MBE Gene editing

1. Experimental Purpose

• Scientific Question: How do specific genes or regulatory elements contribute to cellular function, development, and disease?
• Design Rationale: Gene editing and expression modulation technologies enable precise manipulation of the genome and gene expression to establish causality
• Follow-up Studies: Phenotypic analysis, mechanistic investigations, therapeutic applications, genetic interaction mapping

2. Model System

• Primary Systems: Cell lines, primary cells, organoids, model organisms, patient-derived cells
• Rationale: These systems allow genetic manipulation while maintaining relevant biological context for functional analysis
• Alternatives:
• In vitro biochemical systems (pros: mechanistic detail; cons: lack cellular context)
• Ex vivo tissue cultures (pros: tissue architecture; cons: limited viability)
• In vivo models (pros: physiological relevance; cons: delivery challenges, ethical considerations)
• Ethical Considerations: Off-target effects, germline editing concerns, animal welfare, consent for human cells

3. Measurement Approach

• Common Elements:
• Validation of editing efficiency
• Off-target analysis
• Phenotypic readouts
• Molecular characterization
• Technical Replicates: Multiple transfection/transduction experiments, multiple edited clones
• Potential Biases:
• Delivery method efficiency
• Cell type-specific editing outcomes
• Clonal selection artifacts
• Off-target effects

4. Group Setting

• Experimental Groups:
• Test: Cells/organisms with targeted genetic modification
• Control 1: Wild-type/unmodified cells
• Control 2: Mock-treated cells (transfection reagents only)
• Control 3: Non-targeting guide RNA or scrambled siRNA controls
• Controlled Variables: Cell passage number, transfection conditions, selection methods
• Biological Replicates: Minimum 3 independent editing experiments; multiple clones for stable modifications
• Modified Design: Multiplexed editing, inducible systems, combinatorial modifications

5. Data Analysis & Presentation

• Common Analysis Elements:
• Editing efficiency quantification
• Off-target analysis
• Expression level verification
• Phenotypic measurements
• Presentation Approaches:
• Sequencing traces showing edits
• Western blots/qPCR for expression changes
• Phenotypic assay results
• Off-target analysis plots

6. Technique Comparison - Genome Editing Methods

Feature	Homologous Recombination	ZFNs (Zinc Finger Nucleases)	TALENs	CRISPR-Cas9
Mechanism	Endogenous DNA repair	Engineered nuclease + DNA repair	Engineered nuclease + DNA repair	RNA-guided nuclease + DNA repair
Design Complexity	High (homology arms)	Very high (protein engineering)	High (protein assembly)	Low (guide RNA design)
Efficiency	Very low (0.1-1%)	Moderate (1-10%)	Moderate (1-10%)	High (1-90%, system-dependent)
Specificity	Very high	High	Very high	Moderate to high (guide-dependent)
Size of Edit	Unlimited (replacement)	Small to large	Small to large	Small to large
Multiplexing	Difficult	Difficult	Difficult	Easy
Time to Implement	Months	Months	Weeks to months	Days to weeks
Cost	High	Very high	High	Low
Best For	• Precise gene replacement • Knock-in of large sequences • Clean modifications • ES cell modifications	• Targeted gene disruption • Editing in specific contexts • When high specificity is critical • Historic datasets	• Highly specific editing • Modification of methylated regions • Alternative to CRISPR • Reduced off-target concerns	• Rapid genetic screening • Multiplexed editing • Versatile applications • Complex genetic manipulations
Limitations	• Extremely low efficiency • Labor intensive • Limited to dividing cells • Complex construct design	• Difficult protein design • Limited targeting range • High cost • Technical expertise required	• Complex assembly • Large protein size limits delivery • Time-consuming design • Lower efficiency than CRISPR	• Off-target concerns • PAM site requirements • Delivery challenges for large Cas9 • Immune responses in vivo

7. Technique Comparison - Expression Modulation Methods

Feature	RNAi	CRISPRi	CRISPRa	Gene Overexpression	Epigenome Engineering
Mechanism	mRNA degradation	Transcriptional repression	Transcriptional activation	Increased gene dosage	Modification of epigenetic marks
Target	mRNA	DNA (promoters/enhancers)	DNA (promoters/enhancers)	Coding sequence	DNA/histones
Effect Level	Post-transcriptional	Transcriptional	Transcriptional	Post-transcriptional	Transcriptional
Duration	Transient (siRNA) Stable (shRNA)	Stable while expressed	Stable while expressed	Variable (transient to stable)	Potentially heritable
Completeness	Partial knockdown	Near-complete silencing possible	Variable activation	Controlled by promoter/enhancer	Variable and context-dependent
Specificity	Moderate (off-targets)	High (guide-dependent)	High (guide-dependent)	Very high (gene-specific)	High (site-specific)
Ease of Design	Easy	Easy	Moderate	Easy	Moderate to complex
Best For	• Rapid gene inhibition • Transient effects • Dose-dependent studies • Non-coding RNAs	• Gene silencing • Regulatory element analysis • Non-coding regions • Stable repression	• Upregulating endogenous genes • Enhancer activation • Screening enhancers • Complex gene regulation	• Rescue experiments • Protein function studies • Dominant effects • Dose-response analysis	• Chromatin state manipulation • Imprinting studies • Heritable modifications • Regulatory element analysis
Limitations	• Incomplete knockdown • Off-target effects • Variable efficiency • Interferon responses	• Requires continuous expression • Variable across genomic contexts • Limited to accessible regions • Delivery challenges	• Context-dependent efficiency • Chromatin state dependent • Limited by endogenous potential • Delivery challenges	• Non-physiological levels • Ectopic expression artifacts • Toxicity concerns • Delivery limitations	• Context-dependent effects • Complex readouts • Variable stability • Technical complexity

8. Complementary Usage Strategy

• Gene Function Analysis:
• Use CRISPR-Cas9 for complete gene knockout
• Apply RNAi for dose-dependent or transient knockdown

• Implement gene overexpression for rescue experiments

• Regulatory Element Analysis:

• Employ CRISPRi to silence specific regulatory elements
• Use CRISPRa to activate enhancers or promoters

• Apply epigenome engineering to modify chromatin states

• Therapeutic Development:

• CRISPR-Cas9 for correction of pathogenic mutations
• RNAi for targeting disease-causing gene products

• Gene overexpression for replacement of deficient proteins

• Integrated Approach: Design multi-platform studies for comprehensive characterization:

• CRISPR-Cas9 to generate complete knockouts for core phenotypic analysis
• RNAi for temporal or partial inhibition studies
• CRISPRi/a for regulatory element mapping
• Overexpression for structure-function and rescue studies

9. Technology-Specific Considerations

CRISPR-Cas9 System

• Guide RNA Design:
• Optimize for on-target efficiency and minimal off-targets
• Consider chromatin accessibility at target site

• Account for PAM requirements of specific Cas variants

• Delivery Methods:

• Plasmid transfection (simple, transient)
• Viral vectors (efficient, stable integration)

• RNP delivery (rapid, reduced off-targets)

• Variants and Adaptations:

• Cas9 nickase for reduced off-targets
• High-fidelity Cas9 variants (SpCas9-HF1, eSpCas9)
• Cas12a/Cpf1 for alternative PAM requirements
• Base editors for precise nucleotide changes
• Prime editors for targeted insertions and deletions

RNAi Technology

• Design Considerations:
• siRNA vs. shRNA selection based on duration needs
• Seed region optimization to reduce off-targets

• Pooled vs. individual siRNAs

• Validation Approaches:

• Multiple independent siRNAs targeting different regions
• Rescue experiments with RNAi-resistant constructs
• Dose-response analysis

CRISPRi and CRISPRa

• Component Selection:
• dCas9 fusion partners (KRAB, VP64, p65, HSF1)
• Guide RNA positioning relative to TSS

• Single guides vs. multiple guides for synergistic effects

• Applications:

• Tiling of regulatory regions to map functional elements
• Multiplexed activation/repression for pathway analysis
• Inducible systems for temporal control

Gene Overexpression

• Vector Selection:
• Viral (lentivirus, AAV, adenovirus) based on cell type
• Inducible promoters for controlled expression

• Tagged constructs for tracking and purification

• Considerations:

• Expression level optimization
• Codon optimization for efficient translation
• Subcellular targeting signals if needed

Epigenome Engineering

• Effector Domains:
• DNA methyltransferases (DNMT3A, DNMT3B)
• Histone modifiers (p300, LSD1, EZH2)

• Combinations for synergistic effects

• Target Selection:

• CpG islands for DNA methylation
• Promoters vs. enhancers
• Boundary elements and insulators

This comprehensive framework provides researchers with a structured approach to selecting and implementing gene editing and expression modulation technologies. The complementary use of these methods enables precise dissection of gene function and regulatory mechanisms in diverse biological contexts.