RNA-seq validation: software for selection of reference and variable candidate genes for RT-qPCR.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Real-time quantitative PCR (RT-qPCR) is crucial for validating RNA sequencing (RNA-seq) data.
• Accurate RT-qPCR requires stable, highly expressed reference genes across diverse biological conditions.
• Neglecting proper gene selection can lead to misinterpretation of gene expression results.

Purpose of the Study:

• To develop a software tool, Gene Selector for Validation (GSV), for selecting optimal reference and variable genes from quantitative transcriptome data.
• To enhance the accuracy and efficiency of gene expression validation using RT-qPCR.

Main Methods:

• Development of the Gene Selector for Validation (GSV) software.
• Comparison of GSV with existing software using synthetic datasets.
• Application of GSV to an Aedes aegypti transcriptome dataset and a large meta-transcriptome dataset.

Main Results:

• GSV outperformed other software by accurately identifying stable reference genes and variable expression genes.
• GSV successfully filtered candidate genes based on RT-qPCR assay detection limits.
• Analysis of an Aedes aegypti transcriptome confirmed eiF1A and eiF3j as highly stable reference genes, outperforming traditional choices.

Conclusions:

• GSV is an effective, time-saving, and cost-efficient tool for selecting reference and validation genes from transcriptomic data.
• GSV aids in making more appropriate gene selection choices for RT-qPCR validation.
• The software successfully processed large and complex transcriptomic datasets.