High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer

Charting the spatiotemporal dynamics of cell fate determination in development and disease is a long-standing objective in biology. Here we present the design, development, and extensive validation of PEtracer, a prime editing-based, evolving lineage tracing technology compatible with both single-cell sequencing and multimodal imaging methodologies to jointly profile cell state and lineage in dissociated cells or while preserving cellular context in tissues with high spatial resolution. Using PEtracer coupled with MERFISH spatial transcriptomic profiling in a syngeneic mouse model of tumor metastasis, we reconstruct the growth of individually-seeded tumors in vivo and uncover distinct modules of cell-intrinsic and cell-extrinsic factors that coordinate tumor growth. More generally, PEtracer enables systematic characterization of cell state and lineage relationships in intact tissues over biologically-relevant temporal and spatial scales. Overall design: 10X Genomics scRNA-seq (3' v3.1) libraries were generated from cell lines engineered with PEtracer lineage tracing components. Multiple libraries can be associated with a single sample and library type is indicated in the sample name, including: 1) transcriptome data, _GEX; 2) lineage tracing cassette data, _LTC; 3) integration barcode data, _intBC; 4) Puromycin or blasticidin static barcode data, _PURO or _BLAST; 5) pegRNA mismatch data from CROP-seq vector, _pegRNA