Details

Autor(en) / Beteiligte

• Mangoni, Manuel
• Petrizzelli, Francesco
• Liorni, Niccolò
• Bianco, Salvatore Daniele
• Biagini, Tommaso
• Napoli, Alessandro
• Adinolfi, Marta
• Guzzi, Pietro Hiram
• Novelli, Antonio
• Caputo, Viviana
• Mazza, Tommaso

Titel

Investigating Mitochondrial Gene Expression Patterns in IDrosophila melanogaster/I Using Network Analysis to Understand Aging Mechanisms

Ist Teil von

• Applied sciences, 2023-06, Vol.13 (12)

Ort / Verlag

MDPI AG

Erscheinungsjahr

2023

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• The process of aging is a complex phenomenon that involves a progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, the scientific community has utilized several tools. Among them, mitochondrial DNA has emerged as a crucial factor in biological aging, given that mitochondrial dysfunction is thought to significantly contribute to this phenomenon. Additionally, Drosophila melanogaster has proven to be a valuable model organism for studying aging due to its low cost, capacity to generate large populations, and ease of genetic manipulation and tissue dissection. Moreover, graph theory has been employed to understand the dynamic changes in gene expression patterns associated with aging and to investigate the interactions between aging and aging-related diseases. In this study, we have integrated these approaches to examine the patterns of gene co-expression in Drosophila melanogaster at various stages of development. By applying graph-theory techniques, we have identified modules of co-expressing genes, highlighting those that contain a significantly high number of mitochondrial genes. We found important mitochondrial genes involved in aging and age-related diseases in Drosophila melanogaster, including UQCR-C1, ND-B17.2, ND-20, and Pdhb. Our findings shed light on the role of mitochondrial genes in the aging process and demonstrate the utility of Drosophila melanogaster as a model organism and graph theory in aging research.