整合组织学图像信息增强空间转录组细胞聚类的分辨率  

Integrating Histological Image Information to Enhance Cell Clustering Resolution in Spatial Transcriptome

作　　者：王睿 戚继[1] WANG Rui;QI Ji(School of Life Sciences,Fudan University,Shanghai 200000)

机构地区：[1]复旦大学生命科学学院,上海200000

出　　处：《生物技术通报》2024年第8期39-46,共8页Biotechnology Bulletin

基　　金：国家自然科学基金项目(32070247)。

摘　　要：【目的】增加空间转录组基因表达的空间分辨率以提升遗传发育与疾病研究中的细胞谱系和类型变化的精度,提供更精细的分子表型信息。【方法】通过图像分割实现空间转录组点阵的细胞空间分布模拟,使用线性插值方法重构超分辨率基因空间表达,并利用图聚类方法揭示组织中细胞分布的空间偏好性。【结果】将新方法SpaGMM在小鼠后脑10X Visium数据集上进行检验,可以精确识别小鼠脑神经空间结构域。通过与几种空间转录组聚类的常用方法进行比较,结果显示SpaGMM的聚类结果更加符合组织学区域的注释,这些区域具有大量标记基因的空间表达支持。SpaGMM还可以从小鼠小脑区域中区分出浦肯野细胞(Purkinje cell)和伯格曼胶质细胞(Bergmann glial cell)所对应的组织区域,发现不同细胞层中存在互补的基因表达模式。【结论】SpaGMM可以通过提高点阵的空间分辨率揭示组织结构域的精细结构。【Objective】Increasing the spatial resolution of transcriptome gene expression can improve the accuracy of cell lineage and type changes in genetic development and disease studies,providing more detailed molecular phenotypic information.【Method】Using image segmentation to simulate the spatial distribution of cells in a spatial transcriptomics grid,the high-resolution spatial gene expression using linear interpolation was reconstructed.Graph clustering methods were used to reveal the spatial preferences of cell distribution within tissues.【Result】Application of SpaGMM on the 10X Visium dataset of the mouse posterior brain helped to accurately identify various spatial domains of the mouse brain.Compared with several commonly used methods for spatial transcriptome clustering,the results showed that the clustering results by SpaGMM were more consistent with the annotated histological regions,which were supported by the spatial expression of many marker genes.SpaGMM also recognized layers corresponding to Purkinje cells and Bergmann glial cells from mouse cerebellum,revealing complementary gene expression patterns in different cell layers.【Conclusion】SpaGMM may reveal the fine structure of tissue domains by improving the spatial resolution of spots.

关 键 词：空间转录组学 细胞分割 空间域识别 细胞聚类 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] Q811.4[自动化与计算机技术—计算机科学与技术]