A guidebook of spatial transcriptomic technologies, data resources and analysis approaches

Liangchen Yue; Feng Liu; Jiongsong Hu; Pin Yang; Yuxiang Wang; Junguo Dong; Wenjie Shu; Xingxu Huang; Shengqi Wang

doi:10.1016/j.csbj.2023.01.016

A guidebook of spatial transcriptomic technologies, data resources and analysis approaches

Comput Struct Biotechnol J. 2023 Jan 16:21:940-955. doi: 10.1016/j.csbj.2023.01.016. eCollection 2023.

Authors

Liangchen Yue¹, Feng Liu², Jiongsong Hu³, Pin Yang⁴, Yuxiang Wang¹, Junguo Dong¹, Wenjie Shu¹, Xingxu Huang^{5

6}, Shengqi Wang¹

Affiliations

¹ Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China.
² College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China.
³ University of South China, Hengyang, Hunan 421001, China.
⁴ Anhui Medical University, Hefei 230022, Anhui, China.
⁵ Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, and Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310029, China.
⁶ School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.

Abstract

Advances in transcriptomic technologies have deepened our understanding of the cellular gene expression programs of multicellular organisms and provided a theoretical basis for disease diagnosis and therapy. However, both bulk and single-cell RNA sequencing approaches lose the spatial context of cells within the tissue microenvironment, and the development of spatial transcriptomics has made overall bias-free access to both transcriptional information and spatial information possible. Here, we elaborate development of spatial transcriptomic technologies to help researchers select the best-suited technology for their goals and integrate the vast amounts of data to facilitate data accessibility and availability. Then, we marshal various computational approaches to analyze spatial transcriptomic data for various purposes and describe the spatial multimodal omics and its potential for application in tumor tissue. Finally, we provide a detailed discussion and outlook of the spatial transcriptomic technologies, data resources and analysis approaches to guide current and future research on spatial transcriptomics.

Keywords: Spatial transcriptomic technologies.

Publication types

Review