These authors contributed equally to the work.
Age-related behaviors have distinct transcriptional profiles in Caenorhabditis elegans
Version of Record online: 5 SEP 2008
© 2008 The Authors. Journal compilation © Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland 2008
Volume 7, Issue 6, pages 850–865, December 2008
How to Cite
Golden, T. R., Hubbard, A., Dando, C., Herren, M. A. and Melov, S. (2008), Age-related behaviors have distinct transcriptional profiles in Caenorhabditis elegans. Aging Cell, 7: 850–865. doi: 10.1111/j.1474-9726.2008.00433.x
- Issue online: 24 NOV 2008
- Version of Record online: 5 SEP 2008
- Accepted for publication 24 August 2008
- Caenorhabditis elegans
There has been a great deal of interest in identifying potential biomarkers of aging. Biomarkers of aging would be useful to predict potential vulnerabilities in an individual that may arise well before they are chronologically expected, due to idiosyncratic aging rates that occur between individuals. Prior attempts to identify biomarkers of aging have often relied on the comparisons of long-lived animals to a wild-type control. However, the effect of interventions in model systems that prolong lifespan (such as single gene mutations or caloric restriction) can sometimes be difficult to interpret due to the manipulation itself having multiple unforeseen consequences on physiology, unrelated to aging itself. The search for predictive biomarkers of aging therefore is problematic, and the identification of metrics that can be used to predict either physiological or chronological age would be of great value. One methodology that has been used to identify biomarkers for numerous pathologies is gene expression profiling. Here, we report whole-genome expression profiles of individual wild-type Caenorhabditis elegans covering the entire wild-type nematode lifespan. Individual nematodes were scored for either age-related behavioral phenotypes, or survival, and then subsequently associated with their respective gene expression profiles. This facilitated the identification of transcriptional profiles that were highly associated with either physiological or chronological age. Overall, our approach serves as a paradigm for identifying potential biomarkers of aging in higher organisms that can be repeatedly sampled throughout their lifespan.