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Article: Refining orthologue groups at the transcript level
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TitleRefining orthologue groups at the transcript level
 
AuthorsJia, Y1
Wong, TKF1
Song, YQ1
Yiu, SM1
Smith, DK1
 
Issue Date2010
 
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/
 
CitationBmc Genomics, 2010, v. 11 SUPPL. 4 [How to Cite?]
DOI: http://dx.doi.org/10.1186/1471-2164-11-S4-S11
 
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.
 
DescriptionProceedings of the Asia Pacific Bioinformatics Network (APBioNet) Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology, Tokyo, Japan, 26-28 September 2010
This article is part of the supplement: Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology
 
ISSN1471-2164
2012 Impact Factor: 4.397
2012 SCImago Journal Rankings: 1.772
 
DOIhttp://dx.doi.org/10.1186/1471-2164-11-S4-S11
 
PubMed Central IDPMC3005912
 
ISI Accession Number IDWOS:000289200700011
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorJia, Y
 
dc.contributor.authorWong, TKF
 
dc.contributor.authorSong, YQ
 
dc.contributor.authorYiu, SM
 
dc.contributor.authorSmith, DK
 
dc.date.accessioned2011-09-23T06:19:26Z
 
dc.date.available2011-09-23T06:19:26Z
 
dc.date.issued2010
 
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.
 
dc.description.naturepublished_or_final_version
 
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.identifier.citationBmc Genomics, 2010, v. 11 SUPPL. 4 [How to Cite?]
DOI: http://dx.doi.org/10.1186/1471-2164-11-S4-S11
 
dc.identifier.doihttp://dx.doi.org/10.1186/1471-2164-11-S4-S11
 
dc.identifier.epageS11
 
dc.identifier.hkuros192231
 
dc.identifier.isiWOS:000289200700011
 
dc.identifier.issn1471-2164
2012 Impact Factor: 4.397
2012 SCImago Journal Rankings: 1.772
 
dc.identifier.issueSUPPL. 4
 
dc.identifier.pmcidPMC3005912
 
dc.identifier.pmid21143794
 
dc.identifier.scopuseid_2-s2.0-78649766484
 
dc.identifier.spageS11
 
dc.identifier.urihttp://hdl.handle.net/10722/140793
 
dc.identifier.volume11
 
dc.languageeng
 
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/
 
dc.publisher.placeUnited Kingdom
 
dc.relation.ispartofBMC Genomics
 
dc.relation.referencesReferences in Scopus
 
dc.rightsBMC Genomics. Copyright © BioMed Central Ltd.
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.titleRefining orthologue groups at the transcript level
 
dc.typeArticle
 
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<description.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. &#169; 2010 Jia et al; licensee BioMed Central Ltd.</description.abstract>
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Author Affiliations
  1. The University of Hong Kong