Sox9 and BMP2 Dual-Channel Analysis Tutorial

Welcome to the comprehensive guide for analyzing Sox9 and BMP2 gene expression using LimbLab! This tutorial focuses on dual-channel analysis, which is crucial for understanding gene interactions and spatial relationships in limb development.

🎯 Objective

The goal of this tutorial is to analyze the spatial relationship between Sox9 and BMP2 gene expression in mouse limb development. Sox9 is essential for cartilage formation, while BMP2 regulates bone development. Understanding their 3D co-expression patterns provides insights into the molecular mechanisms of limb development.

What you'll learn: - Dual-channel volume processing - Comparative gene expression analysis - Spatial relationship mapping - Multi-channel visualization techniques - Advanced alignment and morphing

📁 Data Overview

Dataset: Sox9 and BMP2 HCR expression data
Location: example_data/sox9_bmp2_raw_data/
Channels: - DAPI (nuclear staining) - Sox9 (cartilage marker) - BMP2 (bone morphogenetic protein)

Files: - HCR20_BMP2_l1_dapi_405_LF.tif - DAPI channel - HCR20_BMP2_l1_sox9_594_LF.tif - Sox9 channel - HCR20_BMP2_l1_bmp2_647_LF.tif - BMP2 channel

Download the data

mkdir example_data
mkdir example_data/sox9_bmp2_raw_data

Then, you go to: XX From here you can download the needed files and locate them to the folder example_data/sox9_bmp2_raw_data/

🚀 Step-by-Step Pipeline

Step 1: Create Experiment Structure

Set up a new experiment for the dual-channel analysis.

limb create-experiment case_studies/sox9_bmp2_pipeline

Interactive prompts: - Limb side: Select L (Left) - Limb position: Select F (Forelimb) - Microscope spacing: Use default 0.65 0.65 2.0

Expected output:

✅ Experiment created: case_studies/sox9_bmp2_pipeline
📝 Pipeline log initialized

Your pipeline.log should contain:

BASE ./case_studies/sox9_bmp2_pipeline
SIDE L
POSITION F
SPACING 0.65 0.65 2.0

Step 2: Clean DAPI Volume

Process the structural reference channel first.

limb clean-volume case_studies/sox9_bmp2_pipeline example_data/sox9_bmp2_raw_data/HCR20_BMP2_l1_dapi_405_LF.tif dapi

Processing details: - Threshold selection: Focus on nuclear staining - Smoothing: (6, 6, 6) Gaussian filter - Output size: (512, 512, 296) - Expected reduction: ~75% file size

Expected result:

✅ DAPI volume cleaned and saved
📊 Volume size: 180MB (from 720MB)
📝 Pipeline log updated

Step 3: Clean Sox9 Volume

Process the Sox9 cartilage marker channel.

limb clean-volume case_studies/sox9_bmp2_pipeline example_data/sox9_bmp2_raw_data/HCR20_BMP2_l1_sox9_594_LF.tif sox9

Key considerations for Sox9: - Expression pattern: Cartilage-forming regions - Threshold values: Typically higher than DAPI - Spatial distribution: Concentrated in digit-forming areas

Expected result:

✅ Sox9 volume cleaned and saved
📊 Expression preserved in cartilage regions
📝 Pipeline log updated

Step 4: Clean BMP2 Volume

Process the BMP2 bone morphogenetic protein channel.

limb clean-volume case_studies/sox9_bmp2_pipeline example_data/sox9_bmp2_raw_data/HCR20_BMP2_l1_bmp2_647_LF.tif bmp2

Key considerations for BMP2: - Expression pattern: Bone-forming regions - Relationship to Sox9: Often complementary expression - Threshold selection: Balance signal and background

Expected result:

✅ BMP2 volume cleaned and saved
📊 Expression preserved in bone-forming regions
📝 Pipeline log updated

Step 5: Extract 3D Surface

Create a surface mesh from the DAPI volume for analysis.

limb extract-surface case_studies/sox9_bmp2_pipeline/

Surface quality note: Real experimental data may produce imperfect surfaces.

OPTIONALLY, you can clean the surface created with Blender. Then, LimbLab will use it by default. Note use vtk in blender you just need

Manual surface replacement:

# Add the pre-cleaned surface to pipeline.log
echo 'BLENDER HCR20_BMP2_l1_dapi_405_LF_surface_blender.vtk' >> case_studies/sox9_bmp2_pipeline/pipeline.log

# Copy the pre-cleaned surface
cp ${your_path}/HCR20_BMP2_l1_dapi_405_LF_surface_blender.vtk case_studies/sox9_bmp2_pipeline/

Expected result:

✅ Surface mesh loaded
📊 Mesh: 12,845 vertices, 25,690 faces
💾 Using pre-cleaned Blender surface

Step 6: Stage the Limb

Determine the developmental stage for proper reference alignment.

limb stage case_studies/sox9_bmp2_pipeline/

Staging process: 1. Place points along the proximal-distal axis 2. Focus on digit-forming regions 3. Ensure good point distribution 4. Calculate stage automatically

Expected result:

🎯 Limb stage determined: 24.7
📊 Confidence: 91.8%
📝 Results saved to: case_studies/sox9_bmp2_pipeline/staging.txt

Step 7: Align with Reference (Morphing)

Use non-linear morphing for precise alignment with the reference template.

limb align case_studies/sox9_bmp2_pipeline/ --morph

Why morphing for dual-channel analysis: - Better alignment: Non-linear transformation captures complex morphology - Preserves relationships: Maintains spatial relationships between channels - Higher accuracy: Essential for comparative analysis

Morphing process: 1. Reference template of stage 24.7 is loaded 2. Non-linear registration is performed 3. Transformation is applied to all channels 4. Results are saved for visualization

Expected result:

✅ Non-linear morphing completed
📊 Transformation applied to all channels
📝 Pipeline log updated

Step 8: Dual-Channel Visualization

Create comprehensive visualizations of both gene expression patterns.

8.1 Dual-Channel Isosurface Visualization

limb vis isosurfaces case_studies/sox9_bmp2_pipeline SOX9 BMP2

What happens: 1. Interactive isovalue selection for both channels 2. Dual-channel 3D surface rendering 3. Color-coded expression mapping 4. Overlap analysis

Visualization features: - Sox9 (Red): Cartilage-forming regions - BMP2 (Green): Bone-forming regions - Overlap (Yellow): Co-expression regions - Transparency: Adjustable for depth perception

Expected output:

🎨 Dual-channel isosurface rendered
📊 Sox9 expression range: 0.3 - 0.9
📊 BMP2 expression range: 0.2 - 0.8
📊 Overlap regions: 15% of total volume
💾 Image saved: case_studies/sox9_bmp2_pipeline/dual_isosurface.png

8.2 Dual-Channel Slice Visualization

limb vis slices case_studies/sox9_bmp2_pipeline SOX9 BMP2

What happens: 1. Interactive 2D slicing through 3D volume 2. Dual-channel overlay visualization 3. Real-time expression comparison 4. Quantitative analysis tools

Interactive features: - Mouse wheel: Adjust slice position - Mouse drag: Move through volume - Color channels: Toggle individual channels - Intensity scaling: Adjust expression ranges

8.3 Probe Visualization

limb vis probe case_studies/sox9_bmp2_pipeline SOX9 BMP2

What happens: 1. Interactive probe placement 2. Real-time expression measurement 3. Multi-channel data extraction 4. Statistical analysis

Probe features: - Point probes: Single-point measurements - Line probes: Linear expression profiles - Volume probes: Regional analysis - Export data: CSV format for further analysis

📊 Results and Analysis

Expected Outcomes

After completing this tutorial, you should have:

Processed data:
Cleaned DAPI, Sox9, and BMP2 volumes
3D surface mesh
Staging results
Non-linear transformation
Visualizations:
Dual-channel 3D isosurfaces
2D slice overlays
Interactive probe data
Publication-ready images
Analysis insights:
Spatial relationship between Sox9 and BMP2
Co-expression patterns
Developmental stage context
Quantitative expression data

Data Files Generated

case_studies/sox9_bmp2_pipeline/
├── pipeline.log                                    # Processing log
├── HCR20_BMP2_l1_dapi_405_LF_cleaned.tif          # Cleaned DAPI
├── HCR20_BMP2_l1_sox9_594_LF_cleaned.tif          # Cleaned Sox9
├── HCR20_BMP2_l1_bmp2_647_LF_cleaned.tif          # Cleaned BMP2
├── HCR20_BMP2_l1_dapi_405_LF_surface_blender.vtk  # 3D surface
├── staging.txt                                     # Staging results
├── morphing_transformation.txt                     # Morphing data

This tutorial demonstrates the power of LimbLab for dual-channel gene expression analysis. The same approach can be applied to any combination of genes or markers in limb development research.