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Pipelines

CAS9point4

Overview

Flow provides CAS9point4 v1.0.0, a specialized CRISPR/Cas9 genome editing pipeline designed for efficient and validated generation of genetically modified mouse models. Developed by the Mary Lyon Centre at MRC Harwell, this pipeline implements best practices for mouse genome engineering with a focus on reducing animal use through improved validation methods and quality control.

The pipeline streamlines the process of creating knock-out, knock-in, and point mutation mouse models using CRISPR/Cas9 technology, with comprehensive validation to ensure correct genome modifications before breeding.

Pipeline Summary

The workflow encompasses:

  1. Guide RNA Design

    • Target site identification
    • sgRNA design and scoring
    • Off-target prediction
    • PAM site analysis

  2. Donor Template Preparation

    • Long single-stranded DNA (lssDNA) donors
    • Homology arm optimization
    • Point mutation integration
    • Conditional allele design

  3. Embryo Injection

    • Ribonucleoprotein (RNP) preparation
    • Zygote electroporation/microinjection
    • Embryo culture monitoring
    • Quality control checkpoints

  4. Validation & Screening

    • Long-read sequencing validation
    • Allele-specific PCR
    • Off-target analysis
    • Mosaicism detection

  5. Founder Analysis

    • Genotype confirmation
    • Transmission testing
    • Germline validation
    • Colony establishment

Input Requirements

Design Inputs

  • Target gene coordinates (GRCm38/mm10 or GRCm39/mm39)
  • Desired modification type (KO, KI, point mutation)
  • Sequence context (±500bp from target)
  • Known SNPs/variants in target region

Experimental Inputs

project_id: PROJ001
gene_symbol: Trp53
modification_type: knockout
chromosome: 11
start_position: 69580359
end_position: 69591873
strain: C57BL/6J

Reagent Requirements

  • Cas9 protein (high purity)
  • Synthetic guide RNAs
  • Donor DNA templates
  • Validation primers

Key Parameters

Guide RNA Design

  • --pam_sequence: PAM preference (NGG, NAG)
  • --guide_length: sgRNA length (17-20nt)
  • --gc_content: GC% range (40-60%)
  • --off_target_threshold: Maximum mismatches (0-3)

Editing Strategy

  • --edit_type: Modification strategy
    • knockout: NHEJ-mediated disruption
    • knockin: HDR-mediated insertion
    • point_mutation: Precise base changes
    • conditional: LoxP site insertion

Validation Options

  • --sequencing_method:
    • long_read: Oxford Nanopore/PacBio
    • short_read: Illumina sequencing
    • sanger: Traditional validation
  • --min_read_depth: Coverage for calling (100X)
  • --allele_frequency: Detection threshold (5%)

Quality Control

  • --max_off_targets: Acceptable off-target sites
  • --indel_window: Base pairs around cut site
  • --homology_arms: Length for HDR (500-1000bp)
  • --validation_stringency: QC level (low/medium/high)

Pipeline Outputs

Design Files

  1. Guide RNA Sequences

    • Primary and alternate guides
    • Off-target predictions
    • Efficiency scores
    • Oligo order sheets

  2. Donor Templates

    • Annotated sequences
    • Homology arm designs
    • Cloning strategies
    • Quality metrics

Validation Results

  1. Sequencing Data

    • Allele frequencies
    • Indel profiles
    • Integration accuracy
    • Off-target summary

  2. Founder Reports

    • Genotype classifications
    • Mosaicism assessment
    • Breeding recommendations
    • Validation certificates

Analysis Reports

  1. Edit Outcomes

    • Success rates
    • Mutation spectra
    • Unexpected events
    • Transmission data

  2. Quality Metrics

    • On-target efficiency
    • Off-target activity
    • HDR frequencies
    • Germline transmission

Editing Strategies

Simple Knockout

--edit_type knockout
--guide_count 2
--deletion_size large
--frameshift_required true

Knock-in Reporter

--edit_type knockin
--donor_type lssDNA
--insert_size 2kb
--homology_arms 800bp

Point Mutation

--edit_type point_mutation
--mutation_distance 10bp
--silent_mutations true
--pam_blocking true

Conditional Allele

--edit_type conditional
--flox_exons 3-5
--selection_marker none
--validate_functionality true

Best Practices

Guide Design

  1. Screen multiple guide RNAs
  2. Avoid repetitive sequences
  3. Check for SNPs in target region
  4. Validate cutting efficiency

Donor Design

  1. Use long ssDNA for insertions
  2. Include silent PAM mutations
  3. Optimize homology arm length
  4. Avoid secondary structures

Validation Strategy

  1. Use long-read sequencing when possible
  2. Screen sufficient founders
  3. Validate germline transmission
  4. Check for large deletions

Animal Welfare (3Rs)

  1. Optimize injection conditions
  2. Minimize animal numbers
  3. Use validation before breeding
  4. Archive validated lines

Troubleshooting

Common Issues

Low Editing Efficiency

  • Optimize RNP concentrations
  • Test alternative guides
  • Improve injection technique
  • Check reagent quality

Unexpected Alleles

  • Screen for large deletions
  • Check donor integrations
  • Analyze microhomology
  • Sequence junction sites

Mosaicism

  • Increase founder screening
  • Validate germline early
  • Use allele-specific assays
  • Consider re-injection

Off-Target Effects

  • Use high-fidelity Cas9
  • Reduce RNP concentration
  • Shorten guide length
  • Validate predicted sites

Advanced Features

Multiplexing

--multiplex_guides 4
--target_genes "Trp53,Rb1,Pten,Nf1"
--validation_strategy pooled

Prime Editing

--editor_type prime
--pegrna_design auto
--edit_verification sequencing

Base Editing

--editor_type base
--target_nucleotide C>T
--editing_window 4-8

Large Deletions

--deletion_strategy dual_guide
--deletion_size 10kb
--screen_method long_range_pcr

Output Interpretation

Key Metrics

  1. Cutting Efficiency: >80% recommended
  2. HDR Rate: >20% for knock-ins
  3. Germline Rate: >50% transmission
  4. Off-Target Rate: <1% detectable

Allele Classification

  • Perfect: Intended edit only
  • Imperfect: Partial integration
  • Mosaic: Multiple alleles
  • Wild-type: No editing

Decision Points

  • Proceed with <3 off-targets
  • Breed if germline confirmed
  • Re-inject if low efficiency
  • Archive validated lines

Additional Resources

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