Introduction to RT-qPCR
Real-time quantitative PCR (RT-qPCR) is a powerful tool used by scientists to measure gene expression levels. This technique is often employed to validate results obtained from RNA sequencing (RNA-seq) experiments. RT-qPCR works by amplifying specific RNA sequences and measuring their quantity in real time, which helps researchers understand how genes are expressed under different conditions.
The Importance of Reference Genes
For RT-qPCR to produce accurate results, it requires stable reference genes. These are genes that consistently express at stable levels across different biological conditions. They serve as a baseline or control to compare the expression of other genes. Choosing the right reference genes is crucial because using unstable ones can lead to incorrect conclusions about gene expression.
Introducing GSV: Gene Selector for Validation
To address the challenge of selecting the best reference genes, researchers at the Instituto Oswaldo Cruz have developed a software tool called “Gene Selector for Validation” (GSV). This tool helps identify the most suitable reference and variable candidate genes from a transcriptome, which is the complete set of RNA molecules in a cell or organism.
GSV software logic
The left-hand side path shows the genes with the most stable expression (reference candidate genes), and the right-hand path shows the genes with the most variable expression (validation candidate genes). Equation 1: TPM > 0; Eq. 2: SD(Log2TPM) < 1; Eq. 3: |Log2TPM – AVRG(Log2TPM)| < 2; Eq. 4: AVRG(Log2TPM) > 5; Eq. 5: CV < 0.2; Eq. 6: SD(Log2TPM) > 1. Where TPM is transcripts per million, SD is standard deviation, AVRG is average, and CV is coefficient of variation. The equations are described in the text
How GSV Works
GSV analyzes the gene expression data from RNA-seq and selects genes that are highly expressed and stable across different conditions. It also filters out genes that are expressed at low levels, as these might not be reliable for RT-qPCR analysis. The tool was tested against other software using synthetic datasets and showed superior performance by effectively removing low-expression stable genes and creating a robust list of variable-expression validation genes.
Case Study: Aedes aegypti Transcriptome
To demonstrate its effectiveness, GSV was used on a real dataset from the mosquito species Aedes aegypti. The tool identified the most stable reference genes, eiF1A and eiF3j, for RT-qPCR analysis. Interestingly, it also revealed that some traditionally used mosquito reference genes were less stable in these samples, indicating they might not be the best choice for accurate gene expression analysis.
Advantages of GSV
Efficiency: It saves time and reduces costs by streamlining the selection of reference and validation candidate genes.
Accuracy: By ensuring the selection of stable reference genes, it improves the reliability of RT-qPCR results.
Versatility: The tool can handle large datasets, as shown in its successful processing of a meta-transcriptome with over ninety thousand genes.
The development of GSV marks a significant advancement in the field of gene expression analysis. By providing a reliable method for selecting reference and variable candidate genes, GSV enhances the accuracy and efficiency of RT-qPCR, making it a valuable tool for researchers studying gene expression across various biological conditions.
Availability – Project home page: https://github.com/rdmesquita/GSV
de Brito, M.W.D., de Carvalho, S.S., Mota, M.B.d. et al. (2024) RNA-seq validation: software for selection of reference and variable candidate genes for RT-qPCR. BMC Genomics [Epub ahead of print]. [article]