Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization.
Transcription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Exis...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2018-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC6049898?pdf=render |
| _version_ | 1818924963762012160 |
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| author | Vishaka Datta Rahul Siddharthan Sandeep Krishna |
| author_facet | Vishaka Datta Rahul Siddharthan Sandeep Krishna |
| author_sort | Vishaka Datta |
| collection | DOAJ |
| description | Transcription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Existing methods to detect cooperative binding of a TF pair rely on analyzing the sequence that is bound. We propose a method that uses, instead, only ChIP-seq peak intensities and an expectation maximization (CPI-EM) algorithm. We validate our method using ChIP-seq data from cells where one of a pair of TFs under consideration has been genetically knocked out. Our algorithm relies on our observation that cooperative TF-TF binding is correlated with weak binding of one of the TFs, which we demonstrate in a variety of cell types, including E. coli, S. cerevisiae and M. musculus cells. We show that this method performs significantly better than a predictor based only on the ChIP-seq peak distance of the TFs under consideration. This suggests that peak intensities contain information that can help detect the cooperative binding of a TF pair. CPI-EM also outperforms an existing sequence-based algorithm in detecting cooperative binding. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em. |
| first_indexed | 2024-12-20T02:33:41Z |
| format | Article |
| id | doaj.art-ba9e3b592a5e4ab2b6983b5458361418 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T02:33:41Z |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-ba9e3b592a5e4ab2b6983b54583614182022-12-21T19:56:30ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01137e019977110.1371/journal.pone.0199771Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization.Vishaka DattaRahul SiddharthanSandeep KrishnaTranscription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Existing methods to detect cooperative binding of a TF pair rely on analyzing the sequence that is bound. We propose a method that uses, instead, only ChIP-seq peak intensities and an expectation maximization (CPI-EM) algorithm. We validate our method using ChIP-seq data from cells where one of a pair of TFs under consideration has been genetically knocked out. Our algorithm relies on our observation that cooperative TF-TF binding is correlated with weak binding of one of the TFs, which we demonstrate in a variety of cell types, including E. coli, S. cerevisiae and M. musculus cells. We show that this method performs significantly better than a predictor based only on the ChIP-seq peak distance of the TFs under consideration. This suggests that peak intensities contain information that can help detect the cooperative binding of a TF pair. CPI-EM also outperforms an existing sequence-based algorithm in detecting cooperative binding. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em.http://europepmc.org/articles/PMC6049898?pdf=render |
| spellingShingle | Vishaka Datta Rahul Siddharthan Sandeep Krishna Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. PLoS ONE |
| title | Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. |
| title_full | Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. |
| title_fullStr | Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. |
| title_full_unstemmed | Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. |
| title_short | Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization. |
| title_sort | detection of cooperatively bound transcription factor pairs using chip seq peak intensities and expectation maximization |
| url | http://europepmc.org/articles/PMC6049898?pdf=render |
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