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Cited by 283Genomics and Chromatin DynamicsGene Regulatory Network AnalysisFungal and yeast genetics research

Deciphering eukaryotic gene-regulatory logic with 100 million random promoters

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de Boer, Carl G., Vaishnav, Eeshit Dhaval, Sadeh, Ronen, Abeyta, Esteban Luis, Friedman, Nir, Regev, Aviv·2020·Nature Biotechnology
DOI 10.1038/s41587-019-0315-8PMC PMC6954276

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Abstract

How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene expression remains unclear, largely because past studies using native and engineered sequences had insufficient scale. Here, we measure the expression output of >100 million synthetic yeast promoter sequences that are fully random. These sequences yield diverse, reproducible expression levels that can be explained by their chance inclusion of functional TF binding sites. We use machine learning to build interpretable models of transcriptional regulation that predict ~94% of the expression driven from independent test promoters and ~89% of the expression driven from native yeast promoter fragments. These models allow us to characterize each TF's specificity, activity and interactions with chromatin. TF activity depends on binding-site strand, position, DNA helical face and chromatin context. Notably, expression level is influenced by weak regulatory interactions, which confound designed-sequence studies. Our analyses show that massive-throughput assays of fully random DNA can provide the big data necessary to develop complex, predictive models of gene regulation.

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  • The bottom-up synthetic approach can provide data of sufficient statistical power to characterize combinatorial action of TFBSs, as demonstrated by recent studies that have profiled tens of thousands to millions of synthetic or even random DNA sequences in cell lines or yeast.

    “and it can provide data of sufficient statistical power to characterize combinatorial action of TFBSs, as demonstrated by recent studies that have profiled tens of thousands to millions of synthetic or even random DNA sequences in cell lines or yeast.33,35,36”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [35]

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Cited by

Sorted by citations

Authors
de Boer, C. G., Vaishnav, E. D., Sadeh, R., Abeyta, E. L., Friedman, N., & Regev, A.
Affiliations
  • Broad Institute (US)
  • Hebrew University of Jerusalem (IL)
  • University of New Mexico (US)
Corresponding author
Regev, Aviv
ORCID
Venue
Nature Biotechnology
Publisher
Springer Science and Business Media LLC
Published
2019-12-02
Volume
38
Issue
1
Pages
56-65
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
DOI
10.1038/s41587-019-0315-8
PMC
PMC6954276
OpenAlex
W2990395719
Cited by
283
References
6
Citations by year
2026: 39 · 2025: 44 · 2024: 48 · 2023: 48 · 2022: 40 · 2021: 31 · 2020: 29 · 2019: 4
FWCI
8.53
Type
journal article
Language
en
Update notices
correction (2020-08-13)
Open access
Licence
Locations
  • Nature Biotechnology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Funders
  • U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (K99-HG009920-01, CEGS)
  • Massachusetts Institute of Technology (Presidential Fellowship)
  • Israel Science Foundation (ICORE)
  • Howard Hughes Medical Institute
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 › Fungal and yeast genetics research
Keywords
transcription factor binding sites, cis-regulatory elements, transcriptional regulation, transcription factor specificity, chromatin context, regulatory interactions, gene expression prediction
MeSH terms
Binding Sites, DNA, Gene Expression Regulation, Logic, Models, Genetic, Promoter Regions, Genetic, Saccharomyces cerevisiae, Transcription Factors, Genes, Reporter, Eukaryota

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