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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

Allele-specific immune gene quantification and expression analysis in single-cell RNA-seq data.

Ahmad Al Ajami^1,2,3, Jonas Schuck^1,2,3, Federico Marini^4,5

¹Goethe University, University Hospital Frankfurt, Neurological Institute (Edinger Institute), Frankfurt/Main 60528, Germany.

NAR Genomics and Bioinformatics

|November 13, 2025

Summary

This summary is machine-generated.

This study introduces a new computational method to quantify allele-specific expression of immune genes in single-cell RNA sequencing data. This approach enhances understanding of human immunogenomic diversity and gene expression variations.

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

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Area of Science:

Immunogenomics
Computational Biology
Single-cell analysis

Background:

Immune genes like human leukocyte antigens (HLAs) show high genetic diversity.
Understanding allele-specific expression is crucial for immunogenomics.
Existing methods may not fully capture immune gene allelic diversity.

Purpose of the Study:

To develop a novel computational methodology for allele-specific expression quantification of immune genes.
To enable interactive exploration of immune gene expression across multiple annotation layers.
To provide insights into human immunogenomic diversity.

Main Methods:

Developed a novel R/Bioconductor data structure for handling multi-layered immunogenetic annotation.
Applied a computational methodology for allele-specific expression quantification in single-cell RNA sequencing (scRNA-seq) data.
Validated the methodology on diverse scRNA-seq datasets.

Main Results:

Demonstrated robust performance across different experimental setups.
Enabled the study of human leukocyte antigen (HLA) expression loss in tumor cells.
Facilitated the discovery of differential HLA allele expression in specific immune cell subtypes.

Conclusions:

The novel methodology accurately quantifies allele-specific immune gene expression.
This approach offers new insights into human immunogenomic diversity.
The tools facilitate interactive exploration of complex immune gene expression patterns.