Documentation

T-GUIDE is a bioinformatics platform for the design and analysis of TnpB-mediated genome editing guides. The system identifies target sites, predicts on-target efficiency using deep learning models, and evaluates genome-wide specificity via Cas-OFFinder. It further automates the generation of experimental validation primers.

The system provides quantitative metrics for the efficiency and specificity of proposed guide RNAs, facilitating high-precision targeting across a broad spectrum of species and ortholog variants.

Four-Step Process

• 1. Select Genome: Choose from a wide range of high-quality genomes spanning vertebrates, plants, and microbial systems.
• 2. Select Variant: Pick the specific ortholog you are using. Each variant has a unique TAM requirement.
• 3. Define Target: Enter a standard Gene Symbol, paste raw DNA, or fetch via NCBI Accession.
• 4. Analyze Results: Generate a list of guides sorted by efficiency and checked for off-targets.

CNN Efficiency Scoring

Efficiency prediction is powered by a Convolutional Neural Network (CNN) trained on experimentally verified TnpB screening data. The model produces an activity score (0-100) based on the 20nt spacer and flanking genomic context.

Cas-OFFinder Integration

Genome-wide specificity is evaluated for every identified guide. The results table provides a mismatch matrix (MM0 to MM3), allowing users to prioritize guides with zero or minimal off-target risks across the selected genome.

We support an extensive collection of high-quality genomes sourced from Ensembl Release 109 and NCBI. Each genome is indexed for rapid sequence retrieval and off-target screening.

An extensive collection of TnpB variants are supported, each with specific Transposon-Associated Motif (TAM) requirements for precise editing.

Automated Primer Design

T-GUIDE generates PCR validation primers for every guide RNA using the Primer3 engine. Pairs are optimized for a 60°C melting temperature and amplicon sizes between 250-350 bp, facilitating rapid gel or sequencing-based validation.

Genome Visualization

An interactive browser visualizes guide distribution across gene structures (exons and introns). This helps in selecting targets that maximize the likelihood of functional modifications.