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Cell Specific Gene Expression

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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Related Experiment Video

Updated: Aug 4, 2025

Cell Type-specific Gene Expression Profiling in the Mouse Liver

Cell Type-specific Gene Expression Profiling in the Mouse Liver

Published on: September 17, 2019

Single-cell and spatially resolved transcriptomics for liver biology.

Ping Lin¹, Xi Yan¹, Siyu Jing¹

¹CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.

Hepatology (Baltimore, Md.)

|April 1, 2023

Summary

Single-cell and spatial transcriptomics reveal liver cell diversity and spatial organization, advancing understanding of liver health, disease, and potential therapies.

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Area of Science:

Molecular Biology
Genomics
Cell Biology

Background:

Single-cell transcriptomics identifies rare cells and state transitions.
Spatially resolved transcriptomics quantifies cells and genes within tissues.
These technologies are crucial for understanding the cellular landscape in health and disease.

Purpose of the Study:

To review biological insights into liver homeostasis, development, regeneration, chronic liver disease, and cancer.
To highlight advances from single-cell and spatially resolved transcriptomics in liver research.
To discuss challenges and future directions in liver cell atlas research.

Main Methods:

Review of key biological insights derived from single-cell transcriptomics.
Analysis of findings from spatially resolved transcriptomics in liver studies.
Integration of data to characterize liver cellular composition, diversity, function, and spatial architecture.

Main Results:

Characterization of comprehensive liver cellular composition and diversity.
Elucidation of liver zonation, cell communication, and cell proximity.
Identification of cell identity conversion and cell-specific alterations in liver pathology, revealing new therapeutic targets.

Conclusions:

Single-cell and spatial transcriptomics provide critical insights into liver biology and disease.
These technologies are instrumental in building a comprehensive liver cell atlas.
Future research should focus on addressing current challenges with advanced technologies and computational methods.