Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding
Background The combinatorial binding of trans-acting factors (TFs) to the DNA is critical to the spatial and temporal specificity of gene regulation. For certain regulatory regions, more than one regulatory module (set of TFs that bind together) are combined to achieve context-specific gene regulat...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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BioMed Central
2017
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| Online Access: | http://hdl.handle.net/1721.1/106853 https://orcid.org/0000-0003-2357-1546 https://orcid.org/0000-0003-1709-4034 |
| _version_ | 1826200513294630912 |
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| author | Guo, Yuchun Gifford, David K |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Guo, Yuchun Gifford, David K |
| author_sort | Guo, Yuchun |
| collection | MIT |
| description | Background
The combinatorial binding of trans-acting factors (TFs) to the DNA is critical to the spatial and temporal specificity of gene regulation. For certain regulatory regions, more than one regulatory module (set of TFs that bind together) are combined to achieve context-specific gene regulation. However, previous approaches are limited to either pairwise TF co-association analysis or assuming that only one module is used in each regulatory region.
Results
We present a new computational approach that models the modular organization of TF combinatorial binding. Our method learns compact and coherent regulatory modules from in vivo binding data using a topic model. We found that the binding of 115 TFs in K562 cells can be organized into 49 interpretable modules. Furthermore, we found that tens of thousands of regulatory regions use multiple modules, a structure that cannot be observed with previous hard clustering based methods. The modules discovered recapitulate many published protein-protein physical interactions, have consistent functional annotations of chromatin states, and uncover context specific co-binding such as gene proximal binding of NFY + FOS + SP and distal binding of NFY + FOS + USF. For certain TFs, the co-binding partners of direct binding (motif present) differs from those of indirect binding (motif absent); the distinct set of co-binding partners can predict whether the TF binds directly or indirectly with up to 95% accuracy. Joint analysis across two cell types reveals both cell-type-specific and shared regulatory modules.
Conclusions
Our results provide comprehensive cell-type-specific combinatorial binding maps and suggest a modular organization of combinatorial binding.
Keywords
Computational genomics Transcription factor Combinatorial binding Direct and indirect binding Topic model |
| first_indexed | 2024-09-23T11:37:38Z |
| format | Article |
| id | mit-1721.1/106853 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:37:38Z |
| publishDate | 2017 |
| publisher | BioMed Central |
| record_format | dspace |
| spelling | mit-1721.1/1068532022-09-27T20:50:54Z Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding Guo, Yuchun Gifford, David K Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Guo, Yuchun Gifford, David K Background The combinatorial binding of trans-acting factors (TFs) to the DNA is critical to the spatial and temporal specificity of gene regulation. For certain regulatory regions, more than one regulatory module (set of TFs that bind together) are combined to achieve context-specific gene regulation. However, previous approaches are limited to either pairwise TF co-association analysis or assuming that only one module is used in each regulatory region. Results We present a new computational approach that models the modular organization of TF combinatorial binding. Our method learns compact and coherent regulatory modules from in vivo binding data using a topic model. We found that the binding of 115 TFs in K562 cells can be organized into 49 interpretable modules. Furthermore, we found that tens of thousands of regulatory regions use multiple modules, a structure that cannot be observed with previous hard clustering based methods. The modules discovered recapitulate many published protein-protein physical interactions, have consistent functional annotations of chromatin states, and uncover context specific co-binding such as gene proximal binding of NFY + FOS + SP and distal binding of NFY + FOS + USF. For certain TFs, the co-binding partners of direct binding (motif present) differs from those of indirect binding (motif absent); the distinct set of co-binding partners can predict whether the TF binds directly or indirectly with up to 95% accuracy. Joint analysis across two cell types reveals both cell-type-specific and shared regulatory modules. Conclusions Our results provide comprehensive cell-type-specific combinatorial binding maps and suggest a modular organization of combinatorial binding. Keywords Computational genomics Transcription factor Combinatorial binding Direct and indirect binding Topic model National Institutes of Health (U.S.) (grant 1U01HG007037-01) 2017-02-03T18:01:26Z 2017-02-03T18:01:26Z 2017-01 2016-04 2017-01-07T04:40:17Z Article http://purl.org/eprint/type/JournalArticle 1471-2164 http://hdl.handle.net/1721.1/106853 Guo, Yuchun, and David K. Gifford. “Modular Combinatorial Binding among Human Trans-Acting Factors Reveals Direct and Indirect Factor Binding.” BMC Genomics 18.1 (2017): n. pag. https://orcid.org/0000-0003-2357-1546 https://orcid.org/0000-0003-1709-4034 en http://dx.doi.org/10.1186/s12864-016-3434-3 BMC Genomics Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ The Author(s). application/pdf BioMed Central BioMed Central |
| spellingShingle | Guo, Yuchun Gifford, David K Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title | Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title_full | Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title_fullStr | Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title_full_unstemmed | Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title_short | Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding |
| title_sort | modular combinatorial binding among human trans acting factors reveals direct and indirect factor binding |
| url | http://hdl.handle.net/1721.1/106853 https://orcid.org/0000-0003-2357-1546 https://orcid.org/0000-0003-1709-4034 |
| work_keys_str_mv | AT guoyuchun modularcombinatorialbindingamonghumantransactingfactorsrevealsdirectandindirectfactorbinding AT gifforddavidk modularcombinatorialbindingamonghumantransactingfactorsrevealsdirectandindirectfactorbinding |