H2M is a computational framework that models human genetic variants in the mouse genome, predicting murine equivalents that mirror the sequence and functional consequences of human variants. H2M supports mouse-to-human and paralog-to-paralog mapping, and ships with a database of over three million human-mouse mutation pairs together with base- and prime-editing libraries for thousands of variant pairs.
@article{dong2025h2m,title={Computational prediction of human genetic variants in the mouse genome},author={Dong, Kexin and Gould, Samuel I. and Li, Minghang and S{\'a}nchez-Rivera, Francisco J.},journal={Nature Biotechnology},year={2025},month=dec,doi={10.1038/s41587-025-02925-0},url={https://doi.org/10.1038/s41587-025-02925-0},}
bioRxiv
Multiplexed in vivo base editing identifies functional gene-variant-context interactions
Jonuelle Acosta, Grace A. Johnson, Samuel I. Gould, and 11 more authors
@article{acosta2025multiplexed,title={Multiplexed in vivo base editing identifies functional gene-variant-context interactions},author={Acosta, Jonuelle and Johnson, Grace A. and Gould, Samuel I. and Dong, Kexin and Lendner, Yovel and Detr{\'e}s, Diego and Atwa, Ondine and Bulkens, Jari and Gruber, Samuel and Contreras, Manuel E. and Wuest, Alexandra N. and Narendra, Varun K. and Hemann, Michael T. and S{\'a}nchez-Rivera, Francisco J.},journal={bioRxiv},year={2025},doi={10.1101/2025.02.23.639770},url={https://doi.org/10.1101/2025.02.23.639770},}
2024
Nat Biotechnol
High-throughput evaluation of genetic variants with prime editing sensor libraries
Samuel I. Gould, Alexandra N. Wuest, Kexin Dong, and 7 more authors
A high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites, enabling quantitative assessment of the functional impact of endogenous genetic variants at scale.
@article{gould2024sensor,title={High-throughput evaluation of genetic variants with prime editing sensor libraries},author={Gould, Samuel I. and Wuest, Alexandra N. and Dong, Kexin and Johnson, Grace A. and Hsu, Alvin and Narendra, Varun K. and Atwa, Ondine and Levine, Stuart S. and Liu, David R. and S{\'a}nchez-Rivera, Francisco J.},journal={Nature Biotechnology},volume={43},number={10},pages={1648--1662},year={2024},doi={10.1038/s41587-024-02172-9},url={https://doi.org/10.1038/s41587-024-02172-9},}