Telemetry and genetics reveal asymmetric dispersal of a lake-feeding salmonid between inflow and outflow spawning streams at a microgeographic scale

The degree of natal philopatry relative to natal dispersal in animal populations has important demographic and genetic consequences and often varies substantially within species. In salmonid fishes, lakes have been shown to have a strong influence on dispersal and gene flow within catchments; for example, populations spawning in inflow streams are often reproductively isolated and genetically distinct from those spawning in relatively distant outflow streams. Less is known, however, regarding the level of philopatry and genetic differentiation occurring at microgeographic scales, for example, where inflow and outflow streams are separated by very small expanses of lake habitat. Here, we investigated the interplay between genetic differentiation and fine-scale spawning movements of brown trout between their lake-feeding habitat and two spawning streams (one inflow, one outflow, separated by <100 m of lake habitat). Most (69.2%) of the lake-tagged trout subsequently detected during the spawning period were recorded in just one of the two streams, consistent with natal fidelity, while the remainder were detected in both streams, creating an opportunity for these individuals to spawn in both natal and non-natal streams. The latter behavior was supported by genetic sibship analysis, which revealed several half-sibling dyads containing one individual that was sampled as a fry in the outflow and another that was sampled as fry in the inflow. Genetic clustering analyses in conjunction with telemetry data suggested that asymmetrical dispersal patterns were occurring, with natal fidelity being more common among individuals originating from the outflow than the inflow stream. This was corroborated by Bayesian analysis of gene flow, which indicated significantly higher rates of gene flow from the inflow into the outflow than vice versa. Collectively, these results reveal how a combination of telemetry and genetics can identify distinct reproductive behaviors and associated asymmetries in natal dispersal that produce subtle, but nonetheless biologically relevant, population structuring at microgeographic scales

Assessing population genetic structure via the maximisation of genetic distance

<p>Abstract</p> <p>Background</p> <p>The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.</p> <p>Methods</p> <p>In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a <it>simulated annealing </it>algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.</p> <p>Results</p> <p>The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for <it>F</it>_{<it>ST </it>}≥ 0.03, but only STRUCTURE estimates the correct number of clusters for <it>F</it>_{<it>ST </it>}as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.</p> <p>Conclusion</p> <p>This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.</p

A predictive assessment of genetic correlations between traits in chickens using markers

International audienceAbstractBackgroundGenomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations.MethodsA multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λG + (1 − λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the “optimum” λ was determined using cross-validation.ResultsEstimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW–HHP and BM–HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together.ConclusionsOur findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection

Relaxation of Selection With Equalization of Parental Contributions in Conservation Programs: An Experimental Test With Drosophila melanogaster

Equalization of parental contributions is one of the most simple and widely recognized methods to maintain genetic diversity in conservation programs, as it halves the rate of increase in inbreeding and genetic drift. It has, however, the negative side effect of implying a reduced intensity of natural selection so that deleterious genes are less efficiently removed from the population with possible negative consequences on the reproductive capacity of the individuals. Theoretical results suggest that the lower fitness resulting from equalization of family sizes relative to that for free contribution schemes is expected to be substantial only for relatively large population sizes and after many generations. We present a long-term experiment with Drosophila melanogaster, comparing the fitness performance of lines maintained with equalization of contributions (EC) and others maintained with no management (NM), allowing for free matings and contributions from parents. Two (five) replicates of size N = 100 (20) individuals of each type of line were maintained for 38 generations. As expected, EC lines retained higher gene diversity and allelic richness for four microsatellite markers and a higher heritability for sternopleural bristle number. Measures of life-history traits, such as egg-to-adult viability, mating success, and global fitness declined with generations, but no significant differences were observed between EC and NM lines. Our results, therefore, provide no evidence to suggest that equalization of family sizes entails a disadvantage on the reproductive capacity of conserved populations in comparison with no management procedures, even after long periods of captivity

Management of genetic diversity of subdivided populations in conservation programmes

Population subdivision must be explicitly considered in the management of conservation programmes, as most populations of wild species at risk of extinction and those kept in captivity are spatially structured. The partition of gene and allelic diversity in within- and between-subpopulation components allows for the integral management of populations. We summarise the main aspects of this partition and some of its applications in terms of priorisation of populations for conservation and establishment of synthetic populations. The procedures for the maintenance of diversity in subdivided populations making use of molecular markers and its implementation by the software METAPOP are illustrated with empirical data. © 2009 Springer Science+Business Media B.V

The accuracy of a heritability estimator using molecular information

The heritability of a quantitative trait is a key parameter to quantify the genetic variation present in a population. Although estimates of heritability require accurate information on the genetic relationship among individuals, pedigree data is generally lacking in natural populations. Nowadays, the increasing availability of DNA markers is making possible the estimation of coancestries from neutral molecular information. In 1996, K. Ritland developed an approach to estimate heritability from the regression of the phenotypic similarity on the marker-based coancestry. We carried out simulations to analyze the accuracy of the estimates of heritability obtained by this method using information from a variable number of neutral codominant markers. Because the main application of the estimator is on populations with no family structure, such as natural populations, its accuracy was tested under this scenario. However, the method was also investigated under other scenarios, in order to test the influence of different factors (family structure, assortative mating and phenotypic selection) on the precision. Our results suggest that the main factor causing a directional bias in the estimated heritability is the presence of phenotypic selection, and that very noisy estimates are obtained in the absence of a familiar structure and for small population sizes. The estimated heritabilities from marker-based coancestries showed lower accuracy than the estimated heritabilities from genealogical coancestries. However, a large amount of bias occurred even in the most favourable situation where genealogical coancestries are known. The results also indicate that the molecular markers are more suitable to infer coancestry than inbreeding

Improving the inference of population genetic structure in the presence of related individuals

It is well known that the presence of related individuals can affect the inference of population genetic structure from molecular data. This has been verified, for example, on the unsupervised Bayesian clustering algorithm implemented in the software STRUCTURE. This methodology assumes, among others, Hardy-Weinberg and linkage equilibrium within subpopulations. The existence of groups of close relatives, such as full-sib families, may prevent these assumptions to be fulfilled, causing the algorithm to work suboptimally. The purpose of this study was to evaluate the effect of the presence of related individuals on a different methodology (implemented in CLUSTER_DIST) for population genetic structure inference. This approach arranges individuals to maximize the genetic distance between groups and does not make Hardy-Weinberg and linkage equilibrium assumptions. We study the robustness of this approach to the presence of close relatives in a sample using simulated scenarios involving combinations of several factors, including the number of subpopulations, the level of differentiation between them, the number, size and type (full or half-sibs) of families in a sample, and the type and number of molecular markers available for clustering analysis. Results indicate that the methodology that maximizes the genetic distance between subpopulations is less influenced by the presence of related individuals than the program STRUCTURE. Therefore, the former can be used, in combination with the program STRUCTURE, to analyse population genetic structure when related individuals are suspected to be present in a sample

The role of local ecology during hybridization at the initial stages of ecological speciation in a marine snail

Hybrid zones of ecologically divergent populations are ideal systems to study the interaction between natural selection and gene flow during the initial stages of speciation. Here, we perform an amplified fragment length polymorphism (AFLP) genome scan in parallel hybrid zones between divergent ecotypes of the marine snail Littorina saxatilis, which is considered a model case for the study of ecological speciation. Ridged-Banded (RB) and Smooth-Unbanded (SU) ecotypes are adapted to different shore levels and microhabitats, although they present a sympatric distribution at the mid-shore where they meet and mate (partially assortatively). We used shell morphology, outlier and nonoutlier AFLP loci from RB, SU and hybrid specimens captured in sympatry to determine the level of phenotypic and genetic introgression. We found different levels of introgression at parallel hybrid zones and nonoutlier loci showed more gene flow with greater phenotypic introgression. These results were independent from the phylogeography of the studied populations, but not from the local ecological conditions. Genetic variation at outlier loci was highly correlated with phenotypic variation. In addition, we used the relationship between genetic and phenotypic variation to estimate the heritability of morphological traits and to identify potential Quantitative Trait Loci to be confirmed in future crosses. These results suggest that ecology (exogenous selection) plays an important role in this hybrid zone. Thus, ecologically based divergent natural selection is responsible, simultaneously, for both ecotype divergence and hybridization. On the other hand, genetic introgression occurs only at neutral loci (nonoutliers). In the future, genome-wide studies and controlled crosses would give more valuable information about this process of speciation in the face of gene flow. © 2013 European Society For Evolutionary Biology