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Senior Scholar Award in Aging
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Daniel
Promislow,
Ph.D.
University of Georgia
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Gene-gene interactions, gene networks and aging in natural population of Drosophila
Most of what we know about the genetics of aging comes from four organisms well-adapted to life in the lab--yeast, nematodes, fruit flies and mice. These are powerful model systems, but not without problems. Previous studies have shown that organisms maintained in the lab often evolve increased early fecundity and greatly shortened life spans. In the search for genes that extend life span in laboratory organisms, many of the genes that we identify may simply restore average longevity in a population to its pre-lab state. It is hard to know in this case whether such a gene could also restore longevity in natural populations. Imagine an isolated human population in which the gene for Huntington Disease (HD) was fixed. If one were to eliminate the mutant gene from the population, life expectancy at birth in this population would increase dramatically. The naïve observer might assume that HD was an 'aging gene'. This hypothetical scenario may actually occur in fruit flies, where lab-adapted populations may have many novel mutants that would be rare or non-existent in the wild.
In general, we know little about how the many recently discovered genes that extend life span might interact with one another, and how their effects might be influenced by the many thousands of other genes in the genome. Recent studies in our lab with the fruit fly, Drosophila melanogaster, have found that the effects on longevity of two such genes, Superoxide Dismutase and Methuselah, depended on genetic background. These mutants extended longevity in some natural genetic backgrounds but actually reduced longevity in others.
Our goal is to study how genes that extend longevity interact not only with one another, but also with other genes in the genomes of naturally long-lived wild caught flies as well as short-lived lab strains. In addition to these empirical studies, we will explore theoretical models of gene networks to predict what types of genes are most likely to play a role in the aging process.
Contact
Dr. Promislow.
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