Transcriptome analysis allows the study of gene expression of human tissues and it is a valuable tool to characterize liver function, gene expression changes during liver disease, identify prognostic markers or signatures, and to facilitate discovery of new therapeutic targets. In contrast to whole tissue RNA sequencing analysis, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics enables the study of transcriptional activity at the single cell or spatial level. ScRNA-seq has paved the way to the discovery of previously unknown cell types and subtypes in normal and diseased liver, the study of rare cells such as liver progenitor cells as well as the functional role of non-parenchymal cells in chronic liver disease and cancer. By adding spatial information to scRNA-seq data, spatial transcriptomics transforms understanding of tissue functional organization and cell-to-cell interactions in their native environment. These approaches have recently been applied to investigate liver regeneration, organization and division of labor of hepatocytes and non-parenchymal cells, and to profile the single cell landscape of chronic liver diseases and cancer. Here we review the principles and technologies behind scRNA-seq and spatial transcriptomics approaches, highlighting the recent discoveries and novel insights these methodologies have yielded in both liver physiology and disease biology.
Keywords: cirrhosis fibrosis hepatocellular carcinoma liver diseases microenvironment non-parenchymal cells single-cell single-cell RNA sequencing spatial transcriptomics zonation