Overview of the Multispecies Ovary Tissue Histology Electronic Repository†

Area of Science:

• Reproductive Biology
• Comparative Anatomy
• Bioinformatics

Background:

• Ovarian histology research requires accessible, high-quality image data.
• Existing resources lack comprehensive multispecies coverage and detailed annotations.
• Understanding ovarian function and fertility necessitates comparative analysis across species.

Purpose of the Study:

• To establish the Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) as a public resource.
• To curate and provide access to a diverse collection of ovary histology images with associated metadata.
• To develop and integrate automated pipelines for ovarian follicle analysis.

Main Methods:

• Collection and curation of ovary histology images from various species, including nonhuman primates.
• Development of a structured database (MOTHER-DB) for storing images and metadata.
• Implementation of manual and machine learning-based methods for follicle identification and staging.
• Generation of follicle identification annotations for selected species.

Main Results:

• MOTHER offers a growing collection of histology images from multiple species.
• Associated metadata enhances the utility of the image data.
• Follicle identification annotations are available for specific species, aiding quantitative analysis.
• Ongoing development focuses on expanding data contribution and automated analysis capabilities.

Conclusions:

• MOTHER serves as a critical data repository for reproductive biology research.
• The repository facilitates studies on ovarian function, fertility, and inter-species variability.
• Automated analysis pipelines will enhance the value and accessibility of follicle data within MOTHER-DB.