Genome-Wide CRISPR Screening: Coverage, MOI and Readout Design

A screen is defined by three numbers and one design choice:

• • Coverage: cells per guide at the point of selection.
• • MOI: integrations per cell, which determines whether a phenotype can be attributed to one guide.
• • Depth: sequencing reads per guide, which determines whether abundance changes are measurable.
• • Readout: what you select or sort on, which determines whether the phenotype is visible at all.

Get these right and a modest screen produces interpretable hits. Get them wrong and a large screen produces a list that will not validate.

Coverage is the single strongest predictor of screen performance, because it sets the noise floor for guide abundance estimates.

Two practical refinements. First, coverage must be maintained at every bottleneck — transduction, selection, splitting, and harvest — not only at the start. Second, if the phenotype is subtle, increase coverage rather than library size: a smaller library at high coverage outperforms a larger one at the margin.

Multiplicity of infection determines how many guides each cell receives. At high MOI, many cells carry two or more, and a phenotype cannot be assigned to a single perturbation.

• • Target MOI 0.1–0.3 for knockout and interference libraries; this keeps the majority of transduced cells singly integrated.
• • Measure it, don't assume it. MOI depends on cell type, viral titer, and transduction conditions; determine it empirically for each new batch and cell line.
• • Verify by sequencing the cassette. A proportion of double integrants is acceptable only if it is quantified and reported.

The readout determines the biological question you can answer. A dropout screen will not find a regulator of a non-essential pathway, and a reporter screen will not find genes that affect viability.

Distance matters. The closer the readout is to the mechanism, the fewer false positives at the hit-calling stage — and the more work required to build the assay.

• • Reads per guide: a few hundred is a reasonable planning figure for reliable abundance estimates.
• • Replicate structure: two to three biological replicates, with library-level replicates distinguished from transduction replicates.
• • Control arms: baseline library at the start of selection, plus non-targeting guides at a few percent.
• • Analysis plan: pre-specify the aggregation from guides to genes, the normalization, and the hit-calling method. Best-guide reporting inflates false positives.

A screen is a nomination step. The sequence that makes hits usable:

1. Re-test top candidates individually (knockout or CRISPRi, 2–3 guides each).
2. Confirm the perturbation worked at protein or transcript level.
3. Measure the same phenotype in the individual format that the screen used, then in a second assay.
4. Where the claim is mechanistic, add a rescue or a second modality.

Screens that skip step 1 produce hit lists; screens that complete the sequence produce findings.

Before ordering a library, write these eight numbers down. If any of them is unknown, the screen is not ready:

1. Guides in the library, and guides per gene.
2. Cells per guide required at selection.
3. Total cells needed at transduction — higher than at selection, because transduction efficiency is below 100%.
4. MOI target and the empirical measurement plan.
5. Number of doublings over the selection window.
6. Sequencing reads per guide, and total reads per sample.
7. Number of replicate arms, including the baseline library.
8. Positive and negative control guides, and their expected behaviour.

The third and fifth items are the most often underestimated: a screen planned at 500 cells per guide at selection may need several times that at transduction, and a long selection window quietly reduces effective coverage through uneven growth.

EDITGENE builds screening-ready models: CRISPRi and knockout lines with documented single-integration behaviour, reporter lines for expression readouts, and matched parental controls — plus arrayed validation of nominated hits.

Tell us the phenotype and the readout you need. Contact EDITGENE to request a project consultation or quote.

Coverage, MOI, and depth recommendations are planning ranges; requirements depend on cell type, doubling time, library design, and effect size.

Screen hits are hypotheses until individually validated; guide-level effects should be aggregated to the gene level before interpretation.

• • Shalem O, et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science. 2014;343:84–87.
• • Wang T, et al. Genetic screens in human cells using the CRISPR-Cas9 system. Science. 2014;343:80–84.
• • Hart T, et al. Evaluation and design of genome-wide CRISPR/SpCas9 knockout screens. G3. 2017;7:2719–2727.
• • Doench JG, et al. Optimized sgRNA design to maximize activity and minimize off-target effects. Nature Biotechnology. 2016;34:184–191.