Creating Tissue Atlases with Spatial Transcriptomics

New methods of tissue analysis are furthering our understanding of disease mechanisms, allowing researchers to generate gene expression datasets of tissues and organs. In order to retain spatial information, these methods may use next-generation sequencing (NGS) to encode position onto RNA transcripts before sequencing, or instead may employ imaging-based approaches using in situ sequencing or hybridization. Alternatively, some approaches use a combination of methods. The result is large datasets of RNA expression that researchers are organizing into tissue atlases as they use the information to identify and annotate cell types.