CRISPR Screen Protocol for Genome-Wide Gene Analysis

CRISPR-based screening has transformed genome-wide gene analysis by enabling systematic interrogation of gene function. This approach utilizes pooled guide RNA (gRNA) libraries to induce targeted genetic modifications, allowing researchers to identify genes involved in cellular processes such as drug resistance, proliferation, and differentiation.

A well-designed CRISPR screen requires careful planning, from reagent preparation to data interpretation. Each step must be optimized to ensure reliable results.

Reagent Preparation

The success of a CRISPR screen hinges on the quality and consistency of reagents. Every component, from plasmid DNA to transfection reagents, must be carefully selected and prepared to minimize variability. Plasmid DNA purity is critical, as contaminants such as endotoxins can interfere with transfection efficiency and cell viability. High-quality plasmid DNA should be prepared using endotoxin-free maxi or mega prep kits, with concentrations verified via spectrophotometry in the 500–1000 ng/µL range. Agarose gel electrophoresis can confirm plasmid integrity, ensuring no degradation or unwanted recombination events.

Guide RNA (gRNA) oligonucleotides must be synthesized with high fidelity to prevent off-target effects. Commercial synthesis providers offer gRNAs with or without chemical modifications, with 2′-O-methyl and phosphorothioate modifications enhancing stability in certain environments. Upon receipt, gRNAs should be resuspended in nuclease-free water or TE buffer at 100 µM and stored at -80°C to prevent degradation. Before use, aliquots should be thawed on ice.

Lentiviral packaging reagents determine the efficiency of viral particle production. The widely used three-plasmid system—comprising the transfer vector, packaging plasmid (psPAX2), and envelope plasmid (pMD2.G)—should be sequence-verified to prevent mutations that could affect viral production. Transfection-grade polyethyleneimine (PEI) or calcium phosphate reagents are commonly used for HEK293T cell transfection, with PEI requiring careful pH adjustment. The transfer vector to packaging plasmid ratio should be maintained at 4:3:1 to maximize viral yield while minimizing cytotoxicity.

To enhance viral transduction, polybrene or protamine sulfate is often added. Polybrene, typically used at 4–8 µg/mL, reduces electrostatic repulsion between the viral envelope and the cell membrane. Some cell types are sensitive to polybrene, requiring titration. For refractory cells, spinfection—centrifugation at 1000 × g for 90 minutes—can significantly improve uptake.

Library Design And Generation

Constructing a high-quality gRNA library is essential for a successful CRISPR screen. The library must maximize genome coverage while minimizing off-target effects.

Pooling gRNA Sequences

gRNA selection directly influences targeting efficiency and specificity. Computational tools such as CHOPCHOP, CRISPRko, and the Broad Institute’s GPP sgRNA Designer help identify optimal sequences by assessing on-target activity, off-target potential, and sequence uniqueness. Each gene is typically targeted by 3–10 gRNAs to ensure robust knockdown.

Once selected, gRNA sequences are synthesized as oligonucleotides and pooled to create a diverse library. Genome-wide libraries often contain 50,000–200,000 unique gRNAs, while focused libraries may include a few thousand. Oligonucleotide pools are amplified using PCR with high-fidelity polymerases to prevent sequence errors. Proper primer design is necessary to avoid amplification bias. The amplified gRNA pool is then prepared for cloning into lentiviral vectors.

Vector Cloning

gRNA sequences are inserted into a lentiviral backbone under a U6 or H1 promoter for strong, constitutive expression. Cloning methods include Gibson assembly, Golden Gate cloning, or ligation-based techniques. Golden Gate cloning is particularly efficient for large-scale library construction, utilizing type IIS restriction enzymes such as BsmBI or Esp3I.

Following ligation, recombinant plasmids are transformed into electrocompetent bacteria with high transformation efficiency (e.g., NEB 10-beta or Endura cells) to maintain library complexity. Plating on selective agar ensures each gRNA is adequately represented. Colony counting and plasmid extraction from pooled bacterial cultures confirm library diversity. The extracted plasmid pool undergoes next-generation sequencing (NGS) to verify uniform gRNA representation before lentiviral packaging.

Confirming Construct Integrity

Before large-scale viral production, gRNA constructs must be verified for correct integration and expression. Sanger sequencing of randomly selected clones confirms proper insertion and rules out mutations. Restriction enzyme digestion ensures expected fragment sizes.

A small-scale transduction in a test cell line, followed by RNA extraction and RT-qPCR, confirms gRNA expression. For knockout screens, Western blotting or flow cytometry can validate gene disruption in a subset of target genes. Ensuring library complexity and functionality at this stage is essential before proceeding to large-scale screening.

Transduction And Growth Conditions

Efficient and uniform transduction is critical for minimizing biases. The optimal multiplicity of infection (MOI), which represents the average number of viral particles delivered per cell, should be between 0.3 and 0.5 to ensure single viral integration events. A pilot transduction using a control lentivirus expressing GFP helps determine MOI via flow cytometry.

Once MOI is optimized, cells are plated at a density that supports robust growth. Lentiviral transduction is typically performed with polybrene to enhance viral entry. Some cell types, particularly primary or suspension cells, require alternative methods such as spinfection, which significantly increases transduction efficiency.

Following transduction, antibiotic selection enriches for successfully infected cells. The selection marker in the lentiviral vector determines the antibiotic used, with puromycin being the most common. A kill curve experiment establishes the minimal concentration required to eliminate untransduced cells while preserving viability. Puromycin concentrations typically range from 1 to 5 µg/mL, with selection lasting 3 to 5 days.

Screening Protocol

Once a stable population of transduced cells is established, the screening phase begins. Cells are subjected to experimental conditions designed to reveal functional genetic interactions, such as drug exposure or nutrient deprivation. The goal is to create selective pressure that allows cells with advantageous genetic modifications to survive while others are depleted.

To maintain statistical robustness, at least 300–500 cells per gRNA should be preserved throughout the experiment. Cells are cultured over multiple population doublings (10–14 days) to allow phenotypic changes to manifest. Sampling at defined intervals tracks shifts in gRNA representation, capturing both acute and long-term effects.

Sequencing And Data Readout

After screening, sequencing quantifies gRNA abundance in selected populations. Genomic DNA is extracted using column-based or phenol-chloroform methods to ensure high yield and purity. Since each gRNA integrates into the genome, at least 20 µg per sample is recommended to capture low-frequency gRNAs.

PCR amplification of gRNA sequences uses barcoded primers for multiplexing. High-fidelity polymerases prevent amplification bias, and cycle numbers are optimized to avoid over-representation of abundant gRNAs. The amplified products undergo gel purification or SPRI bead cleanup before next-generation sequencing (NGS) on platforms like Illumina NovaSeq or NextSeq. Sequencing depth should provide at least 300 reads per gRNA.

Raw sequencing data undergo quality control checks, including read alignment, removal of low-quality reads, and normalization to correct for PCR artifacts. Bioinformatic analysis with tools such as MAGeCK, CRISPResso, or PinAPL-Py quantifies gRNA enrichment or depletion. Statistical methods like the robust rank aggregation (RRA) algorithm prioritize candidate genes. Pathway enrichment tools such as GSEA or DAVID help identify affected biological networks. False discovery rate (FDR) thresholds below 0.1 minimize false positives while retaining meaningful insights.

Hit Verification

Candidate genes identified through sequencing require validation to confirm their functional relevance. This eliminates false positives and ensures observed effects are due to gene disruption rather than off-target effects or statistical anomalies. Validation typically involves independent gRNA constructs targeting the same gene and complementary approaches such as CRISPR interference (CRISPRi) or CRISPR activation (CRISPRa).

Functional assays measure gene perturbation effects on cellular behavior. In drug resistance screens, knockdown or knockout of candidate genes is tested in dose-response experiments to confirm altered sensitivity profiles. In proliferation studies, real-time cell tracking or clonogenic survival assays provide quantitative confirmation of growth effects. Transcriptomic analysis via RNA sequencing (RNA-seq) or quantitative PCR (qPCR) can assess downstream regulatory changes. These secondary assays establish mechanistic links between identified genes and observed phenotypes.