๐Ÿงฌ CRISPR gRNA Design & Analysis Tool

Design gRNAs ยท Analyze off-targets ยท Verify target sites

๐Ÿ“˜ New to CRISPR? Read the tutorial to learn how to choose guides and interpret results.
Example: ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG

๐Ÿงฌ 1. CRISPR Basics

CRISPR-Cas9 is a programmable nuclease that cuts DNA at a target site defined by two components:

  • Guide RNA (gRNA / spacer) โ€” 20 nt sequence complementary to the target DNA.
  • PAM โ€” Protospacer Adjacent Motif, a short sequence (e.g., NGG for SpCas9) that Cas9 requires immediately 3' of the guide-binding site.
Key rule: No PAM = no cut. A perfect 20-nt match without a PAM will not be cleaved.

๐ŸŽฏ 2. gRNA Design โ€” Result Interpretation

Input format

Provide a DNA sequence (A/C/G/T) plus a PAM pattern. The tool scans both strands and returns all possible 20-nt guides followed by a valid PAM.

Columns explained

ColumnMeaningPreferred value
Guide20-nt spacer sequenceUnique in genome
PAMProtospacer Adjacent MotifMatches chosen Cas variant
Strand+ (sense) or โˆ’ (antisense)Both are usable
Position1-based start in targetโ€”
GC%G+C content of the guide40โ€“60%
ScoreHeuristic on-target quality (0โ€“100)โ‰ฅ 80

How the score is calculated

  • Start at 100.
  • โˆ’30 if GC < 30% or > 70%; โˆ’15 if outside 40โ€“60%.
  • โˆ’25 if the guide contains TTTT (Pol III termination signal).
  • โˆ’15 if it contains GGGG (secondary structure risk).
  • โˆ’20 if it can self-anneal (self-complementarity).

Score interpretation

ScoreRatingRecommendation
80โ€“100ExcellentTop priority โ€” use if off-targets are clean.
60โ€“79AcceptableUse if no better option; validate experimentally.
< 60PoorAvoid โ€” high chance of low editing efficiency.

Worked example

Suppose a candidate GCCATTGTAATGGGCCGCT + GAA scores 85 with GC = 55%. Interpretation:

  • GC within optimal range โ†’ good stability.
  • No poly-T, no poly-G, no self-complementarity โ†’ no penalties.
  • This guide is a strong candidate for experimental validation.
Tip: Always design 2โ€“3 independent guides per target gene. Even a perfect in-silico score can fail in the lab.

๐Ÿ”Ž 3. Off-Target Analysis โ€” Reading the Results

The seed region

The last 10โ€“12 nt at the 3' end of the guide (adjacent to the PAM) โ€” the seed region โ€” is the most critical for Cas9 binding. Mismatches here usually abolish activity; mismatches at the 5' end are usually tolerated.

Result interpretation

Off-target seed matchesMeaningAction
0 hits No seed match in the searched reference โ†’ very low off-target risk. Proceed with this guide.
1โ€“2 hits Some potential off-targets โ€” inspect the context. Verify if the site is in a coding region; consider alternatives.
โ‰ฅ 3 hits High off-target risk. Choose a different guide if possible.

What the columns mean

  • Guide โ€” the query guide used in the search.
  • Seed region โ€” the last 12 nt used for matching.
  • Position in reference โ€” 1-based coordinate of the match.
  • Context (ยฑ10 nt) โ€” surrounding sequence so you can judge whether the site looks like a real protospacer (with its own PAM).
Important limitation: This is a simplified seed-based scan, not a full genome-wide alignment. For real experiments, always confirm with validated tools: Cas-OFFinder, CRISPOR, Benchling, or CHOPCHOP.

โœ… 4. Target-Site Verification

Purpose

Confirms whether a chosen guide + PAM exists in a given target sequence. Useful before ordering oligos, or to troubleshoot a failed experiment.

Match types

Match typeWhat it meansVerdict
exact Full guide + PAM present on the + strand. โœ” Target site is valid.
exact (reverse complement) Full guide + PAM present on the โˆ’ strand. โœ” Valid (CRISPR works on both strands).
guide only (PAM missing) The 20-nt guide exists but no PAM follows. โœ— Cas9 will not cut this site.
No match Guide not found in target. โœ— Wrong sequence or wrong guide.

Worked example

Guide = GCCATTGTAATGGGCCGCT, PAM = GAA, target = ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG.

  • Full sequence GCCATTGTAATGGGCCGCTGAA is present starting at position 3.
  • Match type: exact, strand +.
  • Interpretation: the target site is valid โ€” proceed to design experiments.

๐Ÿš€ 5. Recommended Workflow

  1. Obtain target sequence (gene of interest, exon, promoter, etc.) from NCBI or Ensembl.
  2. Tab 1 โ€” Design: run gRNA design, filter for GC 40โ€“60% and Score โ‰ฅ 80.
  3. Tab 2 โ€” Off-target: check the top 3โ€“5 candidates against a reference; prefer 0โ€“1 hits.
  4. Tab 3 โ€” Verify: confirm the chosen guide + PAM exists in the target.
  5. Cross-validate with CRISPOR / CHOPCHOP to catch what the heuristic misses.
  6. Order 2โ€“3 guides per target and test in parallel.
  7. Validate editing by Sanger sequencing, T7E1 assay, or NGS.

โš ๏ธ 6. Common Pitfalls & Best Practices

Perfect score โ‰  perfect guide: In-silico scores predict but do not guarantee editing efficiency. Chromatin state, methylation, and delivery method all matter.
Off-target โ‰  only seed: Real off-targets can exist with mismatches outside the seed. Use validated aligners for critical work.
Poly-T warning: Guides containing TTTT can terminate U6-driven transcription โ†’ poor gRNA expression.
SNPs in the target: Population SNPs inside the guide or PAM can abolish cutting in some individuals. Check dbSNP for your target region.
Best practice: Design 2โ€“3 independent guides, use at least one with a high score AND a unique seed region. Validate editing by sequencing.

Design checklist

  • โœ” GC% between 40โ€“60%
  • โœ” No poly-T (TTTT) or poly-G (GGGG)
  • โœ” Score โ‰ฅ 80
  • โœ” 0โ€“1 off-target seed matches in reference
  • โœ” Target site confirmed by verification step
  • โœ” Cross-validated with a second tool
  • โœ” 2โ€“3 guides ordered per gene
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