Pooled tagging of endogenous genes for the study of proteome dynamics at scale Yevgeniy V Serebrenik 1,2,*, Stephanie E Sansbury 1,2,*, Christopher Buenaventura 1,2, Tomer Lapidot 1,2, and Ophir Shalem 1,2 1 Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA 2 Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA * Equal contribution Visualizing endogenous proteins in cells affords deep insight into their function and regulation. This insight comes at a cost, as tagging endogenous proteins can be difficult and the tag itself may interfere with protein functions. Consequently, endogenously-tagged proteins are studied one at a time and require extensive validation. Here, we develop a high-throughput approach to endogenous protein tagging that enables us to gather insight on the proteome as a whole and allows validation through big data-driven approaches. This approach is based on homology-independent intron tagging, which allows for tagging of genes with a synthetic exon using an sgRNA as the only site-specific reagent. Thus, with a synthetic exon encoding a fluorescent protein domain and an sgRNA library, we can generate a pool of differentially-tagged cells representing a large subset of the proteome. The identity of the protein site tagged in each cell is encoded in the integrated sgRNA, allowing us to examine the cell library by sequencing. In this way, we determine that our high-throughput gene tagging approach enables a high rate of diverse and functional tagging. Tagging essential gene products preserves functions necessary for cell survival, and most tagged proteins are represented by multiple tag-site variants, allowing us to identify disruptive tags with outlying effects. Combining this tool with flow cytometry or pooled imaging and in-situ sequencing will allow us to gain deep insight into the localization, function, and regulation of the proteome as a whole in both steady and stress conditions.