AI Article Synopsis

  • - Single-cell sequencing offers detailed genomic insights but lacks the spatial context of cells; advancements in spatial transcriptomics and multi-omics technologies aim to bridge this gap by analyzing tissue molecular profiles.
  • - The article classifies current spatial genomics technologies into three categories: optical imaging, positional indexing, and mathematical cartography, while discussing their trade-offs, limitations, and potential synergies with single-cell methods.
  • - A proposed theoretical framework called DNA-GPS aims to enhance large-scale spatial genomics by integrating concepts from mathematical cartography and positional indexing, potentially allowing for 3D positioning of cells without optical measurements.

Article Abstract

While single-cell sequencing technologies provide unprecedented insights into genomic profiles at the cellular level, they lose the spatial context of cells. Over the past decade, diverse spatial transcriptomics and multi-omics technologies have been developed to analyze molecular profiles of tissues. In this article, we categorize current spatial genomics technologies into three classes: optical imaging, positional indexing, and mathematical cartography. We discuss trade-offs in resolution and scale, identify limitations, and highlight synergies between existing single-cell and spatial genomics methods. Further, we propose DNA-GPS (global positioning system), a theoretical framework for large-scale optics-free spatial genomics that combines ideas from mathematical cartography and positional indexing. DNA-GPS has the potential to achieve scalable spatial genomics for multiple measurement modalities, and by eliminating the need for optical measurement, it has the potential to position cells in three-dimensions (3D).

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Source
http://dx.doi.org/10.1016/j.cels.2023.08.005DOI Listing

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