mirror of
https://github.com/K-Dense-AI/claude-scientific-skills.git
synced 2026-03-27 07:09:27 +08:00
fix(attribution): correct source repo URL to SuperiorByteWorks-LLC/agent-project
All 40 references to borealBytes/opencode updated to the correct source: https://github.com/SuperiorByteWorks-LLC/agent-project Affected files: SKILL.md, all 24 diagram guides, 9 templates, issue and PR docs, plus assets/examples/example-research-report.md (new file). The example report demonstrates full skill usage: flowchart, sequence, timeline, xychart, radar diagrams — all with accTitle/accDescr and classDef colors, no %%{init}. Covers HEK293T CRISPR editing efficiency as a realistic scientific context.
This commit is contained in:
Clayton Young
@@ -0,0 +1,218 @@
|
||||
# CRISPR-Based Gene Editing Efficiency Analysis
|
||||
|
||||
_Example research report — demonstrates markdown-mermaid-writing skill standards. All diagrams use Mermaid embedded in markdown as the source format._
|
||||
|
||||
---
|
||||
|
||||
## 📋 Overview
|
||||
|
||||
This report analyzes the efficiency of CRISPR-Cas9 gene editing across three cell line models under variable guide RNA (gRNA) conditions. Editing efficiency was quantified by T7E1 assay and next-generation sequencing (NGS) of on-target loci[^1].
|
||||
|
||||
**Key findings:**
|
||||
|
||||
- HEK293T cells show highest editing efficiency (mean 78%) across all gRNA designs
|
||||
- GC content between 40–65% correlates with editing efficiency (r = 0.82)
|
||||
- Off-target events occur at <0.1% frequency across all conditions tested
|
||||
|
||||
---
|
||||
|
||||
## 🔄 Experimental workflow
|
||||
|
||||
CRISPR editing experiments followed a standardized five-stage protocol. Each stage has defined go/no-go criteria before proceeding.
|
||||
|
||||
```mermaid
|
||||
flowchart TD
|
||||
accTitle: CRISPR Editing Experimental Workflow
|
||||
accDescr: Five-stage experimental pipeline from gRNA design through data analysis, with quality checkpoints between each stage.
|
||||
|
||||
design["🧬 Stage 1\ngRNA Design\n(CRISPRscan + Cas-OFFinder)"]
|
||||
synth["⚙️ Stage 2\nOligo Synthesis\n& Annealing"]
|
||||
transfect["🔬 Stage 3\nCell Transfection\n(Lipofectamine 3000)"]
|
||||
screen["🧪 Stage 4\nPrimary Screen\n(T7E1 assay)"]
|
||||
ngs["📊 Stage 5\nNGS Validation\n(150 bp PE reads)"]
|
||||
|
||||
qc1{GC 40-65%?}
|
||||
qc2{Yield ≥ 2 µg?}
|
||||
qc3{Viability ≥ 85%?}
|
||||
qc4{Band visible?}
|
||||
|
||||
design --> qc1
|
||||
qc1 -->|"✅ Pass"| synth
|
||||
qc1 -->|"❌ Redesign"| design
|
||||
synth --> qc2
|
||||
qc2 -->|"✅ Pass"| transfect
|
||||
qc2 -->|"❌ Re-synthesize"| synth
|
||||
transfect --> qc3
|
||||
qc3 -->|"✅ Pass"| screen
|
||||
qc3 -->|"❌ Optimize"| transfect
|
||||
screen --> qc4
|
||||
qc4 -->|"✅ Pass"| ngs
|
||||
qc4 -->|"❌ Repeat"| screen
|
||||
|
||||
classDef stage fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f
|
||||
classDef gate fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12
|
||||
classDef fail fill:#fee2e2,stroke:#dc2626,stroke-width:2px,color:#7f1d1d
|
||||
|
||||
class design,synth,transfect,screen,ngs stage
|
||||
class qc1,qc2,qc3,qc4 gate
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🔬 Methods
|
||||
|
||||
### Cell lines and culture
|
||||
|
||||
Three cell lines were used: HEK293T (human embryonic kidney), K562 (chronic myelogenous leukemia), and Jurkat (T-lymphocyte). All lines were maintained in RPMI-1640 with 10% FBS at 37°C / 5% CO₂[^2].
|
||||
|
||||
### gRNA design and efficiency prediction
|
||||
|
||||
gRNAs targeting the _EMX1_ locus were designed using CRISPRscan[^3] with the following criteria:
|
||||
|
||||
| Criterion | Threshold | Rationale |
|
||||
| -------------------- | --------- | ------------------------------------- |
|
||||
| GC content | 40–65% | Optimal Tm and Cas9 binding |
|
||||
| CRISPRscan score | ≥ 0.6 | Predicted on-target activity |
|
||||
| Off-target sites | ≤ 5 (≤3 mismatches) | Reduce off-target editing risk |
|
||||
| Homopolymer runs | None (>4 nt) | Prevents premature transcription stop |
|
||||
|
||||
### Transfection protocol
|
||||
|
||||
RNP complexes were assembled at 1:1.2 molar ratio (Cas9:gRNA) and delivered by lipofection. Cells were harvested 72 hours post-transfection for genomic DNA extraction.
|
||||
|
||||
### Analysis pipeline
|
||||
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
accTitle: NGS Data Analysis Pipeline
|
||||
accDescr: Sequence of computational steps from raw FASTQ files through variant calling to final efficiency report.
|
||||
|
||||
participant raw as 📥 Raw FASTQ
|
||||
participant qc as 🔍 FastQC
|
||||
participant trim as ✂️ Trimmomatic
|
||||
participant align as 🗺️ BWA-MEM2
|
||||
participant call as ⚙️ CRISPResso2
|
||||
participant report as 📊 Report
|
||||
|
||||
raw->>qc: Per-base quality scores
|
||||
qc-->>trim: Flag low-Q reads (Q<20)
|
||||
trim->>align: Cleaned reads
|
||||
align->>align: Index reference genome (hg38)
|
||||
align->>call: BAM + target region BED
|
||||
call->>call: Quantify indel frequency
|
||||
call-->>report: Editing efficiency (%)
|
||||
call-->>report: Off-target events
|
||||
report-->>report: Statistical summary
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 📊 Results
|
||||
|
||||
### Editing efficiency by cell line
|
||||
|
||||
| Cell line | n (replicates) | Mean efficiency (%) | SD (%) | Range (%) |
|
||||
| ---------- | -------------- | ------------------- | ------ | --------- |
|
||||
| **HEK293T** | 6 | **78.4** | 4.2 | 71.2–84.6 |
|
||||
| K562 | 6 | 52.1 | 8.7 | 38.4–63.2 |
|
||||
| Jurkat | 6 | 31.8 | 11.3 | 14.2–47.5 |
|
||||
|
||||
HEK293T cells showed significantly higher editing efficiency than both K562 (p < 0.001) and Jurkat (p < 0.001) lines by one-way ANOVA with Tukey post-hoc correction.
|
||||
|
||||
### Effect of GC content on efficiency
|
||||
|
||||
GC content between 40–65% was strongly correlated with editing efficiency (Pearson r = 0.82, p < 0.0001, n = 48 gRNAs).
|
||||
|
||||
```mermaid
|
||||
xychart-beta
|
||||
accTitle: Editing Efficiency vs gRNA GC Content
|
||||
accDescr: Bar chart showing mean editing efficiency grouped by GC content bins, demonstrating optimal performance in the 40 to 65 percent GC range
|
||||
|
||||
title "Mean Editing Efficiency by GC Content Bin (HEK293T)"
|
||||
x-axis ["< 30%", "30–40%", "40–50%", "50–65%", "> 65%"]
|
||||
y-axis "Editing Efficiency (%)" 0 --> 100
|
||||
bar [18, 42, 76, 81, 38]
|
||||
```
|
||||
|
||||
### Timeline of key experimental milestones
|
||||
|
||||
```mermaid
|
||||
timeline
|
||||
accTitle: Experiment Timeline — CRISPR Efficiency Study
|
||||
accDescr: Chronological milestones from study design through manuscript submission across six months
|
||||
|
||||
section Month 1
|
||||
Study design and gRNA library design : 48 gRNAs across 3 target loci
|
||||
Cell line authentication : STR profiling confirmed all three lines
|
||||
section Month 2
|
||||
gRNA synthesis and QC : 46/48 gRNAs passed yield threshold
|
||||
Pilot transfections (HEK293T) : Optimized lipofection conditions
|
||||
section Month 3
|
||||
Full transfection series : All 3 cell lines, all 46 gRNAs, 6 replicates
|
||||
T7E1 primary screening : Passed go/no-go for all conditions
|
||||
section Month 4
|
||||
NGS library preparation : 276 samples processed
|
||||
Sequencing run (NovaSeq) : 150 bp PE, mean 50k reads/sample
|
||||
section Month 5
|
||||
Bioinformatic analysis : CRISPResso2 pipeline
|
||||
Statistical analysis : ANOVA, correlation, regression
|
||||
section Month 6
|
||||
Manuscript preparation : This report
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🔍 Discussion
|
||||
|
||||
### Why HEK293T outperforms suspension lines
|
||||
|
||||
HEK293T's superior editing efficiency relative to K562 and Jurkat likely reflects three factors[^4]:
|
||||
|
||||
1. **Adherent morphology** — enables more uniform lipofection contact
|
||||
2. **High transfection permissiveness** — HEK293T expresses the SV40 large T antigen, which may facilitate nuclear import
|
||||
3. **Cell cycle distribution** — higher proportion in S/G2 phase where HDR is favored
|
||||
|
||||
<details>
|
||||
<summary><strong>🔧 Technical details — off-target analysis</strong></summary>
|
||||
|
||||
Off-target editing was assessed by GUIDE-seq at the 5 highest-activity gRNAs. No off-target sites exceeding 0.1% editing frequency were detected. The three potential sites flagged by Cas-OFFinder (≤2 mismatches) showed 0.00%, 0.02%, and 0.04% indel frequencies — all below the assay noise floor of 0.05%.
|
||||
|
||||
Full GUIDE-seq data available in supplementary data package (GEO accession pending).
|
||||
|
||||
</details>
|
||||
|
||||
---
|
||||
|
||||
### Comparison with published benchmarks
|
||||
|
||||
```mermaid
|
||||
radar
|
||||
accTitle: CRISPR Method Comparison Radar
|
||||
accDescr: Multi-dimensional radar chart comparing our protocol against published Cas9 and base editing benchmarks across five performance axes
|
||||
|
||||
title Performance vs. Published Methods
|
||||
x-axis ["Efficiency", "Specificity", "Delivery ease", "Cost", "Cell viability"]
|
||||
"This study (RNP + Lipo)" : [78, 95, 80, 85, 90]
|
||||
"Plasmid Cas9 (lit.)" : [55, 70, 90, 95, 75]
|
||||
"Electroporation RNP (lit.)" : [88, 96, 50, 60, 65]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Conclusions
|
||||
|
||||
1. RNP-lipofection in HEK293T achieves >75% CRISPR editing efficiency — competitive with electroporation without the associated viability cost
|
||||
2. gRNA GC content is the single strongest predictor of editing efficiency in our dataset (r = 0.82)
|
||||
3. This protocol is not directly transferable to suspension lines without further optimization; K562 and Jurkat require electroporation or viral delivery for comparable efficiency
|
||||
|
||||
---
|
||||
|
||||
## 🔗 References
|
||||
|
||||
[^1]: Ran, F.A. et al. (2013). "Genome engineering using the CRISPR-Cas9 system." _Nature Protocols_, 8(11), 2281–2308. https://doi.org/10.1038/nprot.2013.143
|
||||
|
||||
[^2]: ATCC. (2024). "Cell Line Authentication and Quality Control." https://www.atcc.org/resources/technical-documents/cell-line-authentication
|
||||
|
||||
[^3]: Moreno-Mateos, M.A. et al. (2015). "CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo." _Nature Methods_, 12(10), 982–988. https://doi.org/10.1038/nmeth.3543
|
||||
|
||||
[^4]: Molla, K.A. & Yang, Y. (2019). "CRISPR/Cas-Mediated Base Editing: Technical Considerations and Practical Applications." _Trends in Biotechnology_, 37(10), 1121–1142. https://doi.org/10.1016/j.tibtech.2019.03.008
|
||||
Reference in New Issue
Block a user