Rapid divergence and convergence of life-history in experimentally evolved Drosophila melanogaster.

Laboratory selection experiments are alluring in their simplicity, power, and ability to inform us about how evolution works. A longstanding challenge facing evolution experiments with metazoans is that significant generational turnover takes a long time. In this work, we present data from a unique system of experimentally evolved laboratory populations of Drosophila melanogaster that have experienced three distinct life-history selection regimes. The goal of our study was to determine how quickly populations of a certain selection regime diverge phenotypically from their ancestors, and how quickly they converge with independently derived populations that share a selection regime. Our results indicate that phenotypic divergence from an ancestral population occurs rapidly, within dozens of generations, regardless of that population's evolutionary history. Similarly, populations sharing a selection treatment converge on common phenotypes in this same time frame, regardless of selection pressures those populations may have experienced in the past. These patterns of convergence and divergence emerged much faster than expected, suggesting that intermediate evolutionary history has transient effects in this system. The results we draw from this system are applicable to other experimental evolution projects, and suggest that many relevant questions can be sufficiently tested on shorter timescales than previously thought.

The great evolutionary divide: two genomic systems biologies of aging.

There is not one systems biology of aging, but two. Though aging can evolve in either sexual or asexual species when there is asymmetric reproduction, the evolutionary genetics of aging in species with frequent sexual recombination are quite different from those arising when sex is rare or absent. When recombination is rare, selection is expected to act chiefly on rare large-effect mutations, which purge genetic variation due to genome-wide hitchhiking. In such species, the systems biology of aging can focus on the effects of large-effect mutants, transgenics, and combinations of such genetic manipulations. By contrast, sexually outbreeding species maintain abundant genetic polymorphism within populations. In such species, the systems biology of aging can examine the genome-wide effects of selection and genetic drift on the numerous polymorphic loci that respond to laboratory selection for different patterns of aging. An important question of medical relevance is to what extent insights derived from the systems biology of aging in model species can be applied to human aging.

An evolutionary and genomic approach to challenges and opportunities for eliminating aging.

While solutions to major scientific and medical problems are never perfect or complete, it is still reasonable to delineate cases where both have been essentially solved. For example, Darwin's theory of natural selection provides a successful solution to the problem of biological adaptation, while the germ theory of infection solved the scientific problem of contagious disease. Likewise in the context of medicine, we have effectively solved the problem of contagious disease, reducing it to a minor cause of death and disability for almost everyone in countries with advanced medicine and adequate resources. Evolutionary biologists claim to have solved the scientific problem of aging: we explain it theoretically using Hamilton's forces of natural selection; in experimental evolution we readily manipulate the onset, rate, and eventual cessation of aging by manipulating these forces. In this article, we turn to the technological challenge of solving the medical problem of aging. While we feel that the broad outlines of such a solution are clear enough starting from the evolutionary solution to the scientific problem of aging, we do not claim that we can give a complete or exhaustive plan for medically solving the problem of aging. But we are confident that biology and medicine will effectively solve the problem of aging within the next 50 years, providing Hamiltonian lifestyle changes, tissue repair, and genomic technological opportunities are fully exploited in public health practices, in medical practice, and in medical research, respectively.