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NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects
Tristan Dubos1,2, Axel Poulet3, Geoffrey Thomson3
1GReD, CNRS, INSERM, Université Clermont Auvergne, Clermont-Ferrand, France.
BMC Bioinformatics
|June 6, 2022
Summary
We developed Nuclear Object DetectionJ (NODeJ), an automated ImageJ plugin for analyzing 3D chromatin organization. NODeJ accurately identifies heterochromatin and DNA FISH signals, reducing processing time and bias in biological research.
Area of Science:
- Cell Biology
- Genetics
- Bioinformatics
Background:
- The 3D arrangement of chromatin influences DNA-level cellular processes in plants and animals.
- Chromatin organization is dynamic and sensitive to environmental stresses.
- Quantitative analysis of 3D chromatin organization is limited by a lack of automated processing methods.
Purpose of the Study:
- To develop an automated method for analyzing 3D chromatin organization.
- To provide a tool for accurate segmentation and analysis of intra-nuclear structures.
Main Methods:
- Developed Nuclear Object DetectionJ (NODeJ) as an ImageJ plugin.
- Employed Laplacian convolution to enhance contrast of intra-nuclear objects.
- Validated NODeJ on public datasets of Arabidopsis thaliana nuclei stained with DAPI/Hoechst and DNA FISH.
Main Results:
- NODeJ accurately identifies heterochromatin domains in diverse plant nuclei.
- NODeJ successfully detects signals in DNA FISH experiments for specific target analysis.
- The automated method reduces processing time and analytical bias compared to semi-automated approaches.
Conclusions:
- NODeJ offers efficient, automated analysis of subnuclear structures.
- The ImageJ plugin is available with command-line options for high-throughput analysis.
- Source code and data are publicly accessible for reproducibility and further research.
