Generating functional plasmid origins with OriGen
Open accessPublished version of a preprint
Abstract
While generative artificial intelligence has shown promise for biological design, no computational system has yet created sequences proven capable of replication. Focusing on plasmids as minimal replicating systems, we develop OriGen, a language model that generates novel plasmid origins of replication while maintaining essential functional elements. We experimentally validate OriGen’s ability to create active origins in Escherichia coli that diverge from existing wild types, demonstrating the model’s capacity to capture the complex and often enigmatic mechanisms of biological replication. Further, we directed OriGen to produce functional origins that avoid common restriction sites, demonstrating the model’s potential for automated controllable design of vectors with desirable properties.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861 · see citing works
Evolutionary-scale prediction of atomic level protein structure with a language model
Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,523 · see citing works
Large language models generate functional protein sequences across diverse families
Madani, A., Krause, B., Greene, E. R., Subramanian, S., Mohr, B. P., Holton, J. M., Olmos, J. L., Xiong, C., Sun, Z. Z., Socher, R., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01618-2 · Cited by 1,078 · cited 1× · see citing works
“Protein generation models like ProGen [ 6 ] and ProtGPT2 [ 7 ] have demonstrated the ability to create novel functional proteins across a range of structural families.”
Sequence modeling and design from molecular to genome scale with Evo
Nguyen, E., Poli, M., Durrant, M. G., Kang, B., Katrekar, D., Li, D. B., Bartie, L. J., Thomas, A. W., King, S. H., Brixi, G., et al. (2024) · Science · doi:10.1126/science.ado9336 · Cited by 580 · see citing works
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
Zvyagin, M., Brace, A., Hippe, K., Deng, Y., Zhang, B., Bohorquez, C. O., Clyde, A., Kale, B., Perez-Rivera, D., Ma, H., et al. (2023) · The International Journal of High Performance Computing Applications · doi:10.1177/10943420231201154 · Cited by 120 · see citing works
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
Zvyagin, M., Brace, A., Hippe, K., Deng, Y., Zhang, B., Bohorquez, C. O., Clyde, A., Kale, B., Perez-Rivera, D., Ma, H., et al. (2022) · doi:10.1101/2022.10.10.511571 · Cited by 120 · see citing works
Flagged first, then by citations
- Authors
- Irvine, J., Martinson, J. N. V., Arora, J., Hasham, S. I., Patel, J. R., Qi, E. T., Cress, B. F., & Rubin, B. E.
- Affiliations
- Innovative Genomics Institute (US)
- Corresponding author
- Rubin, Benjamin E
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2025-11-26
- Volume
- 53
- Issue
- 22
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC12663086
- OpenAlex
- W4416838960
- Cited by
- 4
- References
- 7
- Citations by year
- 2026: 2 · 2025: 2
- FWCI
- 2.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- Lyda Hill Philanthropies
- Valhalla Foundation
- Hastings/Quillin Fund
- Silicon Valley Community Foundation
- CH Foundation
- Laura and Gary Lauder and Family
- Sea Grape Foundation
- Emerson Collective, Mike Schroepfer and Erin Hoffman Family Fund
- Anne Wojcicki Foundation
- Innovative Genomics Institute; Leona M. and Harry B. Helmsley Charitable Trust (G-2302-06692)
- U.S. Department of Energy (DE-AC02-05CH11231)
- Shurl and Kay Curci Foundation
- Innovative Genomics Institute Genomic Tool Discovery Program at UC Berkeley
- m-CAFEs Microbial Community Analysis & Functional Evaluation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- Origen, generative AI, language models, Escherichia coli, DNA replication, restriction sites
- MeSH terms
- DNA Replication, Escherichia coli, Plasmids, Programming Languages, Replication Origin
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
