Abstract
Purpose:
Diabetic retinopathy remains the leading cause of blindness in working age adults and recent clinical studies have demonstrated that despite achieving good diabetes control, patients with previously poor diabetes control continue to have a higher rate of developing diabetic retinopathy and other complications. To examine this metabolic memory hypothesis of diabetic retinopathy we examined the time course of retinal transcriptomic changes and their epigenetic regulation in a rat model of diabetes. Additionally insulin treatments were begun after different periods of poor glycemic control to test the ability of insulin to prevent changes from occurring and to reverse extant mRNA alterations.
Methods:
An ultra-deep (~100 million reads) RNA-Seq approach of poly-A RNAs was used with multiple biological replicates per group to provide comprehensive description of genes expressed in the retina and accurately quantify differences in gene expression at the transcript variant level. To confirm mRNA changes of interest high throughput qPCR of samples from independent animal sets was used. Epigenetic regulation of differential gene expression was assessed by bisulphite amplicon sequencing (BSAS).
Results:
Inflammatory signatures were induced rapidly with diabetes and were both prevented and reversed by insulin treatment. A subset of mRNA changes with transcription regulation, neuronal and endothelial function, and of unknown function in the retina were resistant to normalization by insulin treatment. The deep level of sequencing also allowed for identification of specific mRNA variants dysregulated with diabetes. Potential regulation through promoter DNA methylation was observed for some genes but not others suggesting a range of regulatory mechanisms.
Conclusions:
Outcomes of this study include identification of targets for functional/interventional and regulation/epigenetic studies of specific genes and pathways that may serve as initiating events in the development of diabetic retinopathy and one of the deepest examinations of the retinal transcriptome to date. This study also provides a demonstration of a standardized RNA-Seq approach (discovery, bioinformatics analysis, and validation) that can be performed in-house by ophthalmology disease biology teams.
Keywords: 533 gene/expression •
499 diabetic retinopathy •
688 retina