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 ...

SUMMARYIt has long been recognised that polyploid species do not always neatly fall into the categories of autoor allopolyploid, leading to the term 'segmental allopolyploid' to describe everything in between. The meiotic behaviour of such intermediate species is not fully understood, nor is there consensus as to how to model their inheritance patterns. In this study we used a tetraploid cut rose (Rosa hybrida) population, genotyped using the 68K WagRhSNP array, to construct an ultra-high-density linkage map of all homologous chromosomes using methods previously developed for autotetraploids. Using the predicted bivalent configurations in this population we quantified differences in pairing behaviour among and along homologous chromosomes, leading us to correct our estimates of recombination frequency to account for this behaviour. This resulted in the re-mapping of 25 695 SNP markers across all homologues of the seven rose chromosomes, tailored to the pairing behaviour of each chromosome in each parent. We confirmed the inferred differences in pairing behaviour among chromosomes by examining repulsionphase linkage estimates, which also carry information about preferential pairing and recombination. Currently, the closest sequenced relative to rose is Fragaria vesca. Aligning the integrated ultra-dense rose map with the strawberry genome sequence provided a detailed picture of the synteny, confirming overall co-linearity but also revealing new genomic rearrangements. Our results suggest that pairing affinities may vary along chromosome arms, which broadens our current understanding of segmental allopolyploidy.

For both plant (e.g., potato) and animal (e.g., salmon) species, unveiling the genetic architecture of complex traits is key to the genetic improvement of polyploids in agriculture. F 1 progenies of a biparental cross are often used for quantitative trait loci (QTL) mapping in outcrossing polyploids, where haplotype reconstruction by identifying the parental origins of marker alleles is necessary. In this paper, we build a novel and integrated statistical framework for multilocus haplotype reconstruction in a full-sib tetraploid family from biallelic marker dosage data collected from single-nucleotide polymorphism (SNP) arrays or next-generation sequencing technology given a genetic linkage map. Compared to diploids, in tetraploids, additional complexity needs to be addressed, including double reduction and possible preferential pairing of chromosomes. We divide haplotype reconstruction into two stages: parental linkage phasing for reconstructing the most probable parental haplotypes and ancestral inference for probabilistically reconstructing the offspring haplotypes conditional on the reconstructed parental haplotypes. The simulation studies and the application to real data from potato show that the parental linkage phasing is robust to, and that the subsequent ancestral inference is accurate for, complex chromosome pairing behaviors during meiosis, various marker segregation types, erroneous genetic maps except for long-range disturbances of marker ordering, various amounts of offspring dosage errors (up to 20%), and various fractions of missing data in parents and offspring dosages.KEYWORDS polyploidy; outbred population; double reduction; preferential pairing; ancestral inference P OLYPLOIDY occurs in some animals such as salmon but is pervasive in plants, including many important crop species such as potato (Solanum tuberosum) and alfalfa (Medicago sativa). Understanding the genetic architecture of complex traits in polyploids plays a fundamental role in their genetic improvement. Numerous statistical methods have been developed for quantitative trait locus mapping in humans, animal, and plant species with diploid genomes. In contrast, corresponding studies in polyploids are very few, although an analogous linear model framework was introduced for tetraploid mapping populations at least 15 years ago (Xie and Xu 2000;Hackett et al. 2001).In the linear (mixed) models for quantitative trait locus mapping in diploid and polyploid species, the genetic component of a quantitative trait requires the calculation of genetic predictors (covariates), often expressed as the probabilities that the alleles at putative quantitative trait loci (QTL) are derived from particular parental chromosomes conditional on the observed genotypic data of mapping individuals and their parents. The haplotype reconstruction for calculating genetic predictors in diploids has been well developed (Mott et al. 2000;Broman et al. 2003;Liu et al. 2010;Zheng et al. 2015). The aim of this work is haplotype reconstruction in a full-sib ...

Dispersal comprises a complex life-history syndrome that influences the demographic dynamics of especially those species that live in fragmented landscapes, the structure of which may in turn be expected to impose selection on dispersal. We have constructed an individual-based evolutionary sexual model of dispersal for species occurring as metapopulations in habitat patch networks. The model assumes correlated random walk dispersal with edge-mediated behaviour (habitat selection) and spatially correlated stochastic local dynamics. The model is parametrized with extensive data for the Glanville fritillary butterfly. Based on empirical results for a single nucleotide polymorphism (SNP) in the phosphoglucose isomerase (Pgi ) gene, we assume that dispersal rate in the landscape matrix, fecundity and survival are affected by a locus with two alleles, A and C, individuals with the C allele being more mobile. The model was successfully tested with two independent empirical datasets on spatial variation in Pgi allele frequency. First, at the level of local populations, the frequency of the C allele is the highest in newly established isolated populations and the lowest in old isolated populations. Second, at the level of sub-networks with dissimilar numbers and connectivities of patches, the frequency of C increases with decreasing network size and hence with decreasing average metapopulation size. The frequency of C is the highest in landscapes where local extinction risk is high and where there are abundant opportunities to establish new populations. Our results indicate that the strength of the coupling of the ecological and evolutionary dynamics depends on the spatial scale and is asymmetric, demographic dynamics having a greater immediate impact on genetic dynamics than vice versa.