Estimation of genealogical coancestry in plant species using a pedigree reconstruction algorithm and application to an oil palm breeding population

Key message

Explicit pedigree reconstruction by simulated annealing gave reliable estimates of genealogical coancestry in plant species, especially when selfing rate was lower than 0.6, using a realistic number of markers. Genealogical coancestry information is crucial in plant breeding to estimate genetic parameters and breeding values. The approach of Fernández and Toro (Mol Ecol 15:1657–1667, 2006) to estimate genealogical coancestries from molecular data through pedigree reconstruction was limited to species with separate sexes. In this study it was extended to plants, allowing hermaphroditism and monoecy, with possible selfing. Moreover, some improvements were made to take previous knowledge on the population demographic history into account. The new method was validated using simulated and real datasets. Simulations showed that accuracy of estimates was high with 30 microsatellites, with the best results obtained for selfing rates below 0.6. In these conditions, the root mean square error (RMSE) between the true and estimated genealogical coancestry was small (<0.07), although the number of ancestors was overestimated and the selfing rate could be biased. Simulations also showed that linkage disequilibrium between markers and departure from the Hardy–Weinberg equilibrium in the founder population did not affect the efficiency of the method. Real oil palm data confirmed the simulation results, with a high correlation between the true and estimated genealogical coancestry (>0.9) and a low RMSE (<0.08) using 38 markers. The method was applied to the Deli oil palm population for which pedigree data were scarce. The estimated genealogical coancestries were highly correlated (>0.9) with the molecular coancestries using 100 markers. Reconstructed pedigrees were used to estimate effective population sizes. In conclusion, this method gave reliable genealogical coancestry estimates. The strategy was implemented in the software MOLCOANC 3.0.     

A note on the rationale for estimating genealogical coancestry from molecular markers

Background

Genetic relatedness or similarity between individuals is a key concept in population, quantitative and conservation genetics. When the pedigree of a population is available and assuming a founder population from which the genealogical records start, genetic relatedness between individuals can be estimated by the coancestry coefficient. If pedigree data is lacking or incomplete, estimation of the genetic similarity between individuals relies on molecular markers, using either molecular coancestry or molecular covariance. Some relationships between genealogical and molecular coancestries and covariances have already been described in the literature.

Methods

We show how the expected values of the empirical measures of similarity based on molecular marker data are functions of the genealogical coancestry. From these formulas, it is easy to derive estimators of genealogical coancestry from molecular data. We include variation of allelic frequencies in the estimators.

Results

The estimators are illustrated with simulated examples and with a real dataset from dairy cattle. In general, estimators are accurate and only slightly biased. From the real data set, estimators based on covariances are more compatible with genealogical coancestries than those based on molecular coancestries. A frequently used estimator based on the average of estimated coancestries produced inflated coancestries and numerical instability. The consequences of unknown gene frequencies in the founder population are briefly discussed, along with alternatives to overcome this limitation.

Conclusions

Estimators of genealogical coancestry based on molecular data are easy to derive. Estimators based on molecular covariance are more accurate than those based on identity by state. A correction considering the random distribution of allelic frequencies improves accuracy of these estimators, especially for populations with very strong drift.     

Assessing the genetic diversity in small farm animal populations

Genetic variation is vital for the populations to adapt to varying environments and to respond to artificial selection; therefore, any conservation and development scheme should start from assessing the state of variation in the population. There are several marker-based and pedigree-based parameters to describe genetic variation. The most suitable ones are rate of inbreeding and effective population size, because they are not dependent on the amount of pedigree records. The acceptable level for effective population size can be considered from different angles leading to a conclusion that it should be at least 50 to 100. The estimates for the effective population size can be computed from the genealogical records or from demographic and marker information when pedigree data are not available. Marker information could also be used for paternity analysis and for estimation of coancestries. The sufficient accuracy in marker-based parameters would require typing thousands of markers. Across breeds, diversity is an important source of variation to rescue problematic populations and to introgress new variants. Consideration of adaptive variation brings new aspects to the estimation of the variation between populations.     

Genome-Wide Estimates of Coancestry and Inbreeding in a Closed Herd of Ancient Iberian Pigs

Maintaining genetic variation and controlling the increase in inbreeding are crucial requirements in animal conservation programs. The most widely accepted strategy for achieving these objectives is to maximize the effective population size by minimizing the global coancestry obtained from a particular pedigree. However, for most natural or captive populations genealogical information is absent. In this situation, microsatellites have been traditionally the markers of choice to characterize genetic variation, and several estimators of genealogical coefficients have been developed using marker data, with unsatisfactory results. The development of high-throughput genotyping techniques states the necessity of reviewing the paradigm that genealogical coancestry is the best parameter for measuring genetic diversity. In this study, the Illumina PorcineSNP60 BeadChip was used to obtain genome-wide estimates of rates of coancestry and inbreeding and effective population size for an ancient strain of Iberian pigs that is now in serious danger of extinction and for which very accurate genealogical information is available (the Guadyerbas strain). Genome-wide estimates were compared with those obtained from microsatellite and from pedigree data. Estimates of coancestry and inbreeding computed from the SNP chip were strongly correlated with genealogical estimates and these correlations were substantially higher than those between microsatellite and genealogical coefficients. Also, molecular coancestry computed from SNP information was a better predictor of genealogical coancestry than coancestry computed from microsatellites. Rates of change in coancestry and inbreeding and effective population size estimated from molecular data were very similar to those estimated from genealogical data. However, estimates of effective population size obtained from changes in coancestry or inbreeding differed. Our results indicate that genome-wide information represents a useful alternative to genealogical information for measuring and maintaining genetic diversity.     

Accuracy of dominant markers for estimation of relatedness and heritability in an experimental stand of Prosopis alba (Leguminosae)

The estimation of genetic components of phenotypic variance is based on the resemblance between relatives. In natural populations of most forest tree species without genealogical information, a possible alternative approach is the use of relatedness estimates obtained indirectly from molecular marker data. Heritability (h ²) is then estimated from the covariance of estimated relatedness and phenotypic resemblance. In a stand of Prosopis alba planted in 1991 in Argentina, relatedness was estimated for all individual pairs of trees by means of the information proceeding from 128 dominant markers (57 AFLPs and 71 ISSRs) and compared with estimates obtained from six microsatellite loci previously studied. We empirically compared the accuracy of different relatedness estimators based on dominant markers proposed by Lynch and Milligan (Mol Ecol 3:91–99, 1994), Hardy (Mol Ecol 12:1577–1588, 2003), Wang (Mol Ecol 13:3169–3178, 2004), and Ritland (Mol Ecol 14:3157–3165, 2005). Heritabilities of 13 quantitative traits were then estimated from the regression of pairwise phenotypic distances on pairwise relatedness according to Ritland (Genet Res 67:175–185, 1996a). Relatedness inferred from molecular markers was in all cases significantly correlated with actual relatedness, although Ritland's estimator showed the highest bias but the lowest variance. Dominant marker-based h ² estimates were evidently downwards biased and showed poor correlation with those based on family records. In conclusion, the use of dominant molecular markers evidently produces much greater underestimates of h ² than from using co-dominant ones, attributable to the lower accuracy in the indirect estimation of relatedness coefficient. Many traits with enough genetic variability as to respond readily to selection would remain undetected; only those with very high heritability would show significant h ² estimates.     

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.     

Realized Sampling Variances of Estimates of Genetic Parameters and the Difference between Genetic and Phenotypic Correlations

A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.     

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).     

Efficiency of the use of pedigree and molecular marker information in conservation programs

The value of molecular markers and pedigree records, separately or in combination, to assist in the management of conserved populations has been tested. The general strategy for managing the population was to optimize contributions of parents to the next generation for minimizing the global weighted coancestry. Strategies differed in the type of information used to compute global coancestries, the number and type of evaluated individuals, and the system of mating. Genealogical information proved to be very useful (at least for 10 generations of management) to arrange individuals' contributions via the minimization of global coancestry. In fact, the level of expected heterozygosity after 10 generations yielded by this strategy was 88-100% of the maximum possible improvement obtained if the genotype for all loci was known. Marker information was of very limited value if used alone. The amount and degree of polymorphism of markers to be used to compute molecular coancestry had to be high to mimic the performance of the strategy relying on pedigree, especially in the short term (for example, >10 markers per chromosome with 10 alleles each were needed if only the parents' genotype was available). When both sources of information are combined to calculate the coancestry conditional on markers, clear increases in effective population size (Ne) were found, but observed diversity levels (either gene or allelic diversity) in the early generations were quite similar to the ones obtained with pedigree alone. The advantage of including molecular information is greater when information is available on a greater number of individuals (offspring and parents vs. parents only). However, for realistic situations (i.e., large genomes) the benefits of using information on offspring are small. The same conclusions were reached when comparing the use of the different types of information (genealogical or/and molecular) to perform minimum coancestry matings.     

Estimation of coancestry in Iberian pigs using molecular markers

Genetic markers provide a useful tool toestimate pairwise coancestry betweenindividuals in the absence of a known pedigree. Inthe present work 62 pigs from two relatedstrains of Iberian breed, Guadyerbas andTorbiscal, belonging to a conservationprogramme with completely known pedigrees since1945, have been genotyped for 49microsatellites. Four coefficients thatsummarise molecular resemblance betweenindividuals together with eightestimators of coancestry have been calculatedfrom this information. Their values werecompared with the genealogical coancestry,calculated from the complete or partialpedigree. The eight estimations obtained usingmolecular information substantiallyunderestimate the coancestry calculated usingthe genealogical analysis. The correlationbetween the estimates and the genealogicalvalues was also calculated. This correlationwas high, between 0.78 and 0.93 for differentestimators, when all pairwise comparisons amongthe 62 animals were considered. However, thecorrelation decreases remarkably to 0.49–0.69and 0.37–0.47 for the Guadyerbas and Torbiscalpopulations respectively, when they wereanalysed separately. All the correlations weresimilar to those obtained when using simplecoefficients of molecular resemblance such asmolecular coancestry or similarity indexes.Finally, simulations were carried out tofurther explore the results obtained. It isconcluded that lack of information on theallele frequencies in the base population mayexplain the bias of these estimators inpopulations with complex pedigrees.     

Impact of reconstructed pedigrees on progeny-test breeding values in red spruce

Pedigrees reconstructed through DNA marker assigned paternities in polymix (PMX) and open pollinated (OP) progeny tests were analyzed using mixed models to test the effect of unequal male reproductive success and pedigree errors on quantitative genetic parameters. The reconstructed pedigree increased heritabilities in the larger PMX test. Increased heritability resulted from adding the paternities to the pedigree per se, not by correcting the male reproductive bias by specifying the exact pedigree. Removing hypothesized pedigree errors had no effect on quantitative parameters, either because the magnitude of the errors was too small (PMX) or the progeny test was too small to detect variance components reliably (OP). Although there was no advantage in backwards selection, the increased additive variance, heritabilities and accuracy of progeny with assigned paternities in the pedigree, should permit forward selection of offspring with greater genetic gain and complete control of coancestry for future breeding decisions. Some possible breeding population structures with the new genetic information are discussed.     

Impact of reconstructed pedigrees on progeny-test breeding values in red spruce

Pedigrees reconstructed through DNA marker assigned paternities in polymix (PMX) and open pollinated (OP) progeny tests were analyzed using mixed models to test the effect of unequal male reproductive success and pedigree errors on quantitative genetic parameters. The reconstructed pedigree increased heritabilities in the larger PMX test. Increased heritability resulted from adding the paternities to the pedigree per se, not by correcting the male reproductive bias by specifying the exact pedigree. Removing hypothesized pedigree errors had no effect on quantitative parameters, either because the magnitude of the errors was too small (PMX) or the progeny test was too small to detect variance components reliably (OP). Although there was no advantage in backwards selection, the increased additive variance, heritabilities and accuracy of progeny with assigned paternities in the pedigree, should permit forward selection of offspring with greater genetic gain and complete control of coancestry for future breeding decisions. Some possible breeding population structures with the new genetic information are discussed.     

Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.     

Effects of Multiple Retrovirus Insertions on Quantitative Traits of Mice

To assess the potential to generate quantitative genetic variation by insertional mutagenesis in a vertebrate, lines of mice in which many provirus vector inserts segregated at a low initial frequency on an inbred background (insert lines) were subjected to divergent artificial selection on body weight at 6 weeks and responses and heritability estimates compared to control lines lacking inserts. Heritability estimates were more than 1.5 times greater in the insert lines than in the controls, but because the phenotypic variance was substantially higher in the insert lines the genetic variance was about 3 times greater. Realized heritability estimates tended to be lower than heritabilities estimated by an animal model which utilizes information in covariances between all relatives in the data set. A surprisingly large response to selection occurred in the inbred control line. Insert lines were about 20% less fertile than controls. Division of the selection lines into inbred sublines in the later generations of the experiment revealed substantially greater variation among sublines of the insert lines than among the controls. Heritabilities were similar to typical estimates for the trait in outbred populations. In conclusion, there was clear evidence of extra variation deriving from inserts, which has yet to be attributed to individual genes.     

QUANTITATIVE GENETICS OF SEXUAL SIZE DIMORPHISM IN THE COLLARED FLYCATCHER,FICEDULA ALBICOLLIS

Quantitative genetic theory predicts that evolution of sexual size dimorphism (SSD) will be a slow process if the genetic correlation in size between the sexes is close to unity, and the heritability of size is similar in both sexes. However, there are very few reliable estimates of genetic correlations and sex-specific heritabilities from natural populations, the reasons for this being that (1) offspring have often been sexed retrospectively, and hence, selection acting differently with respect to body size in the two sexes between measuring and sex identification can bias estimates of SSD; and (2) in many taxa, parents may be incorrectly assigned to offspring either because of assignment errors or because of extrapair paternity. We used molecular sex and paternity identification to overcome these problems and estimated sex-specific heritabilities and the genetic correlation in body size between the two sexes in the collared flycatcher, Ficedula albicollis. After exclusion of the illegitimate offspring, the genetic correlation in body size between the sexes was 1.00 (SE = 0.22), implying a severe constraint on the evolution of SSD in this species. Furthermore, sex-specific heritability estimates were very similar, indicating that neither sex will be able to evolve faster than the other. By using estimated genetic parameters, together with empirically derived estimates of sex-specific selection gradients, we further demonstrated that the predicted selection response in female tarsus length is displaced about 200% in the opposite direction from that to be expected if there were no genetic correlation between the sexes. The correspondence between the biochemically estimated rate of extrapair paternity (about 15 % of the young) and that estimated from the “heritability method” (11%) was good. However, the estimated rate of extrapair paternity with the heritability method after exclusion of the illegitimate young was 22%, adding to increasing evidence that factors other than extrapair paternity (e.g., maternal effects) may be resposible for the commonly observed higher mother-offspring than father-offspring resemblance.     

Genetic and phenotypic correlations among size-related traits, and heritability variation between body parts in Drosophila buzzatii

Recent studies have shown that body size is a heritable trait phenotypically correlated with several fitness components in wild populations of the cactophilic fly Drosophila buzzatii. To obtain further information on size-related variation, heritabilities as well as genetic and phenotypic correlations among size-related traits of several body parts (head, thorax and wings) were estimated. The study was carried out on an Argentinean natural population in which size-related selection was previously detected. The genetic parameters were estimated using offspring-parent regressions (105 families) in the laboratory G₂ generation of a sample of wild flies. The traits were also scored in Wild-Caught Flies (WCF). Laboratory-Reared Flies (LRF) were larger and less variable than WCF. Although heritability estimates were significant for all traits, heritabilities were higher for thorax-wing traits than for head traits. Phenotypic and genetic correlations were all positive. The highest genetic correlations were found between traits which are both functionally and developmentally related. Genetic and phenotypic correlations estimated in the lab show similar correlation patterns (r = 0.49; TP = 0.02, Mantel's test). However, phenotypic correlations were found to be typically larger in WCF than in LRF. The genetic correlation matrix estimated in the relatively homogeneous lab environment is not simply a constant multiplicative factor of the phenotypic correlation matrix estimated in WCF. This revised version was published online in July 2006 with corrections to the Cover Date.     

NATURAL HERITABILITIES: CAN THEY BE RELIABLY ESTIMATED IN THE LABORATORY?

The validity of the assumption, that laboratory estimates of heritabilities will tend to overestimate natural heritabilities, due to a reduction in environmental variability and thus the phenotypic variance of traits, is examined. One hundred sixty-five field estimates of narrow sense heritabilities derived from the literature are compared with 189 estimates from laboratory studies on wild, outbred animal populations derived from the data set of Mousseau and Roff. The results indicate that 84% of field heritabilities are significantly different from zero and that for morphological, behavioral, and life-history traits there are no significant differences between laboratory and field estimates of heritability. Unexpectedly, mean heritabilities for morphological and life-history traits are actually higher in the field than in the lab. Twenty-two cases were found for which both laboratory and natural heritabilities had been estimated on the same traits. For this subset of the data, laboratory heritabilities tended to be higher than field estimates, but the difference was not significant. Also, the correlation between lab and field estimates was high (r = 0.6, P < 0.001), and the regression slope did not differ significantly from one. The major implications of this study are that laboratory estimates of heritability should generally provide reasonable estimations of both the magnitude and the significance of heritabilities in nature.     

Accuracy of marker-assisted selection with auxiliary traits

Genetic information on molecular markers is increasingly being used in plant and animal improvement programmes particularly as indirect means to improve a metric trait by selection either on an individual basis or on the basis of an index incorporating such information. This paper examines the utility of an index of selection that not only combines phenotypic and molecular information on the trait under improvement but also combines similar information on one or more auxiliary traits. The accuracy of such a selection procedure has been theoretically studied for sufficiently large populations so that the effects of detected quantitative trait loci can be perfectly estimated. The theory is illustrated numerically by considering one auxiliary trait. It is shown that the use of an auxiliary trait improves the selection accuracy; and, hence, the relative efficiency of index selection compared to individual selection which is based on the same intensity of selection. This is particularly so for higher magnitudes of residual genetic correlation and environmental correlation having opposite signs, lower values of the proportion of genetic variation in the main trait associated with the markers, negligible proportion of genetic variation in the auxiliary trait associated with the markers, and lower values of the heritability of the main trait but higher values of the heritability of the auxiliary trait.     

Marker-Based Estimation of Heritability in Immortal Populations

Heritability is a central parameter in quantitative genetics, from both an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within- and between-genotype variability. This approach estimates broad-sense heritability and does not account for different genetic relatedness. With the availability of high-density markers there is growing interest in marker-based estimates of narrow-sense heritability, using mixed models in which genetic relatedness is estimated from genetic markers. Such estimates have received much attention in human genetics but are rarely reported for plant traits. A major obstacle is that current methodology and software assume a single phenotypic value per genotype, hence requiring genotypic means. An alternative that we propose here is to use mixed models at the individual plant or plot level. Using statistical arguments, simulations, and real data we investigate the feasibility of both approaches and how these affect genomic prediction with the best linear unbiased predictor and genome-wide association studies. Heritability estimates obtained from genotypic means had very large standard errors and were sometimes biologically unrealistic. Mixed models at the individual plant or plot level produced more realistic estimates, and for simulated traits standard errors were up to 13 times smaller. Genomic prediction was also improved by using these mixed models, with up to a 49% increase in accuracy. For genome-wide association studies on simulated traits, the use of individual plant data gave almost no increase in power. The new methodology is applicable to any complex trait where multiple replicates of individual genotypes can be scored. This includes important agronomic crops, as well as bacteria and fungi.     

Molecular marker-based pedigrees for animal conservation biologists

Pedigrees, depicting the genealogical relationships between individuals in a population, are of fundamental importance to several research areas including conservation biology. For example, they are useful for estimating inbreeding, heritability, selection, studying kin selection and for measuring gene flow between populations. Pedigrees constructed from direct observations of reproduction are usually unavailable for wild populations. Therefore, pedigrees for these populations are usually estimated using molecular marker data. Despite their obvious importance, and the fact that pedigrees are conceptually well understood, the methods, and limitations of marker-based pedigree inference are often less well understood. Here we introduce animal conservation biologists to molecular marker-based pedigrees. We briefly describe the history of pedigree inference research, before explaining the underlying theory and basic mechanics of pedigree construction using standard methods. We explain the assumptions and limitations that accompany many of these methods, before going on to explain methods that relax several of these assumptions. Finally, we look to future and discuss some recent exciting advances such as the use of single-nucleotide polymorphisms, inference of multigenerational pedigrees and incorporation of non-genetic data such as field observations into the calculations. We also provide some guidelines on efficient marker selection in order to maximize accuracy and power. Throughout we use examples from the field of animal conservation and refer readers to appropriate software where possible. It is our hope that this review will help animal conservation biologists to understand, choose, and use the methods and tools of this fast-moving field.