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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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Related Experiment Video

Updated: May 30, 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

Superloaded Multiplexed scRNA-seq Data Preserves Primary Immune Cell Heterogeneity but Necessitates Stringent Doublet

Henry Sserwadda¹, Jung Ho Lee¹, Brian H Lee¹

¹Department of Biomedical Sciences, College of Medicine, Seoul National University, Seoul, South Korea.

Immunological Investigations

|January 30, 2025

Summary

Superloading in single-cell RNA sequencing (scRNA-seq) is cost-effective for multiplexing samples. While transcriptomic data quality remains high, T cell receptor analysis requires careful doublet removal to ensure accuracy.

Keywords:

Doublet exclusion T cell receptor multiplexing scRNA-seq superloading

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Last Updated: May 30, 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

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Published on: January 19, 2017

Area of Science:

Genomics
Immunology
Bioinformatics

Background:

Single-cell RNA sequencing (scRNA-seq) enables rare cell population characterization.
Multiplexing (superloading) increases throughput and reduces costs but can complicate analysis due to higher doublet rates.
Understanding superloading's impact on gene expression and T cell receptor (TCR) data is crucial for optimizing experimental design.

Purpose of the Study:

To compare the effects of standard versus superloading on multiplexed scRNA-seq data.
To evaluate data quality and doublet rates in human thymus and blood samples.
To assess the impact on T cell receptor (TCR) data analysis.

Main Methods:

Multiplexed scRNA-seq was performed on human thymus and blood samples.
Standard loading and superloading conditions were compared.
Gene expression and TCR sequencing data were analyzed.

Main Results:

Transcriptomic differences between standard and superloading were minimal.
Over 50% of T cells expressing multiple TCR chains were identified as doublets, irrespective of loading density.
Superloading did not compromise overall gene expression data quality.

Conclusions:

Multiplexing samples via superloading is feasible without compromising scRNA-seq data quality for general analyses.
TCR analysis requires an additional doublet removal step to improve accuracy, especially when using superloading.
Optimized experimental and computational strategies can leverage superloading for cost-effective scRNA-seq studies.