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Cited by 198Genomics and Chromatin DynamicsGene Regulatory Network AnalysisChromatin Remodeling and Cancer

Sequence determinants of human gene regulatory elements

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Sahu, Biswajyoti, Hartonen, Tuomo, Pihlajamaa, Päivi, Wei, Bei, Dave, Kashyap, Zhu, Fangjie, Kaasinen, Eevi, Lidschreiber, Katja +5 more·2022·Nature Genetics
DOI 10.1038/s41588-021-01009-4PMC PMC8920891

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Abstract

DNA can determine where and when genes are expressed, but the full set of sequence determinants that control gene expression is unknown. Here, we measured the transcriptional activity of DNA sequences that represent an ~100 times larger sequence space than the human genome using massively parallel reporter assays (MPRAs). Machine learning models revealed that transcription factors (TFs) generally act in an additive manner with weak grammar and that most enhancers increase expression from a promoter by a mechanism that does not appear to involve specific TF–TF interactions. The enhancers themselves can be classified into three types: classical, closed chromatin and chromatin dependent. We also show that few TFs are strongly active in a cell, with most activities being similar between cell types. Individual TFs can have multiple gene regulatory activities, including chromatin opening and enhancing, promoting and determining transcription start site (TSS) activity, consistent with the view that the TF binding motif is the key atomic unit of gene expression.

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  • Sahu and colleagues used STARR-seq to show that four out of the five MYC super-enhancer constituents have no detectable enhancer activity in HepG2 cells.

    “Sahu and colleagues recently used a STARR-seq method to show that four out of the five MYC SE constituents have no detectable enhancer activity in HepG2 cells.59”

    From Super-enhancers include classical enhancers and facilitators to fully activate gene expression (2023) · cites this paper as [59]

    The Results (Fig. 4b caption; page unavailable) show one STARR-seq peak at a MYC super-enhancer in HepG2 cells, alongside chromatin-dependent enhancers that the Results describe as poorly detected by STARR-seq. Our copy does not state that the super-enhancer has five constituents or establish that exactly four lack detectable activity. It also treats chromatin-dependent enhancers as active through mechanisms the assay may not detect. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • 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 [36]

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Authors
Sahu, B., Hartonen, T., Pihlajamaa, P., Wei, B., Dave, K., Zhu, F., Kaasinen, E., Lidschreiber, K., Lidschreiber, M., Daub, C. O., Cramer, P., Kivioja, T., & Taipale, J.
Affiliations
  • University of Helsinki (FI)
  • Karolinska Institutet (SE)
  • University of Cambridge (GB)
  • Science for Life Laboratory (SE)
Corresponding author
Taipale, Jussi
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2022-02-21
Volume
54
Issue
3
Pages
283-294
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-021-01009-4
PMC
PMC8920891
OpenAlex
W4213140257
Cited by
198
References
29
Citations by year
2026: 36 · 2025: 49 · 2024: 56 · 2023: 37 · 2022: 18 · 2021: 2
FWCI
13.14
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Genetics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo
Funders
  • Cancer Research UK (C55958/A28801/RG99643)
  • Academy of Finland (250345, 312042, 274555, 317807, 288836)
  • RCUK | Medical Research Council (MR/V000500/1)
  • Sigrid Juséliuksen Säätiö
  • Jane ja Aatos Erkon Säätiö
  • Syöpäsäätiö
  • Emil Aaltosen Säätiö
  • Science for Life Laboratory
  • CIMED
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 › Chromatin Remodeling and Cancer
Keywords
gene regulatory elements, sequence determinants, transcription factors, enhancers, transcriptional activity, massively parallel reporter assay, machine learning, transcription factor binding motifs, chromatin accessibility, transcription start sites, cell type specificity
MeSH terms
Binding Sites, Humans, Protein Binding, Regulatory Sequences, Nucleic Acid, Transcription Factors, Genome, Human

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