Cookies on the
LGC website
We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we’ll assume that you are happy to receive all cookies on the LGC website. However, if you would like to, you can change your cookie settings at anytime.
Question markFind out more

LGC scientists outline strategy for minimising experimental error when using RT-qPCR

01 Oct 2014
If gene expression measurement is going to realise its full potential for diagnosing and monitoring patients, LGC scientists believe the reporting of studies using reverse transcription quantitative PCR (RT-qPCR), and the standardisation of measurements, needs to be improved.
 
In a study published in Analytical and Bioanalytical Chemistry, scientists from LGC’s Molecular and Cell Biology Team discuss the steps involved in gene expression measurement that need consideration for accurate, reproducible analysis when dealing with patient samples.
 
Gene expression is the process by which information encoded in a gene is used in the synthesis of ribonucleic acid (RNA) or, through an RNA intermediary, a protein. It is the process that determines whether a cell is, for example, a liver cell or a muscle cell. It is also the process by which a cell could develop into a cancer cell.
 
The ability to measure the level at which a particular gene is expressed within a cell, tissue or organism can allow the detection and quantification of mutations that act as disease markers, providing important insights into patient health.
 
RT-qPCR is an established, simple and effective technique that enables rapid and precise assessment of changes in gene expression. It has been used to measure bacterial gene expression and RNA viral loads, to evaluate cancer status, track disease progression and response to treatment. As a result, this method is being applied to the discovery and development of putative biomarkers. However, for the analysis to be clinically informative, reliable measurements that are reproducible between laboratories are essential.
 
The paper highlights the stages at which variability can be introduced into the measurement process, and suggests ways to minimise these technical errors. By employing such strategies, scientists can maximise the impact of gene expression studies, increasing the likelihood of robust findings and eventual translation to clinical tools.
 
Rebecca Sanders, a researcher in the Molecular and Cell Biology team, and one of the authors of the paper, said: “We performed a review of articles published reporting RT-qPCR data and found that they often don’t report all experimental details relating to RTqPCR experiments.
 
“These cover key aspects including sample acquisition, assay design and validation as well as details about data analysis, enabling other scientists to easily assess and, if necessary, repeat the experiment. This is fundamental if findings are to be corroborated, which is in turn crucial for the observation to be translated into a clinically useful tool.”
 
In addition to identifying the various steps at which error can be introduced and suggesting appropriate controls, the paper also outlines the considerations required to improve measurement reproducibility.
 
Rebecca said: “In adopting these measures, scientists will increase the likelihood that significant findings are both real and translatable to routine clinical care.”
 
This study was funded under the National Measurement System Chemical and Biological Metrology programme, as part of a project entitled ‘Mechanisms for SI traceable bio molecular metrology’. This project is investigating the ability of a range of technologies to perform molecular enumeration and describe how such approaches can be used to assign traceable values to reference materials to facilitate traceable measurement.
 
To download the paper, entitled ‘Considerations for accurate gene expression measurement by reverse transcription quantitative PCR when analysing clinical samples’, visit the Springer website.