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.     

A comparison of biallelic markers and microsatellites for the estimation of population and conservation genetic parameters in Atlantic salmon (Salmo salar)

Biallelic markers such as single nucleotide polymorphisms (SNPs) and insertion/deletion polymorphisms have become increasingly popular markers for various population genetics applications. However, the effort required to develop biallelic markers in nonmodel organisms is still substantial. In this study, we compared the estimation of various population genetic parameters (genetic divergence and structuring, isolation-by-distance, genetic diversity) using a limited number of biallelic markers (in total 7 loci) to those estimated with 14 microsatellite loci in 21 Atlantic salmon (Salmo salar) populations from northern Europe. Pairwise FST values were significantly correlated between biallelic loci and microsatellite datasets, as was overall heterozygosity when both anadromous and nonanadromous populations were analyzed together. However, when the anadromous and nonanadromous samples were analyzed separately, only genetic divergence correlations remained significant. Biallelic markers alone were not sufficient for reliable neighbor-joining clustering of populations but gave highly similar isolation-by-distance signals when compared with microsatellites. Finally, although several population prioritization measures for conservation exhibited significant correlation between different marker types, the specific populations highlighted as being most valuable for conservation purposes varied depending on the marker type and conservation criteria applied. This study demonstrates that a relatively small set of biallelic markers can be sufficient for obtaining concordant results in most of the analyses compared with microsatellites, although estimates of genetic distance are generally more concordant than estimates of genetic diversity. This suggests that a relatively small number of biallelic markers can provide useful information for various population genetic applications. However, we emphasize that the use of much higher number of loci is preferable, especially when the genetic differences between populations are subtle or individual multilocus genotype-based analyses are to be performed.     

A computer simulation study on the number of loci and trees required to estimate genetic variability in cacao (Theobroma cacao L.)

Current methods for measures of genetic diversity of populations and germplasm collections are often based on statistics calculated from molecular markers. The objective of this study was to investigate the precision and accuracy of the most common estimators of genetic variability and population structure, as calculated from simple sequence repeat (SSR) marker data from cacao (Theobroma cacao L.). Computer simulated genomes of replicate populations were generated from initial allele frequencies estimated using SSR data from cacao accessions in a collection. The simulated genomes consisted of ten linkage groups of 100 cM in length each. Heterozygosity, gene diversity and the F statistics were studied as a function of number of loci and trees sampled. The results showed that relatively small random samples of trees were needed to achieve consistency in the observed estimations. In contrast, very large random samples of loci per linkage group were required to enable reliable inferences on the whole genome. Precision of estimates was increased by more than 50% with an increase in sample size from one to five loci per linkage group or 50 per genome, and up to 70% with ten loci per linkage group, or equivalently, 100 loci per genome. The use of fewer, highly polymorphic loci to analyze genetic variability led to estimates with substantially smaller variance but with an upward bias. Nevertheless, the relative differences of estimates among populations were generally consistent for the different levels of polymorphism considered.     

Characterizing genic and nongenic molecular markers: comparison of microsatellites and SNPs

The implications of transitioning to single nucleotide polymorphism (SNPs) from microsatellite markers (MSs) have been investigated in a number of population genetics studies, but the effect of genomic location on the amount of information each type of marker reveals has not been explored in detail. We developed novel SNP markers flanking 1 kb regions of 13 genic (within gene or <1 kb away from gene) and 13 nongenic (>10 kb from annotated gene) MSs in the threespine stickleback genome to obtain comparable data for both types of markers. We analysed patterns of genetic diversity and divergence on various geographic scales after converting the SNP loci within each genomic region into haplotypes. Marker type (SNP haplotype or MS) and location (genic or nongenic) significantly affected most estimates of population diversity and divergence. Between‐lineage divergence was significantly higher in SNP haplotypes (genic and nongenic), however, within‐lineage divergence was similar between marker types. Most divergence and diversity measures were uncorrelated between markers, except for population differentiation which was correlated between MSs and SNP haplotypes (both genic and nongenic). Broad‐scale population structure and assignment were similarly resolved by both marker types, however, only the MSs were able to delimit fine‐scale population structuring, particularly when genic and nongenic markers were combined. These results demonstrate that estimates of genetic variability and differentiation among populations can be strongly influenced by marker type, their genomic location in relation to genes and by the interaction of these two factors. This highlights the importance of having an awareness of the inherent strengths and limitations associated with different molecular tools to select the most appropriate methods for accurately addressing various ecological and evolutionary questions.     

Genomic distribution and estimation of nucleotide diversity in natural populations: perspectives from the collared flycatcher (Ficedula albicollis) genome

Properly estimating genetic diversity in populations of nonmodel species requires a basic understanding of how diversity is distributed across the genome and among individuals. To this end, we analysed whole‐genome resequencing data from 20 collared flycatchers (genome size ≈1.1 Gb; 10.13 million single nucleotide polymorphisms detected). Genomewide nucleotide diversity was almost identical among individuals (mean = 0.00394, range = 0.00384–0.00401), but diversity levels varied extensively across the genome (95% confidence interval for 200‐kb windows = 0.0013–0.0053). Diversity was related to selective constraint such that in comparison with intergenic DNA, diversity at fourfold degenerate sites was reduced to 85%, 3′ UTRs to 82%, 5′ UTRs to 70% and nondegenerate sites to 12%. There was a strong positive correlation between diversity and chromosome size, probably driven by a higher density of targets for selection on smaller chromosomes increasing the diversity‐reducing effect of linked selection. Simulations exploring the ability of sequence data from a small number of genetic markers to capture the observed diversity clearly demonstrated that diversity estimation from finite sampling of such data is bound to be associated with large confidence intervals. Nevertheless, we show that precision in diversity estimation in large outbred population benefits from increasing the number of loci rather than the number of individuals. Simulations mimicking RAD sequencing showed that this approach gives accurate estimates of genomewide diversity. Based on the patterns of observed diversity and the performed simulations, we provide broad recommendations for how genetic diversity should be estimated in natural populations.     

To what extent do microsatellite markers reflect genome‐wide genetic diversity in natural populations?

Microsatellite variability is widely used to infer levels of genetic diversity in natural populations. However, the ascertainment bias caused by typically selecting only the most polymorphic markers in the genome may lead to reduced sensitivity for judging genome-wide levels of genetic diversity. To test this potential limitation of microsatellite-based approaches, we assessed the degree of nucleotide diversity in noncoding regions of eight different carnivore populations, including inbred as well as outbred populations, by sequencing 10 introns (5.4–5.7 kb) in 20 individuals of each population (wolves, coyotes, wolverines and lynxes). Estimates of nucleotide diversity varied 30-fold (7.1 × 10⁻⁵ –2.1 × 10⁻³), with densities of one single nucleotide polymorphism every 112–5446 bp. Microsatellite genotyping (10–27 markers) of the same animals revealed mean multilocus heterozygosities of 0.54–0.78, a 1.4-fold difference among populations. There was a positive yet not perfect ( r ²  = 0.70) correlation between microsatellite marker heterozygosity and nucleotide diversity at the population level. For example, point estimates of nucleotide diversity varied in some cases with an order of magnitude despite very similar levels of microsatellite marker heterozygosity. Moreover, at the individual level, no significant correlation was found. Our results imply that variability at microsatellite marker sets typically used in population studies may not accurately reflect the underlying genomic diversity. This suggests that researchers should consider using resequencing-based approaches for assessing genetic diversity when accurate inference is critical, as in many conservation and management contexts.     

The genetic diversity of UK,US and Australian cultivars of <Emphasis Type="Italic">Triticum aestivum</Emphasis> measured by DArT markers and considered by genome

The genetic diversity of UK, US and Australian wheat varieties over the period of modern plant breeding is estimated using diversity array technology markers. Diversity is assessed by both genetic distance between varieties, by AMOVA and as the volumes of multi-dimensional convex hulls estimated from principal co-ordinate analysis. At the whole genome level the three populations are genetically distinct; this is also true of the B genome. However, the US and Australian D genomes are found to occupy the same region of diversity space and the A genomes for these countries are partially overlapping. The use of high-density genotyping with a common marker set allows an unprecedented direct comparison between the diversities of the national populations, between individual genomes and the fluctuation of diversity over time. The highest genetic diversity amongst varieties is reported in the Australian population followed by the US, which in turn is more diverse than the UK. However the average diversity of loci is higher in the US set than in the Australian. Non-random fluctuations in genetic diversity over time are observed.     

Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross‐specific and species‐specific amplifications

Although whole‐genome sequencing is becoming more accessible and feasible for nonmodel organisms, microsatellites have remained the markers of choice for various population and conservation genetic studies. However, the criteria for choosing microsatellites are still controversial due to ascertainment bias that may be introduced into the genetic inference. An empirical study of red deer (Cervus elaphus) populations, in which cross‐specific and species‐specific microsatellites developed through pyrosequencing of enriched libraries, was performed for this study. Two different strategies were used to select the species‐specific panels: randomly vs. highly polymorphic markers. The results suggest that reliable and accurate estimations of genetic diversity can be obtained using random microsatellites distributed throughout the genome. In addition, the results reinforce previous evidence that selecting the most polymorphic markers leads to an ascertainment bias in estimates of genetic diversity, when compared with randomly selected microsatellites. Analyses of population differentiation and clustering seem less influenced by the approach of microsatellite selection, whereas assigning individuals to populations might be affected by a random selection of a small number of microsatellites. Individual multilocus heterozygosity measures produced various discordant results, which in turn had impacts on the heterozygosity‐fitness correlation test. Finally, we argue that picking the appropriate microsatellite set should primarily take into account the ecological and evolutionary questions studied. Selecting the most polymorphic markers will generally overestimate genetic diversity parameters, leading to misinterpretations of the real genetic diversity, which is particularly important in managed and threatened populations.     

Distinct evolutionary strategies of human leucocyte antigen loci in pathogen-rich environments

Human leucocyte antigen (HLA) loci have a complex evolution where both stochastic (e.g. genetic drift) and deterministic (natural selection) forces are involved. Owing to their extraordinary level of polymorphism, HLA genes are useful markers for reconstructing human settlement history. However, HLA variation often deviates significantly from neutral expectations towards an excess of genetic diversity. Because HLA molecules play a crucial role in immunity, this observation is generally explained by pathogen-driven-balancing selection (PDBS). In this study, we investigate the PDBS model by analysing HLA allelic diversity on a large database of 535 populations in relation to pathogen richness. Our results confirm that geographical distances are excellent predictors of HLA genetic differentiation worldwide. We also find a significant positive correlation between genetic diversity and pathogen richness at two HLA class I loci (HLA-A and -B), as predicted by PDBS, and a significant negative correlation at one HLA class II locus (HLA-DQB1). Although these effects are weak, as shown by a loss of significance when populations submitted to rapid genetic drift are removed from the analysis, the inverse relationship between genetic diversity and pathogen richness at different loci indicates that HLA genes have adopted distinct evolutionary strategies to provide immune protection in pathogen-rich environments.     

2D random walk representation of Begonia × tuberhybrida multiallelic loci used for germplasm identification

In this study, we wanted to inspect whether the evolutionary driven differences in primary sequences could correlate, and thus predict the genetic diversity of related marker loci, which is an important criterion to assess the quality of any DNA marker. We adopted new approach of quantitative symbolic DNA sequence analysis called DNA random walk representation to study multiallelic marker loci from Begonia × tuberhybrida Voss. We described significant correlation of random walk-derived digital invariants to genetic diversity of the marker loci. Specifically, on the 3D-contour plot of multivariate principal component analysis (PCA), we revealed statistical correlation between the first two PCA factors and the number of alleles per marker locus. Based on that correlation, we suggest that DNA walk representation may predict allele-rich loci solely from their primary sequences, which improves current design of new DNA germplasm identificators.     

Does natural selection promote population divergence? A comparative analysis of population structure using amplified fragment length polymorphism markers and quantitative traits

Divergent natural selection is considered an important force in plant evolution leading to phenotypic differentiation between populations exploiting different environments. Extending an earlier greenhouse study of population differentiation in the selfing annual plant Senecio vulgaris, we estimated the degree of population divergence in several quantitative traits related to growth and life history and compared these estimates with those based on presumably neutral molecular markers (amplified fragment length polymorphisms; AFLPs). This approach allowed us to disentangle the effects of divergent selection from that of other evolutionary forces (e.g. genetic drift). Five populations were examined from each of two habitat types (ruderal and agricultural habitats). We found a high proportion of total genetic variance to be among populations, both for AFLP markers (phiST = 0.49) and for quantitative traits (range of QST: 0.26-0.77). There was a strong correlation between molecular and quantitative genetic differentiation between pairs of populations (Mantel's r = 0.59). However, estimates of population differentiation in several quantitative traits exceeded the neutral expectation (estimated from AFLP data), suggesting that divergent selection contributed to phenotypic differentiation, especially between populations from ruderal and agricultural habitats. Estimates of within-population variation in AFLP markers and quantitative genetic were poorly correlated, indicating that molecular marker data may be of limited value to predict the evolutionary potential of populations of S. vulgaris.     

Comparative analysis of population genetic structure in Athyrium distentifolium (Pteridophyta) using AFLPs and SSRs from anonymous and transcribed gene regions

To examine the performance and information content of different marker systems, comparative assessment of population genetic diversity was undertaken in nine populations of Athyrium distentifolium using nine genomic and 10 expressed sequence tag (EST) microsatellite (SSR) loci, and 265 amplified fragment length polymorphism (AFLP) loci from two primer combinations. In range-wide comparisons (European vs. North American populations), the EST-SSR loci showed more reliable amplification and produced more easily scorable bands than genomic simple sequence repeats (SSRs). Genomic SSRs showed significantly higher levels of allelic diversity than EST-SSRs, but there was a significant correlation in the rank order of population diversities revealed by both marker types. When AFLPs, genomic SSRs, and EST-SSRs are considered, comparisons of different population diversity metrics/markers revealed a mixture of significant and nonsignificant rank-order correlations. However, no hard incongruence was detected (in no pairwise comparison of populations did different marker systems or metrics detect opposingly significant different amounts of variation). Comparable population pairwise estimates of F(ST) were obtained for all marker types, but whilst absolute values for genomic and EST-SSRs were very similar (F(ST) = 0.355 and 0.342, respectively), differentiation was consistently higher for AFLPs in pairwise and global comparisons (global AFLP F(ST) = 0.496). The two AFLP primer combinations outperformed 18 SSR loci in assignment tests and discriminatory power in phenetic cluster analyses. The results from marker comparisons on A. distentifolium are discussed in the context of the few other studies on natural plant populations comparing microsatellite and AFLP variability.     

Contrasting responses to selection in class I and class IIα major histocompatibility-linked markers in salmon

Comparison of levels and patterns of genetic variation in natural populations either across loci or against neutral expectation can yield insight into locus-specific differences in the strength and direction of evolutionary forces. We used both approaches to test the hypotheses on patterns of selection on major histocompatibility (MH)-linked markers. We performed temporal analyses of class I and class IIα MH-linked markers and eight microsatellite loci in two Atlantic salmon populations in Ireland on two temporal scales: over six decades and 9 years in the rivers Burrishoole and Delphi, respectively. We also compared contemporary Burrishoole and Delphi samples with nearby populations for the same loci. On comparing patterns of temporal and spatial differentiation among classes of loci, the class IIα MH-linked marker was consistently identified as an outlier compared with patterns at the other microsatellite loci or neutral expectation. We found higher levels of temporal and spatial heterogeneity in heterozygosity (but not in allelic richness) for the class IIα MH-linked marker compared with microsatellites. Tests on both within- and among-population differentiation are consistent with directional selection acting on the class IIα-linked marker in both temporal and spatial comparisons, but only in temporal comparisons for the class I-linked marker. Our results indicate a complex pattern of selection on MH-linked markers in natural populations of Atlantic salmon. These findings highlight the importance of considering selection on MH-linked markers when using these markers for management and conservation purposes.     

The effect of SNP discovery method and sample size on estimation of population genetic data for Chinese and Indian rhesus macaques (<Emphasis Type="Italic">Macaca mulatta</Emphasis>)

This study was designed to address issues regarding sample size and marker location that have arisen from the discovery of SNPs in the genomes of poorly characterized primate species and the application of these markers to the study of primate population genetics. We predict the effect of discovery sample size on the probability of discovering both rare and common SNPs and then compare this prediction with the proportion of common and rare SNPs discovered when different numbers of individuals are sequenced. Second, we examine the effect of genomic region on estimates of common population genetic data, comparing markers from both coding and non-coding regions of the rhesus macaque genome and the population genetic data calculated from these markers, to measure the degree and direction of bias introduced by SNPs located in coding versus non-coding regions of the genome. We found that both discovery sample size and genomic region surveyed affect SNP marker attributes and population genetic estimates, even when these are calculated from an expanded data set containing more individuals than the original discovery data set. Although none of the SNP detection methods or genomic regions tested in this study was completely uninformative, these results show that each has a different kind of genetic variation that is suitable for different purposes, and each introduces specific types of bias. Given that each SNP marker has an individual evolutionary history, we calculated that the most complete and unbiased representation of the genetic diversity present in the individual can be obtained by incorporating at least 10 individuals into the discovery sample set, to ensure the discovery of both common and rare polymorphisms.     

Can a simple algebraic analysis predict markers-genome heterozygosity correlations?

A current algebraic analysis on genome-wide heterozygosity estimates suggests that correlations between molecular markers and genome-wide heterozygosity, rho, depend on the ratio between the number of markers used, r, and the number of genome loci, n; that is: rho approximately square root r/n. Hence, it is unfeasible to obtain reliable estimates of genome-wide heterozygosity in species of large genome using a few markers. We cast some doubts about this analysis as it assumed that the probability that an individual was heterozygous at a locus is equal to the average heterozygosity of this locus in the population. However, we believe that individual heterozygosity at a given locus depends on individual pedigree. Because the pedigree is common for all loci of an individual, their probabilities of heterozygosity are not independent within the genome. We first performed simulations generating random genomes for 100 individuals. Among these individuals, markers and genome-wide heterozygosities correlated as expected from the above equation. However, when we simulated random mating among these individuals and in successive generations including their descendents, as occur in real populations, the correlations between markers and genome-wide heterozygosity were much higher than those predicted from algebraic analyses, and estimates of genome-wide heterozygosity improved slightly with the increment of the number of loci in the genome.     

Investigating sex‐specific dynamics using uniparental markers: West New Guinea as a case study

Mitochondrial DNA (mtDNA) and Y chromosome (NRY) genetic markers have been often contrasted to investigate sex‐specific dynamics. Traditionally, isolation by distance, intrapopulation genetic diversity and population differentiation are estimated from both markers and compared. Two possible sources of bias are often neglected. First, kilometric distances are frequently used as predictor of the connectivity between groups, hiding the role played by environmental features at a microgeographic scale. Second, the comparison of intrapopulation diversity and population differentiation between mtDNA and NRY is hampered by their different mutational mechanisms and rates. Here, we show how to account for these biases by analyzing from a different perspective a published dataset of eight West New Guinea (WNG) populations for which mtDNA control region sequences and seven linked NRY microsatellites had been typed. First, we modeled the connectivity among sampled populations by computing the number of days required to travel between groups. Then, we investigated the differences between the two sexes accounting for the molecular characteristics of the markers examined to obtain estimates on the product of the effective population size and the migration rate among demes (Nm). We achieved this goal by studying the shape of the gene genealogy at several sampling levels and using spatial explicit simulations. Both the direction and the rate of migration differ between male and females, with an Nm estimated to be >6 times higher in the latter under many evolutionary scenarios. We finally highlight the importance of applying metapopulation models when analyzing the genetic diversity of a species.     

How many marker loci are necessary? Analysis of dominant marker data sets using two popular population genetic algorithms

The number of marker loci required to answer a given research question satisfactorily is especially important for dominant markers since they have a lower information content than co‐dominant marker systems. In this study, we used simulated dominant marker data sets to determine the number of dominant marker loci needed to obtain satisfactory results from two popular population genetic analyses: STRUCTURE and AMOVA (analysis of molecular variance). Factors such as migration, level of population differentiation, and unequal sampling were varied in the data sets to mirror a range of realistic research scenarios. AMOVA performed well under all scenarios with a modest quantity of markers while STRUCTURE required a greater number, especially when populations were closely related. The popular ΔK method of determining the number of genetically distinct groups worked well when sampling was balanced, but underestimated the true number of groups with unbalanced sampling. These results provide a window through which to interpret previous work with dominant markers and we provide a protocol for determining the number of markers needed for future dominant marker studies.     

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).     

Genetic population structure in Siniperca scherzeri (Perciformes: Siniperca) in China inferred from mitochondrial DNA sequences and microsatellite loci

This study aims to improve the estimates of fine-scale genetic diversity and to compare the population structure of Siniperca scherzeri with nuclear and mitochondrial DNA (mtDNA) markers. We first combined mtDNA sequences and seven microsatellite loci to examine the genetic diversity of S. scherzeri in China. Phylogenetic and nested clade analyses revealed two major mtDNA lineages and four subclades. Bayesian multilocus genotype clustering from the microsatellite loci revealed that regional divergence estimates were quantitatively congruent between marker classes. These lineages should be recognized as the basic evolutionary significant units for S. scherzeri in China. Contradict to the previous studies on Coreoperca whiteheadi and Siniperca chuatsi, neither the Nanling–Wuyi Mountain range nor the Qingling–Dabie Mountain range represented a major phylogeographic barrier for S. scherzeri. Our fine-scale analyses of the genetic population structure of S. scherzeri provided insights into the evolutionary processes that shaped the genetic heterogeneity of this fish. This study may serve as a basis for the protection, monitoring and breeding improvement of germplasm resources of this commercially important fish.