Demography and selection have been recognized for their important roles in shaping patterns of nucleotide variability. To investigate the relative effects of these forces in the genome of Drosophila melanogaster, we used a multi-locus scan (105 fragments) of X-linked DNA sequence variation in a putatively ancestral African and a derived European population. Surprisingly, we found evidence for a recent size expansion in the African population, i.e., a significant excess of singletons at a chromosome-wide level. In the European population, such an excess was not detected. In contrast to the African population, we found evidence for positive natural selection in the European sample: (i) a large number of loci with low levels of variation and (ii) a significant excess of derived variants at the low-variation loci that are fixed in the European sample but rare in the African population. These results are consistent with the hypothesis that the European population has experienced frequent selective sweeps in the recent past during its adaptation to new habitats. Our study shows the advantages of a genomic approach (over a locus-specific analysis) in disentangling demographic and selective forces.

Identifying regions of the Drosophila melanogaster genome that have been recent targets of positive Darwinian selection will provide evidence for adaptations that have helped this species to colonize temperate habitats. We have begun a search for such genomic regions by analyzing multiple loci (about 250) dispersed across the X chromosome in a putatively ancestral population from East Africa and a derived European population. For both populations we found evidence for past changes in population size. We estimated that a major bottleneck associated with the colonization of Europe occurred about 3,500–16,000 years ago. We also found that while this bottleneck can account for most of the reduction in variation observed in the European sample, there is a deficit of polymorphism in some genomic regions that cannot be explained by demography alone.

Association studies have identified dozens of genetic variants linked to training responses and sport-related traits. However, no intervention studies utilizing the idea of personalised training based on athlete's genetic profile have been conducted. Here we propose an algorithm that allows achieving greater results in response to high- or low-intensity resistance training programs by predicting athlete's potential for the development of power and endurance qualities with the panel of 15 performance-associated gene polymorphisms. To develop and validate such an algorithm we performed two studies in independent cohorts of male athletes (study 1: athletes from different sports (n = 28); study 2: soccer players (n = 39)). In both studies athletes completed an eight-week high- or low-intensity resistance training program, which either matched or mismatched their individual genotype. Two variables of explosive power and aerobic fitness, as measured by the countermovement jump (CMJ) and aerobic 3-min cycle test (Aero3) were assessed pre and post 8 weeks of resistance training. In study 1, the athletes from the matched groups (i.e. high-intensity trained with power genotype or low-intensity trained with endurance genotype) significantly increased results in CMJ (P = 0.0005) and Aero3 (P = 0.0004). Whereas, athletes from the mismatched group (i.e. high-intensity trained with endurance genotype or low-intensity trained with power genotype) demonstrated non-significant improvements in CMJ (P = 0.175) and less prominent results in Aero3 (P = 0.0134). In study 2, soccer players from the matched group also demonstrated significantly greater (P < 0.0001) performance changes in both tests compared to the mismatched group. Among non- or low responders of both studies, 82% of athletes (both for CMJ and Aero3) were from the mismatched group (P < 0.0001). Our results indicate that matching the individual's genotype with the appropriate training modality leads to more effective resistance training. The developed algorithm may be used to guide individualised resistance-training interventions.

It has been hypothesized that the ratio of X-linked to autosomal sequence diversity is influenced by unequal sex ratios in Drosophila melanogaster populations. We conducted a genome scan of single nucleotide polymorphism (SNP) of 378 autosomal loci in a derived European population and of a subset of 53 loci in an ancestral African population. On the basis of these data and our already available X-linked data, we used a coalescent-based maximum-likelihood method to estimate sex ratios and demographic histories simultaneously for both populations. We confirm our previous findings that the African population experienced a population size expansion while the European population suffered a population size bottleneck. Our analysis also indicates that the female population size in Africa is larger than or equal to the male population size. In contrast, the European population shows a huge excess of males. This unequal sex ratio and the bottleneck alone, however, cannot account for the overly strong decrease of X-linked diversity in the European population (compared to the reduction on the autosome). The patterns of the frequency spectrum and the levels of linkage disequilibrium observed in Europe suggest that, in addition, positive selection must have acted in the derived population.

Streptococcal inhibitor of complement (Sic) is a highly polymorphic extracellular protein made predominantly by serotype M1 group A Streptococcus (GA