Sometimes your qPCR results may exhibit very low levels of gene expression in your samples or controls. If this is unexpected, you may wonder whether your results are accurate, if the problem lies with the experiment's design or if your sample's integrity is compromised.
One option is to run the experiment again. However, there are online resources, such as the National Center for Biotechnology Information (NCBI) database, that enable you to check if gene expression results for a specific tissue type are in line with results from other researchers. Consulting the NCBI database is quick and easy, and helps you avoid a laborious literature search. Accessing database information could give you more confidence in your results, or it might help you to optimize your experiment or experimental design. This reference material could also help you choose an appropriate control tissue to validate your experiment. Read on for some examples of situations in which researchers find these resources useful, and discover how to use them with confidence.
Let’s look at some examples where researchers benefited from consulting an online database of gene expression information.
Scenario 1: Researchers investigated vascular endothelial growth factor A (VEGFA) gene expression in human lymph tissue cells treated with a drug known to increase VEGFA gene expression. Their qPCR experiment indicated negligible VEGFA expression in both the treated cells and untreated controls.
Was this negligible expression a genuine biological phenomenon, or was it caused by a problem with the qPCR experiment? To help solve this puzzle, the researchers used the NCBI database to find the expected VEGFA gene expression in human lymph tissue.
Result: According to the database information, VEGFA expression is considered to be extremely low or negligible in human lymph tissue, which means that the results of the researchers’ qPCR experiment were likely to be accurate. To confirm this, the researchers used the online database again to find a tissue expected to express VEGFA in higher quantities, and identified human thyroid tissue.
To validate their qPCR experiment, the researchers used cells from human thyroid tissue as a positive control. They observed significant VEGFA expression in the thyroid tissue sample, and again noted negligible expression in the lymph tissue samples. This confirmed to the researchers that their qPCR experiment was working as expected, and their results were accurate.
Scenario 2: Researchers investigated Ephrin B2 (Efnb2) gene expression in mouse kidney tissue following treatment with a pro-angiogenic drug. They performed a qPCR experiment using the treated kidney tissue samples and matching control samples, and observed negligible Efnb2 expression in the samples from both treated mice and untreated control mice. The researchers then consulted the NCBI database to check the expected levels of Efnb2 expression in mouse kidney tissue.
Result: Using the online database, the researchers found that mouse kidney tissue is expected to express Efnb2, but at a relatively low level compared with other mouse tissues. They used the database to find a mouse tissue with high levels of Efnb2 expression, and identified joint tissue. Using cells from mouse joint tissue as a positive control, the researchers confirmed that their qPCR experiment could detect Efnb2 expression. They suspected that the low Efnb2 levels in the kidney samples had made it difficult to detect.
The researchers optimized their qPCR experiment to better detect Efnb2 gene expression at low levels. They increased the amount of complementary DNA (cDNA) in the qPCR reactions and chose a different housekeeping gene that mouse kidney tissue typically expressed at low levels. Following these changes, the researchers were able to successfully detect Efnb2 expression in the mouse kidney samples, and identified a significant increase in Efnb2 expression in their drug-treated samples.
In the scenarios above, both research teams searched for expected levels of gene expression after their qPCR experiments had produced unexpected results. It might also be useful to consult the NCBI database before conducting your experiments, particularly if you are using a specific cell or tissue source, or investigating a specific gene for the first time. This would enable you to choose an appropriate control tissue and view expected gene expression levels for your chosen tissue in advance. This could help you to anticipate your results more accurately, or to preemptively optimize your experimental procedure for very high or low levels of gene expression.
With these two scenarios in mind, let’s learn how to use these online resources. Let's use Scenario 1, VEGFA gene expression in human lymph tissue, as a step-by-step example.
Although using the Unigene EST database is useful and convenient, this database only approximates expected expression in specific tissues, and is not a highly accurate or comprehensive guide to gene expression levels. The tissue or cell samples that generate the cDNA libraries are not strictly defined, which means the database provides a largely crude measure of expected gene expression. Nevertheless, it is a useful first port of call when troubleshooting unexpected qPCR results, and can help identify potential control tissue samples and plan experiments.
For Research Use Only. Not for use in diagnostic procedures.