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Cited by 130Genomics and Chromatin DynamicsChromatin Remodeling and CancerGene Regulatory Network Analysis

Large-scale mapping and mutagenesis of human transcriptional effector domains

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DelRosso, Nicole, Tycko, Josh, Suzuki, Peter, Andrews, Cecelia, Aradhana, Mukund, Adi, Liongson, Ivan, Ludwig, Connor +4 more·2023·Nature
DOI 10.1038/s41586-023-05906-yPMC PMC10484233
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Abstract

Human gene expression is regulated by more than 2,000 transcription factors and chromatin regulators 1,2. Effector domains within these proteins can activate or repress transcription. However, for many of these regulators we do not know what type of effector domains they contain, their location in the protein, their activation and repression strengths, and the sequences that are necessary for their functions. Here, we systematically measure the effector activity of more than 100,000 protein fragments tiling across most chromatin regulators and transcription factors in human cells (2,047 proteins). By testing the effect they have when recruited at reporter genes, we annotate 374 activation domains and 715 repression domains, roughly 80% of which are new and have not been previously annotated 3-5. Rational mutagenesis and deletion scans across all the effector domains reveal aromatic and/or leucine residues interspersed with acidic, proline, serine and/or glutamine residues are necessary for activation domain activity. Furthermore, most repression domain sequences contain sites for small ubiquitin-like modifier (SUMO)ylation, short interaction motifs for recruiting corepressors or are structured binding domains for recruiting other repressive proteins. We discover bifunctional domains that can both activate and repress, some of which dynamically split a cell population into high- and low-expression subpopulations. Our systematic annotation and characterization of effector domains provide a rich resource for understanding the function of human transcription factors and chromatin regulators, engineering compact tools for controlling gene expression and refining predictive models of effector domain function.

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  • For Fli1-Spi1, structural models suggest that Fli1 binds an activation domain of Spi1.

    “In the case of Fli1-Spi1, these models rather suggest that Fli1 binds an activation domain49 of Spi1 (Figures 4F, S3H, and S3I).”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [49]

    The citation is attached to “activation domain” of Spi1; the structural-model inference appears to be the citing authors’ own. The source’s Activation domain sequence characteristics section discusses activation domains in other proteins, but searches for SPI1, FLI1, and PU.1 found no passage identifying an activation domain of Spi1. Our copy therefore cannot verify the part attributed to this source. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

  • 33/38 factors included in this study contained repressor domains.

    “This model is also supported by the observation that 33/38 factors included in this study contained repressor domains49 and by recent data demonstrating that different co-factors of the same TF modulate different steps in a transcriptional cycle.55”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [49]

    The paper reports 715 repression domains across a survey of 2,047 proteins (Abstract), but our copy does not identify the 38 factors in the citing study or say that 33 of them contain repressor domains. Searches for “33/38” and “38 factors” found no passage establishing that count. (LLM, conf=0.75)

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Authors
DelRosso, N., Tycko, J., Suzuki, P., Andrews, C., Aradhana, Mukund, A., Liongson, I., Ludwig, C., Spees, K., Fordyce, P., Bassik, M. C., & Bintu, L.
Affiliations
  • Stanford University (US)
  • Chan Zuckerberg Biohub San Francisco (US)
Corresponding author
Bintu, Lacramioara
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2023-04-05
Volume
616
Issue
7956
Pages
365-372
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-023-05906-y
PMC
PMC10484233
OpenAlex
W4362607738
Cited by
130
References
5
Citations by year
2026: 36 · 2025: 38 · 2024: 39 · 2023: 16 · 2022: 1
FWCI
11.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Science Foundation (2142336, DGE-165651 8, 1656518, 1DP2HD08406901, CAREER)
  • National Institutes of Health (R35M128947, DGE-1656518, 1dp2hd084069-01, F99/K00)
  • Stanford Bio-X
  • National Human Genome Research Institute (R01HG011866)
  • National Institute of General Medical Sciences (R35M128947, T32GM007365, R35GM128947, T32GM141828)
  • National Institute of Diabetes and Digestive and Kidney Diseases (F99DK126120, F99/K00, K00DK126120)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (1DP2HD08406901)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
transactivation domain, repression domain, chromatin regulators, transcription factors, domain mapping, mutagenesis, SUMOylation, gene expression regulation
MeSH terms
Protein Domains, Chromatin, Gene Expression Regulation, Humans, Repressor Proteins, Transcription Factors, Transcription, Genetic, Mutagenesis, Genes, Reporter, Sumoylation

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