Characterizing Male-Female Interactions Using Natural Genetic Variation in Drosophila melanogaster

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Abstract

Drosophila melanogaster females commonly mate with multiple males establishing the opportunity for pre- and postcopulatory sexual selection. Traits impacting sexual selection can be affected by a complex interplay of the genotypes of the competing males, the genotype of the female, and compatibilities between the males and females. We scored males from 96 2nd and 94 3rd chromosome substitution lines for traits affecting reproductive success when mated with females from 3 different genetic backgrounds. The traits included male-induced female refractoriness, male remating ability, the proportion of offspring sired under competitive conditions and male-induced female fecundity. We observed significant effects of male line, female genetic background, and strong male by female interactions. Some males appeared to be "generalists" and performed consistently across the different females; other males appeared to be "specialists" and performed very well with a particular female and poorly with others. "Specialist" males did not, however, prefer to court those females with whom they had the highest reproductive fitness. Using 143 polymorphisms in male reproductive genes, we mapped several genes that had consistent effects across the different females including a derived, high fitness allele in Acp26Aa that may be the target of adaptive evolution. We also identified a polymorphism upstream of PebII that may interact with the female genetic background to affect male-induced refractoriness to remating. These results suggest that natural variation in PebII might contribute to the observed male-female interactions.

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The ecology of individuals: incidence and implications of individual specialization.

Daniel I. Bolnick, Richard Svanbäck, James A Fordyce … (2003)

Most empirical and theoretical studies of resource use and population dynamics treat conspecific individuals as ecologically equivalent. This simplification is only justified if interindividual niche variation is rare, weak, or has a trivial effect on ecological processes. This article reviews the incidence, degree, causes, and implications of individual-level niche variation to challenge these simplifications. Evidence for individual specialization is available for 93 species distributed across a broad range of taxonomic groups. Although few studies have quantified the degree to which individuals are specialized relative to their population, between-individual variation can sometimes comprise the majority of the population's niche width. The degree of individual specialization varies widely among species and among populations, reflecting a diverse array of physiological, behavioral, and ecological mechanisms that can generate intrapopulation variation. Finally, individual specialization has potentially important ecological, evolutionary, and conservation implications. Theory suggests that niche variation facilitates frequency-dependent interactions that can profoundly affect the population's stability, the amount of intraspecific competition, fitness-function shapes, and the population's capacity to diversify and speciate rapidly. Our collection of case studies suggests that individual specialization is a widespread but underappreciated phenomenon that poses many important but unanswered questions.

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A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

Paul Scheet, Matthew Stephens (2006)

We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.