Article: Refining orthologue groups at the transcript level
| Title | Refining orthologue groups at the transcript level |
|---|---|
| Authors | Jia, Y1 Wong, TKF1 Song, YQ1 Yiu, SM1 Smith, DK1 |
| Issue Date | 2010 |
| Publisher | BioMed 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?] DOI: http://dx.doi.org/10.1186/1471-2164-11-S4-S11 |
| 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. |
| Description | Proceedings 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 |
| ISSN | 1471-2164 2011 Impact Factor: 4.073 2011 SCImago Journal Rankings: 0.533 |
| DOI | http://dx.doi.org/10.1186/1471-2164-11-S4-S11 |
| ISI Accession Number ID | WOS:000289200700011 |
| PubMed Central ID | PMC3005912 |
| References | References in Scopus |
| dc.contributor.author | Jia, Y |
|---|---|
| dc.contributor.author | Wong, TKF |
| dc.contributor.author | Song, YQ |
| dc.contributor.author | Yiu, SM |
| dc.contributor.author | Smith, DK |
| dc.date.accessioned | 2011-09-23T06:19:26Z |
| dc.date.available | 2011-09-23T06:19:26Z |
| dc.date.issued | 2010 |
| dc.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. © 2010 Jia et al; licensee BioMed Central Ltd. |
| dc.description.nature | published_or_final_version |
| dc.description | Proceedings of the Asia Pacific Bioinformatics Network (APBioNet) Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology, Tokyo, Japan, 26-28 September 2010 |
| dc.description | This article is part of the supplement: Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology |
| dc.identifier.citation | Bmc Genomics, 2010, v. 11 SUPPL. 4 [How to Cite?] DOI: http://dx.doi.org/10.1186/1471-2164-11-S4-S11 |
| dc.identifier.doi | http://dx.doi.org/10.1186/1471-2164-11-S4-S11 |
| dc.identifier.epage | S11 |
| dc.identifier.hkuros | 192231 |
| dc.identifier.isi | WOS:000289200700011 |
| dc.identifier.issn | 1471-2164 2011 Impact Factor: 4.073 2011 SCImago Journal Rankings: 0.533 |
| dc.identifier.issue | SUPPL. 4 |
| dc.identifier.pmcid | PMC3005912 |
| dc.identifier.pmid | 21143794 |
| dc.identifier.scopus | eid_2-s2.0-78649766484 |
| dc.identifier.spage | S11 |
| dc.identifier.uri | http://hdl.handle.net/10722/140793 |
| dc.identifier.volume | 11 |
| dc.language | eng |
| dc.publisher | BioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/ |
| dc.publisher.place | United Kingdom |
| dc.relation.ispartof | BMC Genomics |
| dc.relation.references | References in Scopus |
| dc.rights | BMC Genomics. Copyright © BioMed Central Ltd. |
| dc.rights | Creative Commons: Attribution 3.0 Hong Kong License |
| dc.title | Refining orthologue groups at the transcript level |
| dc.type | Article |
Author Affiliations
- The University of Hong Kong