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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Sample multiplexing for retinal single-cell RNA sequencing.

Justin Ma¹, Ting-Kuan Chu², Maria Polo-Prieto³

¹Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA.

|November 21, 2024

Summary

This study introduces a sample multiplexing pipeline for single-cell RNA sequencing (scRNA-seq) of mouse retinal ganglion cells. This method efficiently tags samples, enabling precise analysis of cell type distribution and variation without losing origin information.

Keywords:

Molecular biology Neuroscience Omics Transcriptomics

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Last Updated: Jun 7, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

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Published on: January 7, 2020

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Published on: May 22, 2017

Area of Science:

Genomics
Neuroscience
Bioinformatics

Background:

Characterizing rare cell populations with single-cell RNA sequencing (scRNA-seq) is challenging.
Current methods often require sample enrichment and pooling, losing critical sample origin and phenotypic data.
This is particularly problematic for high-variation experiments like disease models or human sample studies.

Purpose of the Study:

To develop and validate a scRNA-seq sample multiplexing pipeline for mouse retinal ganglion cells.
To enable precise analysis of cell type distribution and transcriptomic variance across multiple samples.
To demonstrate the utility of multiplexing for identifying multiplets in scRNA-seq data.

Main Methods:

Established a sample multiplexing pipeline using cholesterol-modified oligos for scRNA-seq.
Applied the pipeline to mouse retinal ganglion cells.
Bioinformatically resolved unique sequence barcodes to identify sample origin.

Main Results:

Achieved enhanced precision in scRNA-seq data from multiplexed samples.
Investigated cell type distribution and transcriptomic variance across retinal samples.
Demonstrated the pipeline's effectiveness in identifying multiplets in non-labeled samples.

Conclusions:

Sample multiplexing with cholesterol-modified oligos is a viable strategy for scRNA-seq.
This approach overcomes limitations of enrichment and pooling, preserving sample origin and phenotypic data.
The developed pipeline enhances scRNA-seq analysis for rare cell populations and complex experimental designs.