Core Concepts
A high-level overview of CRISPR guide RNA design and how SPACER approaches it.
CRISPR-Based Diagnostics
CRISPR-Cas systems were originally discovered as bacterial immune systems that detect and destroy foreign nucleic acids. Scientists have repurposed certain Cas enzymes — particularly Cas12 and Cas13 — for nucleic acid detection in diagnostic assays.
In a CRISPR diagnostic test, a guide RNA (also called a crRNA) directs the Cas enzyme to a specific target sequence. For Cas12, the enzyme binds and cleaves the target dsDNA, which triggers collateral ssDNA cleavage of nearby reporter molecules. For Cas13, target RNA binding alone is sufficient to activate collateral ssRNA cleavage — the target does not need to be cleaved. In both cases, the collateral activity produces a measurable signal. The specificity and sensitivity of the test depends critically on the guide RNA design.
Guide RNA Design Challenge
Designing optimal guide RNAs is a multi-objective optimization problem. A good guide must:
- Bind specifically to the target (minimize off-target effects)
- Have favorable thermodynamic properties (GC content, no strong secondary structures)
- Avoid sequences that inhibit enzyme activity (homopolymers, poly-T runs)
- Maximize on-target activity (binding and collateral cleavage)
SPACER addresses this by computing a composite score that weights multiple factors, then classifying guides into quality tiers so researchers can quickly identify the best candidates.
The Analysis Pipeline
When you submit a sequence, SPACER runs it through a multi-stage pipeline:
- PAM/PFS scanning — Identifies all valid guide RNA extraction sites based on enzyme requirements
- Spacer extraction — Extracts candidate spacer sequences of the configured length
- Scoring — Evaluates each candidate on GC content, homopolymers, poly-T runs, and optionally AI activity prediction and RNA structure
- Classification — Assigns each guide to a quality tier based on its composite score
- Ranking — Sorts guides within each tier by score