谱系(遗传)
动力学(音乐)
生物
国家(计算机科学)
分辨率(逻辑)
体内
进化生物学
计算机科学
基因
物理
遗传学
人工智能
算法
声学
作者
Luke W. Koblan,Kathryn E. Yost,Pu Zheng,William Colgan,Matthew G. Jones,Dian Yang,Arun Kumar,J. S. Sandhu,Alexandra Schnell,Dawei Sun,Can Ergen,Reuben A. Saunders,Xiaowei Zhuang,William E. Allen,Nir Yosef,Jonathan S. Weissman
标识
DOI:10.1101/2025.06.15.659774
摘要
Abstract 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.
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