Source: NIH Image Gallery via Flickr.
Understanding what a cell is doing at any given moment is one of the biggest challenges in biology. As a scientist, I can’t simply ask a cell what it’s doing. I can’t ask whether it’s fighting a virus, responding to bacteria, or preparing to divide.
Instead, in the lab, I’ve learned that one of the most powerful ways to understand cell behavior is by measuring gene expression, the molecular signals that reveal which biological programs are active.
A helpful way to think about this is through economics. Economists estimate a country’s productivity using gross domestic product (GDP), which reflects the total output generated by its citizens and industries. In a similar way, scientists estimate a cell’s activity by measuring the output of its genes. When certain genes become more active, it signals that the cell has shifted its internal production, just like changes in GDP reflect shifts in a nation’s economy.
When a cell is infected by a virus or bacteria, it shifts its internal production lines: immune genes turn on, inflammatory molecules increase, and defensive pathways activate. Measuring gene expression allows researchers to see these changes in real time.
The Basic Idea: Counting the Messages
You can think about RNA as text messages sent from DNA to the cell’s protein making machines. When there are more messages, the gene is more active. But fewer messages signal that it is quieter. Most gene expression tests will follow these steps:
- Collecting cells or tissue
- Extracting RNA
- Converting RNA into a more stable DNA
- Measuring how much each target is present
Method 1: RT-qPCR
Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is one of the most common methods available to measure gene expression. It is a fast, sensitive and a relatively affordable method. In here, RNA is initially turned into cDNA using an enzyme called reverse transcriptase.
Then PCR will make many copies of the cDNA for a gene you care about. A fluorescent signal will grow as copies accumulate. The machine will then track when the signal crosses threshold.
If the signal crosses threshold earlier, there was more starting material. It reflects that there has been a higher gene expression.
Method 2: RNA Sequencing
RNA sequencing is similar to scanning an entire library instead of checking a few books. It measures thousands of genes at once, including rare ones. With the help of RNA sequencing, scientists try to:
- Turn RNA into cDNA
- Break it into pieces
- Read millions of small fragments with a sequencing machine
- Use software to map those reads back to genes
- Count how many reads match each gene
Having more readings for a gene means there is more expression. RNA sequencing is a powerful discovery method. That’s because it can reveal unexpected pathways and new gene variants.
Method 3: Microarrays
Microarrays were quite popular before RNA-sequencing came into play. It measures many genes at once, but only genes that are already on the array.
A microarray contains many different probes fixed into a chip. Each probe matches a known gene. Labeled cDNA from your sample will bind to matching probes. If the spot is brighter, there is more expression. Microarrays can still be useful for larger studies with tight budgets.
Method 4: Single Cell Sequencing
Like Democracy in America (1835) by Alexis de Tocqueville warned about the “tyranny of the majority,” gene expression averages can also hide important minorities. If half of cells are highly active and half are silent, the average may look normal, which is why single-cell sequencing matters.
This method is useful at the time of finding rare cell types. It can also be used to track how cells change during diseases. Moreover, this method is effective to understand how cells respond to a drug.
The Takeaway
As you can see, gene expression is not just “on” or “off”. It can shift due to temperature, time of day, sample handling and many other factors. However, it is a useful method to determine what genes are active right now.
