FISH-Dist: An Automated Pipeline for 3D Genomic Spatial Distance Quantification in FISH Imaging.

Area of Science:

• Molecular Biology
• Genomics
• Biophysics
• Microscopy

Background:

• Accurate spatial quantification of fluorescent signals in 3D microscopy is vital for understanding genomic organization and gene regulation.
• Chromatic aberration in multi-channel imaging causes systematic spatial offsets, biasing distance measurements, especially for short genomic distances.

Purpose of the Study:

• To develop an automated computational pipeline, FISH-Dist, for accurate quantitative distance measurements in 3D fluorescence in situ hybridization (FISH) experiments.
• To address the challenge of chromatic aberration in standard confocal microscopy, particularly impacting short-range genomic distance measurements.

Main Methods:

• FISH-Dist integrates deep learning for spot segmentation and 3D Gaussian fitting for sub-pixel localization.
• The pipeline employs two chromatic aberration correction methods: affine (ACC) and linear (LCC).
• Validation involved measuring DNA origami nanorulers and evaluating FISH probe design parameters.

Main Results:

• FISH-Dist achieves sub-pixel accuracy in signal detection.
• The pipeline significantly reduces inter-channel distance measurement errors caused by chromatic aberration.
• Demonstrated reproducible quantification of spatial relationships in 3D FISH datasets.

Conclusions:

• FISH-Dist provides a robust solution for accurate 3D distance measurements using standard confocal microscopy.
• The pipeline is specifically optimized for short genomic distances, overcoming limitations of existing tools.
• Enables precise analysis of genomic organization and gene regulation through improved spatial quantification.