  Biological aging is characterized by an age-dependent increase in the
probability of death and by a decrease in the reproductive capacity. Individual
age-dependent rates of survival and reproduction have a strong impact on
population dynamics, and the genetic elements determining survival and
reproduction are under different selective forces throughout an organism
lifespan. Here we develop a highly versatile numerical model of genome
evolution --- both asexual and sexual --- for a population of virtual
individuals with overlapping generations, where the genetic elements affecting
survival and reproduction rate at different life stages are free to evolve due
to mutation and selection. Our model recapitulates several emerging properties
of natural populations, developing longer reproductive lifespan under stable
conditions and shorter survival and reproduction in unstable environments.
Faster aging results as the consequence of the reduced strength of purifying
selection in more unstable populations, which have large portions of the genome
that accumulate detrimental mutations. Unlike sexually reproducing populations
under constant resources, asexually reproducing populations fail to develop an
age-dependent increase in death rates and decrease in reproduction rates,
therefore escaping senescence. Our model provides a powerful in silico
framework to simulate how populations and genomes change in the context of
biological aging and opens a novel analytical opportunity to characterize how
real populations evolve their specific aging dynamics.
