title: Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism.
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 ∼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.
authors: Department of Computer Science, University of Illinois, Urbana, IL 61801, USA.
authors: Charles
authors: C
authors: Blatti
authors: National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
authors: Majid
authors: M
authors: Kazemian
authors: Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA.
authors: Scot
authors: S
authors: Wolfe
authors: Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA.
authors: Michael
authors: M
authors: Brodsky
authors: Department of Computer Science, University of Illinois, Urbana, IL 61801, USA Institute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA sinhas@illinois.edu.
authors: Saurabh
authors: S
authors: Sinha
mesh_terms: D000818:Animals; D004247:DNA / Q000737:chemistry / Q000378:metabolism; D004331:Drosophila melanogaster / Q000196:embryology / Q000235:genetics / Q000378:metabolism; D004742:Enhancer Elements, Genetic; D053263:Gene Regulatory Networks; D059372:Nucleotide Motifs; D050436:Regulatory Elements, Transcriptional; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA