CRISPR Guide RNA Design Tool

Find guide RNA candidates from a DNA sequence, locate PAM sites, and rank sgRNAs with transparent first-pass rules. The tool helps students and researchers shortlist guides before genome-wide off-target analysis.

Design sgRNA candidates from a pasted DNA sequence

Start with SpCas9 NGG in Basic mode. Switch to Advanced mode for Cas12a, SaCas9, SpG, custom IUPAC PAMs, and cloning filters.

Choose a design mode

Basic mode finds common PAMs. Advanced mode exposes custom IUPAC patterns and guide filters.

DNA target sequence

Paste genomic DNA or a PCR amplicon. The scanner removes spaces and ignores non-DNA characters.

Region startRegion end

Clean length

153

bp scanned

Guide rules and filters

Select the nuclease, PAM pattern, and cloning filters that match your experimental plan.

Nuclease / PAM preset

Require 5′ GAvoid TTTTShow top 20

Current rule: 20 nt guide followed by an NGG PAM on the target DNA strand.

Live guide screen

Excellent guide found at 5–24

Best candidate: AGACCGTGGACAAGATCGAG next to PAM TGG. Score 100/100 with 55.0% GC.

Total hits

18

Excellent

18

Good

0

Review

0

Candidate map

The map shows the strongest candidates across your submitted sequence. Purple marks the PAM-side end.

Ranked guide candidates

Review top guides first, then confirm specificity with a genome-aware off-target search.

Rank	Guide DNA	PAM	Strand	Coordinates	GC%	Score	Main note
#1	AGACCGTGGACAAGATCGAG	TGG	+	5–24	55.0	100	GC% sits in the preferred 40–60% range.
#2	GTGCCACTCGATCTTGTCCA	CGG	-	11–30	55.0	100	GC% sits in the preferred 40–60% range.
#3	GGACAAGATCGAGTGGCACG	AGG	+	12–31	60.0	100	GC% sits in the preferred 40–60% range.
#4	GTGGCACGAGGACCTGTTCA	AGG	+	24–43	60.0	100	GC% sits in the preferred 40–60% range.
#5	GGACCTGTTCAAGGCCATCG	TGG	+	33–52	60.0	100	GC% sits in the preferred 40–60% range.
#6	GCTCCACGATGGCCTTGAAC	AGG	-	39–58	60.0	100	GC% sits in the preferred 40–60% range.
#7	CCATCGTGGAGCAGTACGAG	CGG	+	47–66	60.0	100	GC% sits in the preferred 40–60% range.
#8	CGGATCGTGAAGCTGCTGAC	CGG	+	67–86	60.0	100	GC% sits in the preferred 40–60% range.
#9	ATCGTGAAGCTGCTGACCGG	CGG	+	70–89	60.0	100	GC% sits in the preferred 40–60% range.
#10	GAACTCGTCGATGTAGCCGC	CGG	-	89–108	60.0	100	GC% sits in the preferred 40–60% range.
#11	CTACATCGACGAGTTCATCG	AGG	+	93–112	50.0	100	GC% sits in the preferred 40–60% range.
#12	CGAGTTCATCGAGGACGCCA	AGG	+	102–121	60.0	100	GC% sits in the preferred 40–60% range.
#13	AGGACGCCAAGGAGATCGTG	CGG	+	113–132	60.0	100	GC% sits in the preferred 40–60% range.
#14	CAAGGAGATCGTGCGGCTGA	AGG	+	120–139	60.0	100	GC% sits in the preferred 40–60% range.
#15	CTTCAGCCGCACGATCTCCT	TGG	-	122–141	60.0	100	GC% sits in the preferred 40–60% range.
#16	CCGCTCGTACTGCTCCACGA	TGG	-	50–69	65.0	90	GC% is acceptable but outside the strongest 40–60% band.
#17	GGAGATCGTGCGGCTGAAGG	AGG	+	123–142	65.0	90	GC% is acceptable but outside the strongest 40–60% band.
#18	GATCGTGCGGCTGAAGGAGG	AGG	+	126–145	65.0	90	GC% is acceptable but outside the strongest 40–60% band.

#1 Excellent

100

AGACCGTGGACAAGATCGAG

PAM TGG, strand +, coordinates 5–24, GC 55.0%.

GC% sits in the preferred 40–60% range.

#2 Excellent

100

GTGCCACTCGATCTTGTCCA

PAM CGG, strand -, coordinates 11–30, GC 55.0%.

GC% sits in the preferred 40–60% range.

#3 Excellent

100

GGACAAGATCGAGTGGCACG

PAM AGG, strand +, coordinates 12–31, GC 60.0%.

GC% sits in the preferred 40–60% range.

#4 Excellent

100

GTGGCACGAGGACCTGTTCA

PAM AGG, strand +, coordinates 24–43, GC 60.0%.

GC% sits in the preferred 40–60% range.

#5 Excellent

100

GGACCTGTTCAAGGCCATCG

PAM TGG, strand +, coordinates 33–52, GC 60.0%.

GC% sits in the preferred 40–60% range.

#6 Excellent

100

GCTCCACGATGGCCTTGAAC

PAM AGG, strand -, coordinates 39–58, GC 60.0%.

GC% sits in the preferred 40–60% range.

#7 Excellent

100

CCATCGTGGAGCAGTACGAG

PAM CGG, strand +, coordinates 47–66, GC 60.0%.

GC% sits in the preferred 40–60% range.

#8 Excellent

100

CGGATCGTGAAGCTGCTGAC

PAM CGG, strand +, coordinates 67–86, GC 60.0%.

GC% sits in the preferred 40–60% range.

#9 Excellent

100

ATCGTGAAGCTGCTGACCGG

PAM CGG, strand +, coordinates 70–89, GC 60.0%.

GC% sits in the preferred 40–60% range.

#10 Excellent

100

GAACTCGTCGATGTAGCCGC

PAM CGG, strand -, coordinates 89–108, GC 60.0%.

GC% sits in the preferred 40–60% range.

#11 Excellent

100

CTACATCGACGAGTTCATCG

PAM AGG, strand +, coordinates 93–112, GC 50.0%.

GC% sits in the preferred 40–60% range.

#12 Excellent

100

CGAGTTCATCGAGGACGCCA

PAM AGG, strand +, coordinates 102–121, GC 60.0%.

GC% sits in the preferred 40–60% range.

#13 Excellent

100

AGGACGCCAAGGAGATCGTG

PAM CGG, strand +, coordinates 113–132, GC 60.0%.

GC% sits in the preferred 40–60% range.

#14 Excellent

100

CAAGGAGATCGTGCGGCTGA

PAM AGG, strand +, coordinates 120–139, GC 60.0%.

GC% sits in the preferred 40–60% range.

#15 Excellent

100

CTTCAGCCGCACGATCTCCT

PAM TGG, strand -, coordinates 122–141, GC 60.0%.

GC% sits in the preferred 40–60% range.

#16 Excellent

90

CCGCTCGTACTGCTCCACGA

PAM TGG, strand -, coordinates 50–69, GC 65.0%.

GC% is acceptable but outside the strongest 40–60% band.

#17 Excellent

90

GGAGATCGTGCGGCTGAAGG

PAM AGG, strand +, coordinates 123–142, GC 65.0%.

GC% is acceptable but outside the strongest 40–60% band.

#18 Excellent

90

GATCGTGCGGCTGAAGGAGG

PAM AGG, strand +, coordinates 126–145, GC 65.0%.

GC% is acceptable but outside the strongest 40–60% band.

CRISPR guide RNA design diagram showing DNA target sequence, PAM sites, sgRNA candidates, GC content, and guide ranking — Figure 1. CRISPR guide selection starts with a protospacer next to a nuclease-specific PAM. SpCas9 usually uses a 20 nt guide next to NGG, while Cas12a uses a T-rich PAM upstream of the guide. The diagram connects guide coordinates, PAM orientation, GC balance, and sequence-quality flags.

What this guide-design tool checks first

Use this page when you have a target DNA region and need candidate guide RNAs quickly. Paste the sequence, choose a nuclease, and review guides beside valid PAM sites. For a PAM-only scan without guide ranking, use the PAM Sequence Finder first.

The calculator scores sequence features that researchers check before ordering guides: GC percentage, homopolymer runs, U6-compatible 5′ G, and poly-T motifs. It also maps candidates on both DNA strands and reports original sequence coordinates.

Addgene explains that CRISPR specificity depends on both the guide RNA sequence and the Cas enzyme, and that partial homology elsewhere can create off-target activity. The 2016 Doench sgRNA design paper built empirical rules to improve on-target activity and reduce off-target effects in genome-scale libraries. Read Addgene’s CRISPR guide.

Inputs and outputs in the sgRNA workflow

Each field supports one decision in a real guide-selection workflow. Basic users can keep defaults. Advanced users can narrow a chosen exon or test a non-SpCas9 PAM.

DNA target sequence

Provides the source region for protospacer and PAM scanning. Paste the coding strand, genomic strand, or amplicon sequence.

Nuclease preset

Defines PAM pattern, guide length, PAM side, and approximate cut-site position for SpCas9, Cas12a, SaCas9, SpG, or custom enzymes.

Target window

Restricts guide candidates to a chosen exon, domain, enhancer, promoter segment, or classroom example region.

5′ G filter

Flags guides that may need an added G for U6 promoter expression or cloning into a specific vector.

Poly-T filter

Warns when a TTTT motif may stop Pol III transcription before the full sgRNA sequence forms.

Ranked guide table

Shows guide DNA, guide RNA, PAM, strand, coordinates, GC%, score, and warnings for export or review.

Guide quality rules used in the ranking

Balanced GC content

The tool rewards guides near 40–60% GC. That range often balances target binding with manageable synthesis and secondary-structure risk. If your target region has extreme base composition, compare guide candidates with the GC Content Calculator before you choose a final set.

PAM-proximal seed review

SpCas9 recognition depends strongly on the PAM and nearby seed region. This page flags extreme seed GC content and reports the PAM-side end on the map. Hsu and colleagues showed that mismatch effects depend on mismatch number, position, and distribution. View the Cas9 specificity study.

Check	Preferred value	Why it matters
Guide length	20 nt for SpCas9	Matches common SpCas9 protospacer design.
PAM	NGG for SpCas9	Cas9 must recognize a nearby PAM before stable target interrogation.
GC%	40–60%	Balances weak AT-rich guides against overly stable GC-rich guides.
Poly-T	Avoid TTTT	Pol III promoters can terminate at T-rich runs.

Practical examples for guide selection

Knockout screen in a coding exon

A student pastes a 180 bp coding exon and selects SpCas9 NGG. The tool finds several 20 nt guides on both strands. A guide with 52% GC, no TTTT motif, and no 4-base homopolymer earns a strong first-pass score.

The student still checks transcript isoforms, exon usage, and genome-wide specificity before ordering. They also design PCR primers around the cut site and test those primers with the Primer Dimer Calculator.

Cas12a scan in an AT-rich region

A researcher wants guides in an AT-rich promoter. SpCas9 returns few NGG sites, so they switch to Cas12a TTTV. The tool now scans PAMs upstream of 23 nt guide regions and reports both-strand coordinates.

Cas12a candidates may suit AT-rich targets, but the final choice still depends on the nuclease, delivery system, organism, and genome-wide off-target profile.

Before you order a guide RNA

This page gives a transparent first-pass screen. It does not search a whole genome. Off-target risk depends on near matches outside your pasted sequence, mismatch position, chromatin context, guide concentration, nuclease variant, and delivery method.

Use at least two independent guides when possible. Validate editing at the DNA level, confirm transcript or protein disruption when needed, and include non-targeting or safe-targeting controls. Never use this educational tool as clinical guidance.

Use these tools before or after guide selection to check PAM positions, sequence properties, and oligo behavior.

PAM Sequence Finder

Scan DNA for NGG, NAG, TTTV, and custom IUPAC PAM patterns before guide ranking.

DNA Sequence Analyzer

Check sequence length, GC content, reverse complement, ORFs, and restriction sites.

Primer Dimer Calculator

Review short guide-adaptor oligos or validation primers for complementarity risk.

CRISPR guide RNA design FAQs

What does this CRISPR guide RNA design tool calculate?

It scans a DNA sequence for PAM sites, extracts nearby guide sequences, and ranks candidate sgRNAs with simple sequence-quality rules. It reports guide coordinates, PAM sequence, strand, GC percentage, homopolymer warnings, poly-T warnings, and a first-pass score. The tool supports SpCas9 NGG, SpCas9 NAG, Cas12a TTTV, SpG NGN, SaCas9 NNGRRT, and custom IUPAC PAM patterns. It does not replace a genome-wide off-target search.

Which guide length should I use for SpCas9?

SpCas9 guide design usually uses a 20 nucleotide protospacer next to a 3′ NGG PAM. The tool extracts 20 bases upstream of each NGG site on the plus strand and performs the reverse-complement equivalent on the minus strand. It reports the guide DNA sequence and the RNA version with U in place of T. Use the Advanced mode only when your nuclease, vector, or classroom exercise uses a different guide length.

What GC content works best for guide RNA candidates?

A practical first-pass guide often sits near 40–60% GC content. Very low GC can weaken target binding, while very high GC can increase secondary structure or synthesis difficulty. The score in this tool rewards guides inside that 40–60% window and flags guides far outside it. GC content alone never proves that a guide will cut well.

Why does the tool warn about TTTT motifs?

Many sgRNA expression cassettes use a U6 promoter. A run of four or more thymidines in the DNA guide can behave like a Pol III termination signal after transcription. The tool flags TTTT because it can reduce full-length sgRNA expression. This warning matters most for U6-driven guide expression and may not apply to every delivery system.

Can this tool predict genome-wide off-target effects?

No. This page screens the sequence you paste, but it does not search a whole genome. True off-target analysis needs a reference genome, mismatch rules, genomic coordinates, and sometimes chromatin or cell-type context. Use this tool to shortlist candidates, then run genome-aware off-target checks before ordering guides. Experimental validation still matters.

Should I choose a guide near the start of a coding exon?

Knockout experiments often target early constitutive coding exons because frameshift indels can disrupt more of the protein. The best target region depends on transcript isoforms, protein domains, exon usage, and whether the gene tolerates alternative start sites. The tool lets you restrict the scan to a target window, such as a chosen exon or domain. Confirm exon coordinates in a genome browser before final design.

What does the guide score mean?

The score gives a transparent first-pass ranking from sequence features. It rewards balanced GC content and penalizes homopolymers, TTTT motifs, missing 5′ G when requested, and extreme seed composition. It does not use a trained genome-wide model. Treat it as a classroom and planning score, not a clinical or regulatory guide-design decision.