Related Experiment Video
Updated: Jul 30, 2025
10:23
Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
Published on: January 19, 2017
11.0K
A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
Alice Nevone1,2, Francesca Lattarulo1,2, Monica Russo1,2
1Department of Molecular Medicine, University of Pavia, 27100 Pavia, Italy.
Biomedicines
|May 16, 2023
Summary
This study presents a new strategy for selecting accurate reference genes for quantitative reverse transcription polymerase chain reaction (RT-qPCR) experiments. The method uses public data to find the best genes for normalizing nucleic acid quantification in specific research settings.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Quantitative reverse transcription polymerase chain reaction (RT-qPCR) remains a key technique for nucleic acid quantification.
- Accurate normalization in RT-qPCR relies heavily on the selection of appropriate reference genes.
- Existing reference gene selection methods may not be optimal for specific clinical or experimental contexts.
Purpose of the Study:
- To develop and validate a strategy for identifying and selecting optimal reference genes for RT-qPCR normalization.
- To apply this strategy to identify reference genes for transcriptional studies in bone marrow plasma cells from AL amyloidosis patients.
- To demonstrate the superiority of the newly identified reference genes over commonly used housekeeping genes.
Main Methods:
- Conducted a systematic literature review to compile a list of 163 candidate reference genes.
- Utilized the Gene Expression Omnibus (GEO) database to analyze gene expression levels in bone marrow plasma cells from patients with plasma cell dyscrasias.
- Designed and validated RT-qPCR assays for candidate reference genes.
- Experimentally validated the performance of identified candidate reference genes.
Main Results:
- Identified a list of stably expressed genes in bone marrow plasma cells using transcriptomic data analysis.
- Experimental validation confirmed the superior performance of the identified candidate reference genes for normalization.
- The newly identified reference genes demonstrated better accuracy compared to commonly used housekeeping genes.
Conclusions:
- The developed strategy effectively identifies and validates optimal reference genes for RT-qPCR normalization in specific settings.
- This approach enhances the reliability of nucleic acid quantification in clinical and experimental research.
- The strategy is adaptable to other research areas with available public transcriptomic datasets.
