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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: Feb 22, 2026

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response

Published on: August 10, 2017

Using RNA-seq data to select reference genes for normalizing gene expression in apple roots.

Zhe Zhou¹, Peihua Cong¹, Yi Tian¹

¹Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng, Liaoning, P. R. China.

|September 22, 2017

Summary

This summary is machine-generated.

This study identifies stable reference genes for accurate gene expression analysis in apple roots under stress. Using validated genes ensures reliable RT-qPCR data normalization, even with a single reference gene.

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Last Updated: Feb 22, 2026

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Published on: October 22, 2018

Area of Science:

Plant Molecular Biology
Genomics and Genetics

Background:

Gene expression analysis in apple roots under stress is underexplored.
Lack of validated reference genes hinders accurate normalization of quantitative gene expression data in apple roots.

Purpose of the Study:

To evaluate the suitability of 15 candidate genes as reliable reference genes for normalizing gene expression in apple roots.
To identify stably expressed genes for accurate RT-qPCR data normalization under various stress conditions.

Main Methods:

Selection of 15 candidate apple genes based on RNA-seq data and previous studies.
Evaluation of gene stability using four statistical methods: Delta Ct, geNorm, NormFinder, and BestKeeper.
Assessment of gene expression normalization using the most and least stable reference genes on target genes MdLecRLK5 and MdMAPK3.

Main Results:

A panel of five stably expressed genes (MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399, MDP0000173025) were recommended for apple root gene expression studies.
Significant differences in target gene expression patterns were observed when using the most versus least stable reference genes.
A single validated reference gene was found sufficient for reliable normalization.

Conclusions:

The recommended reference genes provide a reliable basis for normalizing quantitative gene expression data in apple roots under diverse abiotic and biotic stresses.
Accurate reference gene selection is critical for interpreting gene expression patterns, particularly for genes like MdLecRLK5 and MdMAPK3.
The choice of the most suitable reference gene may be condition-specific for optimal RT-qPCR data normalization.