Data from: An experimental test of the mutation-selection balance model for the maintenance of genetic variance in fitness components Sharp, Nathaniel P.; Agrawal, Aneil F.
Despite decades of research, the factors that maintain genetic variation for fitness are poorly understood. It is unclear what fraction of the variance in a typical fitness component can be explained by mutation-selection balance and whether fitness components differ in this respect. In theory, the level of standing variance in fitness due to mutation-selection balance can be predicted using the rate of fitness decline under mutation accumulation, and this prediction can be directly compared to the standing variance observed. This approach allows for controlled statistical tests of the sufficiency of the mutation-selection balance model, and could be used to identify traits or populations where genetic variance is maintained by other factors. For example, some traits may be influenced by sexually-antagonistic balancing selection, resulting in an excess of standing variance beyond that generated by deleterious mutations. We describe the underlying theory and use it to test the mutation-selection balance (MSB) model for three traits in Drosophila melanogaster. We find evidence for differences among traits, with MSB being sufficient to explain genetic variance in larval viability but not male mating success or female fecundity. Our results are consistent with balancing selection on sexual fitness components, and demonstrate the feasibility of rigorous statistical tests of the mutation-selection balance model.; Usage notes
trait_measurementsMeasures of three traits for MA lines and corresponding control lines ('MA_control'), and for lines derived from an outbred population ('standing'). The traits are male mating success ('male') female fecundity ('female') and larval viability ('viability'). Female fecundity measures are egg counts. Male mating success measures are number of females inseminated by focal males relative to competitors (total = focal + competitor). Viability measures are number of focal adults that developed relative to competitors (total = focal + competitor).
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