Recent Advances in Spatiotemporal Omics Technology
Spatiotemporal omics technology is a collective term for technologies that observe or detect the multi-omics expression and regulatory features of life in tissues or cells in successive temporal and spatial dimensions,which enables analysis of the nature of life phenomena determined by genetic molecules at the subcellular,cellular,tissue,organ,individual,population,and evolutionary levels.Multi-omics mainly include genomics,epigenomics,transcriptomics and proteomics.Among them,spatial transcriptomics has been developing rapidly in recent years and is more widely used.Based on the principles,spatiotemporal omics techniques can be categorized into imaging-based techniques and sequencing-based techniques.Imaging-based technologies include spatial in situ hybridization technologies(SISH),such as smFISH,seqFISH and MERFISH,and spatial in situ sequencing technologies(SISS),such as ISS,FISSEQ and STARmap.Sequencing-based technologies include spatial in situ microsection(SISM)technologies such as tomo-seq,Geo-seq and DSP,and spatial in situ barcoding(SISB)technologies such as ST,Stereo-seq and seq-Scope technologies.The performance difference between different technologies is mainly reflected in the number of captured genes,spatial resolution,capture area,etc.Imaging-based technologies generally have higher spatial resolution,which can reach the level of cellular and subcellular resolution.However,because of the physical limitations brought by optical crowding and experimental complexity,the number and types of genes captured by the target are limited and difficult to improve.Sequencing-based technologies use polyT to specifically capture poly A,which enables unbiased capture at the whole transcriptome level and greatly improves the variety and number of captured genes.However,due to the mechanical limitations received from microsection and capture barcode planting,their spatial resolution generally falls short of single-cell resolution and is mostly a multicellular region with a mixture of multiple cells.Currently,benefiting from the nanoscale realization of nucleic acid binding site spacing on the surface of sequencing microarrays,Stereo-seq and seq-Scope have for the first time achieved nucleic acid capture at subcellular resolution and cell segmentation through integration with cellular staining profiles,which can truly achieve spatial single-cell resolution.The rapid development of spatial transcriptome technology has laid the foundation for the development of spatiotemporal multi-omics technology.Based on the existing experimental flow of spatial transcriptome or capture chip,through the transformation of the capture target and the supporting experimental flow,spatial genome,epigenome and proteome technologies have appeared one after another,and are gradually developing towards the ability to detect multiple histologists simultaneously in a single slice.The wide application of spatiotemporal genomics technologies has brought many challenges and targeted solutions for data analysis.Some of the more important current analysis methods include cell segmentation,spatial domain identification,and cell interactions.Significant challenges remain in the future for de-batching and integrative analysis of large amounts of data.The spatial information of nucleic acids and cells provided by spatiotemporal genomics can be constructed to detect macroscopic life activities and identify microscopic regulatory information at subcellular,cellular,tissue,organ,and holistic levels in both temporal and spatial dimensions.This has led to breakthroughs in important life science research areas such as developmental biology,complex diseases,neuroscience,and botany.Here,the development history of spatiotemporal omics technology,the characteristics of technical principles and physical limits are summarized,and the overall analysis process of spatiotemporal omics and classical spatiotemporal algorithms are outlined.The breakthroughs brought by spatiotemporal omics to the fields of developmental biology,complex diseases,neuroscience,and botany are summarized.The challenges of spatiotemporal omics in terms of technology iteration,analytical method development,and experimental design are also presented,as well as the outlook for the future development of spatiotemporal omics.
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