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February 16, 2021 | PCR Solutions

Answering your questions about successful gene expression analysis by digital PCR

Performing a successful gene expression analysis on the QIAcuity Digital PCR System requires considering few parameters, including sample input, dilutions and proper controls. The QuantiNova LNA PCR Assays provide highly sensitive and accurate locked nucleic acid (LNA)-enhanced digital PCR quantification for mRNA and lncRNA targets, detecting even the smallest expression changes at the lowest concentrations.

This 2020 webinar demonstrated analysis of gene expression data with accuracy and reliability using the QIAcuity Software Suite, resulting in publication-quality fold change and fold regulation results. Below, we’ve collected some answers to common questions based on the Q&A with our R&D expert, Dr. Ronny Kellner, following his webinar.

Gene expression analysis using LNA-based assays on the QIAcuity Digital PCR System – watch on-demand.

 

When can we use probe or EvaGreen for expression applications? Is there any recommendation to select one over the other?    

Both methods are capable of capturing precise gene expression levels in different organisms and sample types. In the case of off-target amplification with the used primers, probe-based assays provide higher specificity as intercalating dyes like EvaGreen bind to the unwanted amplicons resulting in an over quantification of the target molecule. Besides, probe-based assays can be run in multiplex reactions. EvaGreen-based assays are more cost-effective.

Which fold change amount is expected to be significant among samples using dPCR since this technique detects accurately very small fold changes variations among samples?

In dPCR on the QIAcuity fold changes of >5% can be resolved along with a range of 40 to 86,000 target molecules per reaction using the 26K Nanoplate.

How well does this work for lncRNAs, with multiple isoforms expressed at just a few copies per cell?

Quantification of multiple isoforms of rare lncRNAs with the QIAcuity follows the same principles as quantifying multiple isoforms of rare mRNAs. The high sensitivity of the QIAcuity method enables the quantification of as low as 2 copies per reaction, which is up to 26.8 µl of input template for the 26K Nanoplate. Using isoform-specific assay designs will capture the expression of individual isoforms. Given the large diversity of lncRNAs in, for example, sequence length or secondary structure, it is recommended to use dedicated kits for cDNA synthesis.

How well does the EvaGreen master mix work with highly GC-rich targets? Can you use other master mixes or additives?

The EG master mix was developed for amplicons with a maximum of 65% GC content. Alternative master mixes are not recommended as the QIAcuity dPCR master mixes contain a special reference dye required by the software to distinguish filled from unfilled partitions and calculate the number of valid partitions. Further, the EG dPCR master mix is optimized for optimal distribution in microfluidic structures of the nanoplates.

Have you tried using dPCR for measuring the ratio of two alleles of one gene in RNA expression (allelic bias)?        

We have not tested that. In principle, this is possible with two assays, each specific to one of the two alleles. Using TaqMan probes will enable multiplexing of both assays in one reaction.

Can you do the RT step with the Nanoplate?

This is not recommended, but in principle, it could be done for a single plate. In the QIAcuity Four and Eight, up to 8 plates can be loaded, resulting in queuing plates with waiting times of up to 4 hours at 40 degrees. Under such conditions, in-plate RT is highly inconsistent. A dedicated solution for that is currently under development.

Do you have pathway-based gene expression assays using QIAcuity (similar to RT2 PCR Profiler)?

Currently, we do not offer a pathway-based gene expression panel for dPCR.

How does the software w/Poisson distribution calculate the normalization using the HKG to give a fold change of target?

Fold change calculations are based on copies/µl that is calculated for each well individually. When using housekeeping genes for normalization, the copies/µl counts of the target molecule are normalized against the copies/µl of one or more reference genes from the same sample. For fold change calculation, the normalized counts/µl of the reference sample is set to 1 and compared to the samples of interest.

In microbial detection, generally, the assays are done with a few dilutions of the sample. Can the software calculate it all and give output as targets/µl?

In the current software version, it is not possible to assign a dilution factor to the sample.

Is this method applicable for oncology gene expression studies?

This method is applicable for oncology gene expression studies as dPCR on the QIAcuity is intended for molecular biology applications. However, it is not intended for the diagnosis, prevention or treatment of a disease.

Are 8.5K partitions good enough for low abundant circulating targets (such as lncRNAs)?

It is recommended to use the 26K Nanoplate for very low amounts of target molecules as more template (up to 26.8 µl) can be added to a single reaction. Also, the limit of detection of the 26K Nanoplate is lower compared to the 8.5K Nanoplate.

Does "normalization" approaches in dPCR follow the same principles as with qPCR when quantifying circulating RNA?

Normalization against reference targets works the same in dPCR and qPCR. In dPCR copies/µl counts of the target molecule are normalized against the copies/µl of one or more reference genes from the same sample.

You mentioned there are assays for human, mouse and rat. How about plants?

The QuantiNova LNA PCR Assay portfolio does not cover plants.