File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Refining orthologue groups at the transcript level

TitleRefining orthologue groups at the transcript level
Authors
Issue Date2010
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/
Citation
Bmc Genomics, 2010, v. 11 SUPPL. 4 How to Cite?
Abstract
Background: Orthologues are genes in different species that are related through divergent evolution from a common ancestor and are expected to have similar functions. Many databases have been created to describe orthologous genes based on existing sequence data. However, alternative splicing (in eukaryotes) is usually disregarded in the determination of orthologue groups and the functional consequences of alternative splicing have not been considered. Most multi-exon genes can encode multiple protein isoforms which often have different functions and can be disease-related. Extending the definition of orthologue groups to take account of alternate splicing and the functional differences it causes requires further examination.Results: A subset of the orthologous gene groups between human and mouse was selected from the InParanoid database for this study. Each orthologue group was divided into sub-clusters, at the transcript level, using a method based on the sequence similarity of the isoforms. Transcript based sub-clusters were verified by functional signatures of the cluster members in the InterPro database. Functional similarity was higher within than between transcript-based sub-clusters of a defined orthologous group. In certain cases, cancer-related isoforms of a gene could be distinguished from other isoforms of the gene. Predictions of intrinsic disorder in protein regions were also correlated with the isoform sub-clusters within an orthologue group.Conclusions: Sub-clustering of orthologue groups at the transcript level is an important step to more accurately define functionally equivalent orthologue groups. This work appears to be the first effort to refine orthologous groupings of genes based on the consequences of alternative splicing on function. Further investigation and refinement of the methodology to classify and verify isoform sub-clusters is needed, particularly to extend the technique to more distantly related species. © 2010 Jia et al; licensee BioMed Central Ltd.
DescriptionProceedings of the Asia Pacific Bioinformatics Network (APBioNet) Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology, Tokyo, Japan, 26-28 September 2010
Persistent Identifierhttp://hdl.handle.net/10722/140793
ISSN
2013 Impact Factor: 4.041
2013 SCImago Journal Rankings: 2.139
PubMed Central ID
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorJia, Yen_HK
dc.contributor.authorWong, TKFen_HK
dc.contributor.authorSong, YQen_HK
dc.contributor.authorYiu, SMen_HK
dc.contributor.authorSmith, DKen_HK
dc.date.accessioned2011-09-23T06:19:26Z-
dc.date.available2011-09-23T06:19:26Z-
dc.date.issued2010en_HK
dc.identifier.citationBmc Genomics, 2010, v. 11 SUPPL. 4en_HK
dc.identifier.issn1471-2164en_HK
dc.identifier.urihttp://hdl.handle.net/10722/140793-
dc.descriptionProceedings of the Asia Pacific Bioinformatics Network (APBioNet) Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology, Tokyo, Japan, 26-28 September 2010-
dc.descriptionThis article is part of the supplement: Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology-
dc.description.abstractBackground: Orthologues are genes in different species that are related through divergent evolution from a common ancestor and are expected to have similar functions. Many databases have been created to describe orthologous genes based on existing sequence data. However, alternative splicing (in eukaryotes) is usually disregarded in the determination of orthologue groups and the functional consequences of alternative splicing have not been considered. Most multi-exon genes can encode multiple protein isoforms which often have different functions and can be disease-related. Extending the definition of orthologue groups to take account of alternate splicing and the functional differences it causes requires further examination.Results: A subset of the orthologous gene groups between human and mouse was selected from the InParanoid database for this study. Each orthologue group was divided into sub-clusters, at the transcript level, using a method based on the sequence similarity of the isoforms. Transcript based sub-clusters were verified by functional signatures of the cluster members in the InterPro database. Functional similarity was higher within than between transcript-based sub-clusters of a defined orthologous group. In certain cases, cancer-related isoforms of a gene could be distinguished from other isoforms of the gene. Predictions of intrinsic disorder in protein regions were also correlated with the isoform sub-clusters within an orthologue group.Conclusions: Sub-clustering of orthologue groups at the transcript level is an important step to more accurately define functionally equivalent orthologue groups. This work appears to be the first effort to refine orthologous groupings of genes based on the consequences of alternative splicing on function. Further investigation and refinement of the methodology to classify and verify isoform sub-clusters is needed, particularly to extend the technique to more distantly related species. © 2010 Jia et al; licensee BioMed Central Ltd.en_HK
dc.languageengen_US
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/en_HK
dc.relation.ispartofBMC Genomicsen_HK
dc.rightsBMC Genomics. Copyright © BioMed Central Ltd.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleRefining orthologue groups at the transcript levelen_HK
dc.typeArticleen_HK
dc.identifier.emailSong, YQ:songy@hkucc.hku.hken_HK
dc.identifier.emailYiu, SM:smyiu@cs.hku.hken_HK
dc.identifier.authoritySong, YQ=rp00488en_HK
dc.identifier.authorityYiu, SM=rp00207en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/1471-2164-11-S4-S11en_HK
dc.identifier.pmid21143794-
dc.identifier.pmcidPMC3005912-
dc.identifier.scopuseid_2-s2.0-78649766484en_HK
dc.identifier.hkuros192231en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78649766484&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.issueSUPPL. 4en_HK
dc.identifier.spageS11en_US
dc.identifier.epageS11en_US
dc.identifier.isiWOS:000289200700011-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridJia, Y=36660934900en_HK
dc.identifier.scopusauthoridWong, TKF=25423289800en_HK
dc.identifier.scopusauthoridSong, YQ=7404921212en_HK
dc.identifier.scopusauthoridYiu, SM=7003282240en_HK
dc.identifier.scopusauthoridSmith, DK=36464390700en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats