美国密歇根大学Hyun Min Kang和美国密歇根大学医学院Jun Hee Lee共同合作，近期取得重要工作进展。他们研究开发了FICTURE工具，一种亚微米分辨率空间转录组学的可扩展无分割分析方案。相关研究成果2024年9月12日在线发表于《自然—方法学》杂志上。

据介绍，空间转录组学（ST）技术已经发展到能够在大面积上以亚微米分辨率进行全转录组基因表达分析。然而，高分辨率ST的分析经常受到复杂组织结构的挑战，现有的细胞分割方法由于不规则的细胞大小和形状而难以实现，并且缺乏可扩展到整个转录组分析的无分割方法。

研究人员提出了FICTURE（超高分辨率下的制图转录组因子推断），这是一种无分割的空间因子分解方法，可以处理标记有数十亿亚微米分辨率空间坐标的转录组数据，并且与基于测序和基于成像的ST数据兼容。FICTURE使用多层Dirichlet模型对像素级空间因子进行随机变分推理，比现有方法高效几个数量级。FICTURE揭示了挑战性组织的微观ST结构，如血管、纤维化、肌肉和脂质负荷区域，在真实数据中，以前的方法失败了。

总之，FICTURE的跨平台通用性、可扩展性和精确性使其成为探索高分辨率ST的强大工具。

附：英文原文

Title: FICTURE: scalable segmentation-free analysis of submicron-resolution spatial transcriptomics

Author: Si, Yichen, Lee, ChangHee, Hwang, Yongha, Yun, Jeong H., Cheng, Weiqiu, Cho, Chun-Seok, Quiros, Miguel, Nusrat, Asma, Zhang, Weizhou, Jun, Goo, Zllner, Sebastian, Lee, Jun Hee, Kang, Hyun Min

Issue&Volume: 2024-09-12

Abstract: Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. However, analysis of high-resolution ST is often challenged by complex tissue structure, where existing cell segmentation methods struggle due to the irregular cell sizes and shapes, and by the absence of segmentation-free methods scalable to whole-transcriptome analysis. Here we present FICTURE (Factor Inference of Cartographic Transcriptome at Ultra-high REsolution), a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron-resolution spatial coordinates and is compatible with both sequencing-based and imaging-based ST data. FICTURE uses the multilayered Dirichlet model for stochastic variational inference of pixel-level spatial factors, and is orders of magnitude more efficient than existing methods. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular and lipid-laden areas in real data where previous methods failed. FICTURE’s cross-platform generality, scalability and precision make it a powerful tool for exploring high-resolution ST.

DOI: 10.1038/s41592-024-02415-2

Source: https://www.nature.com/articles/s41592-024-02415-2