Accurate detection of offspring resulting from hybridization between individuals of distinct populations has a range of applications in conservation and population genetics. We assessed the hybrid identification efficiency of two methods (implemented in the STRUCTURE and NEWHYBRIDS programs) which are tailored to identifying hybrid individuals but use different approaches. Simulated first- and second-generation hybrids were used to assess the performance of these two methods in detecting recent hybridization under scenarios with different levels of genetic divergence and varying numbers of loci. Despite the different approaches of the methods, the hybrid detection efficiency was generally similar and neither of the two methods outperformed the other in all scenarios assessed. Interestingly, hybrid detection efficiency was only minimally affected by whether reference population allele frequency information was included or not. In terms of genotyping effort, efficient detection of F1 hybrid individuals requires the use of 12 or 24 loci with pairwise F(ST) between hybridizing parental populations of 0.21 or 0.12, respectively. While achievable, these locus numbers are nevertheless higher than the number of loci currently commonly applied in population genetic studies. The method of STRUCTURE seemed to be less sensitive to the proportion of hybrids included in the sample, while NEWHYBRIDS seemed to perform slightly better when individuals from both backcross and F1 hybrid classes were present in the sample. However, separating backcrosses from purebred parental individuals requires a considerable genotyping effort (at least 48 loci), even when divergence between parental populations is high.

Defining populations and identifying ecological and life-history characteristics affecting genetic structure is important for understanding species biology and hence, for managing threatened or endangered species or populations. In this study, populations of the world's largest indigenous Atlantic salmon (Salmo salar) stock were first inferred using model-based clustering methods, following which life-history and habitat variables best predicting the genetic diversity of populations were identified. This study revealed that natal homing of Atlantic salmon within the Teno River system is accurate at least to the tributary level. Generally, defining populations by main tributaries was observed to be a reasonable approach in this large river system, whereas in the mainstem of the river, the number of inferred populations was fewer than the number of distinct sampling sites. Mainstem and headwater populations were genetically more diverse and less diverged, while each tributary fostered a distinct population with high genetic differentiation and lower genetic diversity. Population structure and variation in genetic diversity among populations were poorly explained by geographical distance. In contrast, age-structure, as estimated by the proportion of multisea-winter spawners, was the most predictive variable in explaining the variation in the genetic diversity of the populations. This observation, being in agreement with theoretical predictions, emphasizes the essence of large multisea-winter females in maintaining the genetic diversity of populations. In addition, the unique genetic diversity of populations, as estimated by private allele richness, was affected by the ease of accessibility of a site, with more difficult to access sites having lower unique genetic diversity. Our results show that despite this species' high capacity for migration, tributaries foster relatively closed populations with little gene flow which will be important to consider when developing management strategies for the system.

Elucidating the genetic basis of adaptation to the local environment can improve our understanding of how the diversity of life has evolved. In this study, we used a dense SNP array to identify candidate loci potentially underlying fine-scale local adaptation within a large Atlantic salmon (Salmo salar) population. By combining outlier, gene-environment association and haplotype homozygosity analyses, we identified multiple regions of the genome with strong evidence for diversifying selection. Several of these candidate regions had previously been identified in other studies, demonstrating that the same loci could be adaptively important in Atlantic salmon at subdrainage, regional and continental scales. Notably, we identified signals consistent with local selection around genes associated with variation in sexual maturation, energy homeostasis and immune defence. These included the large-effect age-at-maturity gene vgll3, the known obesity gene mc4r, and major histocompatibility complex II. Most strikingly, we confirmed a genomic region on Ssa09 that was extremely differentiated among subpopulations and that is also a candidate for local selection over the global range of Atlantic salmon. This region colocalized with a haplotype strongly associated with spawning ecotype in sockeye salmon (Oncorhynchus nerka), with circumstantial evidence that the same gene (six6) may be the selective target in both cases. The phenotypic effect of this region in Atlantic salmon remains cryptic, although allelic variation is related to upstream catchment area and covaries with timing of the return spawning migration. Our results further inform management of Atlantic salmon and open multiple avenues for future research.

Microsatellite genotyping is a common DNA characterization technique in population, ecological and evolutionary genetics research. Since different alleles are sized relative to internal size-standards, different laboratories must calibrate and standardize allelic designations when exchanging data. This interchange of microsatellite data can often prove problematic. Here, 16 microsatellite loci were calibrated and standardized for the Atlantic salmon, Salmo salar, across 12 laboratories. Although inconsistencies were observed, particularly due to differences between migration of DNA fragments and actual allelic size (‘size shifts’), inter-laboratory calibration was successful. Standardization also allowed an assessment of the degree and partitioning of genotyping error. Notably, the global allelic error rate was reduced from 0.05 ± 0.01 prior to calibration to 0.01 ± 0.002 post-calibration. Most errors were found to occur during analysis (i.e. when size-calling alleles; the mean proportion of all errors that were analytical errors across loci was 0.58 after calibration). No evidence was found of an association between the degree of error and allelic size range of a locus, number of alleles, nor repeat type, nor was there evidence that genotyping errors were more prevalent when a laboratory analyzed samples outside of the usual geographic area they encounter. The microsatellite calibration between laboratories presented here will be especially important for genetic assignment of marine-caught Atlantic salmon, enabling analysis of marine mortality, a major factor in the observed declines of this highly valued species.Electronic supplementary materialThe online version of this article (doi:10.1007/s10709-011-9554-4) contains supplementary material, which is available to authorized users.

A long-held, but poorly tested, assumption in natural populations is that individuals that disperse into new areas for reproduction are at a disadvantage compared to individuals that reproduce in their natal habitat, underpinning the eco-evolutionary processes of local adaptation and ecological speciation. Here, we capitalize on fine-scale population structure and natural dispersal events to compare the reproductive success of local and dispersing individuals captured on the same spawning ground in four consecutive parent-offspring cohorts of wild Atlantic salmon (Salmo salar). Parentage analysis conducted on adults and juvenile fish showed that local females and males had 9.6 and 2.9 times higher reproductive success than dispersers, respectively. Our results reveal how higher reproductive success in local spawners compared to dispersers may act in natural populations to drive population divergence and promote local adaptation over microgeographic spatial scales without clear morphological differences between populations.