UMMS Affiliation
Department of Molecular, Cell and Cancer Biology
Publication Date
4-30-2015
Document Type
Article
Disciplines
Cell Biology | Computational Biology | Molecular Biology | Molecular Genetics
Abstract
Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF-DNA binding specificities ('motifs'). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF-DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of approximately 200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays. Acids Research.
Rights and Permissions
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI of Published Version
10.1093/nar/gkv195
Source
Blatti C, Kazemian M, Wolfe S, Brodsky M, Sinha S. Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism. Nucleic Acids Res. 2015 Apr 30;43(8):3998-4012. doi: 10.1093/nar/gkv195. Epub 2015 Mar 19. PubMed PMID: 25791631. Link to article on publisher's site
Journal/Book/Conference Title
Nucleic acids research
Related Resources
PubMed ID
25791631
Repository Citation
Blatti, Charles; Kazemian, Majid; Wolfe, Scot A.; Brodsky, Michael H.; and Sinha, Saurabh, "Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism" (2015). Molecular, Cell and Cancer Biology Publications. 8.
https://escholarship.umassmed.edu/mccb_pubs/8
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Cell Biology Commons, Computational Biology Commons, Molecular Biology Commons, Molecular Genetics Commons