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- Publisher Website: 10.1093/bioinformatics/btr503
- Scopus: eid_2-s2.0-80054901781
- PMID: 21896508
- WOS: WOS:000296099300007
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Article: Correlated evolution of transcription factors and their binding sites
Title | Correlated evolution of transcription factors and their binding sites | ||||||||
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Authors | |||||||||
Issue Date | 2011 | ||||||||
Publisher | Oxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/ | ||||||||
Citation | Bioinformatics, 2011, v. 27 n. 21, p. 2972-2978 How to Cite? | ||||||||
Abstract | MOTIVATION: The interaction between transcription factor (TF) and transcription factor binding site (TFBS) is essential for gene regulation. Mutation in either the TF or the TFBS may weaken their interaction and thus result in abnormalities. To maintain such vital interaction, a mutation in one of the interacting partners might be compensated by a corresponding mutation in its binding partner during the course of evolution. Confirming this co-evolutionary relationship will guide us in designing protein sequences to target a specific DNA sequence or in predicting TFBS for poorly studied proteins, or even correcting and rescuing disease mutations in clinical applications. RESULTS: Based on six, publicly available, experimentally validated TF-TFBS binding datasets for the basic Helix-Loop-Helix (bHLH) family, Homeo family, High-Mobility Group (HMG) family and Transient Receptor Potential channels (TRP) family, we showed that the evolutions of the TFs and their TFBSs are significantly correlated across eukaryotes. We further developed a mutual information-based method to identify co-evolved protein residues and DNA bases. This research sheds light on the dynamic relationship between TF and TFBS during their evolution. The same principle and strategy can be applied to co-evolutionary studies on protein-DNA interactions in other protein families. AVAILABILITY: All the datasets, scripts and other related files have been made freely available at: http://jjwanglab.org/co-evo. CONTACT: junwen@uw.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. | ||||||||
Persistent Identifier | http://hdl.handle.net/10722/147648 | ||||||||
ISSN | 2023 Impact Factor: 4.4 2023 SCImago Journal Rankings: 2.574 | ||||||||
ISI Accession Number ID |
Funding Information: The Research Grants Council of Hong Kong (781511M, 778609M, N_HKU752/ 10, AoE M-04/04); Food and Health Bureau of Hong Kong (10091262); the National Science Foundation of China (31061160497). | ||||||||
References | |||||||||
Grants |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, S | en_HK |
dc.contributor.author | Yalamanchili, HK | en_HK |
dc.contributor.author | Li, X | en_HK |
dc.contributor.author | Yao, KM | en_HK |
dc.contributor.author | Sham, PC | en_HK |
dc.contributor.author | Zhang, MQ | en_HK |
dc.contributor.author | Wang, J | en_HK |
dc.date.accessioned | 2012-05-29T06:05:12Z | - |
dc.date.available | 2012-05-29T06:05:12Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Bioinformatics, 2011, v. 27 n. 21, p. 2972-2978 | en_HK |
dc.identifier.issn | 1367-4803 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/147648 | - |
dc.description.abstract | MOTIVATION: The interaction between transcription factor (TF) and transcription factor binding site (TFBS) is essential for gene regulation. Mutation in either the TF or the TFBS may weaken their interaction and thus result in abnormalities. To maintain such vital interaction, a mutation in one of the interacting partners might be compensated by a corresponding mutation in its binding partner during the course of evolution. Confirming this co-evolutionary relationship will guide us in designing protein sequences to target a specific DNA sequence or in predicting TFBS for poorly studied proteins, or even correcting and rescuing disease mutations in clinical applications. RESULTS: Based on six, publicly available, experimentally validated TF-TFBS binding datasets for the basic Helix-Loop-Helix (bHLH) family, Homeo family, High-Mobility Group (HMG) family and Transient Receptor Potential channels (TRP) family, we showed that the evolutions of the TFs and their TFBSs are significantly correlated across eukaryotes. We further developed a mutual information-based method to identify co-evolved protein residues and DNA bases. This research sheds light on the dynamic relationship between TF and TFBS during their evolution. The same principle and strategy can be applied to co-evolutionary studies on protein-DNA interactions in other protein families. AVAILABILITY: All the datasets, scripts and other related files have been made freely available at: http://jjwanglab.org/co-evo. CONTACT: junwen@uw.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. | en_HK |
dc.language | eng | en_US |
dc.publisher | Oxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/ | en_HK |
dc.relation.ispartof | Bioinformatics | en_HK |
dc.subject.mesh | Base Sequence | - |
dc.subject.mesh | DNA - chemistry - metabolism | - |
dc.subject.mesh | Evolution, Molecular | - |
dc.subject.mesh | Regulatory Elements, Transcriptional | - |
dc.subject.mesh | Transcription Factors - chemistry - genetics - metabolism | - |
dc.title | Correlated evolution of transcription factors and their binding sites | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Yao, KM: kmyao@hku.hk | en_HK |
dc.identifier.email | Sham, PC: pcsham@hku.hk | en_HK |
dc.identifier.email | Wang, J: junwen@hku.hk | en_HK |
dc.identifier.authority | Yao, KM=rp00344 | en_HK |
dc.identifier.authority | Sham, PC=rp00459 | en_HK |
dc.identifier.authority | Wang, J=rp00280 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1093/bioinformatics/btr503 | en_HK |
dc.identifier.pmid | 21896508 | - |
dc.identifier.scopus | eid_2-s2.0-80054901781 | en_HK |
dc.identifier.hkuros | 208293 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-80054901781&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 27 | en_HK |
dc.identifier.issue | 21 | en_HK |
dc.identifier.spage | 2972 | en_HK |
dc.identifier.epage | 2978 | en_HK |
dc.identifier.eissn | 1460-2059 | - |
dc.identifier.isi | WOS:000296099300007 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.relation.project | A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus | - |
dc.identifier.scopusauthorid | Wang, J=8950599500 | en_HK |
dc.identifier.scopusauthorid | Zhang, MQ=7601558554 | en_HK |
dc.identifier.scopusauthorid | Sham, PC=34573429300 | en_HK |
dc.identifier.scopusauthorid | Yao, KM=7403234578 | en_HK |
dc.identifier.scopusauthorid | Li, X=53877702500 | en_HK |
dc.identifier.scopusauthorid | Yalamanchili, HK=35182263500 | en_HK |
dc.identifier.scopusauthorid | Yang, S=53878833500 | en_HK |
dc.identifier.citeulike | 9757170 | - |