https://doi.org/10.1093/nar/gki021
Close
Navbar Search Filter Mobile Enter search term Search
Abstract
The 5′ and 3′ untranslated regions of eukaryotic mRNAs play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5′ and 3′ untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated (and also collated as the UTRsite database) and cross-links to genomic and protein data are provided. The integration of UTRdb with genomic and protein data has allowed the implementation of a powerful retrieval resource for the selection and extraction of UTR subsets based on their genomic coordinates and/or features of the protein encoded by the relevant mRNA (e.g. GO term, PFAM domain, etc.). All internet resources implemented for retrieval and functional analysis of 5′ and 3′ untranslated regions of eukaryotic mRNAs are accessible at http://www.ba.itb.cnr.it/UTR/ .
Received September 15, 2004; Accepted September 18, 2004
INTRODUCTION
One of the main challenges of the post-genomic era is the understanding of the mechanisms that control the spatio-temporal regulation of gene expression. The fate of newly synthesized mRNA with respect to its nucleo-cytoplasmic transport, stability, translation efficiency and subcellular localization is determined at the post-transcriptional level. Such regulation is mostly mediated by cis-acting elements located in the 5′ and 3′ untranslated regions of mRNAs (5′ UTR and 3′ UTR) ( 1 ).
In several cases, specific functional sequence elements have been identified and characterized. These usually correspond to short oligonucleotide tracts whose biological activity relies on a combination of their primary sequence and specific secondary structure. These motifs act either as target sites for RNA-binding factors or interact directly with the translation machinery.
The availability of a large collection of functionally related sequences—such as UTRs—is invaluable for the inference of structural and compositional features and for the identification of conserved candidate regulatory motifs. For this reason, we have developed UTRdb, a collection of 5′ and 3′ UTR sequences derived from eukaryotic mRNAs. Sequences collated in UTRdb were generated by custom software. UTRdb is a non-redundant database and annotation includes information not available in the primary databases such as genome localization and structure and presence of known regulatory elements.
We have also created UTRsite, a collection of regulatory elements located in 5′ and 3′ UTRs whose function and structure have been experimentally determined and published. The UTRsite collection may prove useful in automatic annotation projects of unknown sequences as well as for finding previously undetected signals in known sequences.
For the most recent release of the UTRdb and UTRsite databases, we have focused on the improvement of data quality, increasing the degree of integration with other resources and the incorporation of genome-related facilities. Besides a new graphical interface, we have introduced new specific UTR collections: (i) UTRef from RefSeq database ( 2 ); (ii) UTRait from TRAIT database of muscle-specific transcripts ( 3 ); and (iii) UTRexp, a collection of UTR sequences whose functional activity has been experimentally investigated (see below for details). The UTRsite collection of functional motifs has also been significantly expanded. Moreover, we have mapped human UTRs on genome assemblies, facilitating the direct comparison and integration of several annotated genomic features available through batch queries of Ensembl databases.
The integration of UTRs and protein/genomic resources is potent in that it allows the retrieval of specific UTR subsets based on their genomic coordinates and/or features associated with the encoded proteins (e.g. GO terms, PFAM domains, etc.).
GENERATION OF UTRdb AND ITS INTEGRATION WITH OTHER DATABASES
UTRdb entries are automatically generated through the accurate parsing of the Feature Table of entries in primary databases (e.g. EMBL). Entry curation includes the detection of contaminating vector sequences, the removal of sequence redundancy and the annotation of repetitive elements and known regulatory motifs collected in the UTRsite database. Details of this process can be found in ( 4 ).
The current release of UTRdb contains three further specialized divisions: UTRef, UTRait and UTRexp. Sequences collected in UTRef and UTRait have been generated from the RefSeq ( 2 ) and TRAIT ( 3 ) databases, respectively. UTRexp contains UTRs that have been investigated experimentally and shown to contain functional motifs. Some of these sequences are not present in primary sequence databases and have been manually extracted from literature resources.
In the current release, we have also determined the genomic coordinates of human UTR sequences using the program BLAT ( 5 ) with the human genome assembly (Release NCBI 34). Only those UTRs that unambiguously mapped to a single genomic location were considered. Exonic structure of mapped UTRs was then refined by applying the program Spidey ( 6 ) to compare the UTR and its corresponding genomic location.
We have tried to associate each mapped UTR to the specific protein encoded by the corresponding mRNA using the relevant Ensembl coordinates. A protein was defined a ‘neighbor’ of a 5′ UTR if its start site corresponds to the end of the 5′ UTR sequence (and the converse for 3′ UTRs) Once the neighbor protein of a given UTR entry had been defined, we were also able to identify the Ensembl transcripts cross-referenced to the neighbor protein. If, for a given UTR entry, no annotated protein matched our criteria, we associated any Ensembl gene overlapping the same genomic region with the UTR.
The cross-referencing of UTRs and Ensembl features (protein, transcript, gene) provides a valuable resource as UTRs automatically inherit the large body of functional features annotated with the Ensembl project ( 7 ).
We have also endeavored to cross-link the UTRdb human division with IPI (International Protein Index) ( 8 ), which contains a complete non-redundant data set representing the human proteome, derived from different curated protein databases.
In future releases of UTRdb, we plan to extend the cross-referencing between UTRs and protein/genomic resources to all other organisms included in Ensembl.
UTRdb entries (see Figure 1 for an example) are annotated for the occurrence of regulatory motifs whose activity has been assessed by experimental investigation, located in the 5′ or 3′ UTR of eukaryotic mRNAs. All these motifs are collected in the UTRsite database. Each UTRsite entry ( Figure 2 ) is prepared/reviewed/updated by expert scientists (in many cases, those who performed the experimental analysis). We have now developed a Submission Tool for the generation/management/update of UTRsite entries ( Figure 3 ). This tool allows selected annotators, to annotate/update all the information in the entry in a user-friendly manner via a personal login.
Figure 1.
Sample entry of UTRdb database. The Genomic Features section includes information on genome mapping coordinates and links to the related transcript and protein sequences.
Figure 2.
Sample UTRsite entry. The General Information section includes the pattern syntax of the regulatory motif in a format suitable for PatSearch analysis ( 9 ) and the number of hits/kb randomly expected in a sequence collection of the same nucleotide composition of UTRdb. The cross-link to the RFAM database ( 10 ) if available is also provided.
Figure 3.
Home page of the Submission Tool for the management of UTRsite entries. The ‘Guest’ login only gives access to the ‘View’ option, whereas the ‘Annotator’ login allows to ‘Edit/Create’ UTRsite entries.
The databases UTRdb, UTRsite and the new specific UTR collections (UTRef, UTRait, UTRexp) have been organized into MySQL relational database management system.
UTRdb CONTENT
The main section of UTRdb (Release 19) contains nine sequence collections, one for each of the eukaryotic divisions of the EMBL nucleotide database (Release 78), namely (i) human; (ii) mouse; (ii) rodent; (iv) other mammal; (v) other vertebrate; (vi) invertebrate; (vii) plant; (viii) fungi; and (ix) virus.
UTRef was generated from Reference Sequence collections (RefSeq Rel. 3). Table 1 reports a summary description of UTRdb which contains 298 036 entries and 128 286 081 nucleotides. UTRsite collects a total of 52 regulatory motifs, including upstream Open Reading Frames (uORFs) with known regulatory activity, whose occurrences have been annotated in 30 370 entries of UTRef collection.
Table 1.
Number of unique 5′ and 3′ UTR entries in the different UTRdb sections and of annotated UTRsite motifs (release 19.0)
| | 5′UTR | 3′UTR | Total | | | ----------------- | ------- | ------- | ------- | | UTRdb | 139.019 | 159.017 | 298.036 | | UTRef | 83.326 | 87.969 | 171.295 | | UTRait | 6.290 | 5570 | 11.860 | | UTRexp | 18 | 34 | 52 | | UTR-Genome | 18.864 | 26.903 | 45.767 | | Neighbor proteins | 25.362 | 25.648 | 51.010 | | UTRSite | 52 | | |
| | 5′UTR | 3′UTR | Total | | | ----------------- | ------- | ------- | ------- | | UTRdb | 139.019 | 159.017 | 298.036 | | UTRef | 83.326 | 87.969 | 171.295 | | UTRait | 6.290 | 5570 | 11.860 | | UTRexp | 18 | 34 | 52 | | UTR-Genome | 18.864 | 26.903 | 45.767 | | Neighbor proteins | 25.362 | 25.648 | 51.010 | | UTRSite | 52 | | |
Table 1.
Number of unique 5′ and 3′ UTR entries in the different UTRdb sections and of annotated UTRsite motifs (release 19.0)
| | 5′UTR | 3′UTR | Total | | | ----------------- | ------- | ------- | ------- | | UTRdb | 139.019 | 159.017 | 298.036 | | UTRef | 83.326 | 87.969 | 171.295 | | UTRait | 6.290 | 5570 | 11.860 | | UTRexp | 18 | 34 | 52 | | UTR-Genome | 18.864 | 26.903 | 45.767 | | Neighbor proteins | 25.362 | 25.648 | 51.010 | | UTRSite | 52 | | |
| | 5′UTR | 3′UTR | Total | | | ----------------- | ------- | ------- | ------- | | UTRdb | 139.019 | 159.017 | 298.036 | | UTRef | 83.326 | 87.969 | 171.295 | | UTRait | 6.290 | 5570 | 11.860 | | UTRexp | 18 | 34 | 52 | | UTR-Genome | 18.864 | 26.903 | 45.767 | | Neighbor proteins | 25.362 | 25.648 | 51.010 | | UTRSite | 52 | | |
AVAILABILITY OF UTRdb
UTRdb and UTRsite are accessible through an SRS retrieval system, which has been updated to include the new fields added. In particular, all the information derived from genome mapping of UTRs, the IPI cross-link, and cross-referencing to ‘neighbor proteins’ and Ensembl genes/transcripts is available through a new field named ‘Genomic Features’ as reported in Figure 1 . It is also possible to browse these fields by querying the SRS ‘Extended query form’ where relevant query fields have been added.
In addition, to access all of the information indirectly linked to UTRs, we have developed a custom browsing system—the ‘UTR genome browser’ ( Figure 4 ). Through this retrieval system, it is possible to select and extract specific UTR subsets defined by accession numbers derived from a variety of databases including IPI ( 8 ), Interpro ( 11 ), GO ( 12 ), GENEW ( 13 ), MIM ( 14 ), etc. as well as by genomic coordinates.
Figure 4.
Home page of the UTRgenome browser for the retrieval of UTR subset based on their genomic coordinates and/or features of the protein encoded by the corresponding mRNAs.
The user can choose to download selected entries in Fasta format or to display a summary of their relevant genomic features, including genomic coordinates and cross-references to a variety of genomic resources. A graphical representation displays selected UTRs in terms of genomic coordinates and shows other human UTRs, cDNAs, proteins and ESTs in the same genome location.
With this new tool, it is now possible to obtain specific UTR subsets from mRNAs coding for proteins of a selected protein family, containing a specific domain or belonging to a specific GO class. Further investigations of such homogeneous sets of UTRs may allow the identification of common features or conserved regions whose potential functional activity may then be experimentally characterized.
Further on-line utilities are UTRscan and UTRblast. The UTRscan feature allows the enquirer to search user submitted sequences for any of the motifs collected in UTRsite. The UTRblast utility allows database searches against any of the UTRdb sections.
UTRdb, UTRsite and other related resources are publicly available at http://www.ba.itb.cnr.it/UTR/ .
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions@oupjournals.org .
We thank David Horner for helpful comments on the manuscript. This work was supported by Ministero dell'Istruzione e Ricerca, Italy (projects: MIUR Cluster C03/2000-CEGB, PON 2000-2006 Progetto BIG, FIRB project ‘Bioinformatica per la Genomica e la Proteomica’) and Telethon. F.M. was the recipient of a EU Marie Curie fellowship at the European Bioinformatic Institute, Hinxton, UK.
REFERENCES
Mignone,F., Gissi,C., Liuni,S. and Pesole,G. (
2002
) Untranslated regions of mRNAs.
Genome Biol.
,
3
, REVIEWS0004.
Pruitt,K.D., Tatusova,T. and Maglott,D.R. (
2003
) NCBI Reference Sequence project: update and current status.
Nucleic Acids Res.
,
31
,
34
–37.
Toppo,S., Cannata,N., Fontana,P., Romualdi,C., Laveder,P., Bertocco,E., Lanfranchi,G. and Valle,G. (
2003
) TRAIT (TRAnscript Integrated Table): a knowledgebase of human skeletal muscle transcripts.
Bioinformatics
,
19
,
661
–662.
Pesole,G., Liuni,S., Grillo,G., Licciulli,F., Mignone,F., Gissi,C. and Saccone,C. (
2002
) UTRdb and UTRsite: specialized databases of sequences and functional elements of 5′ and 3′ untranslated regions of eukaryotic mRNAs. Update 2002.
Nucleic Acids Res.
,
30
,
335
–340.
Kent,W.J. (
2002
) BLAT—the BLAST-like alignment tool.
Genome Res.
,
12
,
656
–664.
Wheelan,S.J., Church,D.M. and Ostell,J.M. (
2001
) Spidey: a tool for mRNA-to-genomic alignments.
Genome Res.
,
11
,
1952
–1957.
Birney,E., Andrews,T.D., Bevan,P., Caccamo,M., Chen,Y., Clarke,L., Coates,G., Cuff,J., Curwen,V., Cutts,T. et al . (
2004
) An overview of Ensembl.
Genome Res.
,
14
,
925
–928.
Kersey,P.J., Duarte,J., Williams,A., Karavidopoulou,Y., Birney,E. and Apweiler,R. (
2004
) The International Protein Index: an integrated database for proteomics experiments.
Proteomics
,
4
,
1985
–1988.
Grillo,G., Licciulli,F., Liuni,S., Sbisa,E. and Pesole,G. (
2003
) PatSearch: a program for the detection of patterns and structural motifs in nucleotide sequences.
Nucleic Acids Res.
,
31
,
3608
–3612.
Griffiths-Jones,S., Bateman,A., Marshall,M., Khanna,A. and Eddy,S.R. (
2003
) Rfam: an RNA family database.
Nucleic Acids Res.
,
31
,
439
–441.
Mulder,N.J., Apweiler,R., Attwood,T.K., Bairoch,A., Barrell,D., Bateman,A., Binns,D., Biswas,M., Bradley,P., Bork,P. et al . (
2003
) The InterPro Database, 2003 brings increased coverage and new features.
Nucleic Acids Res.
,
31
,
315
–318.
Harris,M.A., Clark,J., Ireland,A., Lomax,J., Ashburner,M., Foulger,R., Eilbeck,K., Lewis,S., Marshall,B., Mungall,C. et al . (
2004
) The Gene Ontology (GO) database and informatics resource.
Nucleic Acids Res.
,
32
(Database issue),
D258
–D261.
Wain,H.M., Lush,M.J., Ducluzeau,F., Khodiyar,V.K. and Povey,S. (
2004
) Genew: the Human Gene Nomenclature Database, 2004 updates.
Nucleic Acids Res.
,
32
(Database issue),
D255
–D257.
Hamosh,A., Scott,A.F., Amberger,J., Bocchini,C., Valle,D. and McKusick,V.A. (
2002
) Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.
Nucleic Acids Res.
,
30
,
52
–55.
Author notes
1Dipartimento di Scienze Biomolecolari e Biotecnologie, Università di Milano, via Celoria 26, 20133 Milano, Italy, 2Sezione di Bioinformatica e Genomica, Istituto Tecnologie Biomediche del Consiglio Nazionale delle Ricerche (CNR), via Amendola 165/A, 70126 Bari, Italy, 3Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, via Orabona 4, 70126 Bari, Italy and 4EMBL Outstation, The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
© 2005, the authors Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved
I agree to the terms and conditions. You must accept the terms and conditions.
Submit a comment
Name
Affiliations
Comment title
Comment
You have entered an invalid code
Thank you for submitting a comment on this article. Your comment will be reviewed and published at the journal's discretion. Please check for further notifications by email.
Citations
Views
Altmetric
Metrics
Total Views 1,651
1,364 Pageviews
287 PDF Downloads
Since 1/1/2017
Month: | Total Views: |
---|---|
January 2017 | 4 |
February 2017 | 2 |
March 2017 | 3 |
April 2017 | 5 |
May 2017 | 2 |
June 2017 | 7 |
July 2017 | 3 |
August 2017 | 2 |
October 2017 | 1 |
November 2017 | 1 |
December 2017 | 11 |
January 2018 | 6 |
February 2018 | 17 |
March 2018 | 19 |
April 2018 | 12 |
May 2018 | 13 |
June 2018 | 11 |
July 2018 | 13 |
August 2018 | 12 |
September 2018 | 5 |
October 2018 | 5 |
November 2018 | 9 |
December 2018 | 9 |
January 2019 | 10 |
February 2019 | 11 |
March 2019 | 18 |
April 2019 | 14 |
May 2019 | 7 |
June 2019 | 10 |
July 2019 | 4 |
August 2019 | 19 |
September 2019 | 17 |
October 2019 | 6 |
November 2019 | 6 |
December 2019 | 6 |
January 2020 | 15 |
February 2020 | 7 |
March 2020 | 11 |
April 2020 | 5 |
May 2020 | 4 |
June 2020 | 4 |
July 2020 | 13 |
August 2020 | 10 |
September 2020 | 6 |
October 2020 | 3 |
November 2020 | 13 |
December 2020 | 9 |
January 2021 | 7 |
February 2021 | 22 |
March 2021 | 13 |
April 2021 | 10 |
May 2021 | 47 |
June 2021 | 59 |
July 2021 | 42 |
August 2021 | 33 |
September 2021 | 22 |
October 2021 | 20 |
November 2021 | 15 |
December 2021 | 22 |
January 2022 | 29 |
February 2022 | 20 |
March 2022 | 30 |
April 2022 | 29 |
May 2022 | 28 |
June 2022 | 28 |
July 2022 | 39 |
August 2022 | 41 |
September 2022 | 37 |
October 2022 | 36 |
November 2022 | 36 |
December 2022 | 24 |
January 2023 | 37 |
February 2023 | 14 |
March 2023 | 36 |
April 2023 | 42 |
May 2023 | 33 |
June 2023 | 22 |
July 2023 | 26 |
August 2023 | 37 |
September 2023 | 34 |
October 2023 | 28 |
November 2023 | 42 |
December 2023 | 51 |
January 2024 | 27 |
February 2024 | 25 |
March 2024 | 11 |
April 2024 | 12 |
May 2024 | 10 |
June 2024 | 16 |
July 2024 | 16 |
August 2024 | 18 |
September 2024 | 11 |
October 2024 | 14 |
Citations
127 Web of Science
×
Email alerts
Citing articles via
More from Oxford Academic