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Updated: Dec 23, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Stably expressed genes in single-cell RNA sequencing.

Julie M Deeke¹, Johann A Gagnon-Bartsch¹

¹Department of Statistics, University of Michigan, 1085 South University Ave, Ann Arbor, MI 48109, USA.

Journal of Bioinformatics and Computational Biology

|April 28, 2020

Summary

Researchers identified stable endogenous genes for normalizing single-cell RNA sequencing (scRNA-seq) data. Genes involved in cytosolic ribosome function show stable expression, offering a reliable reference for scRNA-seq analysis.

Keywords:

Gene expression single-cell RNA sequencing stably expressed genes

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Single-cell RNA sequencing (scRNA-seq) measures gene expression at the cellular level.
Technical artifacts, such as batch effects, can impact scRNA-seq measurements.
External spike-ins are controversial in scRNA-seq due to differences with endogenous genes.

Purpose of the Study:

To investigate the use of endogenous genes as stable references for normalizing scRNA-seq data.
To define and identify genes with stable expression at the single-cell level.
To address the limitations of external spike-ins in scRNA-seq normalization.

Main Methods:

Compilation of gene sets associated with cellular structures.
Analysis of gene expression stability in scRNA-seq data.
Comparison of stability in single-cell versus bulk gene expression measurements.

Main Results:

Genes encoding cytosolic ribosome proteins exhibit high expression stability relative to total RNA content.
These stable genes are also consistent in bulk gene expression measurements.
Identified gene sets provide potential references for scRNA-seq normalization.

Conclusions:

Endogenous genes, particularly those related to the cytosolic ribosome, can serve as reliable references for scRNA-seq data normalization.
Defining and discovering stable endogenous genes is crucial for improving scRNA-seq data accuracy.
This approach offers an alternative to controversial external spike-ins for scRNA-seq analysis.