Abstract
Purpose :
Cataract is a major cause of blindness which is treated by surgical lens fiber cell removal followed by intraocular lens implantation. However, the lens epithelial cells (LECs) remaining behind post-surgery undergo an injury response which reduces treatment effectiveness. This often could cause a secondary cataract known as posterior capsular opacification (PCO). Our lab has generated numerous RNA-seq datasets that reveal the time course of transcriptomic changes occurring in response to surgery. However, these large datasets are cumbersome to query simultaneously limiting their utility in hypothesis generation. Here we develop a user-friendly and interactive data visualization tool for the lens injury response time series (LIRTS).
Methods :
Existing RNA-seq datasets from wildtype mouse LECs at 0h, 6h, 24h, 48h, 72h and 120h post injury were reanalyzed using a standard pipeline incorporating edgeR to obtain fragments per kilobase million (FPKM) values for all genes. The R Shiny package was deployed for data visualization.
Results :
The LIRTS viewer allows users without bioinformatics experience to visualize the expression time course for any gene of interest during the LEC wound healing response via both a normalized boxplot and a scatterplot expressing FPKM values obtained for each analyzed sample.
Conclusions :
This visualization tool has already contributed to numerous ongoing studies of the lens injury response leading to both a recent publication and grant funding. Currently, our focus is to make the tool publicly accessible by hosting on a web server. This will aid researchers interested in the pathogenesis of PCO, and fibrotic diseases in general, understand the dynamics of gene expression during injury induced epithelial to mesenchymal transition.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.