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Identification of Ageing-related Hub Genes in Humans, Mouse and Rat Based on Bioinformatics Analysis
Mona Chaurasiya1, Gajendra Prasad2
1University Department of Biotechnology, L.N. Mithila University, Darbhanga, Bihar, India.
Background:
Ageing is a natural process observed in all living organisms. It is a complex biological process involving many genes and pathways. As such, ageing in an organism is associated with an increased likelihood of developing various neurological diseases, for example, Alzheimer's disease (AD) and Parkinson's disease (PD).
Purpose:
Ageing is associated with many complex processes and functions that are highly interconnected. In this study, we identified pivotal nodes or hubs that significantly contribute to an ageing network, including those highly connected nodes within the network that are particularly important, using available bioinformatics tools in humans and other model organisms. Thus, mutating or altering any of these nodes in a network can result in significant changes in the overall functioning of an organism.
Methods:
For this study, the ageing genes of humans and mice were retrieved from the GenAge database, while the ageing genes of rats were retrieved from the Ageing & Age related Diseases present in Rat Genome Database. STRING (version 11.5), an online tool, was used to create the network. Cytoscape (version 3.10.0), an open-source software with an integrated tool called cytoHubba, was used to identify the hubs from the STRING network in humans, mice and rats. The online tool Enrichr was used to test the functional enrichment of hub genes in humans.
Results:
TP53, Trp53 and Actb were identified as important genes in the network, contributing significantly to the process of ageing in humans, mice and rats, respectively, along with others in the network.
Conclusion:
Identification of these hubs from the network of ageing and ageing-associated genes deserves further investigation to advance existing knowledge and to improve our understanding of ageing in humans and other model organisms.
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