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Updated: Nov 23, 2025

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

TARGET-Seq: A Protocol for High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing.

Alba Rodriguez-Meira^1,2,3, Jennifer O'Sullivan^1,2,3, Haseeb Rahman^1,2,3

¹Haematopoietic Stem Cell Laboratory, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), University of Oxford, Oxford OX3 9DS, UK.

|December 30, 2020

Summary

This summary is machine-generated.

TARGET-seq enables simultaneous genetic and transcriptional analysis from single cells, overcoming limitations in mutation hotspot coverage. This protocol offers high-sensitivity mutational analysis, parallel RNA sequencing, and cell-surface proteomics for comprehensive single-cell studies.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

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Area of Science:

Genomics
Molecular Biology
Cancer Research

Background:

Single-cell RNA sequencing (scRNA-seq) is crucial for understanding intratumoral heterogeneity.
Current scRNA-seq methods struggle to correlate genetic mutations with transcriptional profiles in the same cell due to coverage gaps at mutation hotspots.
This limitation hinders a complete understanding of tumor evolution and driver mutations.

Purpose of the Study:

To introduce TARGET-seq, a novel protocol designed to bridge the gap between genetic and transcriptional analyses at the single-cell level.
To provide a detailed, step-by-step protocol for TARGET-seq, enabling researchers to overcome allelic dropout issues and analyze multiple data types simultaneously.
To facilitate high-throughput, multiplexed analysis of single cells for comprehensive molecular profiling.

Main Methods:

Development of TARGET-seq, a protocol for targeted high-sensitivity single-cell mutational analysis.
Integration of parallel RNA sequencing (scRNA-seq) within the same single cell.
Incorporation of cell-surface proteomics for multi-modal single-cell analysis.
Minimization of allelic dropout rates for accurate mutation detection.

Main Results:

TARGET-seq achieves extremely low allelic dropout rates, enhancing the reliability of mutation detection.
The protocol enables parallel RNA sequencing and cell-surface proteomics alongside mutational analysis from individual cells.
Detailed troubleshooting, automation strategies, and multiplexing methods are presented for practical implementation.

Conclusions:

TARGET-seq is a powerful tool for resolving intratumoral heterogeneity by enabling integrated genetic and transcriptional profiling of single cells.
This protocol overcomes previous technical limitations, paving the way for more comprehensive studies of cancer biology and evolution.
The presented methods support high-throughput and multiplexed applications, advancing single-cell multi-omics research.