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

doi:10.13560/j.cnki.biotech.bull.1985.2024-0334

Abstract

Abstract:

【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.

Key words: spatial transcriptomics, cell segmentation, spatial domain recognition, cell clustering

WANG Rui, QI Ji. Integrating Histological Image Information to Enhance Cell Clustering Resolution in Spatial Transcriptome[J]. Biotechnology Bulletin, 2024, 40(8): 39-46.

Figures/Tables 4

Fig. 1 Performance comparison of the dataset of posterior section of mouse brain on 10X Visium platform by four methods A: Illustration of clustering results（30 groups）of posterior section of mouse brain by each method. B: Outlier numbers in clustering results by the each method

Fig. 2 Reconstruction of gene spatial expression pattern of SpaGMM in the hippocampus region of mouse brain and classification result A: Comparison of spatial expressions of marker genes in the CA1，CA3 and DG regions of hippocampus. B: Evaluation of the four algorithms on the classification of dentate gyrus type neurons according to spatial expression of marker gene C1ql2

Fig. 3 Comparison of classification results on the cerebellum of mouse brain by four methods A: Spatial expression pattern of marker genes at molecular layer and particle layer, and evaluation of the classification results of the four methods. B: Illustration of different layers on cerebellum recognized by SpaGMM. C: Illustration of expression of marker genes for Purkinje and Bergman cells in different spatial domains

Fig. 4 Spatial expression patterns of Aldoc（Zebrin II positive）and Cck, H2-D1（Zebrin II negative）genes in Purkinje cell layer From top to bottom, the images indicate the heat map of original gene expression（the color from blue to red indicates the gene expressions from low to high）, the heat map of SpaGMM reconstructed super-resolution gene expression（the color from light to deep indicates the gene expressions from low to high）, and the integration of multiple genes shows the complementary expression pattern in the Purkinje cell layer

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