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Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
Published on: May 6, 2010
The HUDSEN Atlas: a three-dimensional (3D) spatial framework for studying gene expression in the developing human
Janet Kerwin1, Yiya Yang, Paloma Merchan
1Institute of Human Genetics, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, UK. j.m.kerwin@ncl.ac.uk
Journal of Anatomy
|October 29, 2010
Summary
This study creates a 3D human embryonic brain atlas using anatomical landmarks and gene expression data. The atlas maps gene patterns to brain development stages, aiding research and data dissemination.
Area of Science:
- Neuroscience
- Developmental Biology
- Bioinformatics
Background:
- Understanding human embryonic brain development is crucial.
- Existing atlases lack comprehensive 3D spatial and gene expression data.
- Mapping gene expression to anatomical structures aids in defining developmental domains.
Purpose of the Study:
- To develop a 3D atlas of the human embryonic brain.
- To integrate anatomical landmarks and gene expression data across 12 developmental stages (Carnegie Stages 12-23).
- To create a developmental neuroanatomic ontology linked to 3D models.
Main Methods:
- Generating virtual 3D anatomical models using optical projection tomography (OPT).
- Mapping gene expression data (in situ hybridization, immunohistochemistry) to 3D models using MAPAINT software.
- Utilizing interpolation software for generating complete anatomical domains from partial data.
Main Results:
- Developed 3D models and a preliminary anatomical domain ontology for human embryonic brain development.
- Mapped gene expression data for approximately 100 genes in the HUDSEN database.
- Used conserved vertebrate gene expression patterns (e.g., PAX6, GAD65, OLIG2) to refine anatomical boundaries.
Conclusions:
- The 3D atlas provides a valuable resource for studying human embryonic brain development.
- Integration of spatial gene expression data refines anatomical domain definitions.
- The HUDSEN database and atlas facilitate data sharing and maximize research utility.
