RESEARCH ARTICLE


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



Luigi Donato1, 2, 3, *, Lucia Denaro1
1 Department of Biomedical and Dental Sciences and Morphofunctional Images, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Messina, Italy
2 Department of vanguard medicine and therapies, biomolecular strategies and neuroscience, Section of Neuroscience-Applied Molecular Genetics and Predictive Medicine, I. E. ME. S. T., Palermo, Italy
3 Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Messina, Italy


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© 2018 Donato and Denaro.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Biomedical and Dental Sciences and Morphofunctional Images, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, via C. Valeria 1, 98125 Messina, Italy; Tel: +39 0902213324; Fax: +39 090692449; E-mail: ldonato@unime.it


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.