By exploiting recent advances in modern artificial intelligence and large-scale functional genomic datasets, sequence-to-function models learn the relationship between genomic DNA and its multilayer gene regulatory functions. These models are poised to uncover mechanistic relationships across layers of cellular biology, which will transform our understanding of cis gene regulation and open new avenues for discovering disease mechanisms.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Conditional deep learning model reveals translation elongation determinants during amino acid deprivation
Communications Biology Open Access 26 November 2025
-
scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution
Nature Methods Open Access 22 October 2025
-
scTFBridge: a disentangled deep generative model informed by TF-motif binding for gene regulation inference in single-cell multi-omics
Nature Communications Open Access 15 October 2025
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout

References
Uffelmann, E. et al. Nat. Rev. Methods Primers 1, 59 (2021).
Li, Z. et al. Cell Rep. Methods 3, 100384 (2023).
Luo, Y. et al. Nucleic Acids Res 48, D882–D889 (2020).
Avsec, Ž. et al. Nat. Methods 18, 1196–1203 (2021).
Avsec, Ž. et al. Nat. Genet. 53, 354–366 (2021).
Zhou, J. et al. Nat. Genet. 50, 1171–1179 (2018).
Zhou, J. Nat. Genet 54, 725–734 (2022).
Sasse, A. et al. Nat. Genet. 55, 2060–2064 (2023).
Huang, C. et al. Nat. Genet. 55, 2056–2059 (2023).
Kelley, D. R. PLOS Comput. Biol. 16, e1008050 (2020).
de Boer, C. G. & Taipale, J. Nature 625, 41–50 (2024).
Dalla-Torre, H. et al. Preprint at bioRxiv https://doi.org/10.1101/2023.01.11.523679 (2023).
Tang, Z. & Koo, P. K. Preprint at bioRxiv https://doi.org/10.1101/2024.02.29.582810 (2024).
Mostafavi, H., Spence, J. P., Naqvi, S. & Pritchard, J. K. Nat. Genet. 55, 1866–1875 (2023).
Arthur, T. D. et al. Preprint at bioRxiv https://doi.org/10.1101/2024.04.10.588874 (2024).
Acknowledgements
We thank C. de Boer and X. Tu for helpful comments. ChatGPT was used to refine some of the sentences.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Rights and permissions
About this article
Cite this article
Sasse, A., Chikina, M. & Mostafavi, S. Unlocking gene regulation with sequence-to-function models. Nat Methods 21, 1374–1377 (2024). https://doi.org/10.1038/s41592-024-02331-5
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s41592-024-02331-5
This article is cited by
-
Conditional deep learning model reveals translation elongation determinants during amino acid deprivation
Communications Biology (2025)
-
scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution
Nature Methods (2025)
-
Adapting systems biology to address the complexity of human disease in the single-cell era
Nature Reviews Genetics (2025)
-
scTFBridge: a disentangled deep generative model informed by TF-motif binding for gene regulation inference in single-cell multi-omics
Nature Communications (2025)
-
Embedding AI in biology
Nature Methods (2024)