Circuitry and Dynamics of Human Transcription Factor Regulatory Networks
Open accessAbstract
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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Genome-wide measurements of chromatin accessibility locate REs, enabling TF-RE connections by motif matching and connecting REs to nearby TGs.
“Genome-wide measurements of chromatin accessibility, such as DNase-seq17 and assay for transposase-accessible chromatin sequencing (ATAC-seq)18, locate REs, enabling TF–RE connections by motif matching and connecting REs to their nearby TGs19.”
From Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data (2025) · cites this paper as [19]
The Experimental Procedures (Regulatory network construction; page unavailable) describe matching TF motifs to DNaseI footprints and linking those footprints to genes whose transcription start sites are within 5,000 nucleotides. This supports the proposed connection method, but the study constructed networks for TF genes specifically, not target genes generally; the Discussion also cautions that proximity does not reliably assign distal regulatory elements to their target genes. (LLM, conf=0.85)
Experimental — accuracy not yet measuredIntegration of open chromatin data with RNA-seq has mostly been limited to verifying the expression status of genes that overlap a region of interest.
“Integration of open chromatin data such as that from FAIRE-seq and DNase-seq with RNA-seq has mostly been limited to verifying the expression status of genes that overlap a region of interest [150].”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [150]
DNase-seq can be used for genome-wide footprinting of DNA-binding factors, and this in combination with the actual expression of genes can be used to infer active transcriptional networks.
“DNase-seq can be used for genome-wide footprinting of DNA-binding factors, and this in combination with the actual expression of genes can be used to infer active transcriptional networks [150].”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [150]
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- Authors
- Neph, S., Stergachis, A. B., Reynolds, A., Sandstrom, R., Borenstein, E., & Stamatoyannopoulos, J. A.
- Affiliations
- University of Washington (US)
- Santa Fe Institute (US)
- Corresponding author
- Borenstein, Elhanan
- Stamatoyannopoulos, John A.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-09
- Volume
- 150
- Issue
- 6
- Pages
- 1274-1286
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3679407
- OpenAlex
- W2110503722
- Cited by
- 467
- References
- 75
- Citations by year
- 2026: 8 · 2025: 15 · 2024: 20 · 2023: 41 · 2022: 22 · 2021: 27 · 2020: 46 · 2019: 38 · 2018: 39 · 2017: 34 · 2016: 47 · 2015: 49 · 2014: 37 · 2013: 42 · 2012: 1
- FWCI
- 16.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 380 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- U.S. Public Health Service (F30 FDK095678A)
- National Human Genome Research Institute (U54HG004592, HG004592)
- National Institute of Diabetes and Digestive and Kidney Diseases (F30DK095678)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- transcriptional regulatory networks, sequence-specific transcription factors, cell type specificity, cell identity, network topology, transcriptional regulation, human cell types
- MeSH terms
- Animals, Deoxyribonuclease I, Gene Expression Regulation, Humans, Organ Specificity, Transcription Factors, DNA Footprinting, Gene Regulatory Networks, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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