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The Power of Single‐Cell Analysis for the Study of Liver Pathobiology
Author(s) -
Chu Angela L.,
Schilling Joel D.,
King Kevin R.,
Feldstein Ariel E.
Publication year - 2021
Publication title -
hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.488
H-Index - 361
eISSN - 1527-3350
pISSN - 0270-9139
DOI - 10.1002/hep.31485
Subject(s) - transcriptome , biology , computational biology , cell type , single cell analysis , cell , gene expression profiling , cell sorting , rna , gene expression , liver cell , microbiology and biotechnology , gene , bioinformatics , genetics , medicine
Single cell transcriptomics has emerged as a powerful lens through which to study the molecular diversity of complex tissues such as the liver, during health and disease, both in animal models and in humans. The earliest gene expression methods measured bulk tissue RNA, but the results were often confusing because they derived from the combined transcriptomes of many different cell types in unknown proportions. To better delineate cell‐type‐specific expression, investigators developed cell isolation, purification, and sorting protocols, yet still, the RNA derived from ensembles of cells obscured recognition of cellular heterogeneity. Profiling transcriptomes at the single‐cell level has opened the door to analyses that were not possible in the past. In this review, we discuss the evolution of single cell transcriptomics and how it has been applied for the study of liver physiology and pathobiology to date.