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Real Time RT-PCR

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Updated: May 12, 2026

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

Quantification method affects replicability of eQTL analysis, colocalization, and TWAS.

Nolan Cole¹, William Wu¹, S Taylor Head²

¹Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Biorxiv : the Preprint Server for Biology

|September 2, 2025

Summary

This summary is machine-generated.

RNA-sequencing (RNA-seq) processing choices significantly impact gene expression analyses. Methodological decisions in RNA-seq quantification and reference choice affect eQTL detection and TWAS results, stressing the need for standardization.

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Last Updated: May 12, 2026

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Published on: October 14, 2021

Area of Science:

Genomics
Bioinformatics
Statistical Genetics

Background:

Genome-wide association studies (GWAS) are powerful for identifying genetic variants associated with traits.
eQTL mapping and transcriptome-wide association studies (TWAS) are commonly used to interpret GWAS findings by linking genetic variants to gene expression.
The influence of RNA-sequencing (RNA-seq) data processing choices on these downstream analyses is not well understood.

Purpose of the Study:

To investigate how different RNA-seq quantification methods and transcriptomic references impact eQTL detection and gene expression prediction.
To assess the downstream consequences of these RNA-seq processing choices on genetic colocalization and TWAS results.
To highlight the need for standardized RNA-seq processing protocols in genetic association studies.

Main Methods:

Systematic evaluation of various RNA-seq quantification tools.
Comparison of results using different transcriptomic references.
Analysis of eQTL detection rates and gene expression prediction accuracy.
Assessment of the impact on gene-trait colocalization and TWAS summary statistics.

Main Results:

The choice of RNA-seq quantification method significantly alters eQTL detection and gene expression prediction.
The selection of a transcriptomic reference also substantially impacts eQTL mapping and TWAS outcomes.
These methodological variations lead to significant downstream effects on the interpretation of genetic association studies.

Conclusions:

Seemingly minor decisions in RNA-seq data processing have a substantial impact on eQTL and TWAS results.
Current practices in RNA-seq processing introduce variability that can affect the reproducibility of genetic association studies.
Standardization of RNA-seq quantification and reference selection is crucial for robust and reproducible genetic research.