Article

Circuitry and Dynamics of Human Transcription Factor Regulatory Networks

Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Cell (Impact Factor: 33.12). 09/2012; 150(6):1274-86. DOI: 10.1016/j.cell.2012.04.040
Source: PubMed

ABSTRACT The combinatorial cross-regulation of hundreds of sequence-specific transcription factors (TFs) defines a regulatory network that underlies cellular identity and function. Here we use genome-wide maps of in vivo DNaseI footprints to assemble an extensive core human regulatory network comprising connections among 475 sequence-specific TFs and to analyze the dynamics of these connections across 41 diverse cell and tissue types. We find that human TF networks are highly cell selective and are driven by cohorts of factors that include regulators with previously unrecognized roles in control of cellular identity. Moreover, we identify many widely expressed factors that impact transcriptional regulatory networks in a cell-selective manner. Strikingly, in spite of their inherent diversity, all cell-type regulatory networks independently converge on a common architecture that closely resembles the topology of living neuronal networks. Together, our results provide an extensive description of the circuitry, dynamics, and organizing principles of the human TF regulatory network.

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Available from: Alex Reynolds, Dec 18, 2013
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    • "DGF was originally applied to the yeast genome, which allows a more accurate cleavage profile because of its small genome size (Hesselberth et al., 2009; Chen et al., 2010). Subsequently, computational detection of footprint candidates has been performed on the mitochondrial genome and the entire human genome (Mercer et al., 2011; Neph et al., 2012a, 2012b; Piper et al., 2013). However, the algorithms used in previous studies are either inefficient for mammalian genomes , or not publicly available, leaving the general community without proper computational tools. "
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    ABSTRACT: Genomic footprinting has emerged as an unbiased discovery method for transcription factor (TF) occupancy at cognate DNA in vivo. A basic premise of footprinting is that sequence-specific TF-DNA interactions are associated with localized resistance to nucleases, leaving observable signatures of cleavage within accessible chromatin. This phenomenon is interpreted to imply protection of the critical nucleotides by the stably bound protein factor. However, this model conflicts with previous reports of many TFs exchanging with specific binding sites in living cells on a timescale of seconds. We show that TFs with short DNA residence times have no footprints at bound motif elements. Moreover, the nuclease cleavage profile within a footprint originates from the DNA sequence in the factor-binding site, rather than from the protein occupying specific nucleotides. These findings suggest a revised understanding of TF footprinting and reveal limitations in comprehensive reconstruction of the TF regulatory network using this approach.
    Molecular Cell 10/2014; 56(2):275-285. DOI:10.1016/j.molcel.2014.08.016
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    • "The DNase I footprints data of 475 human TFs were extracted from the work of Neph, Stergachis, et al. (2012). This data set includes 225,625 combinations of TF-TF regulatory interactions within promoter-proximal regions among 475 human TFs across 41 different cell and tissue types, including epithelial cells, endothelial cells, blood cells, cancer cells, fetal cells, and embryonic stem cells (Neph, Stergachis, et al. 2012). "
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    Molecular Biology and Evolution 08/2014; 31(8):2149-2155. DOI:10.1093/molbev/msu163
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    • "Regulator-gene interactions can be summed up into a transcriptional regulatory network [15]. Given various experimental limitations, up till date, only a handful of transcriptional regulatory networks for complex biological systems have been defined [16]. Graph theoretic approaches offer insight into the structure of these networks and allow us to single out properties of a network, or its parts, which are different from expected by random. "
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