Identifying core biological processes distinguishing human eye tissues with precise systems-level gene expression...

Area of Science:

• Genomics
• Ophthalmology
• Bioinformatics

Background:

• Gene expression profiling using RNA-sequencing (RNA-seq) is crucial for understanding tissue function.
• Previous studies have profiled eye tissues and other human tissues separately, but lacked integrated analysis.
• An integrated dataset of human eye and other body tissues is needed to understand pan-expression relationships.

Purpose of the Study:

• To integrate all publicly available healthy human eye RNA-sequencing datasets with other human tissue datasets.
• To analyze gene expression patterns and relationships between different eye tissues (cornea, retina, RPE-choroid) and other body tissues.
• To build the first human weighted gene correlation networks for eye tissues and identify disease associations.

Main Methods:

• Collation of all publicly available healthy human eye RNA-seq datasets and other human tissue datasets.
• Application of differential expression analysis, clustering, and gene ontology term enrichment.
• Construction of human weighted gene correlation networks and integration of single-cell RNA-seq data from mouse retina.

Main Results:

• Identification of biological processes and pan-expression relationships across multiple human eye tissues and other body tissues.
• Development of the first human weighted gene correlation networks for retina and RPE-choroid tissues.
• Highlighting of known biological pathways and enrichment of eye gene disease associations.

Conclusions:

• This integrated study provides a comprehensive resource for understanding human eye gene expression.
• The developed web application offers powerful tools for data exploration and discovery in ophthalmology.
• The findings pave the way for new insights into eye biology and the genetic basis of eye diseases.