Limitations of qPCR detection in evaluating CRISPR/Cas9 gene knockout efficiency

Real-time quantitative polymerase chain reaction (qRT-PCR/qPCT), a widely used technique for gene expression quantification, has limitations in evaluating CRISPR/Cas9-mediated knockout (KO) efficiency despite its extensive applications across research fields. This paper analyzes why qPCR is not fully suitable for assessing knockout efficiency in KO cells, examining its fundamental principles, practical applications, and case studies.

1. The mismatch between qPCR technology and KO cell evaluation

1.1 Inconsistent detection objects

While qPCR primarily detects mRNA levels in cells, CRISPR/Cas9 gene editing directly targets genomic DNA. This fundamental mismatch makes qPCR less accurate in measuring true genome editing outcomes. KO may lead to the occurrence of nonsense-mediated mRNA decay (NMD), in which case qPCR can detect downregulation or disappearance of the gene's mRNA levels.  However, not all KOs result in NMD, so using qPCR to determine the success of KO is insufficient.

1.2 "blind spots" of small fragment insertion or deletio

The most common outcome of CRISPR/Cas9 editing is the creation of small insertions or deletions (indels) at DNA cleavage sites. These minor modifications typically do not affect transcription processes, allowing the edited gene to continue producing mRNA, and when a gene is knocked out, cells may activate compensatory mechanisms. In some cases, this could even upregulate the expression of homologous genes, further complicating qPCR results.

1.3 Challenges in primer design

Quantitative PCR (qPCR) relies on the binding of specific primers to target sequences. When a genome undergoes editing, if the primer-binding regions remain unaffected, even after functional knockout of genes, qPCR may still detect false-positive signals. It is emphasized that primer design is crucial for the accuracy of qPCR results when evaluating different gene editing detection methods. However, designing primers that perfectly match all possible editing outcomes proves challenging in cases where editing patterns are unknown.

2. Limitations of qPCR application under different gene editing conditions

2.1 Detection blind spots caused by small indels

When CRISPR/Cas9 introduces small insertions/deletions (indels) at target sites, these changes are often insufficient to affect transcription and qPCR detection. Comparative analysis of various gene editing detection methods reveals that for 1-10 bp indels, qPCR sensitivity is significantly lower than sequencing-based methods, with detection rates ranging only 30-50%. Since qPCR can only detect the presence or absence of mRNA rather than its functional status, even when genes have been functionally knocked out (resulting in frameshift mutations or premature termination codons), normal mRNA expression levels may still be detected. This phenomenon could mislead researchers into concluding that the editing was unsuccessful.

2.2 Detection capability of large fragment deletion

When gene editing results in large deletions, qPCR may show significantly reduced signals if the deletion region contains primer binding sites. However, such quantitative results still cannot fully reflect knockout efficiency, as mixed editing states (including complete knockouts, partial knockouts, and unedited cells) may exist within the cell population. Certain large deletions might induce abnormal transcript generation, which could be recognized by specific qPCR primers. Through deep sequencing analysis, it has been found that even under the same single-guide RNA (sgRNA) action, different cells can produce over 10 distinct editing patterns. This complexity makes qPCR difficult to provide accurate quantitative information.

2.3 Complex interaction between stop codon introduction and NMD mechanism

When gene editing introduces an early termination codon, it theoretically triggers the NMD mechanism to degrade mRNA containing abnormal termination codons. Studies have shown that the NMD mechanism can indeed target many transcripts containing premature termination codons, including viral and host RNAs, serving as a quality control mechanism. However, the efficiency of the NMD mechanism is influenced by multiple factors: the position of the termination codon must be at least 50-55 nucleotides away from the last exon splice site to effectively activate NMD; long 3'UTRs may also trigger NMD, though with significant variations in efficiency; and there are notable differences in NMD efficiency across different cell types.

Furthermore, certain RNAs can evade NMD surveillance through specific mechanisms. Studies have shown that the transcriptome of Kaposi sarcoma-associated herpes virus (KSHV) contains numerous features that may trigger NMD, yet not all transcripts exhibiting these characteristics undergo effective degradation. This complexity makes it challenging to determine gene knockout efficiency solely based on qPCR results.

3 Case Analysises--The actual performance of qPCR in the evaluation of gene knockout efficiency

3.1 NMD and viral RNA studies

In a study published in Nature Communications, Zhao et al. (2020). conducted a detailed analysis of how NMD targets cellular and viral RNAs to suppress KSHV. They found that while NMD can recognize and degrade some RNAs with abnormal features, this recognition is not complete. Certain viral RNAs can evade degradation even when triggering NMD signatures (as shown in Figure 1), indicating that relying solely on qPCR to detect mRNA level changes may not accurately reflect the true post-CRISPR/Cas9 editing status. Notably, they observed that ORF50 mRNA, despite containing features like a long 3'UTR and introns that should activate NMD, has its degradation efficiency regulated by multiple factors. This complexity further demonstrates that qPCR results require comprehensive interpretation through integrated methods to obtain reliable conclusions.

Figure 1. NMD targets the UPR pathway in cells to limit the transcription of ORF50

3.2 Research on gene compensation mechanism

El-Brolosy et al.(2017). reported in Nature the transcriptional adaptive responses following gene knockout. When a gene is knocked out to produce an early termination codon, it not only triggers NMD degradation of the corresponding mRNA but may also activate and upregulate compensatory mechanisms in homologous genes. This complex response complicates qPCR interpretation, as detected mRNA level changes may reflect intricate regulatory network responses rather than simple gene knockout effects (as shown in Figure 2).

Figure 2 Transcriptional adaptation involves chromatin remodeling dependent on the activity of decay factors

3.3 Comparative study of gene editing detection methods

Systems such as Smits compared the advantages and disadvantages of various gene editing detection methods. They found that compared to gene sequencing, qPCR has significant limitations in detecting CRISPR/Cas9 edits, particularly when identifying small indels. For evaluating gene editing efficiency, multiple complementary methods should be combined rather than relying solely on qPCR. Even if a frameshift mutation occurs, situations like NMD or exon skipping may prevent qPCR from detecting it (as shown in Figure 3).

Figure 3. Results of several transcode mutations generated by CRISPR/Cas9

4 Alternative and complementary approaches

4.1 DNA-based approaches

1) Sanger sequencing: the most direct method to verify the changes of editing sites, but the resolution ability of mixed editing groups is limited;

2) High-throughput sequencing: It can accurately detect and quantify various editing patterns, which is the most comprehensive evaluation method at present;

3) Digital PCR: more sensitive than qPCR, can detect low frequency editing events;

4) T7E1 nuclease cutting method: can detect hybrid editing and semi-quantitative properties.

4.2 Protein-based approaches

1) Western blot analysis: Direct detection of the presence of target protein is the gold standard for functional KO evaluation;

2) Proteomics/mass spectrometry analysis: more comprehensive evaluation of changes in target proteins and related protein networks;

3) Immunofluorescence staining: can detect target protein at single cell level.

4.3 Function-based approach

1) Phenotypic analysis: observation of cell morphology, growth and functional changes;

2) Functional experiments: design specific tests for the function of target genes;

3) Single cell analysis: to evaluate heterogeneous responses in a population of cells.

In conclusion, qPCR, as a mature quantitative method for gene expression analysis, has notable limitations when evaluating CRISPR/Cas9-mediated gene knockout efficiency. These limitations primarily stem from qPCR's detection of mRNA rather than genomic DNA, difficulties in accurately identifying small indels, the complexity and variability of the NMD mechanism, and transcriptional adaptation responses following gene editing. Therefore, relying solely on qPCR to assess knockout efficiency may lead to misjudgment. It is recommended to employ a comprehensive evaluation approach combining multiple complementary methods, particularly with genomic sequencing and protein-level validation, to obtain more accurate conclusions.

References

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8. Tuladhar R, Yeu Y, Tyler Piazza J, Tuladhar R, Yeu Y, Tyler Piazza J,  et al. CRISPR-Cas9-based mutagenesis frequently provokes on-target mRNA misregulation. Nature Communications. 2019;10:4056.

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08/19/2025

Anqi Chen

Supervisor of R&D

GenuIN Biotechnologies