Spatial Transcriptomic Technologies

被引:16
|
作者
Chen, Tsai-Ying [1 ,2 ,3 ]
You, Li [1 ,2 ,3 ]
Hardillo, Jose Angelito U. [2 ,4 ]
Chien, Miao-Ping [1 ,2 ,3 ,4 ]
机构
[1] Erasmus MC, Dept Mol Genet, NL-3015 GD Rotterdam, Netherlands
[2] Erasmus MC Canc Inst, NL-3015 GD Rotterdam, Netherlands
[3] Oncode Inst, NL-3521 AL Utrecht, Netherlands
[4] Erasmus MC, Dept Otorhinolaryngol Head & Neck Surg, NL-3015 GD Rotterdam, Netherlands
关键词
spatial omics technologies; NGS-based spatial profiling; probe-based spatial profiling; imaging-based spatial profiling; image-guided spatially resolved single cell sequencing; SINGLE-CELL TRANSCRIPTOMICS; GENE-EXPRESSION; RNA; SEQ;
D O I
10.3390/cells12162042
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] A guidebook of spatial transcriptomic technologies, data resources and analysis approaches
    Yue, Liangchen
    Liu, Feng
    Hu, Jiongsong
    Yang, Pin
    Wang, Yuxiang
    Dong, Junguo
    Shu, Wenjie
    Huang, Xingxu
    Wang, Shengqi
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2023, 21 : 940 - 955
  • [2] Emerging high-resolution spatial transcriptomic technologies in kidney research
    Qiao, Xuanyuan
    Wu, Haojia
    Humphreys, Benjamin D.
    NEPHROLOGY DIALYSIS TRANSPLANTATION, 2024, 39 (11) : 1747 - 1750
  • [3] Integrating multiple spatial transcriptomic and proteomic technologies to generate a cancer atlas to understand the tumor microenvironment
    Price, Colles
    Nishimura, Kazuho
    Bandyopadhyay, Som
    Borger, Darrell
    Weiner, Russell
    CANCER RESEARCH, 2024, 84 (07)
  • [4] Designing spatial transcriptomic experiments
    Righelli, Dario
    Sottosanti, Andrea
    Risso, Davide
    NATURE METHODS, 2023, 20 (03) : 355 - 356
  • [5] Designing spatial transcriptomic experiments
    Dario Righelli
    Andrea Sottosanti
    Davide Risso
    Nature Methods, 2023, 20 : 355 - 356
  • [6] SPATIAL TECHNOLOGIES
    COUCLELIS, H
    ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 1994, 21 (02): : 142 - 143
  • [7] The unveiled mosaic of intra-tumor heterogeneity in ovarian cancer through spatial transcriptomic technologies: A systematic review
    Masatti, Laura
    Marchetti, Matteo
    Pirrotta, Stefania
    Spagnol, Giulia
    Corra, Anna
    Ferrari, Jacopo
    Noventa, Marco
    Saccardi, Carlo
    Calura, Enrica
    Tozzi, Roberto
    TRANSLATIONAL RESEARCH, 2024, 273 : 104 - 114
  • [8] Analysis and Visualization of Spatial Transcriptomic Data
    Liu, Boxiang
    Li, Yanjun
    Zhang, Liang
    FRONTIERS IN GENETICS, 2022, 12
  • [9] SPATIAL TRANSCRIPTOMIC LANDSCAPE OF DIFFUSE GLIOMA
    Wu, Zhichao
    Dazelle, Karen
    Chung, Hye-Jung
    Aldape, Kenneth
    NEURO-ONCOLOGY, 2022, 24 : 276 - 277
  • [10] Advances in spatial transcriptomic data analysis
    Dries, Ruben
    Chen, Jiaji
    Del Rossi, Natalie
    Khan, Mohammed Muzamil
    Sistig, Adriana
    Yuan, Guo-Cheng
    GENOME RESEARCH, 2021, 31 (10) : 1706 - 1718