Computational modeling of chromatin accessibility identified important epigenomic regulators
Abstract Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-01-01
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| Series: | BMC Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12864-021-08234-5 |
| _version_ | 1818979353634013184 |
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| author | Yanding Zhao Yadong Dong Wei Hong Chongming Jiang Kevin Yao Chao Cheng |
| author_facet | Yanding Zhao Yadong Dong Wei Hong Chongming Jiang Kevin Yao Chao Cheng |
| author_sort | Yanding Zhao |
| collection | DOAJ |
| description | Abstract Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy. |
| first_indexed | 2024-12-20T16:58:11Z |
| format | Article |
| id | doaj.art-71beec6330d24f74bced0c7a522b5bdb |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-12-20T16:58:11Z |
| publishDate | 2022-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genomics |
| spelling | doaj.art-71beec6330d24f74bced0c7a522b5bdb2022-12-21T19:32:39ZengBMCBMC Genomics1471-21642022-01-0123111610.1186/s12864-021-08234-5Computational modeling of chromatin accessibility identified important epigenomic regulatorsYanding Zhao0Yadong Dong1Wei Hong2Chongming Jiang3Kevin Yao4Chao Cheng5Department of Medicine, Baylor College of MedicineDepartment of Medicine, Baylor College of MedicineDepartment of Medicine, Baylor College of MedicineDepartment of Medicine, Baylor College of MedicineDepartment of Electrical and Computer Engineering, Texas A&M UniversityDepartment of Medicine, Baylor College of MedicineAbstract Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy.https://doi.org/10.1186/s12864-021-08234-5ENCODEChromatin accessibilityHistone modificationsTranscription factorMachine learning |
| spellingShingle | Yanding Zhao Yadong Dong Wei Hong Chongming Jiang Kevin Yao Chao Cheng Computational modeling of chromatin accessibility identified important epigenomic regulators BMC Genomics ENCODE Chromatin accessibility Histone modifications Transcription factor Machine learning |
| title | Computational modeling of chromatin accessibility identified important epigenomic regulators |
| title_full | Computational modeling of chromatin accessibility identified important epigenomic regulators |
| title_fullStr | Computational modeling of chromatin accessibility identified important epigenomic regulators |
| title_full_unstemmed | Computational modeling of chromatin accessibility identified important epigenomic regulators |
| title_short | Computational modeling of chromatin accessibility identified important epigenomic regulators |
| title_sort | computational modeling of chromatin accessibility identified important epigenomic regulators |
| topic | ENCODE Chromatin accessibility Histone modifications Transcription factor Machine learning |
| url | https://doi.org/10.1186/s12864-021-08234-5 |
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