生物
动力学(音乐)
跟踪(教育)
细胞生物学
细胞
细胞迁移
计算生物学
生物系统
转录组
上皮
活体细胞成像
作者
Haofu Niu,Shuang Zhang,Jizhong Mao,Yimian Wu,Yuting Chen,Jianhui Chen,Renying Wang,Guodong Zhang,Peijing Zhang,Xinlian Zhang,Siqi Wang,Danmei Jia,Jingjing Wang,Libin Zhou,Maode Lai,Guoji Guo,Xiaoping Han
出处
期刊:Cell Stem Cell
[Elsevier BV]
日期:2026-03-26
卷期号:33 (5): 872-890.e11
标识
DOI:10.1016/j.stem.2026.03.001
摘要
Understanding biological processes requires spatiotemporal mapping of proliferative and transcriptional dynamics. Current spatial transcriptomics methods capture only protein-coding transcripts and static snapshots, obscuring non-coding RNAs (ncRNAs) and dynamic events. We developed SPTEdU-seq, integrating spatial total transcriptomics with 5-ethynyl-2′-deoxyuridine tracking to co-profile gene expression and proliferation dynamics. SPTEdU-seq demonstrates ultrahigh sensitivity for coding and non-coding transcripts and for splicing isoforms, with single-molecule probe design eliminating optical imaging. Applied to developing and adult mouse brains, it revealed spatial lncRNA patterns, reconstructed developmental trajectories, and enabled spatiotemporal lineage tracing. In murine ischemic stroke, it mapped regeneration dynamics and identified an Igfbp5 + astrocyte subtype within a pro-repair niche. In mouse and human renal tumors, it uncovered tumor-associated splicing and detected diagnostic 3p loss. By profiling newborn and resident cells in intact microenvironments, it unveiled previously inaccessible interaction networks. SPTEdU-seq thus establishes a powerful framework for investigating cell fate dynamics in regeneration, development, and cancer. • SPTEdU-seq co-maps newborn cell dynamics and spatial total transcriptomes • Dissects regeneration dynamics and uncovers a pro-repair niche after stroke • Reveals newborn-resident cell interactions in tissue remodeling and tumor invasion • Detects diagnostic 3p loss in human renal cell carcinoma Niu et al. present SPTEdU-seq, a spatial omics platform that enables co-profiling of newborn cell dynamics and full-length total transcriptomes at cellular resolution. This approach illuminates non-coding RNA regulations, spatial splicing, transient states, lineage trajectories, and cellular interactions in the contexts of regeneration, development, and tumor biology.
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