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

作者全名："Yue, Liangchen; Liu, Feng; Hu, Jiongsong; Yang, Pin; Wang, Yuxiang; Dong, Junguo; Shu, Wenjie; Huang, Xingxu; Wang, Shengqi"

作者地址："[Yue, Liangchen; Wang, Yuxiang; Dong, Junguo; Shu, Wenjie; Wang, Shengqi] Beijing Inst Microbiol & Epidemiol, Beijing 100850, Peoples R China; [Liu, Feng] Chongqing Med Univ, Coll Med Informat, Chongqing 400016, Peoples R China; [Hu, Jiongsong] Univ South China, Hengyang 421001, Hunan, Peoples R China; [Yang, Pin] Anhui Med Univ, Hefei 230022, Anhui, Peoples R China; [Huang, Xingxu] Zhejiang Univ, Affiliated Hosp 1, Inst Translat Med, Zhejiang Prov Key Lab Pancreat Dis,Sch Med, Hangzhou 310029, Peoples R China; [Huang, Xingxu] ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China"

通信作者："Shu, WJ; Wang, SQ (通讯作者)，Beijing Inst Microbiol & Epidemiol, Beijing 100850, Peoples R China.; Huang, XX (通讯作者)，Zhejiang Univ, Affiliated Hosp 1, Inst Translat Med, Zhejiang Prov Key Lab Pancreat Dis,Sch Med, Hangzhou 310029, Peoples R China."

来源：COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL

ESI学科分类：BIOLOGY & BIOCHEMISTRY

WOS号：WOS:000922345500001

JCR分区：Q2

影响因子：4.4

年份：2023

卷号：21

期号：　

开始页：940

结束页：955

文献类型：Review

关键词：Spatial transcriptomic technologies

摘要："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.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/)."

基金机构："National Key Research and Development Project of China [2021YFC2302400, 2021YFC2302403]; National Natural Science Foundation of China [81830101, 31901064]; General Project of Chongqing Natural Science Foundation of China [CSTB2022NSCQ-MSX1059]; Intelligent Medicine Research Project of Chongqing Medical University [ZHYXQNRC202103]"

基金资助正文："Funding This work was supported in part by the National Key Research and Development Project of China (2021YFC2302400 and 2021YFC2302403) , National Natural Science Foundation of China (81830101 and 31901064) , General Project of Chongqing Natural Science Foundation of China (CSTB2022NSCQ-MSX1059) , and Intelligent Medicine Research Project of Chongqing Medical University (ZHYXQNRC202103) ."