Gene Expression Analysis Methods: A Guide
What Is Gene Expression?
Before we explain the different gene expression analysis methods, it is important to understand exactly what gene expression is. Gene expression is where information from a gene is used to create a functional gene product. These products can be proteins if the genes are protein-coding, or RNA molecules if not. Gene expression is a carefully regulated process which gives rise to the phenotypes of all living organisms.
Measuring and analysing gene expression is important, as the level of expression of a particular gene within a cell can give large amounts of information. There are various gene expression analysis methods, including serial analysis of gene expression (SAGE), microarrays, and RNA sequencing (RNA-Seq).
Gene Expression Analysis Methods
The SAGE Method
SAGE is a transcriptomic technique which produces a snapshot of the mRNA in a sample. This snapshot is made up of small tags which correspond to fragments of RNA code in the sample, no matter which gene they are found in. Longer tags have also been created to give more confident identification of genes targeted.
SAGE output gives a list of short sequence tags and the number of times they were observed in the sample. This enables researchers to determine which mRNA section (and which gene) the sequence came from. SAGE achieves similar aims to microarrays, however, the results are more quantitative. Unlike with microarrays, the mRNA sequences for SAGE do not need to be done before the sample is processed. On a larger scale however, microarrays are more commonly used as they can process far more samples.
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Microarrays
Microarrays are used to genotype multiple sections of the genome or measure gene expression levels of many genes simultaneously. They are made up of a solid surface such as glass or plastic with microscopic DNA spots attached. Each spot contains picomoles of a specific DNA sequence (called probes) and these sequences can be short sections of a gene or other sections of DNA. Microarrays can be used to detect either DNA or RNA depending on what is required by a study.
The results from microarrays are quantified by the amount of luminescence detected – the emission of light as a result of binding between the two DNA sequences. This luminescence detection allows the relative abundance of relevant sequences to be detected. There are drawbacks to using microarrays, however, such as needing specific probes and having lower sensitivity when compared to RNA-Seq.
Using RNA-Seq For Gene Expression
RNA-Seq has become the standard way to analyse gene expression and better understand what is happening in a specific sample. It can analyse the transcriptome and allows the behaviours of all genes to be seen in response to specific stimuli. This enables the monitoring of gene behaviour and the pathways that are changing in response to different drugs or external conditions, whatever the cause of the response is.
RNA-Seq can also look at the differences in gene expression between different groups or treatments in trials, which allows for better comparisons between control and treated groups. It can detect rare or weakly expressed transcripts as well, allowing for higher specificity in a sample. RNA-Seq is a highly accurate tool that can provide information about minor and previously unnoticed changes, whether they are caused by different environmental conditions, different study groups, or through other study setups. The large volumes of data generated through clinical trials and research studies mean that the analysis stage of RNA-Seq data can be long.
Gene Expression Analysis at Fios
Our team take data at any stage of your research timeline in many different formats. Quality control (QC) is our first step taken once the data is received, to isolate any poor-quality samples. Once the data has been checked, analysis can start. For RNA-sequencing data, often this is through differential expression analysis. When samples are either controls or treated samples, for example, our team can look to find the differentially expressed genes between the two sample types. Once analysis is completed, an interactive and easy to navigate report is produced documenting the analysis methods, references and (QC) outcomes.
Find out more about gene expression analysis and how the Fios team can help with your studies:
