genhet: an easy-to-use R function to estimate individual heterozygosity

genhet is an R function which calculates the five most used estimates of individual heterozygosity. The advantage of this program is that it can be applied to any diploid genotype dataset, without any limitation in the number of individuals, loci or alleles. Its detailed manual should allow people who have never used R before to make the function work quite easily. The program is freely available at http://www.aureliecoulon.net/research/ac-computer-programs.html.     

Multilocus heterozygosity and inbreeding depression in an insular house sparrow metapopulation

Inbreeding causes reduction of genetic variability that may have severe fitness consequences. In spite of its potentially huge impact on viability and evolutionary processes especially in small populations, quantitative demonstrations of genetic and demographic effects of inbreeding in natural populations are few. Here, we examine the relationship between individual inbreeding coefficients (F) and individual standardized multilocus heterozygosity (H) in an insular metapopulation of house sparrows (Passer domesticus) in northern Norway in order to evaluate whether H is a good predictor for F. We then relate variation in fitness (i.e. the probability of surviving from fledging to recruitment) to F and H, which enables us to examine whether inbreeding depression is associated with a reduction in genetic variability. The average level of inbreeding in the house sparrow metapopulation was high, and there was large inter-individual variation in F. As expected, standardized multilocus heterozygosity decreased with the level of inbreeding. The probability of recruitment was significantly negatively related to F, and, accordingly, increased with H. However, H explained no significant additional variation in recruitment rate than was explained by F. This suggests that H is a good predictor for F in this metapopulation, and that an increase in F is likely to be associated with a general increase in the level of homozygosity on loci across the genome, which has severe fitness consequences.     

What should we weigh to estimate heterozygosity,alleles or loci?

The interest to study the effects of inbreeding in natural populations has increased in the last years. Several microsatellite-derived metrics have recently been developed to infer inbreeding from multilocus heterozygosity data without requiring detailed pedigrees that are difficult to obtain in open populations. Internal relatedness (IR) is currently the most widespread used index and its main attribute is that allele frequency is incorporated into the measure. However, IR underestimates heterozygosity of individuals carrying rare alleles. For example, descendants of immigrants paired with natives (normally more outbred) bearing novel or rare alleles would be considered more homozygous than descendants of native parents. Thus, the analogy between homozygosity and inbreeding that generally is carried out would have no logic in those cases. We propose an alternative index, homozygosity by loci (HL) that avoids such problems by weighing the contribution of each locus to the homozygosity index depending on their allelic variability. Under a wide range of simulated scenarios, we found that our index (HL) correlated better than both IR and uncorrected homozygosity (H(O)), measured as proportion of homozygous loci) with genome-wide homozygosity and inbreeding coefficients in open populations. In these populations, which are likely to prevail in nature, the use of HL instead of IR reduced considerably the sample sizes required to achieve a given statistical power. This is likely to have important consequences on the ability to detect heterozygosity fitness correlations assuming the relationship between genome-wide heterozygosity and fitness traits.     

On the correlation between heterozygosity and fitness in natural populations

Three primary hypotheses currently prevail for correlations between heterozygosity at a set of molecular markers and fitness in natural populations. First, multilocus heterozygosity-fitness correlations might result from selection acting directly on the scored loci, such as at particular allozyme loci. Second, significant levels of linkage disequilibrium, as in recently bottlenecked-and-expanded populations, might cause associations between the markers and fitness loci in the local chromosomal vicinity. Third, in partially inbred populations, heterozygosity at the markers might reflect variation in the inbreeding coefficient and might associate with fitness as a result of effects of homozygosity at genome-wide distributed loci. Despite years of research, the relative importance of these hypotheses remains unclear. The screening of heterozygosity at polymorphic DNA markers offers an opportunity to resolve this issue, and relevant empirical studies have now emerged. We provide an account of the recent progress on the subject, and give suggestions on how to distinguish between the three hypotheses in future studies.     

Considerations for measuring genetic variation and population structure with multilocus fingerprinting

Multilocus DNA fingerprinting provides a cost-effective means to rapidly assay genetic variation at many loci. While this makes the technique particularly attractive for studies of evolution and conservation biology, fingerprint data can be difficult to interpret. Measurement errors inherent with the technique force investigators to group similar-sized alleles (bands) into discrete bins before estimating genetic parameters. If too little error is accounted for in this process homologous alleles will not be grouped in a common bin, whereas overestimated error can produce bins with homoplasic alleles. We used simulations and empirical data for two frog species ( Rana luteiventris and Hyla regilla ) to demonstrate that mean band-sharing ( S¯_xy ) and heterozygosity ( H ¯_E) are a function of both bin width and band profile complexity (i.e. number and distribution of bands). These estimators are also sensitive to the number of lanes included in the analysis when bin width is wide and a floating bin algorithm is employed. Multilocus estimates of H ¯_E were highly correlated with S¯_xy and thus provide no additional information about genetic variation. Estimates of population subdivision ( F ^ and Φ^_ST) appeared robust to changes in bin size. We also examined the issue of statistical independence for band-sharing data when comparisons are made among all samples. This analysis indicated that the covariance between band-sharing statistics was very small and not statistically different from zero. We recommend that sensitivity analyses for bin size be used to improve confidence in the biological interpretation of multilocus fingerprints, and that the covariance structure for band-sharing statistics be examined.     

Estimating genome-wide heterozygosity: effects of demographic history and marker type

Heterozygosity–fitness correlations (HFCs) are often used to link individual genetic variation to differences in fitness. However, most studies examining HFCs find weak or no correlations. Here, we derive broad theoretical predictions about how many loci are needed to adequately measure genomic heterozygosity assuming different levels of identity disequilibrium (ID), a proxy for inbreeding. We then evaluate the expected ability to detect HFCs using an empirical data set of 200 microsatellites and 412 single nucleotide polymorphisms (SNPs) genotyped in two populations of bighorn sheep (Ovis canadensis), with different demographic histories. In both populations, heterozygosity was significantly correlated across marker types, although the strength of the correlation was weaker in a native population compared with one founded via translocation and later supplemented with additional individuals. Despite being bi-allelic, SNPs had similar correlations to genome-wide heterozygosity as microsatellites in both populations. For both marker types, this association became stronger and less variable as more markers were considered. Both populations had significant levels of ID; however, estimates were an order of magnitude lower in the native population. As with heterozygosity, SNPs performed similarly to microsatellites, and precision and accuracy of the estimates of ID increased as more loci were considered. Although dependent on the demographic history of the population considered, these results illustrate that genome-wide heterozygosity, and therefore HFCs, are best measured by a large number of markers, a feat now more realistically accomplished with SNPs than microsatellites.     

Estimating relatedness and inbreeding using molecular markers and pedigrees: the effect of demographic history

Estimates of inbreeding and relatedness are commonly calculated using molecular markers, although the accuracy of such estimates has been questioned. As a further complication, in many situations, such estimates are required in populations with reduced genetic diversity, which is likely to affect their accuracy. We investigated the correlation between microsatellite‐ and pedigree‐based coefficients of inbreeding and relatedness in laboratory populations of Drosophila melanogaster that had passed through bottlenecks to manipulate their genetic diversity. We also used simulations to predict expected correlations between marker‐ and pedigree‐based estimates and to investigate the influence of linkage between loci and null alleles. Our empirical data showed lower correlations between marker‐ and pedigree‐based estimates in our control (nonbottleneck) population than were predicted by our simulations or those found in similar studies. Correlations were weaker in bottleneck populations, confirming that extreme reductions in diversity can compromise the ability of molecular estimates to detect recent inbreeding events. However, this result was highly dependent on the strength of the bottleneck and we did not observe or predict any reduction in correlations in our population that went through a relatively severe bottleneck of N = 10 for one generation. Our results are therefore encouraging, as molecular estimates appeared robust to quite severe reductions in genetic diversity. It should also be remembered that pedigree‐based estimates may not capture realized identity‐by‐decent and that marker‐based estimates may actually be more useful in certain situations.     

Assessment of identity disequilibrium and its relation to empirical heterozygosity fitness correlations: a meta‐analysis

Heterozygosity fitness correlations (HFCs) have frequently been used to detect inbreeding depression, under the assumption that genome‐wide heterozygosity is a good proxy for inbreeding. However, meta‐analyses of the association between fitness measures and individual heterozygosity have shown that often either no correlations are observed or the effect sizes are small. One of the reasons for this may be the absence of variance in inbreeding, a requisite for generating general‐effect HFCs. Recent work has highlighted identity disequilibrium (ID) as a measure that may capture variance in the level of inbreeding within a population; however, no thorough assessment of ID in natural populations has been conducted. In this meta‐analysis, we assess the magnitude of ID (as measured by the g₂ statistic) from 50 previously published HFC studies and its relationship to the observed effect sizes of those studies. We then assess how much power the studies had to detect general‐effect HFCs, and the number of markers that would have been needed to generate a high expected correlation (r² = 0.9) between observed heterozygosity and inbreeding. Across the majority of studies, g₂ values were not significantly different than zero. Despite this, we found that the magnitude of g₂ was associated with the average effect sizes observed in a population, even when point estimates were nonsignificant. These low values of g₂ translated into low expected correlations between heterozygosity and inbreeding and suggest that many more markers than typically used are needed to robustly detect HFCs.     

COANCESTRY: a program for simulating, estimating and analysing relatedness and inbreeding coefficients

The software package COANCESTRY implements seven relatedness estimators and three inbreeding estimators to estimate relatedness and inbreeding coefficients from multilocus genotype data. Two likelihood estimators that allow for inbred individuals and account for genotyping errors are for the first time included in this user-friendly program for PCs running Windows operating system. A simulation module is built in the program to simulate multilocus genotype data of individuals with a predefined relationship, and to compare the estimators and the simulated relatedness values to facilitate the selection of the best estimator in a particular situation. Bootstrapping and permutations are used to obtain the 95% confidence intervals of each relatedness or inbreeding estimate, and to test the difference in averages between groups.     

DNA fingerprinting in Speke's gazelle: a test for genetic distinctness, and the correlation between relatedness and similarity

In the absence of pedigree information, the determination of genetic distinctness of populations can only be made by genetic methods. Using DNA fingerprinting on the North American captive herd of Speke's gazelle Gazella spekei , we were able to address two hypotheses. First, two new individuals were found to have come from a genetically distinct population ( P = 0.008, permutation test), and represent potential new founders to be added to the population. Secondly, genetic similarity was not significantly correlated with relatedness under extreme inbreeding and very close relationship (coefficient of relationship range 0.304-0.717).     

related: an R package for analysing pairwise relatedness from codominant molecular markers

Analyses of pairwise relatedness represent a key component to addressing many topics in biology. However, such analyses have been limited because most available programs provide a means to estimate relatedness based on only a single estimator, making comparison across estimators difficult. Second, all programs to date have been platform specific, working only on a specific operating system. This has the undesirable outcome of making choice of relatedness estimator limited by operating system preference, rather than being based on scientific rationale. Here, we present a new R package, called related, that can calculate relatedness based on seven estimators, can account for genotyping errors, missing data and inbreeding, and can estimate 95% confidence intervals. Moreover, simulation functions are provided that allow for easy comparison of the performance of different estimators and for analyses of how much resolution to expect from a given data set. Because this package works in R, it is platform independent. Combined, this functionality should allow for more appropriate analyses and interpretation of pairwise relatedness and will also allow for the integration of relatedness data into larger R workflows.     

Marker‐based estimates of relatedness and inbreeding coefficients: an assessment of current methods

Inbreeding (F) of and relatedness (r) between individuals are now routinely calculated from marker data in studies in the fields of quantitative genetics, conservation genetics, forensics, evolution and ecology. Although definable in terms of either correlation coefficient or probability of identity by descent (IBD) relative to a reference, they are better interpreted as correlations in marker‐based analyses because the reference in practice is frequently the current sample or population whose F and r are being estimated. In such situations, negative estimates have a biological meaning, a substantial proportion of the estimates are expected to be negative, and the average estimates are close to zero for r and equivalent to F_IS for F. I show that although current r estimators were developed from the IBD‐based concept of relatedness, some of them conform to the correlation‐based concept of relatedness and some do not. The latter estimators can be modified, however, so that they estimate r as a correlation coefficient. I also show that F and r estimates can be misleading and become biased and marker dependent when a sample containing a high proportion of highly inbred and/or closely related individuals is used as reference. In analyses depending on the comparison between r (or F) estimates and a priori values expected under ideal conditions (e.g. for identifying genealogical relationship), the estimators should be used with caution.     

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.     

Minimal selection requirements for the correlation between heterozygosity and growth,and for the deficiency of heterozygotes,in oyster population

We examine several models that may account for the observation that in populations of marine molluscs in general, and of the American oyster (Crassostrea virginica) in particular, the growth of an individual is related to its degree of heterozygosity and, also, that the number of heterozygous individuals in the population is less than expected on the assumption of random mating and no selection. We classify these models into nonselective, selective, and mixed models. We conclude that mixed models are the most likely to apply to real populations, but cannot exclude selective models. Nonselective models appear least likely. Current evidence favors a model that assumes that heterozygotes enjoy a fitness advantage as adults, primarily because of their faster growth, and that the lower numbers of heterozygotes in the population result from some form of nonrandom fertilization. One possible source of nonrandom fertilization is variation in the time of spawning of individuals due to differences in body size.     

Correlations between heterozygosity and reproductive success in the blue tit (Cyanistes caeruleus): an analysis of inbreeding and single locus effects

To understand the mechanisms behind heterozygosity-fitness correlations (HFC), it is necessary to employ large numbers of markers with known function and independently estimate the variation in inbreeding in the population. Here we genotyped 794 blue tits with 79 microsatellites that were distributed across 25 chromosomes and that were classified either as "functional" (N= 58) or "neutral" (N= 21). We found a positive effect of individual heterozygosity at multiple loci on clutch size, on the number of eggs sired by males, and on the number of recruits produced by males and females. We documented the occurrence of some consanguineous matings and found evidence for a particular type of population structure that can contribute to the occurrence of inbreeding. As the set of "neutral" loci provided more power to detect HFC and identity disequilibrium, we argue that "neutral" markers are better predictors of the effects of inbreeding. The number of significant effects at single loci did not exceed the expected number of false positives and no strong effects were associated with heterozygosity at "functional" markers. Thus, the HFC found here cannot be attributed to strong effects of the loci under study.     

No relationship between microsatellite variation and neonatal fitness in Antarctic fur seals, Arctocephalus gazella

Published studies of wild vertebrate populations have almost universally reported positive associations between genetic variation measured at microsatellite loci and fitness, creating the impression of ubiquity both in terms of the species and the traits involved. However, there is concern that this picture may be misleading because negative results frequently go unpublished. Here, we analyse the relationship between genotypic variation at nine highly variable microsatellite loci and neonatal fitness in 1070 Antarctic fur seal pups born at Bird Island, South Georgia. Despite our relatively large sample size, we find no significant association between three different measures of heterozygosity and two fitness traits, birth weight and survival. Furthermore, increasing genetic resolution by calculating parental relatedness also yields no association between genetic variation and fitness. Our findings are consistent with necropsy data showing that most pups die from starvation or trauma, conditions that are unlikely to be influenced strongly by genetic factors, particularly if the benefits of high heterozygosity are linked to immune-related genes.     

Seed provenance for changing climates: early growth traits of nonlocal seed are better adapted to future climatic scenarios,but not to current field conditions

The urgency to repair degraded ecosystems is challenged by the need to future‐proof populations to deal with changing climates. Therefore, it is necessary to know if source gene‐pools are resilient to both current and future climatic conditions. We tested this question with the pioneer shrub Hardenbergia violacea (Fabaceae), an important species for restoration in eastern Australia. We evaluated in situ and ex situ performance of seed from eight provenances, two local and six from regions receiving hotter and wetter spring to autumn conditions and/or drier winters and we included wild and commercial collections. We compared survivorship of seedlings in climate‐houses that emulated current and predicted temperature and rainfall. In the field, we measured germination and seedling survivorship. We used neutral codominant markers to provide inbreeding and heterozygosity estimates to evaluate against health and survivorship. All provenances survived the current conditions, but local provenances were the poorest performers in the predicted hotter and wetter scenario compared with nonlocal provenances. No provenance survived more than a fortnight of a climate‐house simulated, but predicted, extreme weather event of a drought (35/22°C 12 hours day/night, 50 mL/week = 220 mm rainfall). Heterozygosity was positively associated with plant health in surviving plants, and plants in poor condition had high inbreeding estimates. In the field, nonlocal provenances performed poorly and most survivors were from local provenances. The contribution of individual genetic variation to stress tolerance will be an important consideration when selecting provenances for future climates.     

Partitioning heterozygosity in subdivided populations: Some misuses of Nei's decomposition and an alternative probabilistic approach

Nei's decomposition of total expected heterozygosity in subdivided populations into within‐ and between‐subpopulation components, H_S and D_ST, respectively, is a classical tool in the conservation and management of genetic resources. Reviewing why this is not a decomposition into independent terms of within‐ and between‐subpopulation gene diversity, we illustrate how this approach can be misleading because it overemphasizes the within‐subpopulation component compared to Jost's nonadditive decomposition based on gene diversity indices. Using probabilistic partitioning of the total expected heterozygosity into independent within‐ and between‐subpopulation contributions, we show that the contribution of the within‐subpopulation expected heterozygosity to the total expected heterozygosity is not H_S, as suggested by Nei's decomposition, but H_S/s, with s being the number of subpopulations. Finally, we compare three possible approaches of decomposing total heterozygosity in subdivided populations (i.e., Nei's decomposition, Jost's approach, and probabilistic partitioning) with regard to independence between terms and sensitivity to unequal subpopulation sizes. For the conservation and management of genetic resources, we recommend using probabilistic partitioning and Jost's differentiation parameter rather than Nei's decomposition.     

Rtreemix: an R package for estimating evolutionary pathways and genetic progression scores

In genetics, many evolutionary pathways can be modeled by the ordered accumulation of permanent changes. Mixture models of mutagenetic trees have been used to describe disease progression in cancer and in HIV. In cancer, progression is modeled by the accumulation of chromosomal gains and losses in tumor cells; in HIV, the accumulation of drug resistance-associated mutations in the viral genome is known to be associated with disease progression. From such evolutionary models, genetic progression scores can be derived that assign measures for the disease state to single patients. Rtreemix is an R package for estimating mixture models of evolutionary pathways from observed cross-sectional data and for estimating associated genetic progression scores. The package also provides extended functionality for estimating confidence intervals for estimated model parameters and for evaluating the stability of the estimated evolutionary mixture models.