Stereo-seq V2: Spatial mapping of total RNA on FFPE sections with high resolution

Performing total RNA profiling on formalin-fixed, paraffin-embedded (FFPE) samples, the predominant sample conservation method in clinical practice, remains challenging for current spatial transcriptomics techniques. Here, we introduce Stereo-seq V2, which employs random primers to capture and sequence RNAs in situ on FFPE sections and provides single-cell resolution. The random-priming-based strategy offers unbiased transcript capturing and uniform gene body coverage, which increase the sensitivity to marker genes, the efficiency of non-polyadenylation (poly(A)) RNA profiling, and immune repertoire coverage. We demonstrated the robust performance of Stereo-seq V2 on clinical FFPE samples using triple-negative breast cancer (TNBC) sections and identified tumor-specific alternative splicing events. In a Mycobacterium tuberculosis (Mtb)-infected mouse model, we monitored gene expression dynamics of host and pathogen transcriptomes simultaneously by utilizing Stereo-seq V2. We also assembled immune repertoires and identified Mtb-specific BCR clones, which could also be observed in human tuberculous lung samples. These results highlight Stereo-seq V2's potential in biomedical research and personalized medicine.

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Publication Details

Journal
Cell
Published
2025-08-28
DOI
https://doi.org/10.1016/j.cell.2025.08.008
Citations
24
Primary Topic
RNA Research and Splicing
Type
article
Field-Weighted Citation Impact
19.34

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article

Stereo-seq V2: Spatial mapping of total RNA on FFPE sections with high resolution

Zhifeng Deng, Sha Liao, Rong Xiang, Gaoyang Wang et al.
24 citations
Cell
RNA Research and Splicing
19.34
article

Stereo-seq V2: Spatial mapping of total RNA on FFPE sections with high resolution

Zhifeng Deng, Sha Liao, Rong Xiang, Gaoyang Wang, Weihong Tan, Longqi Liu, Young Li, Maoyuan Liu, Zhaoxun Li, Jialuo Li, Jing Guo, Xinxing Li, Lei Han, Xia Jiang, Xuan Dong, Tingting Cao, Xiaoxi Zhou, Qiaomei Yuan, Yi Liu, Jiajun Zhang, Ao Chen, Shanshan Li, Dandan Li, Chang Chen, Xun Xu, Yan Zhang, Ying He, Ming Xu, Ying Qiu, Xiaole Hu, Jie Yuan, Mei Yang, Qiuling Chen, Xin Huang, Qin Wu, Guifang Wu, Xinya Zhang, Fan Zhu, Jie Zhai, Huatang Deng, Junqi Wu, Xiawei Liu, Haiying Liu, Haiqiao Pan, Tianbi Duan, Zehao Wang, Yu Zhao
article en
24 citations

Abstract

Performing total RNA profiling on formalin-fixed, paraffin-embedded (FFPE) samples, the predominant sample conservation method in clinical practice, remains challenging for current spatial transcriptomics techniques. Here, we introduce Stereo-seq V2, which employs random primers to capture and sequence RNAs in situ on FFPE sections and provides single-cell resolution. The random-priming-based strategy offers unbiased transcript capturing and uniform gene body coverage, which increase the sensitivity to marker genes, the efficiency of non-polyadenylation (poly(A)) RNA profiling, and immune repertoire coverage. We demonstrated the robust performance of Stereo-seq V2 on clinical FFPE samples using triple-negative breast cancer (TNBC) sections and identified tumor-specific alternative splicing events. In a Mycobacterium tuberculosis (Mtb)-infected mouse model, we monitored gene expression dynamics of host and pathogen transcriptomes simultaneously by utilizing Stereo-seq V2. We also assembled immune repertoires and identified Mtb-specific BCR clones, which could also be observed in human tuberculous lung samples. These results highlight Stereo-seq V2's potential in biomedical research and personalized medicine.

CellVol. 188(23)
BGI Group (China) (CN), Tongji University (CN), Shanxi Medical University (CN), Shanghai Jiao Tong University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Renji Hospital (CN), Zhejiang Cancer Hospital (CN), Shanghai Pulmonary Hospital (CN), University of Chinese Academy of Sciences (CN), BGI Research (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Chinese Academy of Medical Sciences Initiative for Innovative Medicine, Science and Technology Department of Zhejiang Province
Openalex Percentile: Top 0%
RNA Research and Splicing
19.34
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