Investigating mitochondrial gene expression patterns inDrosophila melanogasterusing network analysis to understand aging mechanisms

Drosophila melanogaster; network analysis; mitochondrial DNA; aging Technology QH301-705.5 T Physics QC1-999 aging mitochondrial DNA Engineering (General). Civil engineering (General) Chemistry <i>Drosophila melanogaster</i>; network analysis; mitochondrial DNA; aging TA1-2040 Biology (General) <i>Drosophila melanogaster</i> network analysis QD1-999
DOI: 10.1101/2023.05.16.540914 Publication Date: 2023-05-18T17:40:11Z
ABSTRACT
AbstractThe 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 melanogasterhas 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 inDrosophila melanogasterat 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 inDrosophila 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 ofDrosophila melanogasteras a model organism and graph theory in aging research.
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