Li Zhuxia, Peng Guangdun
Ceter for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Biophys Rep. 2022 Jun 30;8(3):119-135. doi: 10.52601/bpr.2021.210037.
Cells and tissues are exquisitely organized in a complex but ordered manner to form organs and bodies so that individuals can function properly. The spatial organization and tissue architecture represent a keynote property underneath all living organisms. Molecular architecture and cellular composition within intact tissues play a vital role in a variety of biological processes, such as forming the complicated tissue functionality, precise regulation of cell transition in all living activities, consolidation of central nervous system, cellular responses to immunological and pathological cues. To explore these biological events at a large scale and fine resolution, a genome-wide understanding of spatial cellular changes is essential. However, previous bulk RNA sequencing and single-cell RNA sequencing technologies could not obtain the important spatial information of tissues and cells, despite their ability to detect high content transcriptional changes. These limitations have prompted the development of numerous spatially resolved technologies which provide a new dimension to interrogate the regional gene expression, cellular microenvironment, anatomical heterogeneity and cell-cell interactions. Since the advent of spatial transcriptomics, related works that use these technologies have increased rapidly, and new methods with higher throughput and resolution have grown quickly, all of which hold great promise to accelerate new discoveries in understanding the biological complexity. In this review, we briefly discussed the historical evolution of spatially resolved transcriptome. We broadly surveyed the representative methods. Furthermore, we summarized the general computational analysis pipeline for the spatial gene expression data. Finally, we proposed perspectives for technological development of spatial multi-omics.
细胞和组织以复杂但有序的方式精巧地组织起来，形成器官和机体，从而使个体能够正常运作。空间组织和组织结构是所有生物体的一个关键特性。完整组织内的分子结构和细胞组成在各种生物过程中发挥着至关重要的作用，例如形成复杂的组织功能、在所有生命活动中精确调节细胞转变、巩固中枢神经系统、细胞对免疫和病理信号的反应。为了在大规模和高分辨率下探索这些生物学事件，对空间细胞变化进行全基因组范围的了解至关重要。然而，尽管之前的批量RNA测序和单细胞RNA测序技术能够检测到高含量的转录变化，但却无法获得组织和细胞的重要空间信息。这些局限性促使了众多空间分辨技术的发展，这些技术为研究区域基因表达、细胞微环境、解剖学异质性和细胞间相互作用提供了一个新的维度。自空间转录组学出现以来，使用这些技术的相关研究迅速增加，具有更高通量和分辨率的新方法也迅速涌现，所有这些都有望加速在理解生物复杂性方面的新发现。在这篇综述中，我们简要讨论了空间分辨转录组的历史演变。我们广泛调研了代表性方法。此外，我们总结了空间基因表达数据的一般计算分析流程。最后，我们对空间多组学的技术发展提出了展望。
