Inferring the functions of longevity genes with modular subnetwork biomarkers of Caenorhabditis elegans aging.
A central goal of biogerontology is to identify robust gene-expression biomarkers of aging. Here we develop a method where the biomarkers are networks of genes selected based on age-dependent activity and a graph-theoretic property called modularity. Tested on Caenorhabditis elegans, our algorithm yields better biomarkers than previous methods - they are more conserved across studies and better predictors of age. We apply these modular biomarkers to assign novel aging-related functions to poorly characterized longevity genes.
Department of Medical Biophysics, University of Toronto, 610 University Avenue, Toronto, M5G 2M9, Canada.
Kristen
K
Fortney
Max
M
Kotlyar
Igor
I
Jurisica
D000375:Aging / Q000235:genetics; D000465:Algorithms; D000818:Animals; D017173:Caenorhabditis elegans / Q000235:genetics / Q000502:physiology*; D015870:Gene Expression; D053263:Gene Regulatory Networks; D017238:Genes, Helminth; D005819:Genetic Markers; D008136:Longevity / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
D005819:Genetic Markers