Abstract
Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The ‘cis-regulatory code’ — how cells interpret DNA sequences to determine when, where and how much genes should be expressed — has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.
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Acknowledgements
We thank B. Cleary, B. Cohen, G. Eraslan, A. Kundaje, B. Lehner, S. Mostafavi, A. M. Rafi, S. Reilly, C. Rogerson, A. Sasse, J. Schreiber, N. Shakiba, J. Shendure, B. van Steensel, M. Taipale, O. Tariq, X. Tu, M. Underhill, M. Weirauch and N. Yachie for helpful discussions. We apologise to all our colleagues whose work we could not cite due to the limit on the number of references. C.G.d.B. is a Michael Smith Health Research BC Scholar and is supported by a Stem Cell Network Jump Start award (ECR-C4R1-7).
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C.G.d.B. and J.T. conceptualized the paper. C.G.d.B. produced the first draft, analysed the data and created the figures with advice from J.T. C.G.d.B. and J.T. edited the manuscript.
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de Boer, C.G., Taipale, J. Hold out the genome: a roadmap to solving the cis-regulatory code. Nature 625, 41–50 (2024). https://doi.org/10.1038/s41586-023-06661-w
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DOI: https://doi.org/10.1038/s41586-023-06661-w
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