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Genome modeling and design across all domains of life with Evo 2

Garyk Brixi, Matthew G. Durrant, Jerome Ku, Michael Poli, Greg Brockman, Daniel Chang, Gabriel A. Gonzalez, Samuel H. King, David B. Li, View ORCID ProfileAditi T. Merchant, Mohsen Naghipourfar, Eric Nguyen, Chiara Ricci-Tam, David W. Romero, Gwanggyu Sun, Ali Taghibakshi, Anton Vorontsov, Brandon Yang, Myra Deng, Liv Gorton, Nam Nguyen, Nicholas K. Wang, Etowah Adams, Stephen A. Baccus, Steven Dillmann, Stefano Ermon, Daniel Guo, Rajesh Ilango, Ken Janik, Amy X. Lu, Reshma Mehta, View ORCID ProfileMohammad R.K. Mofrad, Madelena Y. Ng, Jaspreet Pannu, Christopher Ré, Jonathan C. Schmok, John St. John, Jeremy Sullivan, Kevin Zhu, Greg Zynda, Daniel Balsam, Patrick Collison, Anthony B. Costa, Tina Hernandez-Boussard, Eric Ho, Ming-Yu Liu, Thomas McGrath, Kimberly Powell, Dave P. Burke, View ORCID ProfileHani Goodarzi, View ORCID ProfilePatrick D. Hsu, View ORCID ProfileBrian L. Hie
doi: https://doi.org/10.1101/2025.02.18.638918
Garyk Brixi
1Arc Institute
3Stanford University
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Matthew G. Durrant
1Arc Institute
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Jerome Ku
1Arc Institute
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Michael Poli
3Stanford University
5Liquid AI
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Greg Brockman
6Independent Researcher
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Daniel Chang
1Arc Institute
3Stanford University
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Gabriel A. Gonzalez
1Arc Institute
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Samuel H. King
1Arc Institute
3Stanford University
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David B. Li
1Arc Institute
3Stanford University
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Aditi T. Merchant
1Arc Institute
3Stanford University
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Mohsen Naghipourfar
1Arc Institute
7University of California, Berkeley
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Eric Nguyen
3Stanford University
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Chiara Ricci-Tam
1Arc Institute
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David W. Romero
4NVIDIA
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Gwanggyu Sun
1Arc Institute
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Ali Taghibakshi
4NVIDIA
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Anton Vorontsov
4NVIDIA
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Brandon Yang
6Independent Researcher
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Myra Deng
8Goodfire
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Liv Gorton
8Goodfire
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Nam Nguyen
8Goodfire
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Nicholas K. Wang
8Goodfire
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Etowah Adams
9Columbia University
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Stephen A. Baccus
3Stanford University
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Steven Dillmann
3Stanford University
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Stefano Ermon
3Stanford University
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Daniel Guo
1Arc Institute
3Stanford University
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Rajesh Ilango
1Arc Institute
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Ken Janik
4NVIDIA
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Amy X. Lu
7University of California, Berkeley
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Reshma Mehta
6Independent Researcher
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Mohammad R.K. Mofrad
7University of California, Berkeley
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Madelena Y. Ng
3Stanford University
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Jaspreet Pannu
3Stanford University
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Christopher Ré
3Stanford University
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Jonathan C. Schmok
1Arc Institute
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John St. John
4NVIDIA
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Jeremy Sullivan
1Arc Institute
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Kevin Zhu
7University of California, Berkeley
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Greg Zynda
4NVIDIA
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Daniel Balsam
8Goodfire
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Patrick Collison
1Arc Institute
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Anthony B. Costa
4NVIDIA
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Tina Hernandez-Boussard
3Stanford University
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Eric Ho
8Goodfire
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Ming-Yu Liu
4NVIDIA
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Thomas McGrath
8Goodfire
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Kimberly Powell
4NVIDIA
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Dave P. Burke
1Arc Institute
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Hani Goodarzi
1Arc Institute
11University of California, San Francisco
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Patrick D. Hsu
1Arc Institute
7University of California, Berkeley
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  • For correspondence: patrick{at}arcinstitute.org brianhie{at}stanford.edu brian.hie{at}arcinstitute.org
Brian L. Hie
1Arc Institute
3Stanford University
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  • For correspondence: patrick{at}arcinstitute.org brianhie{at}stanford.edu brian.hie{at}arcinstitute.org
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Abstract

All of life encodes information with DNA. While tools for sequencing, synthesis, and editing of genomic code have transformed biological research, intelligently composing new biological systems would also require a deep understanding of the immense complexity encoded by genomes. We introduce Evo 2, a biological foundation model trained on 9.3 trillion DNA base pairs from a highly curated genomic atlas spanning all domains of life. We train Evo 2 with 7B and 40B parameters to have an unprecedented 1 million token context window with single-nucleotide resolution. Evo 2 learns from DNA sequence alone to accurately predict the functional impacts of genetic variation—from noncoding pathogenic mutations to clinically significant BRCA1 variants—without task-specific finetuning. Applying mechanistic interpretability analyses, we reveal that Evo 2 autonomously learns a breadth of biological features, including exon–intron boundaries, transcription factor binding sites, protein structural elements, and prophage genomic regions. Beyond its predictive capabilities, Evo 2 generates mitochondrial, prokaryotic, and eukaryotic sequences at genome scale with greater naturalness and coherence than previous methods. Guiding Evo 2 via inference-time search enables controllable generation of epigenomic structure, for which we demonstrate the first inference-time scaling results in biology. We make Evo 2 fully open, including model parameters, training code, inference code, and the OpenGenome2 dataset, to accelerate the exploration and design of biological complexity.

Competing Interest Statement

M.G.D. acknowledges outside interest in Stylus Medicine. M.P. is an employee of Liquid AI. C.R. acknowledges outside interest in Factory and Google Ventures. D.P.B. acknowledges outside interest as a Google Advisor. H.G. acknowledges outside interest as a co-founder of Exai Bio, Vevo Therapeutics, and Therna Therapeutics, serves on the board of directors at Exai Bio, and is a scientific advisory board member for Verge Genomics and Deep Forest Biosciences. P.D.H. acknowledges outside interest as a co-founder of Terrain Biosciences, Stylus Medicine, and Spotlight Therapeutics, serves on the board of directors at Stylus Medicine, is a board observer at EvolutionaryScale and Terrain Biosciences, a scientific advisory board member at Arbor Biosciences and Veda Bio, and an advisor to NFDG, Varda Space, and Vial Health. B.L.H. acknowledges outside interest in Prox Biosciences as a scientific co-founder. All other authors declare no competing interests.

Footnotes

  • ↵‡ These authors jointly supervised this work.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted February 21, 2025.
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Genome modeling and design across all domains of life with Evo 2
Garyk Brixi, Matthew G. Durrant, Jerome Ku, Michael Poli, Greg Brockman, Daniel Chang, Gabriel A. Gonzalez, Samuel H. King, David B. Li, Aditi T. Merchant, Mohsen Naghipourfar, Eric Nguyen, Chiara Ricci-Tam, David W. Romero, Gwanggyu Sun, Ali Taghibakshi, Anton Vorontsov, Brandon Yang, Myra Deng, Liv Gorton, Nam Nguyen, Nicholas K. Wang, Etowah Adams, Stephen A. Baccus, Steven Dillmann, Stefano Ermon, Daniel Guo, Rajesh Ilango, Ken Janik, Amy X. Lu, Reshma Mehta, Mohammad R.K. Mofrad, Madelena Y. Ng, Jaspreet Pannu, Christopher Ré, Jonathan C. Schmok, John St. John, Jeremy Sullivan, Kevin Zhu, Greg Zynda, Daniel Balsam, Patrick Collison, Anthony B. Costa, Tina Hernandez-Boussard, Eric Ho, Ming-Yu Liu, Thomas McGrath, Kimberly Powell, Dave P. Burke, Hani Goodarzi, Patrick D. Hsu, Brian L. Hie
bioRxiv 2025.02.18.638918; doi: https://doi.org/10.1101/2025.02.18.638918
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Genome modeling and design across all domains of life with Evo 2
Garyk Brixi, Matthew G. Durrant, Jerome Ku, Michael Poli, Greg Brockman, Daniel Chang, Gabriel A. Gonzalez, Samuel H. King, David B. Li, Aditi T. Merchant, Mohsen Naghipourfar, Eric Nguyen, Chiara Ricci-Tam, David W. Romero, Gwanggyu Sun, Ali Taghibakshi, Anton Vorontsov, Brandon Yang, Myra Deng, Liv Gorton, Nam Nguyen, Nicholas K. Wang, Etowah Adams, Stephen A. Baccus, Steven Dillmann, Stefano Ermon, Daniel Guo, Rajesh Ilango, Ken Janik, Amy X. Lu, Reshma Mehta, Mohammad R.K. Mofrad, Madelena Y. Ng, Jaspreet Pannu, Christopher Ré, Jonathan C. Schmok, John St. John, Jeremy Sullivan, Kevin Zhu, Greg Zynda, Daniel Balsam, Patrick Collison, Anthony B. Costa, Tina Hernandez-Boussard, Eric Ho, Ming-Yu Liu, Thomas McGrath, Kimberly Powell, Dave P. Burke, Hani Goodarzi, Patrick D. Hsu, Brian L. Hie
bioRxiv 2025.02.18.638918; doi: https://doi.org/10.1101/2025.02.18.638918

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