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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: Jun 5, 2025

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

Label-free single-cell RNA multiplexing leveraging genetic variability.

Konrad Hoeft^1,2, Tore Bleckwehl¹, David Schumacher^1,3

¹Department of Medicine 2 (Nephrology, Rheumatology, Clinical Immunology and Hypertension), Medical Faculty, RWTH Aachen University, Aachen, Germany.

Nature Communications

|December 5, 2024

Summary

High-throughput single cell RNA sequencing is crucial for understanding human disease. A new method, SoupLadle, simplifies multiplexing by using patient genetic differences, overcoming cost and complexity barriers for large studies.

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Last Updated: Jun 5, 2025

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

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

Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing

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Published on: March 23, 2022

Area of Science:

Genomics
Molecular Biology
Computational Biology

Background:

Single cell RNA sequencing (scRNA-seq) reveals cellular heterogeneity in human disease.
High costs and complexity limit large-scale scRNA-seq cohort studies.

Purpose of the Study:

To compare existing single cell multiplexing technologies.
To introduce SoupLadle, a novel, widely applicable demultiplexing method for high-throughput scRNA-seq.

Main Methods:

Evaluation of state-of-the-art single cell multiplexing techniques.
Development and validation of the SoupLadle demultiplexing algorithm.
Leveraging patient-specific genetic variations for sample identification.

Main Results:

SoupLadle enables simple and robust high-throughput sample multiplexing.
The method effectively distinguishes between samples in large cohorts.
Demonstrates a cost-effective approach to scaling scRNA-seq studies.

Conclusions:

SoupLadle significantly reduces barriers to large-scale single cell analysis.
This method facilitates deeper investigation of human disease at the single-cell level.
Enables broader application of scRNA-seq in clinical and research settings.