Quality and quantity of genetic relatedness data affect the analysis of social structure

Kinship plays a fundamental role in the evolution of social systems and is considered a key driver of group living. To understand the role of kinship in the formation and maintenance of social bonds, accurate measures of genetic relatedness are critical. Genotype‐by‐sequencing technologies are rapidly advancing the accuracy and precision of genetic relatedness estimates for wild populations. The ability to assign kinship from genetic data varies depending on a species’ or population's mating system and pattern of dispersal, and empirical data from longitudinal studies are crucial to validate these methods. We use data from a long‐term behavioural study of a polygynandrous, bisexually philopatric marine mammal to measure accuracy and precision of parentage and genetic relatedness estimation against a known partial pedigree. We show that with moderate but obtainable sample sizes of approximately 4,235 SNPs and 272 individuals, highly accurate parentage assignments and genetic relatedness coefficients can be obtained. Additionally, we subsample our data to quantify how data availability affects relatedness estimation and kinship assignment. Lastly, we conduct a social network analysis to investigate the extent to which accuracy and precision of relatedness estimation improve statistical power to detect an effect of relatedness on social structure. Our results provide practical guidance for minimum sample sizes and sequencing depth for future studies, as well as thresholds for post hoc interpretation of previous analyses.     

Unbiased relatedness estimation in structured populations

Knowledge of the genetic relatedness between individuals is important in many research areas in quantitative genetics, conservation genetics, forensics, evolution, and ecology. In the absence of pedigree records, relatedness can be estimated from genetic marker data using a number of estimators. These estimators, however, make the critical assumption of a large random mating population without genetic structures. The assumption is frequently violated in the real world where geographic/social structures or nonrandom mating usually lead to genetic structures. In this study, I investigated two approaches to the estimation of relatedness between a pair of individuals from a subpopulation due to recent common ancestors (i.e., relatedness is defined and measured with the current focal subpopulation as reference). The indirect approach uses the allele frequencies of the entire population with and without accounting for the population structure, and the direct approach uses the allele frequencies of the current focal subpopulation. I found by simulations that currently widely applied relatedness estimators are upwardly biased under the indirect approach, but can be modified to become unbiased and more accurate by using Wright's F(st) to account for population structures. However, the modified unbiased estimators under the indirect approach are clearly inferior to the unmodified original estimators under the direct approach, even when small samples are used in estimating both allele frequencies and relatedness.     

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.     

Genetic fingerprinting of germplasm accessions as an aid for species conservation: a case study with Borderea chouardii (Dioscoreaceae), one of the most critically endangered Iberian plants

BACKGROUND AND AIMS: Molecular markers have changed previous expectations about germplasm collections of endangered plants, as new perspectives aim at holding a significant representation of all the genetic diversity in the studied species to accomplish further conservation initiatives successfully. Borderea chouardii is a critically endangered allotetraploid dioecious member of Dioscoreaceae, known from a single population in the Iberian pre-Pyrenees. This population was reported to be highly structured into two genetically distinct groups of individuals corresponding to their spatial separation along the vertical cliff where it grows. In 1999, the Spanish Government of Aragón launched the first conservation programme for the ex situ preservation of this species, and since then a seed collection has been conserved at the Germplasm Bank of the Universidad Politécnica de Madrid. However, as some seed samples had not been labelled clearly at the time of collection, their origin was uncertain. METHODS: Genetic variation in germplasm accessions of B. chouardii was investigated using microsatellite (simple sequence repeat; SSR) markers. KEY RESULTS: The 17 primer pairs used detected 62 SSR alleles in the 46 samples analysed from five different germplasm stocks. Eight alleles scored from the wild population were not detected in the germplasm samples analysed. The relatedness of the germplasm samples to the wild subpopulations through neighbour-joining clustering, principal coordinates analysis (PCO) and assignment tests revealed a biased higher representation of the genetic diversity of the lower cliff (43 samples) subpopulation than that of the upper cliff (three samples). CONCLUSIONS: The collection of additional samples from the upper cliff is recommended to achieve a better representation of the genetic diversity of this subpopulation. It is also recommended that these stocks should be managed separately according to their distinct microspatial origin in order to preserve the genetic substructuring of the wild population.     

Inbred and furious: negative association between aggression and genetic diversity in highly inbred fish

Aggressive behaviour plays an important role in securing resources, defending against predators and shaping social interactions. Although aggression can have positive effects on growth and reproductive success, it is also energetically costly and may increase injury and compromise survival. Individual genetic diversity has been positively associated with aggression, but the cause for such an association is not clear, and it might be related to the ability to recognize kin. To disentangle the relationships between genetic diversity, kinship and aggression, we quantified aggressive behaviour in a wild, self‐fertilizing fish (Kryptolebias marmoratus) with naturally variable degrees of genetic diversity, relatedness and familiarity. We found that in contrast to captive fish, levels of aggression among wild K. marmoratus are positively associated with individual homozygosity, but not with relatedness or familiarity. We suggest that the higher aggression shown by homozygous fish could be related to better kin discrimination and may be facilitated by hermaphrodite competition for scarce males, given the fitness advantages provided by outcrossing in terms of parasite resistance. It seems likely that the relationship between aggression and genetic diversity is largely influenced by both the environment and population history.     

Measures of Relatedness

Measures of genetic relatedness are essential to models of evolution by kin selection and determinations of inclusive fitness. Under a kin selection paradigm, individuals are expected to distribute actions influencing the fitness of relatives based on the relatedness of these relatives. In addition, it is necessary to have an accurate measure of relatedness to estimate heritability (h²) of phenotypic characters and to predict the efficacy of selection. Relatedness is often defined as the genotypic correlation between individuals. Assessed on the basis of common ancestry, relatedness can only be determined sensu strictu from pedigree analysis. Recent methodological and statistical advances allow the estimation of relatedness from allele frequency data. Many coefficients of relatedness can be found in the literature; I review and evaluate these, with emphasis on situations for which each is appropriate.     

Heritability and Selection on Body Size in a Natural Population of Drosophila Buzzatii

An attempt was made to assess whether the phenotypic differences in body size (as measured by wing length) between wild-caught mating and single Drosophila buzzatii males could be attributed to genetic differences between the samples. Mating males were found to be larger and less variable than a random sample of the population. The progeny of the mating males (produced by crossing to a random female from a stock derived from the same population) were on average larger than those of the single males, but not significantly so (P = 0.063), and less phenotypically variable. This difference in variance between the samples suggests that there are indeed genetic differences between the paternal samples but tests for significant differences in the additive genetic component of variance proved inconclusive. For both samples it was found that while the ratio of additive genetic variation in the laboratory to phenotypic variation in the field yielded estimates of h(s(N))(2) 10% the regression of offspring reared in the laboratory on parents from the wild was not significantly different from zero. In addition, it was found that the average development time of the progeny of the mating males is shorter than that of the random sample.     

spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels

spag e d i version 1.0 is a software primarily designed to characterize the spatial genetic structure of mapped individuals or populations using genotype data of codominant markers. It computes various statistics describing genetic relatedness or differentiation between individuals or populations by pairwise comparisons and tests their significance by appropriate numerical resampling. spag e d i is useful for: (i) detecting isolation by distance within or among populations and estimating gene dispersal parameters; (ii) assessing genetic relatedness between individuals and its actual variance, a parameter of interest for marker based inferences of quantitative inheritance; (iii) assessing genetic differentiation among populations, including the case of haploids or autopolyploids.     

Dcifer: an IBD-based method to calculate genetic distance between polyclonal infections

An essential step toward reconstructing pathogen transmission and answering epidemiologically relevant questions from genomic data is obtaining pairwise genetic distance between infections. For recombining organisms such as malaria parasites, relatedness measures quantifying recent shared ancestry would provide a meaningful distance, suggesting methods based on identity by descent (IBD). While the concept of relatedness and consequently an IBD approach is fairly straightforward for individual parasites, the distance between polyclonal infections, which are prevalent in malaria, presents specific challenges, and awaits a general solution that could be applied to infections of any clonality and accommodate multiallelic (e.g. microsatellite or microhaplotype) and biallelic [single nucleotide polymorphism (SNP)] data. Filling this methodological gap, we present Dcifer (Distance for complex infections: fast estimation of relatedness), a method for calculating genetic distance between polyclonal infections, which is designed for unphased data, explicitly accounts for population allele frequencies and complexity of infection, and provides reliable inference. Dcifer’s IBD-based framework allows us to define model parameters that represent interhost relatedness and to propose corresponding estimators with attractive statistical properties. By using combinatorics to account for unobserved phased haplotypes, Dcifer is able to quickly process large datasets and estimate pairwise relatedness along with measures of uncertainty. We show that Dcifer delivers accurate and interpretable results and detects related infections with statistical power that is 2–4 times greater than that of approaches based on identity by state. Applications to real data indicate that relatedness structure aligns with geographic locations. Dcifer is implemented in a comprehensive publicly available software package.     

Multiple ornamentation, female breeding synchrony, and extra-pair mating success of golden whistlers (Pachycephala pectoralis)

Considerable variation exists in rates of extra-pair paternity between species, and across and within populations of the same species. Explanations for this variation include ecological (e.g. breeding synchrony), morphological (e.g. ornamentation), and genetic (e.g. relatedness) factors, but it is rare for studies to simultaneously explore these factors within a single population. This is especially true for highly ornamented species, where mate choice based on ornamentation may be more complex than in less-adorned species. We conducted such a study in a migratory population of the highly ornamented golden whistler (Pachycephala pectoralis). We quantified male genetic reproductive success and related it to a range of factors putatively involved in determining extra-pair mating success. We found no effects of genetic factors (male heterozygosity and relatedness) on extra-pair success, nor of territory size, male age, or incubation effort. Instead, males possessing yellower breast plumage and large song repertoires enjoyed higher reproductive success. Additionally, we found a negative relationship between local breeding synchrony and male extra-pair mating success. This may be a consequence of mate guarding during the female fertile period and an inability of males to simultaneously mate-guard and pursue extra-pair fertilisations. In this species, the opportunity for extra-pair matings appears to vary temporally with an ecological variable (local breeding synchrony), while fine-scale, inter-male differences in mating success may be influenced by individual attributes (male ornamentation). The migratory nature of the study population and its lack of natal philopatry may mean that relatedness and inbreeding avoidance are less important considerations in mate choice.     

Using partial genotyping to estimate the genetic and maternal determinants of adaptive traits in a progeny trial of <Emphasis Type="Italic">Fagus sylvatica</Emphasis>

Understanding the determinants of phenotypic variation is critical to evaluate the ability of traits to evolve in a changing environment. In trees, the genetic component of the phenotypic variance is most often estimated based on maternal progeny tests. However, the lack of knowledge about the paternal relatedness hampers the accurate estimation of additive genetic and maternal effects. Here, we investigate how different methods accounting for paternal relatedness allow the estimation of heritability and maternal determinants of adaptive traits in a natural population of Fagus sylvatica L., presenting non-random mating. Twelve potentially adaptive functional traits were measured in 60 maternal families in a nursery. We genotyped a subset of offspring and of all the potentially reproductive adults in the population at 13 microsatellite markers to infer paternal relationships and to estimate average relatedness within and between maternal families. This relatedness information was then used in family and animal models to estimate the components of phenotypic variance. All the studied traits displayed significant genetic variance and moderate heritability. Maternal effects were detected for the diameter increment, stem volume and bud burst. Comparison of family and animal models showed that unbalanced mating system led to only slight departures from maternal family assumptions in the progeny trial. However, neglecting the significant maternal effects led to an overestimation of the heritability. Overall, we highlighted the usefulness of relatedness pattern analyses using polymorphic molecular markers to accurately analyse tree sibling designs.     

Estimating heritabilities and genetic correlations with marker-based methods: an experimental test in Mimulus guttatus

The calculation of heritabilities and genetic correlations, which are necessary for predicting evolutionary responses, requires knowledge about the relatedness between individuals. This information is often not directly available, especially not for natural populations, but can be inferred by using molecular markers such as allozymes. Several methods based on inferred relatedness from marker data have been developed to estimate heritabilities and genetic correlations in natural populations. Most methods use maximum-likelihood procedures to assign pairs or groups of individuals to predefined discrete relatedness classes (e.g., half sibs and unrelated individuals). The Ritland method, on the other hand, uses method of moments estimators to estimate pairwise relatedness among individuals as continuous values. We tested both the Ritland method and a maximum-likelihood method by applying them to a greenhouse population consisting of seed families of the herb Mimulus guttatus and comparing the results to the ones from a frequently used standard method based on half-sib families. Estimates of genetic correlations were far from accurate, especially when we used the Ritland method. However, this study shows that even with a few variable allozyme loci, it is possible to get qualitatively good indications about the presence of heritable genetic variation from marker-based methods, even though both methods underestimated it.     

Strategies for determining kinship in wild populations using genetic data

Knowledge of kin relationships between members of wild animal populations has broad application in ecology and evolution research by allowing the investigation of dispersal dynamics, mating systems, inbreeding avoidance, kin recognition, and kin selection as well as aiding the management of endangered populations. However, the assessment of kinship among members of wild animal populations is difficult in the absence of detailed multigenerational pedigrees. Here, we first review the distinction between genetic relatedness and kinship derived from pedigrees and how this makes the identification of kin using genetic data inherently challenging. We then describe useful approaches to kinship classification, such as parentage analysis and sibship reconstruction, and explain how the combined use of marker systems with biparental and uniparental inheritance, demographic information, likelihood analyses, relatedness coefficients, and estimation of misclassification rates can yield reliable classifications of kinship in groups with complex kin structures. We outline alternative approaches for cases in which explicit knowledge of dyadic kinship is not necessary, but indirect inferences about kinship on a group‐ or population‐wide scale suffice, such as whether more highly related dyads are in closer spatial proximity. Although analysis of highly variable microsatellite loci is still the dominant approach for studies on wild populations, we describe how the long‐awaited use of large‐scale single‐nucleotide polymorphism and sequencing data derived from noninvasive low‐quality samples may eventually lead to highly accurate assessments of varying degrees of kinship in wild populations.     

Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within‐pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.     

Controlling for P‐value inflation in allele frequency change in experimental evolution and artificial selection experiments

Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to P‐value inflation and hence be anticonservative. One factor known from genomewide association (GWA) studies to cause P‐value inflation is population stratification, such as relatedness among individuals. Here, we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false‐positives in tests for allele frequency change in simulated data with varying levels of population structure. However, once relatedness has been accounted for, the power to detect causal loci under selection is low. Finally, we demonstrate the presence of P‐value inflation in allele frequency change in empirical data spanning multiple generations from an artificial selection experiment on tarsus length in two free‐living populations of house sparrow and correct for this using genomic control. Our results indicate that since allele frequencies in large parts of the genome may change when selection acts on a heritable trait, such selection is likely to have considerable and immediate consequences for the eco‐evolutionary dynamics of the affected populations.     

Confounding from cryptic relatedness in haplotype-based association studies

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The impact of cryptic relatedness on the performance of haplotype phase inference and haplotype-based association tests is not clear. In this study, we used the Hapmap genetic data to simulate a set of related samples. We evaluated the accuracy of haplotype phase inferred by PHASE 2.1 and calculated the power, type I error rates, accuracy and positive prediction value (PPV) of haplotype frequency-based association tests (HFAT) and haplotype similarity-based association tests (HSAT) under various scenarios, considering relatedness levels, disease models and sample sizes. Cryptic relatedness appeared to slightly increase the accuracy of haplotype phase inference. We observed significant negative effect of cryptic relatedness on the performance of HFAT and HSAT. Ignoring cryptic relatedness may increase spurious association results in haplotype-based PBAS.     

Evidence of opposing fitness effects of parental heterozygosity and relatedness in a critically endangered marine turtle?

How individual genetic variability relates to fitness is important in understanding evolution and the processes affecting populations of conservation concern. Heterozygosity–fitness correlations (HFCs) have been widely used to study this link in wild populations, where key parameters that affect both variability and fitness, such as inbreeding, can be difficult to measure. We used estimates of parental heterozygosity and genetic similarity (‘relatedness’) derived from 32 microsatellite markers to explore the relationship between genetic variability and fitness in a population of the critically endangered hawksbill turtle, Eretmochelys imbricata. We found no effect of maternal MLH (multilocus heterozygosity) on clutch size or egg success rate, and no single‐locus effects. However, we found effects of paternal MLH and parental relatedness on egg success rate that interacted in a way that may result in both positive and negative effects of genetic variability. Multicollinearity in these tests was within safe limits, and null simulations suggested that the effect was not an artefact of using paternal genotypes reconstructed from large samples of offspring. Our results could imply a tension between inbreeding and outbreeding depression in this system, which is biologically feasible in turtles: female‐biased natal philopatry may elevate inbreeding risk and local adaptation, and both processes may be disrupted by male‐biased dispersal. Although this conclusion should be treated with caution due to a lack of significant identity disequilibrium, our study shows the importance of considering both positive and negative effects when assessing how variation in genetic variability affects fitness in wild systems.     

Estimating relatedness in social groups

Genetic relatedness is a vital parameter in the evolution of social behaviour by kin selection. It can be easily estimated using genetic markers and calculating the genotypic correlation or regression of group members. Spatial gene frequency differentiation, due to population subdivision or isolation by distance, boosts the relatedness estimates. In such cases it may be useful to partition the estimate into components, the operational relatedness is normally that among individuals in social groups within the same subpopulation. Although it is straightforward to estimate the average relatedness in social groups, estimating values for specific individuals with the help of genetic markers is still problematic. Current estimators tend to give biased values and the sampling error is large. In spite of these shortcomings, studies of social behaviour combining relatedness and reproductive success are sorely needed.     

Unpedigreed populations and worst‐case scenarios

A population in which parentage information is not recorded is considered a pedigree “black hole” in terms of genetic management. Integration of animals from such an unpedigreed population into a genetically managed population is often accomplished by assuming a worst‐case scenario and recording all animals as highly interrelated (e.g., full siblings). The assumption that a worst‐case scenario is appropriate under a wide variety of circumstances is evaluated. It was determined that the genetic costs of overestimating relationships among animals from an unpedigreed population are always greater than the genetic costs of underestimating relationships by the same amount. This demonstrates that worst‐case scenarios, which are by definition intentional overestimates, are not generally appropriate. A method of obtaining an estimate that will yield the lowest overall genetic cost using the possible maximum and minimum levels of relatedness among animals from the unpedigreed population is presented along with two methods for implementation. Finally, for cases in which the estimated average relatedness among animals from an unpedigreed population is low, it is recommended that different analytical studbook datasets be used for calculation of inbreeding coefficients and mean kinship coefficients. This strategy would allow close estimation of average relatedness without risking inadvertent pairing of highly related animals from the unpedigreed population. Zoo Biol 20:305–314, 2001. © 2001 Wiley‐Liss, Inc.     

Estimates of relatedness and inbreeding in goose strains from DNA fingerprints

The purpose of this study was to determine if DNA fingerprints (DFPs) could be used to estimate relatedness and inbreeding of strains of geese and to compare three methods of calculating relatedness indices. Strains included a control and selected strain from each of the Chinese and Synthetic (Chinese, Hungarian and Pilgrim) breeds. DFP patterns for each strain were based on individual DNA samples from six females, or on pooled DNA from 15 females different from those used for individual samples. Three relatedness indices were used, namely, genetic distance, modified Rogers distance and band sharing. All relatedness indices showed a closer relationship of strains within than between breeds. Correlation coefficients among relatedness indices were higher based on pooled DNA (r ≥|0·97|) than those based on individual DNA (r ≥|0·741). Inbreeding estimates were higher for selected compared with control strains. It appears that the use of DFPs to estimate relatedness, regardless of index used, and inbreeding can be valuable for studying geese where there is a limited breeding history.