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Institute of Technologyhttps://www.ebi.ac.uk/ena/browser/view/PRJNA1271556Fastq files associated with the manuscript "Multiplexed in vivo base editing identifies functional gene-variant-context interactions" by Acosta, Johnson &amp Gould.ABSTRACT: DNA sequencing can identify genetic variants associated with predisposition, progression, and therapeutic outcomes for diseases like cancer. Insights from these studies can guide disease diagnosis and treatment, but the relative importance and functional impact of most variants remain poorly understood. We and others have developed precision genome editing methods to engineer and study the cellular impact of thousands of endogenous variants. However, the impact of most variants in the physiological in vivo setting, including contextual differences depending on the tissue or microenvironment, remains unexplored. Here, we integrate cross-species base editing sensor libraries with syngeneic mouse models to develop a multiplexed platform for systematic in vivo analysis of endogenous mutations in primary and disseminated malignancies. Screening 13,840 guide RNAs to engineer 7,783 cancer-associated mutations in 489 genes allowed us to build a compendium of putative functional interactions between genes, mutations, and physiological contexts. Our findings suggest that distinct in vivo environments can be contextual determinants of gene-variant phenotypes. This platform could be deployed to study how genetic variation impacts in vivo phenotypes associated with cancer and other diseases, as well as identify new potential therapeutic avenues to treat human disease.ENAfalseMultiplexed in vivo base editing identifies functional gene-variant-context interactions2025-06-072025-06-07PRJNA1271556