Benefits of Complementary Methods in Gene Expression Profiling

Realize the Potential of Using Multiple Methods

For a long time, the gold standard used to study a system’s gene expression levels has been qPCR. First, the total RNA of the sample is transcribed into cDNA, followed by a PCR step using a specific primer pair or primer/probe pair to amplify the target sequence. Then, measuring a fluorescent signal from the reaction gives an idea about the amount of cDNA and, thus, RNA in the sample. Hence, with the help of a standard curve, the absolute amount of RNA molecules containing the target sequence can be determined.

A newer addition to the market is ddPCR™ technology. In this workflow, a sample is partitioned into thousands of droplets containing limited nucleic acid templates. Next, each droplet — also called a partition — is amplified to the endpoint in a thermal cycler, with only droplets containing the target sequences becoming fluorescent. A droplet reader then measures the fluorescence levels of all partitions, with partitions containing a target registering as positive and partitions lacking a target being considered negative due to the lack of a fluorescent signal. Thus, absolute quantification of gene expression is possible.

While qPCR and ddPCR technologies allow the quantification of a single target sequence, NGS lets one identify and quantify multiple genetic features in one sample. A sequencing library must first be created from the sample for the multistep NGS workflow. This contains shorter DNA fragments that are attached to a solid surface. Next, all present sequences are identified through PCR amplification of all DNA molecules followed by sequencing of synthesized fragments. Finally, aligning the sequencing data against a reference genome allows the detection and quantification of known and unknown sequences.

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Benefits of Multiple Methods in Gene Expression Research

As outlined above, qPCR, Droplet Digital™ PCR, and NGS rely on different mechanistic principles. Hence, each technique has distinct advantages and disadvantages and is suitable for specific research questions.

All three methods allow quantifying gene expression levels of all or one specific target sequence. However, Droplet Digital PCR does not require a standard curve, which facilitates absolute quantification studies. On the other hand, to quantify the levels of multiple genetic features, NGS should be the method of choice since it determines all molecules in a sample.

Other factors to consider are sensitivity, reproducibility, and challenging sample types. The PCR enzymes and reactions are highly sensitive to inhibiting molecules and contaminants. Due to sample partitioning, Droplet Digital PCR can handle such contaminants without perfect amplification and is thus the better alternative when qPCR fails or gives inconclusive results.

Similarly, NGS and Droplet Digital PCR enable measuring small fold changes of genetic sequences reliably as they enrich for rare targets. NGS and ddPCR technologies can also handle small sample volumes, while Droplet Digital PCR was even shown to give meaningful results for single-cell samples.

While all approaches can be automated, ddPCR and NGS experiment setups are more labor-intensive, harder to train researchers on, and, thus, more prone to error. However, qPCR has been the standard procedure in many laboratories. Protocol transfer and adaptation are easy as many scientists have experience running qPCR experiments.

Lastly, ddPCR and NGS experiments require specific machines, materials, and assays that add to the cost of running a lab. Also, additional software is needed to analyze complex NGS data, while data interpretation is easier for qPCR and ddPCR experiments.

Comparison of qPCR, Droplet Digital PCR, and NGS Methods

Feature	qPCR	Droplet Digital PCR	NGS
Quantification	Relative, absolute, and standard curves needed	Absolute	Relative, absolute
Target numbers	Multiple (up to 5)	Multiple (up to 12)	Multiple variants detected (limitless)
Target numbers	Multiple (up to 5)	Multiple (up to 12)	Multiple variants detected (limitless)
Sample matrix complexity	Simple matrices	Simple to complex matrices	Simple to complex matrices
Sample volume	High volume needed	Low to high	Low
Reproducibility	Standardized	Standardized	Multiple steps, prone to errors
Workflow setup	Automated, fast	Automated, fast	Automated, labor-intensive, hard to train researchers on
Output	Data interpretation easy	Data interpretation easy	Complex, specialized data analysis needed

Assessing the Optimal Gene Expression Analysis Method for Later Research Stages

Having explored the different gene expression profiling methods and their advantages, one can now choose the appropriate method for their research question. NGS is the obvious choice to identify and characterize potential targets as it looks at all present molecules in a sample. However, understanding a target’s impact on the pathway requires focusing on several specific genetic sequences. In such cases, qPCR or ddPCR technology should be used to give insightful results.

Especially during drug optimization stages, reproducible results are needed with standardized workflows and little room for errors. This is where ddPCR technology excels, as it can be fully automated, giving fast and reliable results.

Gene expression profiling techniques are essential throughout all biopharma research stages. However, each method can be suitable to tackle a specific research question. Therefore, one should consider the costs, sample type, and required information to decide on their method of choice.

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