Spotiphy enables single-cell spatial whole transcriptomics across an entire section.

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2025-04-01 Epub Date: 2025-03-12 DOI:10.1038/s41592-025-02622-5

Jiyuan Yang, Ziqian Zheng, Yun Jiao, Kaiwen Yu, Sheetal Bhatara, Xu Yang, Sivaraman Natarajan, Jiahui Zhang, Qingfei Pan, John Easton, Koon-Kiu Yan, Junmin Peng, Kaibo Liu, Jiyang Yu

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引用次数: 0

Abstract

Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole-tissue sections, but current approaches remain plagued by the challenge of achieving single-cell resolution without sacrificing whole-genome coverage. Here we present Spotiphy (spot imager with pseudo-single-cell-resolution histology), a computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. Spotiphy delivers the most precise cellular proportions in extensive benchmarking evaluations. Spotiphy-derived inferred single-cell profiles reveal astrocyte and disease-associated microglia regional specifications in Alzheimer's disease and healthy mouse brains. Spotiphy identifies multiple spatial domains and alterations in tumor-tumor microenvironment interactions in human breast ST data. Spotiphy bridges the information gap and enables visualization of cell localization and transcriptomic profiles throughout entire sections, offering highly informative outputs and an innovative spatial analysis pipeline for exploring complex biological systems.

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Spotiphy使单细胞空间全转录组学跨越整个剖面。

空间转录组学（ST）通过在整个组织切片中实现基因表达的可视化，提高了我们对组织区域的理解，但目前的方法仍然受到在不牺牲全基因组覆盖的情况下实现单细胞分辨率的挑战的困扰。在这里，我们提出Spotiphy（带有伪单细胞分辨率组织学的斑点成像仪），这是一个计算工具包，可将基于测序的ST数据转换为单细胞分辨率的全转录组图像。Spotiphy在广泛的基准评估中提供最精确的细胞比例。spotiphy衍生的推断单细胞谱揭示了阿尔茨海默病和健康小鼠大脑中星形胶质细胞和疾病相关的小胶质细胞区域特征。Spotiphy识别了人类乳腺ST数据中肿瘤-肿瘤微环境相互作用的多个空间域和改变。Spotiphy弥合了信息鸿沟，实现了整个剖面的细胞定位和转录组图谱的可视化，为探索复杂的生物系统提供了高信息量的输出和创新的空间分析管道。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Methods 生物-生化研究方法

CiteScore

58.70

自引率

1.70%

发文量

326

审稿时长

1 months

期刊介绍： Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.