Marker-assisted estimation of quantitative genetic parameters in rainbow trout, Oncorhynchus mykiss

Evolutionary potential in the Alpine: trait heritabilities and performance variation of the dwarf willow Salix herbacea from different elevations and microhabitats

Alpine ecosystems are seriously threatened by climate change. One of the key mechanisms by which plants can adapt to changing environmental conditions is through evolutionary change. However, we still know little about the evolutionary potential in wild populations of long-lived alpine plants. Here, we investigated heritabilities of phenological traits, leaf size, and performance traits in natural populations of the long-lived alpine dwarf shrub Salix herbacea using relatedness estimates inferred from SSR (Simple Sequence Repeat) markers. Salix herbacea occurs in early- and late-snowmelt microhabitats (ridges and snowbeds), and we assessed how performance consequences of phenological traits and leaf size differ between these microhabitats in order to infer potential for evolutionary responses. Salix herbacea showed low, but significant, heritabilities of leaf size, clonal and sexual reproduction, and moderate heritabilities of phenological traits. In both microhabitats, we found that larger leaves, longer intervals between snowmelt and leaf expansion, and longer GDD (growing-degree days) until leaf expansion resulted in a stronger increase in the number of stems (clonal reproduction). In snowbeds, clonal reproduction increased with a shorter GDD until flowering, while the opposite was found on ridges. Furthermore, the proportion of flowering stems increased with GDD until flowering in both microhabitats. Our results suggest that the presence of significant heritable variation in morphology and phenology might help S. herbacea to adapt to changing environmental conditions. However, it remains to be seen if the rate of such an evolutionary response can keep pace with the rapid rate of climate change.

Parentage assignment with genomic markers: a major advance for understanding and exploiting genetic variation of quantitative traits in farmed aquatic animals

Since the middle of the 1990s, parentage assignment using microsatellite markers has been introduced as a tool in aquaculture breeding. It now allows close to 100% assignment success, and offered new ways to develop aquaculture breeding using mixed family designs in commercial conditions. Its main achievements are the knowledge and control of family representation and inbreeding, especially in mass spawning species, above all the capacity to estimate reliable genetic parameters in any species and rearing system with no prior investment in structures, and the development of new breeding programs in many species. Parentage assignment should not be seen as a way to replace physical tagging, but as a new way to conceive breeding programs, which have to be optimized with its specific constraints, one of the most important being to well define the number of individuals to genotype to limit costs, maximize genetic gain while minimizing inbreeding. The recent possible shift to (for the moment) more costly single nucleotide polymorphism markers should benefit from future developments in genomics and marker-assisted selection to combine parentage assignment and indirect prediction of breeding values.

Differences in boldness are repeatable and heritable in a long-lived marine predator

Animal personalities, composed of axes of consistent individual behaviors, are widely reported and can have important fitness consequences. However, despite theoretical predictions that life-history trade-offs may cause and maintain personality differences, our understanding of the evolutionary ecology of personality remains poor, especially in long-lived species where trade-offs and senescence have been shown to be stronger. Furthermore, although much theoretical and empirical work assumes selection shapes variation in personalities, studies exploring the genetic underpinnings of personality traits are rare. Here we study one standard axis of personality, the shy–bold continuum, in a long-lived marine species, the wandering albatross from Possession Island, Crozet, by measuring the behavioral response to a human approach. Using generalized linear mixed models in a Bayesian framework, we show that boldness is highly repeatable and heritable. We also find strong differences in boldness between breeding colonies, which vary in size and density, suggesting birds are shyer in more dense colonies. These results demonstrate that in this seabird population, boldness is both heritable and repeatable and highlights the potential for ecological and evolutionary processes to shape personality traits in species with varying life-history strategies.

Pedigree-free estimates of heritability in the wild: promising prospects for selfing populations

Estimating the genetic variance available for traits informs us about a population's ability to evolve in response to novel selective challenges. In selfing species, theory predicts a loss of genetic diversity that could lead to an evolutionary dead-end, but empirical support remains scarce. Genetic variability in a trait is estimated by correlating the phenotypic resemblance with the proportion of the genome that two relatives share identical by descent ('realized relatedness'). The latter is traditionally predicted from pedigrees (Φ A : expected value) but can also be estimated using molecular markers (average number of alleles shared). Nevertheless, evolutionary biologists, unlike animal breeders, remain cautious about using marker-based relatedness coefficients to study complex phenotypic traits in populations. In this paper, we review published results comparing five different pedigree-free methods and use simulations to test individual-based models (hereafter called animal models) using marker-based relatedness coefficients, with a special focus on the influence of mating systems. Our literature review confirms that Ritland's regression method is unreliable, but suggests that animal models with marker-based estimates of relatedness and genomic selection are promising and that more testing is required. Our simulations show that using molecular markers instead of pedigrees in animal models seriously worsens the estimation of heritability in outcrossing populations, unless a very large number of loci is available. In selfing populations the results are less biased. More generally, populations with high identity disequilibrium (consanguineous or bottlenecked populations) could be propitious for using marker-based animal models, but are also more likely to deviate from the standard assumptions of quantitative genetics models (non-additive variance).

Genomic scan as a tool for assessing the genetic component of phenotypic variance in wild populations

Methods for estimating quantitative trait heritability in wild populations have been developed in recent years which take advantage of the increased availability of genetic markers to reconstruct pedigrees or estimate relatedness between individuals, but their application to real-world data is not exempt from difficulties. This chapter describes a recent marker-based technique which, by adopting a genomic scan approach and focusing on the relationship between phenotypes and genotypes at the individual level, avoids the problems inherent to marker-based estimators of relatedness. This method allows the quantification of the genetic component of phenotypic variance ("degree of genetic determination" or "heritability in the broad sense") in wild populations and is applicable whenever phenotypic trait values and multilocus data for a large number of genetic markers (e.g., amplified fragment length polymorphisms, AFLPs) are simultaneously available for a sample of individuals from the same population. The method proceeds by first identifying those markers whose variation across individuals is significantly correlated with individual phenotypic differences ("adaptive loci"). The proportion of phenotypic variance in the sample that is statistically accounted for by individual differences in adaptive loci is then estimated by fitting a linear model to the data, with trait value as the dependent variable and scores of adaptive loci as independent ones. The method can be easily extended to accommodate quantitative or qualitative information on biologically relevant features of the environment experienced by each sampled individual, in which case estimates of the environmental and genotype × environment components of phenotypic variance can also be obtained.

Additive genetic variance of quantitative traits in natural and pond-bred populations of the Lake Tanganyika cichlid Tropheus moorii

Quantitative genetic studies in natural populations are of growing interest to speciation research since divergence is often believed to arise through micro-evolutionary change, caused by natural selection on functional morphological traits. The species flock of cichlid fishes in Africa's oldest lake, Lake Tanganyika, offers a rare opportunity to study this process. Using the cichlid species Tropheus moorii, we assessed the potential for microevolution in a set of morphological traits by estimating their quantitative genetic basis of variation. Two approaches were employed: (1) estimation of trait heritabilities (h²) in situ from a sample of wild caught fish, and (2) estimation of h² from first generation offspring produced in a semi-natural breeding experiment. In both cases, microsatellite data were used to infer pedigree structure among the sampled individuals and estimates of h² were made using an animal model approach. Although power was limited by the pedigree structures estimated (particularly in the wild caught sample), we nonetheless demonstrate the presence of significant additive genetic variance for aspects of morphology that, in the cichlid species Tropheus moorii, are expected to be functionally and ecologically important, and therefore likely targets of natural selection. We hypothesize that traits showing significant additive genetic variance, such as the mouth position have most likely played a key role in the adaptive evolution of the cichlid fish Tropheus moorii.

Combinatorial reconstruction of half-sibling groups from microsatellite data

While full-sibling group reconstruction from microsatellite data is a well-studied problem, reconstruction of half-sibling groups is much less studied, theoretically challenging, and computationally demanding. In this paper, we present a formulation of the half-sibling reconstruction problem and prove its APX-hardness. We also present exact solutions for this formulation and develop heuristics. Using biological and synthetic datasets we present experimental results and compare them with the leading alternative software COLONY. We show that our results are competitive and allow half-sibling group reconstruction in the presence of polygamy, which is prevalent in nature.

Estimating breeding values with molecular relatedness and reconstructed pedigrees in natural mating populations of common sole, Solea solea

Captive populations where natural mating in groups is used to obtain offspring typically yield unbalanced population structures with highly skewed parental contributions and unknown pedigrees. Consequently, for genetic parameter estimation, relationships need to be reconstructed or estimated using DNA marker data. With missing parents and natural mating groups, commonly used pedigree reconstruction methods are not accurate and lead to loss of data. Relatedness estimators, however, infer relationships between all animals sampled. In this study, we compared a pedigree relatedness method and a relatedness estimator ("molecular relatedness") method using accuracy of estimated breeding values. A commercial data set of common sole, Solea solea, with 51 parents and 1953 offspring ("full data set") was used. Due to missing parents, for 1338 offspring, a pedigree could be reconstructed with 10 microsatellite markers ("reduced data set").

Consistency between marker- and genealogy-based heritability estimates in an experimental stand of Prosopis alba (Leguminosae)

Prosopis represents a valuable forest resource in arid and semiarid regions. Management of promising species requires information about genetic parameters, mainly the heritability (h(2)) of quantitative profitable traits. This parameter is traditionally estimated from progeny tests or half-sib analysis conducted in experimental stands. Such an approach estimates h(2) from the ratio of between-family/total phenotypic variance. These analyses are difficult to apply to natural populations of species with a long life cycle, overlapping generations, and a mixed mating system, without genealogical information. A promising alternative is the use of molecular marker information to infer relatedness between individuals and to estimate h(2) from the regression of phenotypic similarity on inferred relatedness. In the current study we compared h(2) of 13 quantitative traits estimated by these two methods in an experimental stand of P. alba, where genealogical information was available. We inferred pairwise relatedness by Ritland's method using six microsatellite loci. Relatedness and heritability estimates from molecular information were highly correlated to the values obtained from genealogical data. Although Ritland's method yields lower h(2) estimates and tends to overestimate genetic correlations between traits, this approach is useful to predict the expected relative gain of different quantitative traits under selection without genealogical information.

Pedigree-free animal models: the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Wild pedigrees: the way forward

Metrics derived from pedigrees are key to investigating several major issues in evolutionary biology, including the quantitative genetic architecture of traits, inbreeding depression, and the evolution of cooperation and inbreeding avoidance. There is merit in studying these issues in natural populations experiencing spatially and temporally variable environmental conditions, since these analyses may yield different results from laboratory studies and allow us to understand population responses to rapid environmental change. Partial pedigrees are now available for several natural populations which are the subject of long-term individual-based studies, and analyses using these pedigrees are leading to important insights. Accurate pedigree construction supported by molecular genetic data is now feasible across a wide range of taxa, and even where only imprecise pedigrees are available it is possible to estimate the consequences of imprecision for the questions of interest. In outbred diploid populations, the pedigree approach is superior to analyses based on marker-based pairwise estimators of coancestry.

Evolutionary consequences of habitat loss for Pacific anadromous salmonids

Large portions of anadromous salmonid habitat in the western United States has been lost because of dams and other blockages. This loss has the potential to affect salmonid evolution through natural selection if the loss is biased, affecting certain types of habitat differentially, and if phenotypic traits correlated with those habitat types are heritable. Habitat loss can also affect salmonid evolution indirectly, by reducing genetic variation and changing its distribution within and among populations. In this paper, we compare the characteristics of lost habitats with currently accessible habitats and review the heritability of traits which show correlations with habitat/environmental gradients. We find that although there is some regional variation, inaccessible habitats tend to be higher in elevation, wetter and both warmer in the summer and colder in the winter than habitats currently available to anadromous salmonids. We present several case studies that demonstrate either a change in phenotypic or life history expression or an apparent reduction in genetic variation associated with habitat blockages. These results suggest that loss of habitat will alter evolutionary trajectories in salmonid populations and Evolutionarily Significant Units. Changes in both selective regime and standing genetic diversity might affect the ability of these taxa to respond to subsequent environmental perturbations. Both natural and anthropogenic and should be considered seriously in developing management and conservation strategies.

Molecular ecological approaches to studying the evolutionary impact of selective harvesting in wildlife

Harvesting of wildlife populations by humans is usually targeted by sex, age or phenotypic criteria, and is therefore selective. Selective harvesting has the potential to elicit a genetic response from the target populations in several ways. First, selective harvesting may affect population demographic structure (age structure, sex ratio), which in turn may have consequences for effective population size and hence genetic diversity. Second, wildlife-harvesting regimes that use selective criteria based on phenotypic characteristics (e.g. minimum body size, horn length or antler size) have the potential to impose artificial selection on harvested populations. If there is heritable genetic variation for the target characteristic and harvesting occurs before the age of maturity, then an evolutionary response over time may ensue. Molecular ecological techniques offer ways to predict and detect genetic change in harvested populations, and therefore have great utility for effective wildlife management. Molecular markers can be used to assess the genetic structure of wildlife populations, and thereby assist in the prediction of genetic impacts by delineating evolutionarily meaningful management units. Genetic markers can be used for monitoring genetic diversity and changes in effective population size and breeding systems. Tracking evolutionary change at the phenotypic level in the wild through quantitative genetic analysis can be made possible by genetically determined pedigrees. Finally, advances in genome sequencing and bioinformatics offer the opportunity to study the molecular basis of phenotypic variation through trait mapping and candidate gene approaches. With this understanding, it could be possible to monitor the selective impacts of harvesting at a molecular level in the future. Effective wildlife management practice needs to consider more than the direct impact of harvesting on population dynamics. Programs that utilize molecular genetic tools will be better positioned to assess the long-term evolutionary impact of artificial selection on the evolutionary trajectory and viability of harvested populations.

Estimation of quantitative genetic parameters using marker-inferred relatedness in Japanese flounder: a case study of upward bias

Marker-based methods for estimating heritability have been proposed as an effective means to study quantitative traits in long-lived organisms and natural populations. However, practical examinations to evaluate the usefulness and robustness of a regression method are limited. Using several quantitative traits of Japanese flounder Paralichthys olivaceus, the present study examined the influence of relatedness estimator and population structure on the estimation of heritability and genetic correlation under a regression method with 7 microsatellite loci. Significant heritability and genetic correlation were detected for several quantitative traits in 2 laboratory populations but not in a natural population. In the laboratory populations, upward bias in heritability appeared depending on the relatedness estimators and the populations. Upward bias in heritability increased with decreasing the actual variance of relatedness, suggesting that the estimates of heritability under the regression method tend to be overestimated due to the underestimation of the actual variance of relatedness. Therefore, relationship structure and precise estimation of relatedness are critical for applying this method.

Heritability of life-history tactics and genetic correlation with body size in a natural population of brook charr (Salvelinus fontinalis)

A common dimorphism in life-history tactic in salmonids is the presence of an anadromous pathway involving a migration to sea followed by a freshwater reproduction, along with an entirely freshwater resident tactic. Although common, the genetic and environmental influence on the adoption of a particular life-history tactic has rarely been studied under natural conditions. Here, we used sibship-reconstruction based on microsatellite data and an 'animal model' approach to estimate the additive genetic basis of the life-history tactic adopted (anadromy vs. residency) in a natural population of brook charr, Salvelinus fontinalis. We also assess its genetic correlation with phenotypic correlated traits, body size and body shape. Significant heritability was observed for life-history tactic (varying from 0.52 to 0.56 depending on the pedigree scenario adopted) as well as for body size (from 0.44 to 0.50). There was also a significant genetic correlation between these two traits, whereby anadromous fish were genetically associated with bigger size at age 1 (r(G) = -0.52 and -0.61). Our findings thus indicate that life-history tactics in this population have the potential to evolve in response to selection acting on the tactic itself or indirectly via selection on body size. This study is one of the very few to have successfully used sibship-reconstruction to estimate quantitative genetic parameters under wild conditions.

Performance of marker-based relatedness estimators in natural populations of outbred vertebrates

Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent-offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i.e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.

Population structure attributable to reproductive time: isolation by time and adaptation by time

Many populations are composed of a mixture of individuals that reproduce at different times, and these times are often heritable. Under these conditions, gene flow should be limited between early and late reproducers, even within populations having a unimodal temporal distribution of reproductive activity. This temporal restriction on gene flow might be called "isolation by time" (IBT) to acknowledge its analogy with isolation by distance (IBD). IBD and IBT are not exactly equivalent, however, owing to differences between dispersal in space and dispersal in time. We review empirical studies of natural populations that provide evidence for IBT based on heritabilities of reproductive time and on molecular genetic differences associated with reproductive time. When IBT is present, variation in selection through the reproductive season may lead to adaptive temporal variation in phenotypic traits [adaptation by time (ABT)]. We introduce a novel theoretical model that shows how ABT increases as (i) selection on the trait increases; (ii) environmental influences on reproductive time decrease; (iii) the heritability of reproductive time increases; and (iv) the temporal distribution of reproductive activity becomes increasingly uniform. We then review empirical studies of natural populations that provide evidence for ABT by documenting adaptive temporal clines in phenotypic traits. The best evidence for IBT and ABT currently comes from salmonid fishes and flowering plants, but we expect that future work will show these processes are more widespread.

The estimation of genetic relationships using molecular markers and their efficiency in estimating heritability in natural populations

Molecular marker data collected from natural populations allows information on genetic relationships to be established without referencing an exact pedigree. Numerous methods have been developed to exploit the marker data. These fall into two main categories: method of moment estimators and likelihood estimators. Method of moment estimators are essentially unbiased, but utilise weighting schemes that are only optimal if the analysed pair is unrelated. Thus, they differ in their efficiency at estimating parameters for different relationship categories. Likelihood estimators show smaller mean squared errors but are much more biased. Both types of estimator have been used in variance component analysis to estimate heritability. All marker-based heritability estimators require that adequate levels of the true relationship be present in the population of interest and that adequate amounts of informative marker data are available. I review the different approaches to relationship estimation, with particular attention to optimizing the use of this relationship information in subsequent variance component estimation.

Testing marker-based estimates of heritability in the wild

Marker-based estimates of heritability are an attractive alternative to pedigree-based methods for estimating quantitative genetic parameters in field studies where it is difficult or impossible to determine relationships and pedigrees. Here I test the ability of the marker-based method to estimate heritability of a suite of traits in a wild population of bighorn sheep (Ovis canadensis) using marker data from 32 microsatellite loci. I compared marker-based estimates with estimates obtained using a pedigree and the animal model. Marker-based estimates of heritability were imprecise and downwardly biased. The high degree of uncertainty in marker-based estimates suggests that the method may be sufficient to detect the presence of genetic variance for highly heritable traits, but not sufficiently reliable to estimate genetic parameters.

How to use molecular marker data to measure evolutionary parameters in wild populations

Estimating the genetic basis of phenotypic traits and the selection pressures acting on them are central to our understanding of the evolution and conservation of wild populations. However, obtaining such evolutionary-related parameters is not an easy task as it requires accurate information on both relatedness among individuals and their breeding success. Polymorphic molecular markers are very useful in estimating relatedness between individuals and parentage analyses are now extensively used in most taxa. The next step in the application of molecular data to wild populations is to use them to derive estimates of evolutionary-related parameters for quantitative traits, such as quantitative genetic parameters (e.g. heritability, genetic correlations) and measures of selection (e.g. selection gradients). Despite their great appeal and potential, the optimal use of molecular tools is still debated and it remains unclear how they should best be used to obtain reliable estimates of evolutionary parameters in the wild. Here, we review the methods available for estimating quantitative genetic and selection parameters and discuss their merits and shortcomings, to provide a tool that summarizes the potential uses of molecular data to obtain such parameters in wild populations.

Maternal genetic effects set the potential for evolution in a free-living vertebrate population

Heritable maternal effects have important consequences for the evolutionary dynamics of phenotypic traits under selection, but have only rarely been tested for or quantified in evolutionary studies. Here we estimate maternal effects on early-life traits in a feral population of Soay sheep (Ovis aries) from St Kilda, Scotland. We then partition the maternal effects into genetic and environmental components to obtain the first direct estimates of maternal genetic effects in a free-living population, and furthermore test for covariance between direct and maternal genetic effects. Using an animal model approach, direct heritabilities (h2) were low but maternal genetic effects (m2) represented a relatively large proportion of the total phenotypic variance for each trait (birth weight m2=0.119, birth date m2=0.197, natal litter size m2=0.211). A negative correlation between direct and maternal genetic effects was estimated for each trait, but was only statistically significant for natal litter size (ram= -0.714). Total heritabilities (incorporating variance from heritable maternal effects and the direct-maternal genetic covariance) were significant for birth weight and birth date but not for natal litter size. Inadequately specified models greatly overestimated additive genetic variance and hence direct h2 (by a factor of up to 6.45 in the case of birth date). We conclude that failure to model heritable maternal variance can result in over- or under-estimation of the potential for traits to respond to selection, and advocate an increased effort to explicitly measure maternal genetic effects in evolutionary studies.

Estimating genetic parameters in natural populations using the "animal model"

Estimating the genetic basis of quantitative traits can be tricky for wild populations in natural environments, as environmental variation frequently obscures the underlying evolutionary patterns. I review the recent application of restricted maximum-likelihood "animal models" to multigenerational data from natural populations, and show how the estimation of variance components and prediction of breeding values using these methods offer a powerful means of tackling the potentially confounding effects of environmental variation, as well as generating a wealth of new areas of investigation.

Ex situ population management in the absence of pedigree information

For captive breeding to play a significant role in conservation, ex situ populations must be scientifically managed to meet objective goals for retaining representative genetic variation. Imperfect genealogical information requires fundamental assumptions to be made that may bias downstream measures of genetic importance, upon which management decisions are based. The impacts of such assumptions are most pronounced within breeding programmes characterized by a high proportion of individuals of unknown ancestry, as exemplified by the large captive population of the St Vincent parrot (Amazona guildingii). The degree to which microsatellite-based estimates of relatedness may improve upon the assumptions of conventional pedigree-based management was investigated using genotypic data collected at eight microsatellite loci and two marker-based relatedness estimators. The measure, rxyLR, was found to explain the highest amount of variation in true relatedness. Integration of pairwise estimates of founder relatedness with studbook data transformed current understanding of the relatedness structure of the A. guildingii population from two subgroups characterized by a high and low degree of relatedness, respectively, to a situation where all 72 individuals are prioritized for breeding according to their estimated mean kinships. Furthermore, the discovery of opposing, directional bias exhibited by rxyLR and rxyQG in assigning dyads to a given relationship category suggests that an approach that utilizes a combination of pairwise relatedness estimators may provide the most genetic information for balancing the dual considerations of maximizing gene diversity and minimizing inbreeding in developing breeding recommendations.

Accuracy, efficiency and robustness of four algorithms allowing full sibship reconstruction from DNA marker data

In the problem of reconstructing full sib pedigrees from DNA marker data, three existing algorithms and one new algorithm are compared in terms of accuracy, efficiency and robustness using real and simulated data sets. An algorithm based on the exclusion principle and another based on a maximization of the Simpson index were very accurate at reconstructing data sets comprising a few large families but had problems with data sets with limited family structure, while a Markov Chain Monte Carlo (MCMC) algorithm based on the maximization of a partition score had the opposite behaviour. An MCMC algorithm based on maximizing the full joint likelihood performed best in small data sets comprising several medium-sized families but did not work well under most other conditions. It appears that the likelihood surface may be rough and presents challenges for the MCMC algorithm to find the global maximum. This likelihood algorithm also exhibited problems in reconstructing large family groups, due possibly to limits in computational precision. The accuracy of each algorithm improved with an increasing amount of information in the data set, and was very high with eight loci with eight alleles each. All four algorithms were quite robust to deviation from an idealized uniform allelic distribution, to departures from idealized Mendelian inheritance in simulated data sets and to the presence of null alleles. In contrast, none of the algorithms were very robust to the probable presence of error/mutation in the data. Depending upon the type of mutation or errors and the algorithm used, between 70 and 98% of the affected individuals were classified improperly on average.

Selective and genetic constraints on the evolution of body size in a stream-dwelling salmonid fish

To examine constraints on evolution of larger body size in two stunted populations of brook charr (Salvelinus fontinalis) from a single river in Cape Race, Newfoundland, Canada, we measured viability selection acting on length-at-age traits, and estimated quantitative genetic parameters in situ (following reconstruction of pedigree information from microsatellite data). Furthermore we tested for phenotypic differentiation between the populations, and for association of high juvenile growth with early maturity that is predicted by life history theory. Within each population, selection differentials and estimates of heritabilities for length-at-age traits suggested that evolution of larger size is prevented by both selective and genetic constraints. Between the populations, phenotypic differentiation was found in length-at-age and age of maturation traits, whereas early maturation was associated with increased juvenile growth (relative to adult growth) both within and between populations. The results suggest an adaptive plastic response in age of maturation to juvenile growth rates that have a largely environmental basis of determination.