MicroRNAs have been recognized to play critical role in diabetic retinopathy (DR) development. MiR-96 has shown an increased expression in DR. It subsequently regulates expression of its target genes, those involved in insulin signaling pathway in normal retina and DR. One of the most important genes targeted by miR-96 is IRS1 whose protein acts in many important metabolic tasks of insulin that are impaired in diabetes and DR. The aim of our study is in silico identification of genes and proteins related to IRS1 and DR development.

GeneMANIA (version 3.6.0) was used to construct gene interaction networks for IRS1 gene. To investigate protein-protein interactions for IRS1 protein, we used STRING database (version 10.5) which is a biological database useful for our purpose. To confirm the data, BioGRID (version 3.5) database was applied as an additional database for gene and protein interaction networks. In the next step, ArrayExpress (EMBL-EBI) was employed to find Microarray profile and genomics data about gene expression profile of retinal cells associated with DR. Finally, text mining was done through EVEX and COREMINE databases.

Using GeneMANIA, STRING and BioGRID websites, we nominated genes and proteins with physical interactions/ co-expression with IRS1 gene. Intended data was merged with Microarray profiles and eventually a list of genes and proteins and their interaction networks was provided. The network diagram was generated in Cytoscape 3.6.1 (Figure 1).

This study provided a list of candidate genes and proteins which may have an altered expression in different stages of DR. The cognate genes will be studied further in wet lab. The outcome of these data analysis methods could be applicable to find more key factors involved in DR development.