The Human Eye Transcriptome Atlas: A searchable comparative transcriptome database for healthy and diseased human eye...

Area of Science:

• Genomics
• Bioinformatics
• Ophthalmology

Background:

• Deep sequencing technologies have advanced rapidly, increasing data generation in life sciences.
• Despite fast processing algorithms, intuitive and portable data analysis solutions for transcriptomics remain scarce.
• Ocular gene expression analysis is crucial for understanding eye diseases and developing targeted therapies.

Purpose of the Study:

• To develop a user-friendly, web-based transcriptome database for exploring human ocular gene expression.
• To enable comparison of gene expression across healthy and diseased human eye tissues.
• To identify novel tissue-specific genes and potential diagnostic/therapeutic targets in ocular tissues.

Main Methods:

• Development of a platform-independent, web-based transcriptome database.
• Normalization of sequencing reads across 100 human ocular tissue samples (15 types).
• Differential gene expression analysis, unsupervised clustering, and bioinformatic cell type deconvolution (xCell).

Main Results:

• Accurate clustering of samples by tissue type, confirming high tissue specificity.
• Identification of several novel tissue-specific marker genes involved in ocular processes (e.g., myelination, visual perception).
• Detailed cellular profiles of different ocular tissues were revealed through cell type deconvolution.

Conclusions:

• The Human Eye Transcriptome Atlas provides an intuitive platform for exploring ocular gene expression without requiring bioinformatics expertise.
• The database facilitates rapid access to molecular insights into ocular tissues and diseases.
• Identified novel marker genes offer potential as diagnostic and therapeutic targets for various eye conditions.