De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution

Jie Liao, Jingyang Qian, Yin Fang, Zhuo Chen, Xiang Zhuang, Ningyu Zhang, Xin Shao, Yining Hu, Penghui Yang, Junyun Cheng, Yang Hu, Lingqi Yu, Haihong Yang, Jinlu Zhang, Xiaoyan Lu, Li Shao, Dan Wu, Yue Gao (), Huajun Chen () and Xiaohui Fan ()
Additional contact information
Jie Liao: Zhejiang University
Jingyang Qian: Zhejiang University
Yin Fang: Zhejiang University
Zhuo Chen: Zhejiang University
Xiang Zhuang: Zhejiang University
Ningyu Zhang: Zhejiang University
Xin Shao: Zhejiang University
Yining Hu: Zhejiang University
Penghui Yang: Zhejiang University
Junyun Cheng: Zhejiang University
Yang Hu: Zhejiang University
Lingqi Yu: Zhejiang University
Haihong Yang: Zhejiang University
Jinlu Zhang: Zhejiang University
Xiaoyan Lu: Zhejiang University
Li Shao: The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University
Dan Wu: Zhejiang University
Yue Gao: Beijing Institute of Radiation Medicine
Huajun Chen: Zhejiang University
Xiaohui Fan: Zhejiang University

Nature Communications, 2022, vol. 13, issue 1, 1-19

Abstract: Abstract Uncovering the tissue molecular architecture at single-cell resolution could help better understand organisms’ biological and pathological processes. However, bulk RNA-seq can only measure gene expression in cell mixtures, without revealing the transcriptional heterogeneity and spatial patterns of single cells. Herein, we introduce Bulk2Space ( https://github.com/ZJUFanLab/bulk2space ), a deep learning framework-based spatial deconvolution algorithm that can simultaneously disclose the spatial and cellular heterogeneity of bulk RNA-seq data using existing single-cell and spatial transcriptomics references. The use of bulk transcriptomics to validate Bulk2Space unveils, in particular, the spatial variance of immune cells in different tumor regions, the molecular and spatial heterogeneity of tissues during inflammation-induced tumorigenesis, and spatial patterns of novel genes in different cell types. Moreover, Bulk2Space is utilized to perform spatial deconvolution analysis on bulk transcriptome data from two different mouse brain regions derived from our in-house developed sequencing approach termed Spatial-seq. We have not only reconstructed the hierarchical structure of the mouse isocortex but also further annotated cell types that were not identified by original methods in the mouse hypothalamus.

Date: 2022
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DOI: 10.1038/s41467-022-34271-z

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