RAPID FITNESS RECOVERY IN MUTATIONALLY DEGRADED LINES OF CAENORHABDITIS ELEGANS

Selective sweeps and parallel mutation in the adaptive recovery from deleterious mutation in Caenorhabditis elegans

Deleterious mutation poses a serious threat to human health and the persistence of small populations. Although adaptive recovery from deleterious mutation has been well-characterized in prokaryotes, the evolutionary mechanisms by which multicellular eukaryotes recover from deleterious mutation remain unknown. We applied high-throughput DNA sequencing to characterize genomic divergence patterns associated with the adaptive recovery from deleterious mutation using a Caenorhabditis elegans recovery-line system. The C. elegans recovery lines were initiated from a low-fitness mutation-accumulation (MA) line progenitor and allowed to independently evolve in large populations (N ∼ 1000) for 60 generations. All lines rapidly regained levels of fitness similar to the wild-type (N2) MA line progenitor. Although there was a near-zero probability of a single mutation fixing due to genetic drift during the recovery experiment, we observed 28 fixed mutations. Cross-generational analysis showed that all mutations went from undetectable population-level frequencies to a fixed state in 10-20 generations. Many recovery-line mutations fixed at identical timepoints, suggesting that the mutations, if not beneficial, hitchhiked to fixation during selective sweep events observed in the recovery lines. No MA line mutation reversions were detected. Parallel mutation fixation was observed for two sites in two independent recovery lines. Analysis using a C. elegans interactome map revealed many predicted interactions between genes with recovery line-specific mutations and genes with previously accumulated MA line mutations. Our study suggests that recovery-line mutations identified in both coding and noncoding genomic regions might have beneficial effects associated with compensatory epistatic interactions.

Evolution of the Caenorhabditis elegans genome

A fundamental problem in genome biology is to elucidate the evolutionary forces responsible for generating nonrandom patterns of genome organization. As the first metazoan to benefit from full-genome sequencing, Caenorhabditis elegans has been at the forefront of research in this area. Studies of genomic patterns, and their evolutionary underpinnings, continue to be augmented by the recent push to obtain additional full-genome sequences of related Caenorhabditis taxa. In the near future, we expect to see major advances with the onset of whole-genome resequencing of multiple wild individuals of the same species. In this review, we synthesize many of the important insights to date in our understanding of genome organization and function that derive from the evolutionary principles made explicit by theoretical population genetics and molecular evolution and highlight fertile areas for future research on unanswered questions in C. elegans genome evolution. We call attention to the need for C. elegans researchers to generate and critically assess nonadaptive hypotheses for genomic and developmental patterns, in addition to adaptive scenarios. We also emphasize the potential importance of evolution in the gonochoristic (female and male) ancestors of the androdioecious (hermaphrodite and male) C. elegans as the source for many of its genomic and developmental patterns.

Establishment of facultative sexuals

The existence of sex is one of the major unsolved problems in biology. We use computer simulations to model conditions in which sex may first become established. We develop an individual-based population model and show that a hypothetical facultative sex gene can fix, provided that the initial cost is low. It is demonstrated that the equilibrium fitness in the population increases with increasing population size and decreasing mutation rate. The probability of the establishment of the sex gene is found not to be directly related to the fitness difference between the asexual and sexual populations. This change in fitness on changing the parameters of the model is investigated.