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Updated: Aug 9, 2025
Pooled CRISPR-Based Genetic Screens in Mammalian Cells
Published on: September 4, 2019
Efficient prioritization of CRISPR screen hits by accounting for targeting efficiency of guide RNA
Byung-Sun Park1,2, Heeju Jeon1,2, Sung-Gil Chi2
1Medicinal Materials Research Center, Korea Institute of Science and Technology, 5 Hwarangro-14-Gil, SeongbukGu, Seoul, 02792, Republic of Korea.
Background:
CRISPR-based screens are revolutionizing drug discovery as tools to identify genes whose ablation induces a phenotype of interest. For instance, CRISPR-Cas9 screening has been successfully used to identify novel therapeutic targets in cancer where disruption of genes leads to decreased viability of malignant cells. However, low-activity guide RNAs may give rise to variable changes in phenotype, preventing easy identification of hits and leading to false negative results. Therefore, correcting the effects of bias due to differences in guide RNA efficiency in CRISPR screening data can improve the efficiency of prioritizing hits for further validation. Here, we developed an approach to identify hits from negative CRISPR screens by correcting the fold changes (FC) in gRNA frequency by the actual, observed frequency of indel mutations generated by gRNA.
Results:
Each gRNA was coupled with the "reporter sequence" that can be targeted by the same gRNA so that the frequency of mutations in the reporter sequence can be used as a proxy for the endogenous target gene. The measured gRNA activity was used to correct the FC. We identified indel generation efficiency as the dominant factor contributing significant bias to screening results, and our method significantly removed such bias and was better at identifying essential genes when compared to conventional fold change analysis. We successfully applied our gRNA activity data to previously published gRNA screening data, and identified novel genes whose ablation could synergize with vemurafenib in the A375 melanoma cell line. Our method identified nicotinamide N-methyltransferase, lactate dehydrogenase B, and polypyrimidine tract-binding protein 1 as synergistic targets whose ablation sensitized A375 cells to vemurafenib.
Conclusions:
We identified the variations in target cleavage efficiency, even in optimized sgRNA libraries, that pose a strong bias in phenotype and developed an analysis method that corrects phenotype score by the measured differences in the targeting efficiency among sgRNAs. Collectively, we expect that our new analysis method will more accurately identify genes that confer the phenotype of interest.
Insights
This study introduces a new method to improve CRISPR screening accuracy by correcting for guide RNA efficiency bias. This approach enhances the identification of essential genes and potential drug targets, leading to more reliable results in genetic screens.
Area of Science:
- Genomics
- Molecular Biology
- Drug Discovery
Background:
- CRISPR-Cas9 screening is a powerful tool for identifying therapeutic targets in drug discovery, particularly in cancer research.
- Low-efficiency guide RNAs (gRNAs) in CRISPR screens can introduce bias, leading to false negatives and hindering the identification of critical genes.
- Accurate prioritization of gene targets is crucial for effective validation in drug discovery pipelines.
Purpose of the Study:
- To develop and validate a novel computational approach for correcting guide RNA efficiency bias in CRISPR screening data.
- To enhance the accuracy of identifying essential genes and potential therapeutic targets by accounting for variations in gRNA activity.
- To improve the reliability of hit identification in negative CRISPR screens for drug discovery.
Main Methods:
- Developed a method to correct fold changes (FC) in gRNA frequency by the observed indel mutation frequency, serving as a proxy for gRNA activity.
- Coupled each gRNA with a reporter sequence to measure its mutation-generating efficiency.
- Applied the developed analysis method to previously published CRISPR screening data.
Main Results:
- Indel generation efficiency was identified as a major source of bias in CRISPR screening results.
- The developed method effectively removed bias and demonstrated superior performance in identifying essential genes compared to conventional fold change analysis.
- Successfully identified novel genes (nicotinamide N-methyltransferase, lactate dehydrogenase B, polypyrimidine tract-binding protein 1) that synergize with vemurafenib in A375 melanoma cells.
Conclusions:
- Variations in target cleavage efficiency among sgRNAs introduce significant bias in CRISPR screening phenotypes.
- The developed analysis method corrects phenotype scores based on measured targeting efficiencies, leading to more accurate identification of genes of interest.
- This approach is expected to improve the precision of identifying genes that confer specific phenotypes in genetic screens.
