--- license: apache-2.0 task_categories: - text-generation tags: - biology - DNA - genomics - genetics - metagenomics - fasta - json size_categories: - n>1T --- # OpenGenome2

OpenGenome2 is a database of nearly 9 trillion base pairs of curated DNA from across all domains of life. Collected from diverse species and public data sources, OpenGenome2 was used to train Evo 2 models. Please refer to the [Evo 2 preprint](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1) or [github repository](https://github.com/ArcInstitute/evo2) for further details and usage examples. We provide OpenGenome2 in two formats, the dataset is organized into two main directories to reflect this: - **fasta** which contain the DNA sequences - **jsonl** which include the specific preprocessed sequences used for Evo 2 pretraining, such as adding special tokens and phylogenetic tags This dataset was specifically curated and preprocessed for training the Evo 2 family of genomic language models and can be used for training models or bioinformatics. ## Dataset Statistics - **Total size**: 8.8 trillion base pairs - **Coverage**: All domains of life (Bacteria, Archaea, Eukaryota, Viruses) - **Formats available**: FASTA, JSONL ## Data Sources The dataset combines sequences from various public databases and repositories: - **Prokaryotic genomes**: GTDBv220, IMG/PR - **Metagenomics**: MGD DB - **Viral sequences**: IMG/VR - **Eukaryotic data**: NCBI, Ensembl (from which we identified mRNAs, genomic windows) - **Eukaryotic elements**: Eukaryotic Promoter Database new (EPDnew) - **RNA sequences**: RNAcentral, Rfam - **Organellar genomes**: Various organelles ## Training Data Composition Evo 2 uses a two stage to train on OpenGenome2, first pretraining on a focused dataset at shorter sequence length and then longer sequence length with more full genomes and special tags. ### Phase 1: Pretraining | Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight | |---------|------------------------------|-------------|-----------------| | GTDBv220 + IMG/PR | 351 | 18.93% | 18.00% | | Metagenomics (MGD DB) | 854 | 46.06% | 24.00% | | IMG/VR | 34 | 1.83% | 3.00% | | Euk mRNA stitched | 99 | 5.34% | 9.00% | | Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 4.80% | 9.00% | | Euk 5kb windows stitched | 405 | 21.84% | 35.00% | | Organelles | 3 | 0.16% | 0.50% | | ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 1.02% | 2.00% | | Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.01% | 0.02% | ### Phase 2: Context Extension | Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight | |---------|------------------------------|-------------|-----------------| | TAGGED/Long: GTDBv220 + IMG/PR | 351 | 4.08% | 24.00% | | Metagenomics (MGD DB) | 854 | 9.93% | 5.00% | | TAGGED/Long: IMG/VR | 34 | 0.40% | 2.00% | | ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 0.22% | 1.00% | | Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.00% | 0.01% | | Organelles | 3 | 0.03% | 0.25% | | Euk mRNA stitched | 99 | 1.15% | 4.50% | | Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 1.04% | 4.50% | | Euk 5kb windows stitched | 405 | 4.71% | 5.00% | | Tagged/Long: NCBI Eukaryote: Animalia | 4,907 | 104.00% | 36.00% | | Tagged/Long: NCBI Eukaryote: Plantae | 1,652 | 96.00% | 12.00% | | Tagged/Long: NCBI Eukaryote: Fungi | 156 | 24.00% | 4.00% | | Tagged/Long: NCBI Eukaryote: Protista | 17 | 0.00% | 0.80% | | Tagged/Long: NCBI Eukaryote: Chromista | 13 | 6.00% | 0.80% | ## Citation If you use OpenGenome2 in your research, please cite: ```bibtex @article{Brixi2025.02.18.638918, author = {Brixi, Garyk and Durrant, Matthew G and Ku, Jerome and Poli, Michael and Brockman, Greg and Chang, Daniel and Gonzalez, Gabriel A and King, Samuel H and Li, David B and Merchant, Aditi T and Naghipourfar, Mohsen and Nguyen, Eric and Ricci-Tam, Chiara and Romero, David W and Sun, Gwanggyu and Taghibakshi, Ali and Vorontsov, Anton and Yang, Brandon and Deng, Myra and Gorton, Liv and Nguyen, Nam and Wang, Nicholas K and Adams, Etowah and Baccus, Stephen A and Dillmann, Steven and Ermon, Stefano and Guo, Daniel and Ilango, Rajesh and Janik, Ken and Lu, Amy X and Mehta, Reshma and Mofrad, Mohammad R.K. and Ng, Madelena Y and Pannu, Jaspreet and Re, Christopher and Schmok, Jonathan C and St. John, John and Sullivan, Jeremy and Zhu, Kevin and Zynda, Greg and Balsam, Daniel and Collison, Patrick and Costa, Anthony B. and Hernandez-Boussard, Tina and Ho, Eric and Liu, Ming-Yu and McGrath, Tom and Powell, Kimberly and Burke, Dave P. and Goodarzi, Hani and Hsu, Patrick D and Hie, Brian}, title = {Genome modeling and design across all domains of life with Evo 2}, elocation-id = {2025.02.18.638918}, year = {2025}, doi = {10.1101/2025.02.18.638918}, publisher = {Cold Spring Harbor Laboratory}, URL = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918}, eprint = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918.full.pdf}, journal = {bioRxiv} } ``` OpenGenome2 incorporates data from multiple public databases. Please also cite the original data sources as appropriate, and refer to the [Evo 2 preprint](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1) for further details. **GTDB (Genome Taxonomy Database):** Parks, D. H., Chuvochina, M., Rinke, C., Mussig, A. J., Chaumeil, P.-A., & Hugenholtz, P. (2022). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. *Nucleic Acids Research*, 50(D1), D785–D794. **Metagenomics (MGD DB):** Durrant, M. G., Perry, N. T., Pai, J. J., Jangid, A. R., Athukoralage, J. S., Hiraizumi, M., McSpedon, J. P., Pawluk, A., Nishimura, H., Konermann, S., & Hsu, P. D. (2024). Bridge RNAs direct programmable recombination of target and donor DNA. *Nature*, 630(8018), 984–993. Additional data sources include NCBI, Ensembl, IMG/VR, RNAcentral, Rfam, and EPDnew databases. ## License Apache 2.0