While it is well understood that the pace of evolution depends on the interplay between natural selection, random genetic drift, mutation, and gene flow, it is not always easy to disentangle the relative roles of these factors with data from natural populations. One popular approach to infer whether the observed degree of population differentiation has been influenced by local adaptation is the comparison of neutral marker gene differentiation (as reflected in F ST ) and quantitative trait divergence (as reflected in Q ST ). However, this method may lead to compromised statistical power, because F ST and Q ST are summary statistics which neglect information on specific pairs of populations, and because current multivariate tests of neutrality involve an averaging procedure over the traits. Further, most F ST -Q ST comparisons actually replace Q ST by its expectation over the evolutionary process and are thus theoretically flawed. To overcome these caveats, we derived the statistical distribution of population means generated by random genetic drift and used the probability density of this distribution to test whether the observed pattern could be generated by drift alone. We show that our method can differentiate between genetic drift and selection as a cause of population differentiation even in cases with F ST ¼ Q ST and demonstrate with simulated data that it disentangles drift from selection more accurately than conventional F ST -Q ST tests especially when data sets are small. N ULL models have an important role in many areas of biology (e.g., Whitlock and Phillips 2000;Hubbell 2001;Ohta 2002) and not least in studies of population differentiation. For instance, the expectation that genetic differentiation occurs most readily toward the direction of maximum additive genetic variance (Schluter 1996) has provided a useful null model for evaluating the role of the ancestral G matrix in the rate and direction of evolutionary transitions (e.g., McGuigan 2006). Likewise, while few evolutionary biologists would doubt the power of natural selection over genetic drift (Hohenlohe and Arnold 2008), comparisons of the index of quantitative genetic differentiation (Q ST ) to the index of neutral genetic differentiation (F ST ) have provided a useful platform to identify traits and populations subject to directional selection (Merilä and Crnokrak 2001;McKay and Latta 2002;Leinonen et al. 2008).The current neutrality tests of population differentiation make restrictive assumptions or suffer from various methodological or logical problems (e.g., O'Hara and Merilä 2005;Beaumont 2008; Whitlock 2008). To start with, the popular method of comparing the index of quantitative genetic differentiation (Q ST ) to the index of neutral genetic differentiation (F ST ) does not necessarily provide practical means to analyze whether a small number of populations are locally adapted to their environments, as obtaining reliable estimates typically requires data from .10 populations in controlled environmental conditions (O'Hara ...
BackgroundPlasmodium vivax has the widest geographic distribution of the human malaria parasites and nearly 2.5 billion people live at risk of infection. The control of P. vivax in individuals and populations is complicated by its ability to relapse weeks to months after initial infection. Strains of P. vivax from different geographical areas are thought to exhibit varied relapse timings. In tropical regions strains relapse quickly (three to six weeks), whereas those in temperate regions do so more slowly (six to twelve months), but no comprehensive assessment of evidence has been conducted. Here observed patterns of relapse periodicity are used to generate predictions of relapse incidence within geographic regions representative of varying parasite transmission.MethodsA global review of reports of P. vivax relapse in patients not treated with a radical cure was conducted. Records of time to first P. vivax relapse were positioned by geographic origin relative to expert opinion regions of relapse behaviour and epidemiological zones. Mixed-effects meta-analysis was conducted to determine which geographic classification best described the data, such that a description of the pattern of relapse periodicity within each region could be described. Model outputs of incidence and mean time to relapse were mapped to illustrate the global variation in relapse.ResultsDifferences in relapse periodicity were best described by a historical geographic classification system used to describe malaria transmission zones based on areas sharing zoological and ecological features. Maps of incidence and time to relapse showed high relapse frequency to be predominant in tropical regions and prolonged relapse in temperate areas.ConclusionsThe results indicate that relapse periodicity varies systematically by geographic region and are categorized by nine global regions characterized by similar malaria transmission dynamics. This indicates that relapse may be an adaptation evolved to exploit seasonal changes in vector survival and therefore optimize transmission. Geographic patterns in P. vivax relapse are important to clinicians treating individual infections, epidemiologists trying to infer P. vivax burden, and public health officials trying to control and eliminate the disease in human populations.
Understanding how a monophyletic lineage of a species diverges into several adaptive forms has received increased attention in recent years, but the underlying mechanisms in this process are still under debate. Postglacial fishes are excellent model organisms for exploring this process, especially the initial stages of ecological speciation, as postglacial lakes represent replicated discrete environments with variation in available niches. Here, we combine data of niche utilization, trophic morphology, and 17 microsatellite loci to investigate the diversification process of three sympatric European whitefish morphs from three northern Fennoscandian lakes. The morphological divergence in the gill raker number among the whitefish morphs was related to the utilization of different trophic niches and was associated with reproductive isolation within and across lakes. The intralacustrine comparison of whitefish morphs showed that these systems represent two levels of adaptive divergence: (1) a consistent littoral–pelagic resource axis; and (2) a more variable littoral–profundal resource axis. The results also indicate that the profundal whitefish morph has diverged repeatedly from the ancestral littoral whitefish morph in sympatry in two different watercourses. In contrast, all the analyses performed revealed clustering of the pelagic whitefish morphs across lakes suggesting parallel postglacial immigration with the littoral whitefish morph into each lake. Finally, the analyses strongly suggested that the trophic adaptive trait, number of gill rakers, was under diversifying selection in the different whitefish morphs. Together, the results support a complex evolutionary scenario where ecological speciation acts, but where both allopatric (colonization history) and sympatric (within watercourse divergence) processes are involved.
Detection of footprints of historical natural selection on quantitative traits in cross-sectional data sets is challenging, especiallywhen the number of populations to be compared is small and the populations are subject to strong random genetic drift. We extend a recent Bayesian multivariate approach to differentiate between selective and neutral causes of population differentiation by the inclusion of habitat information. The extended framework allows one to test for signals of selection in two ways: by comparing the patterns of population differentiation in quantitative traits and in neutral loci, and by comparing the similarity of habitats and phenotypes. We illustrate the framework using data on variation of eight morphological and behavioral traits among four populations of nine-spined sticklebacks (Pungitius pungitius). In spite of the strong signal of genetic drift in the study system (average F ST = 0.35 in neutral markers), strong footprints of adaptive population differentiation were uncovered both in morphological and behavioral traits. The results give quantitative support for earlier qualitative assessments, which have attributed the observed differentiation to adaptive divergence in response to differing ecological conditions in pond and marine habitats.
Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs.
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