Cited by 287Genomics and Chromatin DynamicsGene Regulatory Network AnalysisCRISPR and Genetic Engineering

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DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers

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de Almeida, Bernardo P., Reiter, Franziska, Pagani, Michaela, Stark, Alexander·2022·Nature Genetics

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Abstract

Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood, and de novo enhancer design has been challenging. Here, we built a deep-learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally nonequivalent instances of the same TF motif that are determined by motif-flanking sequence and intermotif distances. We validated these rules experimentally and demonstrated that they can be generalized to humans by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.

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Authors: de Almeida, B. P., Reiter, F., Pagani, M., & Stark, A.
Affiliations: University of Vienna (AT)
Research Institute of Molecular Pathology (AT)
Corresponding author: Stark, Alexander
ORCID: de Almeida, Bernardo P.
Stark, Alexander
Venue: Nature Genetics
Publisher: Springer Science and Business Media LLC
Published: 2022-05
Volume: 54
Issue: 5
Pages: 613-624
ISSN: 1061-4036 (ISSN-L)
1546-1718
DOI: 10.1038/s41588-022-01048-5
OpenAlex: W4280563114
Cited by: 283
References: 133
Citations by year: 2026: 63 · 2025: 76 · 2024: 64 · 2023: 55 · 2022: 23
FWCI: 17.89
Type: journal article
Language: en
Open access: green
doi.org
Licence: cc-by-nc-nd
www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Nature Genetics (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Funders: European Commission
Austrian Science Fund (F4303-B09, F 4303)
KU Leuven
Österreichische Forschungsförderungsgesellschaft
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 › CRISPR and Genetic Engineering
Keywords: enhancer activity prediction, transcription factor binding motifs, Drosophila melanogaster S2 cells, gene expression regulation
MeSH terms: Animals, Base Sequence, Binding Sites, Drosophila, Drosophila melanogaster, Enhancer Elements, Genetic, Transcription Factors, Gene Expression Regulation, Developmental

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DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers

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