Effects of genotyping errors on parentage exclusion analysis

Genetic markers are widely used to determine the parentage of individuals in studies of mating systems, reproductive success, dispersals, quantitative genetic parameters and in the management of conservation populations. These markers are, however, imperfect for parentage analyses because of the presence of genotyping errors and undetectable alleles, which may cause incompatible genotypes (mismatches) between parents and offspring and thus result in false exclusions of true parentage. Highly polymorphic markers widely used in parentage analyses, such as microsatellites, are especially prone to genotyping errors. In this investigation, I derived the probabilities of excluding a random (related) individual from parentage and the probabilities of Mendelian-inconsistent errors (mismatches) and Mendelian-consistent errors (which do not cause mismatches) in parent-offspring dyads, when a marker having null alleles, allelic dropouts and false alleles is used in a parentage analysis. These probabilities are useful in evaluating the impact of various types of genotyping errors on the information content of a set of markers in and thus the power of a parentage analysis, in determining the threshold number of genetic mismatches that is appropriate for a parentage exclusion analysis and in estimating the rates of genotyping errors and frequencies of null alleles from observed mismatches between known parent-offspring dyads. These applications are demonstrated by numerical examples using both hypothetical and empirical data sets and discussed in the context of practical parentage exclusion analyses.     

Computationally efficient sibship and parentage assignment from multilocus marker data

Quite a few methods have been proposed to infer sibship and parentage among individuals from their multilocus marker genotypes. They are all based on Mendelian laws either qualitatively (exclusion methods) or quantitatively (likelihood methods), have different optimization criteria, and use different algorithms in searching for the optimal solution. The full-likelihood method assigns sibship and parentage relationships among all sampled individuals jointly. It is by far the most accurate method, but is computationally prohibitive for large data sets with many individuals and many loci. In this article I propose a new likelihood-based method that is computationally efficient enough to handle large data sets. The method uses the sum of the log likelihoods of pairwise relationships in a configuration as the score to measure its plausibility, where log likelihoods of pairwise relationships are calculated only once and stored for repeated use. By analyzing several empirical and many simulated data sets, I show that the new method is more accurate than pairwise likelihood and exclusion-based methods, but is slightly less accurate than the full-likelihood method. However, the new method is computationally much more efficient than the full-likelihood method, and for the cases of both sexes polygamous and markers with genotyping errors, it can be several orders faster. The new method can handle a large sample with thousands of individuals and the number of markers limited only by the computer memory.     

Power of exclusion of 19 microsatellite markers for parentage testing in river buffalo (Bubalus bubalis)

In the present study, 19 microsatellite markers were assessed for their power of exclusion to test parentage in river buffalo. Microsatellite genotypes of 216 unrelated buffaloes belonging to five different breeds were utilized for the study. The probabilities of exclusion were calculated for three hypothetical situations viz. paternity testing (PE1), one parental genotype unavailable (PE2) and exclusion of both parents i.e. substituted offspring (PE3). The mean probability of exclusion across 19 investigated markers in buffalo was 0.578 (PE1), 0.405 (PE2) and 0.764 (PE3) respectively. The probability of exclusion for paternity (PE1) ranged between 0.297 and 0.814 across different markers. The exclusion probability for the cases one parent unavailable (PE2) and substituted offspring (PE3) varied from 0.143 to 0.688 and 0.465 to 0.946 respectively. Polymorphism information content and expected heterozygosity were found to have significantly high correlation with probability of exclusion of microsatellite markers. The cumulative PE1 of nine marker loci was estimated to be 0.9999 while in case of absence of one of the parental genotypes, a minimum of 11 markers were required to achieve a cumulative PE2 of 0.999. In conclusion, the present study proposes two multiplex sets with four and five markers respectively for routine parentage testing in buffalo and an additional set of four markers for doubtful cases of paternity.     

Parentage and sibship inference from markers in polyploids

Many plants and some animal species are polyploids. Nondisomically inherited markers (e.g. microsatellites) in such species cannot be analysed directly by standard population genetics methods developed for diploid species. One solution is to transform the polyploid codominant genotypes to pseudodiploid‐dominant genotypes, which can then be analysed by standard methods for various purposes such as spatial genetic structure, individual relatedness and relationship. Although this data transformation approach has been used repeatedly in the literature, no systematic study has been conducted to investigate how efficient it is, how much marker information is lost and thus how much analysis accuracy is reduced. More specifically, it is unknown whether or not the transformed data can be used to infer parentage and sibship jointly, and how different sampling schemes (number and polymorphism of markers, number of individuals) and ploidy level affect the inference accuracy. This study analyses both simulated and empirical data to examine the effects of polyploid levels, actual pedigree structures and marker number and polymorphism on the accuracy of joint parentage and sibship assignments in polyploid species. We show that sibship, parentage and selfing rates in polyploids can be inferred accurately from a typical set of microsatellite loci. We also show that inferences can be substantially improved by allowing for a small genotyping error rate to accommodate the distortion in assumed Mendelian inheritance of the converted markers when large sibship groups are involved. The results are discussed in the context of polyploid data analysis in molecular ecology.     

A simulation module in the computer program colony for sibship and parentage analysis

A simulation module is built into the software package colony to simulate marker genotype data of individuals with a predefined parentage and sibship structure. The simulated data can then be used to compare the accuracy, robustness and computational efficiency of different methods for sibship and parentage reconstruction, to examine the impact of different parameter options in a software on its accuracy and computational efficiency and to assess the information sufficiency of a given set of markers for a sibship and parentage analysis. This computer note describes the method used for simulating genotype data with a pedigree and its possible applications. The method can quickly generate genotype data for a one‐ or two‐generation pedigree of virtually any complexity with up to 30k offspring, at up to 30k codominant or dominant loci with an arbitrary degree of linkage and a user‐defined mistyping rate. The data can be fed directly into the colony program for analysis by three sibship and parentage reconstruction methods and can also be imported into other programs such as Excel and R. With slight modification, the data can be analysed by other relationship analysis software.     

Effectiveness of 10 polymorphic microsatellite markers for parentage and pedigree analysis in plateau pika (Ochotona curzoniae)

Background

The plateau pika (Ochotona curzoniae) is an underground-dwelling mammal, native to the Tibetan plateau of China. A set of 10 polymorphic microsatellite loci has been developed earlier. Its reliability for parentage assignment has been tested in a plateau pika population. Two family groups with a known pedigree were used to validate the power of this set of markers.

Results

The error in parentage assignment using a combination of these 10 loci was very low as indicated by their power of discrimination (0.803 - 0.932), power of exclusion (0.351 - 0.887), and an effectiveness of the combined probability of exclusion in parentage assignment of 99.999%.

Conclusion

All the offspring of a family could be assigned to their biological mother; and their father or relatives could also be identified. This set of markers therefore provides a powerful and efficient tool for parentage assignment and other population analyses in the plateau pika.     

Single nucleotide polymorphisms for DNA typing in the domestic horse

Genetic markers are important resources for individual identification and parentage assessment. Although short tandem repeats (STRs) have been the traditional DNA marker, technological advances have led to single nucleotide polymorphisms (SNPs) becoming an attractive alternative. SNPs can be highly multiplexed and automatically scored, which allows for easier standardization and sharing among laboratories. Equine parentage is currently assessed using STRs. We obtained a publicly available SNP dataset of 729 horses representing 32 diverse breeds. A proposed set of 101 SNPs was analyzed for DNA typing suitability. The overall minor allele frequency of the panel was 0.376 (range 0.304–0.419), with per breed probability of identities ranging from 5.6 × 10^?35 to 1.86 × 10^?42. When one parent was available, exclusion probabilities ranged from 0.9998 to 0.999996, although when both parents were available, all breeds had exclusion probabilities greater than 0.9999999. A set of 388 horses from 35 breeds was genotyped to evaluate marker performance on known families. The set included 107 parent–offspring pairs and 101 full trios. No horses shared identical genotypes across all markers, indicating that the selected set was sufficient for individual identification. All pairwise comparisons were classified using ISAG rules, with one or two excluding markers considered an accepted parent–offspring pair, two or three excluding markers considered doubtful and four or more excluding markers rejecting parentage. The panel had an overall accuracy of 99.9% for identifying true parent–offspring pairs. Our developed marker set is both present on current generation SNP chips and can be highly multiplexed in standalone panels and thus is a promising resource for SNP‐based DNA typing.     

APIS: An auto‐adaptive parentage inference software that tolerates missing parents

In the context of parentage assignment using genomic markers, key issues are genotyping errors and an absence of parent genotypes because of sampling, traceability or genotyping problems. Most likelihood‐based parentage assignment software programs require a priori estimates of genotyping errors and the proportion of missing parents to set up meaningful assignment decision rules. We present here the R package APIS, which can assign offspring to their parents without any prior information other than the offspring and parental genotypes, and a user‐defined, acceptable error rate among assigned offspring. Assignment decision rules use the distributions of average Mendelian transmission probabilities, which enable estimates of the proportion of offspring with missing parental genotypes. APIS has been compared to other software (CERVUS, VITASSIGN), on a real European seabass (Dicentrarchus labrax) single nucleotide polymorphism data set. The type I error rate (false positives) was lower with APIS than with other software, especially when parental genotypes were missing, but the true positive rate was also lower, except when the theoretical exclusion power reached 0.99999. In general, APIS provided assignments that satisfied the user‐set acceptable error rate of 1% or 5%, even when tested on simulated data with high genotyping error rates (1% or 3%) and up to 50% missing sires. Because it uses the observed distribution of Mendelian transmission probabilities, APIS is best suited to assigning parentage when numerous offspring (>200) are genotyped. We have demonstrated that APIS is an easy‐to‐use and reliable software for parentage assignment, even when up to 50% of sires are missing.     

Genetic maternity and paternity in a local population of armadillos assessed by microsatellite DNA markers and field data

Genetic data from polymorphic microsatellite loci were employed to estimate paternity and maternity in a local population of nine-banded armadillos (Dasypus novemcinctus) in northern Florida. The parentage assessments took advantage of maximum likelihood procedures developed expressly for situations when individuals of neither gender can be excluded a priori as candidate parents. The molecular data for 290 individuals, interpreted alone and in conjunction with detailed biological and spatial information for the population, demonstrate high exclusion probabilities and reasonably strong likelihoods of genetic parentage assignment in many cases; low mean probabilities of successful reproductive contribution to the local population by individual armadillo adults in a given year; and statistically significant microspatial associations of parents and their offspring. Results suggest that molecular assays of highly polymorphic genetic systems can add considerable power to assessments of biological parentage in natural populations even when neither parent is otherwise known.     

Exclusion probabilities obtainable by biochemical polymorphisms in dogs

General formulae are given to calculate the exclusion probabilities in false paternity and parentage cases by means of gene loci with an arbitrary number of alleles whereas in paternity cases an arbitrary number of offspring per litter is considered additionally.
By aid of these formulae and on the basis of the allele frequencies of four blood protein and enzyme systems the probabilities of excluding incorrect paternity and parentage are calculated in seven German dog breeds. The results are tabulated and discussed.
It can be shown that the exclusion probability in false paternity cases increases distinctly with an increasing number of offspring per litter and its maximum is nearly attained if 5 offspring are examined. Therefore it is of value to consider entire litters in paternity controls in dogs.     

Twenty-one novel tri- and tetranucleotide microsatellite loci for the Amur tiger (Panthera tigris altaica)

Amur tiger is the largest subspecies of tiger in the world and his conservation has also received much attention. In this study, we isolated and characterized twenty-one tri- and tetranucleotide microsatellite markers from this species. The number of alleles for each locus ranged from two to nine in a group of 60 individuals and the observed and expected heterozygosities were 0.333–0.917 and 0.302–0.822, respectively. The overall discrimination power and exclusion probabilities in parentage and paternity testing for these markers were 1.00, 0.9947 and 0.9999, respectively, indicating high-resolution power of microsatellite markers.     

Validation of 15 microsatellites for parentage testing in North American bison, Bison bison and domestic cattle

Fifteen bovine microsatellites were evaluated for use in parentage testing in 725 bison from 14 public populations, 178 bison from two private ranches and 107 domestic cattle from five different breeds. The number of alleles per locus ranged from five to 16 in bison and from five to 13 in cattle. On average, expected heterozygosity, polymorphism information content (PIC) and probability of exclusion values were slightly lower in bison than in cattle. A core set of 12 loci was further refined to produce a set of multiplexed markers suitable for routine parentage testing. Assuming one known parent, the core set of markers provides exclusion probabilities in bison of 0.9955 and in cattle of 0.9995 averaged across all populations or breeds tested. Tests of Hardy-Weinberg and linkage equilibrium showed only minor deviations. This core set of 12 loci represent a powerful and efficient method for determining parentage in North American bison and domestic cattle.     

Parentage and Sibship Inference From Multilocus Genotype Data Under Polygamy

Likelihood methods have been developed to partition individuals in a sample into sibling clusters using genetic marker data without parental information. Most of these methods assume either both sexes are monogamous to infer full sibships only or only one sex is polygamous to infer full sibships and paternal or maternal (but not both) half sibships. We extend our previous method to the more general case of both sexes being polygamous to infer full sibships, paternal half sibships, and maternal half sibships and to the case of a two-generation sample of individuals to infer parentage jointly with sibships. The extension not only expands enormously the scope of application of the method, but also increases its statistical power. The method is implemented for both diploid and haplodiploid species and for codominant and dominant markers, with mutations and genotyping errors accommodated. The performance and robustness of the method are evaluated by analyzing both simulated and empirical data sets. Our method is shown to be much more powerful than pairwise methods in both parentage and sibship assignments because of the more efficient use of marker information. It is little affected by inbreeding in parents and is moderately robust to nonrandom mating and linkage of markers. We also show that individually much less informative markers, such as SNPs or AFLPs, can reach the same power for parentage and sibship inferences as the highly informative marker simple sequence repeats (SSRs), as long as a sufficient number of loci are employed in the analysis.     

Microsatellite markers for identification and parentage analysis in the European wild boar (Sus scrofa)

ABSTRACT: BACKGROUND: The wild boar (Sus scrofa) is among the most widespread mammal species throughout the old world. Presently, studies concerning microsatellites in domestic pigs and wild boars have been carried out in order to investigate domestication, social behavior and general diversity patterns among either populations or breeds. The purpose of the current study is to develop a robust set of microsatellites markers for parentage analyses and individual identification. FINDINGS: A set of 14 previously reported microsatellites markers have been optimized and tested in three populations from Hungary, Portugal and Spain, in a total of 167 samples. The results indicate high probabilities of exclusion (0.99999), low probability of identity (2.0E-13 -- 2.5E-9) and a parentage assignment of 100%. CONCLUSIONS: Our results demonstrate that this set of markers is a useful and efficient tool for the individual identification and parentage assignment in wild boars.     

Using molecular markers for pedigree reconstruction of the greater amberjack (Seriola dumerili) in the absence of parental information

Ensuring appropriate levels of genetic diversity in captive populations is essential to avoid inbreeding and loss of rare alleles by genetic drift. Pedigree reconstruction and parentage analysis in the absence of parental genotypes can be a challenging task that relies in the assignment of sibship relationships among the offspring. Here, we used eight highly variable microsatellite markers and three different assignment methods to reconstruct the most likely genotypes of a parental group of wild Seriola dumerili fish based on the genotypes of six cohorts of their offspring, to assess their relative contributions to the offspring. We found that a combination of the four most variable microsatellites was enough to identify the number of parents and their contribution to the offspring, suggesting that the variability of the markers can be more critical than the number of markers. Estimated effective population sizes were lower than the number of breeders and variable among years. The results suggest unequal parental contribution that should be accounted for breeding programs in the future.     

Using blocks of linked single nucleotide polymorphisms as highly polymorphic genetic markers for parentage analysis

Single nucleotide polymorphisms (SNPs) are plentiful in most genomes and amenable to high throughput genotyping, but they are not yet popular for parentage or paternity analysis. The markers are bi-allelic, so individually they contain little information about parentage, and in nonmodel organisms the process of identifying large numbers of unlinked SNPs can be daunting. We explore the possibility of using blocks of between three and 26 linked SNPs as highly polymorphic molecular markers for reconstructing male genotypes in polyandrous organisms with moderate (five offspring) to large (25 offspring) clutches of offspring. Haplotypes are inferred for each block of linked SNPs using the programs Haplore and Phase 2.1. Each multi-SNP haplotype is then treated as a separate allele, producing a highly polymorphic, 'microsatellite-like' marker. A simulation study is performed using haplotype frequencies derived from empirical data sets from Drosophila melanogaster and Mus musculus populations. We find that the markers produced are competitive with microsatellite loci in terms of single parent exclusion probabilities, particularly when using six or more linked SNPs to form a haplotype. These markers contain only modest rates of missing data and genotyping or phasing errors and thus should be seriously considered as molecular markers for parentage analysis, particularly when the study is interested in the functional significance of polymorphisms across the genome.     

On minimizing assignment errors and the trade‐off between false positives and negatives in parentage analysis

Genetic parentage analyses provide a practical means with which to identify parent–offspring relationships in the wild. In Harrison et al.'s study (2013a), we compare three methods of parentage analysis and showed that the number and diversity of microsatellite loci were the most important factors defining the accuracy of assignments. Our simulations revealed that an exclusion‐Bayes theorem method was more susceptible to false‐positive and false‐negative assignments than other methods tested. Here, we analyse and discuss the trade‐off between type I and type II errors in parentage analyses. We show that controlling for false‐positive assignments, without reporting type II errors, can be misleading. Our findings illustrate the need to estimate and report both the rate of false‐positive and false‐negative assignments in parentage analyses.     

The power of single-nucleotide polymorphisms for large-scale parentage inference

Likelihood-based parentage inference depends on the distribution of a likelihood-ratio statistic, which, in most cases of interest, cannot be exactly determined, but only approximated by Monte Carlo simulation. We provide importance-sampling algorithms for efficiently approximating very small tail probabilities in the distribution of the likelihood-ratio statistic. These importance-sampling methods allow the estimation of small false-positive rates and hence permit likelihood-based inference of parentage in large studies involving a great number of potential parents and many potential offspring. We investigate the performance of these importance-sampling algorithms in the context of parentage inference using single-nucleotide polymorphism (SNP) data and find that they may accelerate the computation of tail probabilities >1 millionfold. We subsequently use the importance-sampling algorithms to calculate the power available with SNPs for large-scale parentage studies, paying particular attention to the effect of genotyping errors and the occurrence of related individuals among the members of the putative mother-father-offspring trios. These simulations show that 60-100 SNPs may allow accurate pedigree reconstruction, even in situations involving thousands of potential mothers, fathers, and offspring. In addition, we compare the power of exclusion-based parentage inference to that of the likelihood-based method. Likelihood-based inference is much more powerful under many conditions; exclusion-based inference would require 40% more SNP loci to achieve the same accuracy as the likelihood-based approach in one common scenario. Our results demonstrate that SNPs are a powerful tool for parentage inference in large managed and/or natural populations.     

Isolation and characterization of microsatellite loci in Acer opalus (Aceraceae), a sexually-polymorphic tree, through an enriched genomic library

An enrichment protocol was used to isolate and characterize microsatellite loci in Acer opalus, a Mediterranean tree species. Highly polymorphic microsatellite loci were required for paternity analyses in a population of this species. Eight microsatellite loci were amplified and a total of 87 alleles were detected in a sample of 142 individuals from one population, allowing the identification of each individual with a unique multilocus genotype. The paternity exclusion probabilities varied from 0.261 for locus Aop820 to 0.806 for locus Aop450, and the parent-pair exclusion probabilities varied from 0.433 for Aop820 to 0.940 for Aop450. The cumulative probabilities of exclusion for paternity and parentage of the eight loci were both higher than 0.999, supporting the usefulness of these microsatellite loci for future paternity and parentage analyses in A. opalus. Cross-species transferability was also assayed, supporting their potential use in other eight Acer species.     

Eighteen novel polymorphic microsatellite loci developed from the Père David’s deer (<Emphasis Type="Italic">Elaphurus davidianus</Emphasis>)

Père David’s deer is a severely bottlenecked species but without showing inbreeding depression, making it essential to develop molecular markers to explore her genetic mechanism of population recovery. In this study, we isolated 18 novel polymorphic microsatellite loci from a dinucleotide-enriched library. This suit of markers presented 2–3 alleles for each locus and their observed and expected heterozygosities were 0.057–0.610 and 0.056–0.598, respectively. These new microsatellite loci had an average of 2.12 alleles and thus contributed to relatively low exclusion probabilities of parentage and paternity testing (0.768 and 0.921). However, when these loci were examined in combination with previous microsatellite markers, overall probabilities of parentage and paternity exclusion went up to 0.905 and 0.990, respectively, showing that these 26 microsatellite loci should be adopted together in future genetic analyses for this highly inbred species.