How to Design sgRNAs for Enhancer Deletion

Design two guides flanking the element, cutting inward, with an intervening distance of roughly 200 bp to 2 kb — efficiency falls sharply beyond a few kilobases. Use two independent guide pairs with different breakpoints, verify each deletion by junction PCR plus sequencing, and confirm zygosity. Everything else in this article is about avoiding the specific ways that plan goes wrong.

The guides follow from the deletion interval, not the other way round. Decide the interval as described in our piece on deletion fragment size: accessible footprint, summit included, 50–150 bp buffer, no neighbouring element or promoter inside.

Then mark two things on the map: the bases that must be removed (the summit and core motif), and the bases that must not be cut (any element you intend to preserve, and the promoter of the target gene).

Two guides cutting inward at 500–800 bp apart is the workhorse configuration.

• • Repeat content. Guides landing in Alu or LINE sequence produce unreliable junctions and are hard to verify. Filter them out rather than hoping.
• • SNPs in your cell line. A mismatch in the guide's seed region reduces cutting efficiency in that background specifically. Check the line's genotype, not the reference genome.
• • GC extremes. Very high or very low GC guides tend to underperform; the usual 40–70% window is a reasonable filter.
• • Homopolymer runs. Long runs of a single base reduce cutting and complicate sequencing.
• • Overlap with factor motifs. If the guide's cut site sits on a TF motif you want to keep, the deletion will confound motif loss with element loss.

One pair gives one breakpoint, one junction, one clone phenotype. If the phenotype is absent, you cannot tell whether the element is dispensable or the deletion failed. If the phenotype is present, a reviewer will ask whether the breakpoint position caused it.

Two pairs with different breakpoints spanning the same core solve both problems, and cost little more than one: same transfection, same screening pipeline, twice the guides ordered.

1. Junction PCR with primers outside both breakpoints. A product at the predicted size confirms the deletion; a product at wild-type size indicates the unedited allele.
2. Sanger or amplicon sequencing across the junction. Indels at the junction are common and can shift reading frames of nearby elements or create new motifs.
3. Digital PCR or quantitative PCR to determine zygosity; heterozygous clones will show both wild-type and junction products.
4. Absence of the deleted interval. A primer pair inside the deleted region should give no product; this catches mixed populations and unintended duplications.
5. Off-target check at the nearest homologous sites if the guides have close matches in the locus.

• • Non-targeting guide pair processed through the same pipeline, to control for transfection and selection.
• • A control deletion of an element known to be dispensable in the same cells, to show the assay can detect what it should.
• • Matched clones from the same editing campaign, to avoid batch effects between genotypes.
• • Re-sequencing of the target gene's coding region if the deletion is close enough to affect it.

That last row is diagnostic rather than fatal: discordance between two deletions of the same core usually points to a second functional element near one breakpoint.

EDITGENE designs paired-guide strategies, screens clones by junction PCR and digital PCR, confirms breakpoints by sequencing, and delivers clone-matched controls — including combinatorial series for redundancy questions.

Send us the coordinates and the annotation you are working from. Contact EDITGENE to request a project consultation or quote.

Guide efficiency and deletion outcomes vary by locus, chromatin state, cell type, and delivery method; spacing recommendations are planning guidance, not guarantees.

Every clone used for interpretation should have its junction sequenced and its zygosity confirmed; junction PCR alone does not exclude complex rearrangements.

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• • Ran FA, et al. Genome engineering using the CRISPR-Cas9 system. Nature Protocols. 2013;8:2281–2308.
• • Canaj H, et al. Deep profiling reveals substantial heterogeneity of integration outcomes in CRISPR knock-in experiments. Nature Biotechnology. 2019;37:1–8.
• • Tycko J, et al. Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements. Nature Communications. 2019;10:4063.