RESEARCH ARTICLE

Bioinformatic Analysis of a “Functional Cluster” Probably Related to Retinitis Pigmentosa

The Open Bioinformatics Journal 23 May 2018 RESEARCH ARTICLE DOI: 10.2174/1875036201811010089

Abstract

Background:

Retinitis pigmentosa is an eye hereditary disease caused by photoreceptor death. One of the biggest problem is represented by its genetic heterogeneity, which has not yet allowed us to found all causative genes and how known ones could influence each other, leading to retinitis etiopathogenesis.

Objective:

To propose the possible relation between the “functional cluster” of vision dark adaptation, made of five phototransductional genes (RCVRN, GNB1, GNGT1, GRK7 and ARRB1), and retinitis pigmentosa onset.

Methods:

A bioinformatic approach was exploited: the starting point was searching through online database as PubMed and EMBASE to acquire information about the state of art of these gene. This step was followed by an in-silico analysis, performed by softwares as Cytoscape and Genecards Suite Plus, articulated in three phases: I) identification of common pathways and genes involved in; II) collection of previously detected genes; III) deep analysis of intersected genes and implication into etiopathogenesis of analzyed disease.

Results:

The whole in-silico analysis showed that all five gene products cooperate during phototransductional activation, expecially in the dark adaptation. Interestingly, the most exciting aspect regards the direct relation with several known retinitis pigmentosa causative genes, in form of protein interactions or other pathway correlations.

Conclusion:

Pathway analysis permitted us to hypothesize a possible role of analyzed genes in retinitis pigmentosa etiopathogenesis, also considering the key activity of their encoded proteins. Next step will be validating our hypotesis with functional assays to ensure the real meaning of this possible association, leading to new potential retinitis pigmentosa causative genes.

Keywords: Retinitis pigmentosa, Maculopathy, Reactome, Biograph, String, Genecards.
Fulltext HTML PDF ePub
1800
1801
1802
1803
1804