Shortest-path network analysis was employed to identify novel genes that modulate longevity in the baker’s yeast Saccharomyces cerevisiae. Based upon a set of previously reported genes associated with increased life span, a shortest path network algorithm was applied to a pre-existing protein-protein interaction dataset in order to construct a shortest-path longevity network. To validate this network, the replicative aging potential of 88 single gene deletion strains corresponding to predicted components of the shortest path longevity network was determined. The 88 single-gene deletion strains identified by a network approach are significantly enriched for mutation conferring both increased and decreased replicative life span when compared to a randomly selected set of 564 single-gene deletion strains or to the current data set available for the entire haploid deletion collection. In addition, previously unknown longevity genes were identified, several of which function in a longevity pathway believed to mediate life span extension in response to dietary restriction. This study represents the first biologically validated application of a network construct to the study of aging and rigorously demonstrates, also for the first time, that shortest path network analysis is a potentially powerful tool for predicting genes that function as potential modulators of aging.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-2612 |
| Date | 03 September 2008 |
| Creators | Managbanag, JR |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © The Author |
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