iSyTE: integrated Systems Tool for Eye gene discovery

Abstract

Purpose: : To facilitate the identification of genes associated with cataract and other ocular defects, we developed and validated a computational tool termed iSyTE (integrated Systems Tool for Eye gene discovery; http://bioinformatics.udel.edu/Research/iSyTE). iSyTE uses a mouse embryonic lens gene expression dataset as a bioinformatic filter to select candidate genes from human or mouse genomic regions implicated in disease, and to prioritize them for further mutational and functional analyses.

Methods: : We obtained microarray gene expression profiles for microdissected embryonic mouse lens at three key developmental timepoints as it transitions from the embryonic day E10.5 stage of lens placode invagination to E12.5 lens primary fiber cell differentiation. Differentially regulated genes were identified by in silico comparison of lens gene expression profiles to those of whole embryo body (WB) lacking ocular tissue.

Results: : This strategy effectively removes highly expressed but non-specific housekeeping genes from lens tissue expression profiles, allowing identification of less-highly expressed but lens disease associated genes. To present this resource as a user-friendly tool, we created custom iSyTE tracks at the UCSC Genome Browser. iSyTE tracks represent the degree of enrichment of expression in the developing lens that is presented in a color-coded format, with red indicating "highly lens-enriched" and blue indicating "expressed but not lens-enriched" or "highly down-regulated". This representation allows immediate visual detection of the best candidate genes in a given genomic interval, and allows one to zoom in or out to visualize the presence of promising candidates within a particular region or proximal to it. Among 24 previously mapped human genomic intervals containing genes associated with isolated congenital cataract, iSyTE correctly ranked the mutant gene within the top 2 selected candidates in ~88% cases. Finally, we analyzed the Cat-Map datasets and identified 17 mapped cataract intervals for which a gene has not yet been assigned. We then used iSyTE to make predictions of the most promising candidate genes in these loci. We provide the top candidate genes in each mapped interval based on their high lens-enrichment rank in iSyTE. If iSyTE’s ~88% success rate can be extended to new predictions, this list of novel genes can potentially serve as a useful resource for prioritizing candidate cataract associated genes for validation.

Conclusions: : iSyTE is a publically available web resource that can be used to prioritize candidate genes within mapped genomic intervals associated with congenital cataract for further investigation. Extension of this approach to other ocular tissue components will facilitate eye disease gene discovery.

Keywords: cataract • candidate gene analysis • genetics