Maximum-likelihood estimation of allelic dropout and false allele error rates from microsatellite genotypes in the absence of reference data

The importance of quantifying and accounting for stochastic genotyping errors when analyzing microsatellite data is increasingly being recognized. This awareness is motivating the development of data analysis methods that not only take errors into consideration but also recognize the difference between two distinct classes of error, allelic dropout and false alleles. Currently methods to estimate rates of allelic dropout and false alleles depend upon the availability of error-free reference genotypes or reliable pedigree data, which are often not available. We have developed a maximum-likelihood-based method for estimating these error rates from a single replication of a sample of genotypes. Simulations show it to be both accurate and robust to modest violations of its underlying assumptions. We have applied the method to estimating error rates in two microsatellite data sets. It is implemented in a computer program, Pedant, which estimates allelic dropout and false allele error rates with 95% confidence regions from microsatellite genotype data and performs power analysis. Pedant is freely available at http://www.stats.gla.ac.uk/ approximately paulj/pedant.html.     

Allelic dropout from a high-quality DNA source

Allelic dropouts are an important source of genotyping error, particularly in studies using non-invasive sampling techniques. This has important implications for conservation biology, as an increasing number of studies are now using non-invasive techniques to study rare species or endangered populations. Previously, allelic dropout has typically been associated with PCR amplification of low quality/quantity template DNA. However, in this study we recorded high levels of allelic dropout (21–57%) at specific loci amplified from a high quality DNA (63.1 ± 7.8 ng/μl) source in the red fox (Vulpes vulpes). We designed a series of experiments to identify the sources of error. Whilst we were able to show that the best method to identify allelic dropout was the dilution of template DNA prior to PCR amplification, our data also showed two specific patterns: (1) allelic dropouts occurred at specific loci; (2) allelic dropouts occurred at specific pair-wise combinations of alleles. These patterns suggest that mechanisms other than low quantity template DNA are responsible for allelic dropout. Further research on the causes of these patterns in this and other studies would further our understanding of genotyping errors and would aid future studies where allelic dropout may be a serious issue.     

Two-step multiplex polymerase chain reaction improves the speed and accuracy of genotyping using DNA from noninvasive and museum samples

Many studies in molecular ecology rely upon the genotyping of large numbers of low‐quantity DNA extracts derived from noninvasive or museum specimens. To overcome low amplification success rates and avoid genotyping errors such as allelic dropout and false alleles, multiple polymerase chain reaction (PCR) replicates for each sample are typically used. Recently, two‐step multiplex procedures have been introduced which drastically increase the success rate and efficiency of genotyping. However, controversy still exists concerning the amount of replication needed for suitable control of error. Here we describe the use of a two‐step multiplex PCR procedure that allows rapid genotyping using at least 19 different microsatellite loci. We applied this approach to quantified amounts of noninvasive DNAs from western chimpanzee, western gorilla, mountain gorilla and black and white colobus faecal samples, as well as to DNA from ~100‐year‐old gorilla teeth from museums. Analysis of over 45 000 PCRs revealed average success rates of > 90% using faecal DNAs and 74% using museum specimen DNAs. Average allelic dropout rates were substantially reduced compared to those obtained using conventional singleplex PCR protocols, and reliable genotyping using low (< 25 pg) amounts of template DNA was possible. However, four to five replicates of apparently homozygous results are needed to avoid allelic dropout when using the lowest concentration DNAs (< 50 pg/reaction), suggesting that use of protocols allowing routine acceptance of homozygous genotypes after as few as three replicates may lead to unanticipated errors when applied to low‐concentration DNAs.     

A Maximum-Likelihood Method to Correct for Allelic Dropout in Microsatellite Data with No Replicate Genotypes

Allelic dropout is a commonly observed source of missing data in microsatellite genotypes, in which one or both allelic copies at a locus fail to be amplified by the polymerase chain reaction. Especially for samples with poor DNA quality, this problem causes a downward bias in estimates of observed heterozygosity and an upward bias in estimates of inbreeding, owing to mistaken classifications of heterozygotes as homozygotes when one of the two copies drops out. One general approach for avoiding allelic dropout involves repeated genotyping of homozygous loci to minimize the effects of experimental error. Existing computational alternatives often require replicate genotyping as well. These approaches, however, are costly and are suitable only when enough DNA is available for repeated genotyping. In this study, we propose a maximum-likelihood approach together with an expectation-maximization algorithm to jointly estimate allelic dropout rates and allele frequencies when only one set of nonreplicated genotypes is available. Our method considers estimates of allelic dropout caused by both sample-specific factors and locus-specific factors, and it allows for deviation from Hardy–Weinberg equilibrium owing to inbreeding. Using the estimated parameters, we correct the bias in the estimation of observed heterozygosity through the use of multiple imputations of alleles in cases where dropout might have occurred. With simulated data, we show that our method can (1) effectively reproduce patterns of missing data and heterozygosity observed in real data; (2) correctly estimate model parameters, including sample-specific dropout rates, locus-specific dropout rates, and the inbreeding coefficient; and (3) successfully correct the downward bias in estimating the observed heterozygosity. We find that our method is fairly robust to violations of model assumptions caused by population structure and by genotyping errors from sources other than allelic dropout. Because the data sets imputed under our model can be investigated in additional subsequent analyses, our method will be useful for preparing data for applications in diverse contexts in population genetics and molecular ecology.     

DNA sampling from eggshell swabbing is widely applicable in wild bird populations as demonstrated in 23 species

There is increasing interest in noninvasive DNA sampling techniques. In birds, there are several methods proposed for sampling DNA, and of these, the use of eggshell swabbing is potentially applicable to a wide range of species. We estimated the effectiveness of this method in the wild by sampling the eggs of 23 bird species. Sampling of eggs was performed twice per nest, soon after the clutch was laid and again at the end of egg incubation. We genotyped DNA samples using a set of five conserved microsatellite markers, which included a Z-linked locus and a sex-typing marker. We successfully collected avian DNA from the eggs of all species tested and from 88.48% of the samples. In most of the cases, the DNA concentration was low (ca. 10 ng/μL). The number of microsatellite loci amplified per sample (0-5) was used as a measure of the genotyping success of the sample. On average, we genotyped 3.01 ± 0.12 loci per sample (mean ± SE), and time of sampling did not seem to have an effect; however, genotyping success differed among species and was greater in those species that used feather material for lining their nest cups. We also checked for the occurrence of possible genotyping errors derived from using samples with very low DNA quantities (i.e. allelic dropout or false alleles) and for DNA contamination from individuals other than the mother, which appeared at a moderate rate (in 44% of the PCR replicates and in 17.36% of samples, respectively). Additionally, we investigated whether the DNA on eggshells corresponded to maternal DNA by comparing the genotypes obtained from the eggshells to those obtained from blood samples of all the nestlings for six nests of magpies. In five of the six magpie nests, we found evidence that the swab genotypes were a mixture of genotypes from both parents and this finding was independent of the time of incubation. Thus, our results broadly confirm that the swabbing of eggshells can be used as a noninvasive method for obtaining DNA and is applicable across a wide range of bird species. Nonetheless, genotyping errors should be properly estimated for each species by using a suite of highly polymorphic loci. These errors may be resolved by sampling only recently laid eggs (to avoid non-maternal DNA contamination) or by performing several PCR replicates per sample (to avoid allelic dropout and false alleles) and/or by increasing the amount of DNA used in the PCR through increasing the volume of the PCR or increasing the concentration of template DNA.     

First set of microsatellite markers for genetic characterization of the Eurasian beaver (Castor fiber) based on tissue and hair samples

Noninvasive genetic techniques have become indispensible tools in wildlife conservation and management. Here, we report the development of the first set of microsatellite markers for the Eurasian beaver (Castor fiber). All 15 loci show considerable variation within the sampled region in southwestern Germany, with number of alleles ranging from two to six alleles per locus. A comparison between tissue and hair samples revealed that amplification success was only slightly lower for hair samples, making their use in noninvasive monitoring feasible. Despite some evidence for false alleles and allelic dropout, 77% of all loci were genotyped successfully among all hair samples and loci tested. The developed markers will be used for subspecies differentiation and reconstruction of dispersal routes, following reintroductions in Central Europe.     

Microsatellite scoring errors associated with noninvasive genotyping based on nuclear DNA amplified from shed hair

In the context of a study of wild chimpanzees, Pan troglodytes verus, we found that genotypes based on single PCR amplifications of microsatellite loci from single shed hair have a high error rate. We quantified error rates using the comparable results of 791 single shed hair PCR amplifications of 11 microsatellite loci of 18 known individuals. The most frequent error was the amplification of only one of the two alleles present at a heterozygous locus. This phenomenon, called allelic dropout, produced false homozygotes in 31% of single-hair amplifications. There was no difference in the probability of preferential amplification between longer and shorter alleles. The probability of scoring false homozygotes can be reduced to below 0.05 by three separate amplifications from single hairs of the same individual or by pooling hair samples from the same individual. In this study an additional 5.6% of the amplifications gave wrong genotypes because of contamination, labelling and loading errors, and possibly amplification artefacts. In contrast, amplifications from plucked hair taken from four dead individuals gave consistent results (error rate < 0.01%, n= 120). Allelic dropout becomes a problem when the DNA concentration falls below 0.05 ng/10 μL in the template as it can with shed hair, and extracts from faeces and masticated plant matter.     

Incorporating Genotype Uncertainty into Mark–Recapture-Type Models For Estimating Abundance Using DNA Samples

Summary .  Sampling DNA noninvasively has advantages for identifying animals for uses such as mark–recapture modeling that require unique identification of animals in samples. Although it is possible to generate large amounts of data from noninvasive sources of DNA, a challenge is overcoming genotyping errors that can lead to incorrect identification of individuals. A major source of error is allelic dropout, which is failure of DNA amplification at one or more loci. This has the effect of heterozygous individuals being scored as homozygotes at those loci as only one allele is detected. If errors go undetected and the genotypes are naively used in mark–recapture models, significant overestimates of population size can occur. To avoid this it is common to reject low-quality samples but this may lead to the elimination of large amounts of data. It is preferable to retain these low-quality samples as they still contain usable information in the form of partial genotypes. Rather than trying to minimize error or discarding error-prone samples we model dropout in our analysis. We describe a method based on data augmentation that allows us to model data from samples that include uncertain genotypes. Application is illustrated using data from the European badger ( Meles meles ).     

Noninvasive genotyping and Mendelian analysis of microsatellites in African savannah elephants

We obtained fresh dung samples from 202 (133 mother-offspring pairs) savannah elephants (Loxodonta africana) in Samburu, Kenya, and genotyped them at 20 microsatellite loci to assess genotyping success and errors. A total of 98.6% consensus genotypes was successfully obtained, with allelic dropout and false allele rates at 1.6% (n = 46) and 0.9% (n = 37) of heterozygous and total consensus genotypes, respectively, and an overall genotyping error rate of 2.5% based on repeat typing. Mendelian analysis revealed consistent inheritance in all but 38 allelic pairs from mother-offspring, giving an average mismatch error rate of 2.06%, a possible result of null alleles, mutations, genotyping errors, or inaccuracy in maternity assignment. We detected no evidence for large allele dropout, stuttering, or scoring error in the dataset and significant Hardy-Weinberg deviations at only two loci due to heterozygosity deficiency. Across loci, null allele frequencies were low (range: 0.000-0.042) and below the 0.20 threshold that would significantly bias individual-based studies. The high genotyping success and low errors observed in this study demonstrate reliability of the method employed and underscore the application of simple pedigrees in noninvasive studies. Since none of the sires were included in this study, the error rates presented are just estimates.     

Sex identification of wolf (Canis lupus) using non-invasive samples

We have developed new specific primers for sex determination from forensic samples of wolves (Canis lupus), such as hair, saliva, faecal, tooth and urine samples. In order to improve molecular sexing, we performed a multiplex semi-nested polymerase chain reaction (PCR) and several replicated amplifications per sample to avoid errors in low quantity DNA samples, such as allelic dropout and false alleles. The sex of individuals is automatically determined by capillary electrophoresis with a fluorescently labelled internal sex-specific primer from each pair. Our method yielded sex identification on 100% of invasive samples and 93% of forensic samples, being one of the highest success rates obtained from wild animals.     

Assessment of genotyping accuracy in a non-invasive DNA-based population survey of Asiatic black bears (Ursus thibetanus): lessons from a large-scale pilot study in Iwate prefecture,northern Japan

Non-invasive DNA genotyping using hair samples has become a common method in population surveys of Asiatic black bears (Ursus thibetanus) in Japan; however, the accuracy of the genotyping data has rarely been discussed in empirical studies. Therefore, we conducted a large-scale pilot study to examine genotyping accuracy and sought an efficient way of error-checking hair-trapping data. We collected 2,067 hair samples, successfully determined the genotypes of 1,245 samples, and identified 295 individuals. The genotyping data were further divided into 3 subsets of data according to the number of hairs used for DNA extraction in each sample (1–4, 5–9, and ≥10 hairs), and the error rates of allelic dropout and false alleles were estimated for each subset using a maximum likelihood method. The genotyping error rates in the samples with ≥10 hairs were found to be lower than those in the samples with 1–4 and 5–9 hairs. The presence of erroneous genotypes among the identified individuals was further checked using a post hoc goodness-of-fit test that determined the match between the expected and observed frequencies of individual homozygotes at 0–6 loci. The results indicated the presence of erroneous genotypes, possibly as a result of allelic dropout, in the samples. Therefore, for improved accuracy, it is recommended that samples containing ≥10 hairs should be used for genotyping and a post hoc goodness-of-fit test should be performed to exclude erroneous genotypes before proceeding with downstream analysis such as capture-mark-recapture estimation.     

gemini: software for testing the effects of genotyping errors and multitubes approach for individual identification

Improvements in the determination of individual genotypes from samples with low DNA quantity and quality are of prime importance in molecular ecology and conservation for reliable genetic individual identification (molecular tagging using microsatllites loci). Thus, errors (e.g. allelic dropout and false allele) appearing during samples genotyping must be monitored and eliminated as far as possible. The multitubes approach is a very effective but a costly and time‐consuming solution. In this paper, we present a simulation software that allows evaluation of the effect of genotyping errors on genetic identification of individuals and the effectiveness of a multitubes approach to correct these errors.     

A New Method for Noninvasive Genetic Sampling of Saliva in Ecological Research

Noninvasive samples for genetic analyses have become essential to address ecological questions. Popular noninvasive samples such as faeces contain degraded DNA which may compromise genotyping success. Saliva is an excellent alternative DNA source but scarcity of suitable collection methods makes its use anecdotal in field ecological studies. We develop a noninvasive method of collection that combines baits and porous materials able to capture saliva. We report its potential in optimal conditions, using confined dogs and collecting saliva early after deposition. DNA concentration in saliva extracts was generally high (mean 14 ng μl^-1). We correctly identified individuals in 78% of samples conservatively using ten microsatellite loci, and 90% of samples using only eight loci. Consensus genotypes closely matched reference genotypes obtained from hair DNA (99% of identification successes and 91% of failures). Mean genotyping effort needed for identification using ten loci was 2.2 replicates. Genotyping errors occurred at a very low frequency (allelic dropout: 2.3%; false alleles: 1.5%). Individual identification success increased with duration of substrate handling inside dog’s mouth and the volume of saliva collected. Low identification success was associated with baits rich in DNA-oxidant polyphenols and DNA concentrations <1 ng μl^-1. The procedure performed at least as well as other noninvasive methods, and could advantageously allow detection of socially low-ranked individuals underrepresented in sources of DNA that are involved in marking behaviour (faeces or urine). Once adapted and refined, there is promise for this technique to allow potentially high rates of individual identification in ecological field studies requiring noninvasive sampling of wild vertebrates.     

Importance of a pilot study for non-invasive genetic sampling: genotyping errors and population size estimation in red deer

Population size information is critical for managing endangered or harvested populations. Population size can now be estimated from non-invasive genetic sampling. However, pitfalls remain such as genotyping errors (allele dropout and false alleles at microsatellite loci). To evaluate the feasibility of non-invasive sampling (e.g., for population size estimation), a pilot study is required. Here, we present a pilot study consisting of (i) a genetic step to test loci amplification and to estimate allele frequencies and genotyping error rates when using faecal DNA, and (ii) a simulation step to quantify and minimise the effects of errors on estimates of population size. The pilot study was conducted on a population of red deer in a fenced natural area of 5440 ha, in France. Twelve microsatellite loci were tested for amplification and genotyping errors. The genotyping error rates for microsatellite loci were 0–0.83 (mean=0.2) for allele dropout rates and 0–0.14 (mean=0.02) for false allele rates, comparable to rates encountered in other non-invasive studies. Simulation results suggest we must conduct 6 PCR amplifications per sample (per locus) to achieve approximately 97% correct genotypes. The 3% error rate appears to have little influence on the accuracy and precision of population size estimation. This paper illustrates the importance of conducting a pilot study (including genotyping and simulations) when using non-invasive sampling to study threatened or managed populations.     

An empirical approach for reliable microsatellite genotyping of wolf DNA from multiple noninvasive sources

Wildlife management and conservation take advantage of the possibility to study free-living populations by collecting and analysing noninvasive samples. Nevertheless, the commonly adopted approaches, aimed at preventing results being affected by genotyping errors, considerably limit the applicability of noninvasive genotyping. An empirical approach is presented for achieving a reliable data set of wolf (Canis lupus) genotypes from multiple sources of DNA collected in a monitored population. This method relies on the relationship between sample quality and amplification outcome, which is ultimately related to the occurrence of typing errors (allelic dropout, false alleles). After DNA extraction, templates are amplified once at each locus and a conservative rating system (Q-score) is adopted to define the quality of single-locus amplifications. A significant relationship was found between quality scores and error rate (ER) (r ²=0.982). Thus it was possible to predict the chance a genotype has of being affected by errors on the basis of its Q-score. Genotypes not reaching a satisfactory confidence level can either be replicated to become reliable or excluded from the data set. Accordingly, in the present case study, 48–73% of all single-locus and 51–53% of all multilocus (ML) genotypes reached a sufficient (99 and 95%, respectively) reliability level after a single amplification per locus. Despite the possible decrease in overall yield, this method could provide a good compromise between accuracy in genotyping and effectiveness in screening large data sets for long-term or large-scale population surveys. However, to achieve complete and reliable data sets, replicated amplifications are necessary for those samples and loci providing poor results.An erratum to this article can be found at     

Rapid isolation and characterization of polymorphic microsatellite loci in the mud crab, Scylla paramamosain (Portunidae)

Scylla paramamosain is a widespread and commercially important species of coastal marine crab. We identified 13 polymorphic microsatellite loci from a genome library constructed with 5'-anchored PCR method. Thirty-two S. paramamosain from the East China Sea were used to analyze the characteristics of these loci. The number of alleles per locus ranged from 3 to 8, with a mean of 5.923. Observed and expected heterozygosities ranged from 0.500 to 0.875 and from 0.500 to 0.859, respectively. Eleven of the 13 loci were highly polymorphic (polymorphic information content >0.5). All of the 13 novel loci were in Hardy-Weinberg equilibrium after Bonferroni's correction (P < 0.0038). There was no null allele, stuttering errors or evidence of allelic dropout in any of the loci analyzed by MICRO-CHECKER. According to pairwise tests, no significant linkage disequilibrium was found among the 13 loci (P < 0.0038, adjusted value). These novel developed microsatellites will be useful for studies of genetic variation, population structure, conservation genetics, and molecular-assisted selective breeding of S. paramamosain.     

Patterns of nuclear DNA degeneration over time--a case study in historic teeth samples

The amount of nuclear DNA extracted from teeth of 279 individual red fox Vulpes vulpes collected over a period spanning the last three decades was determined by quantitative polymerase chain reaction (PCR). Although teeth were autoclaved during initial collection, 73.8% of extracts contained sufficient DNA concentration (> 5 pg/ micro L) suitable for reliable microsatellite genotyping but the quantity of nuclear DNA decayed significantly over time in a nonlinear pattern. The success of PCR amplification across four examined canine microsatellites over time was dependent on fragment size. By including data from two different tests for human contamination and from frequencies of allelic dropout and false alleles, the methodological constraints of population genetic studies using microsatellite loci amplified from historic DNA are discussed.     

Accurate partition of individuals into full-sib families from genetic data without parental information.

Two Markov chain Monte Carlo algorithms are proposed that allow the partitioning of individuals into full-sib groups using single-locus genetic marker data when no parental information is available. These algorithms present a method of moving through the sibship configuration space and locating the configuration that maximizes an overall score on the basis of pairwise likelihood ratios of being full-sib or unrelated or maximizes the full joint likelihood of the proposed family structure. Using these methods, up to 757 out of 759 Atlantic salmon were correctly classified into 12 full-sib families of unequal size using four microsatellite markers. Large-scale simulations were performed to assess the sensitivity of the procedures to the number of loci and number of alleles per locus, the allelic distribution type, the distribution of families, and the independent knowledge of population allelic frequencies. The number of loci and the number of alleles per locus had the most impact on accuracy. Very good accuracy can be obtained with as few as four loci when they have at least eight alleles. Accuracy decreases when using allelic frequencies estimated in small target samples with skewed family distributions with the pairwise likelihood approach. We present an iterative approach that partly corrects that problem. The full likelihood approach is less sensitive to the precision of allelic frequencies estimates but did not perform as well with the large data set or when little information was available (e.g., four loci with four alleles).     

Relative accuracy of three common methods of parentage analysis in natural populations

Parentage studies and family reconstructions have become increasingly popular for investigating a range of evolutionary, ecological and behavioural processes in natural populations. However, a number of different assignment methods have emerged in common use and the accuracy of each may differ in relation to the number of loci examined, allelic diversity, incomplete sampling of all candidate parents and the presence of genotyping errors. Here, we examine how these factors affect the accuracy of three popular parentage inference methods (colony , famoz and an exclusion‐Bayes’ theorem approach by Christie (Molecular Ecology Resources, 2010a, 10, 115) to resolve true parent–offspring pairs using simulated data. Our findings demonstrate that accuracy increases with the number and diversity of loci. These were clearly the most important factors in obtaining accurate assignments explaining 75–90% of variance in overall accuracy across 60 simulated scenarios. Furthermore, the proportion of candidate parents sampled had a small but significant impact on the susceptibility of each method to either false‐positive or false‐negative assignments. Within the range of values simulated, colony outperformed FaMoz, which outperformed the exclusion‐Bayes’ theorem method. However, with 20 or more highly polymorphic loci, all methods could be applied with confidence. Our results show that for parentage inference in natural populations, careful consideration of the number and quality of markers will increase the accuracy of assignments and mitigate the effects of incomplete sampling of parental populations.     

Microsatellite standardization and evaluation of genotyping error in a large multi-partner research programme for conservation of Atlantic salmon (Salmo salar L.)

Microsatellite genotyping is a common DNA characterization technique in population, ecological and evolutionary genetics research. Since different alleles are sized relative to internal size-standards, different laboratories must calibrate and standardize allelic designations when exchanging data. This interchange of microsatellite data can often prove problematic. Here, 16 microsatellite loci were calibrated and standardized for the Atlantic salmon, Salmo salar, across 12 laboratories. Although inconsistencies were observed, particularly due to differences between migration of DNA fragments and actual allelic size ('size shifts'), inter-laboratory calibration was successful. Standardization also allowed an assessment of the degree and partitioning of genotyping error. Notably, the global allelic error rate was reduced from 0.05 ± 0.01 prior to calibration to 0.01 ± 0.002 post-calibration. Most errors were found to occur during analysis (i.e. when size-calling alleles; the mean proportion of all errors that were analytical errors across loci was 0.58 after calibration). No evidence was found of an association between the degree of error and allelic size range of a locus, number of alleles, nor repeat type, nor was there evidence that genotyping errors were more prevalent when a laboratory analyzed samples outside of the usual geographic area they encounter. The microsatellite calibration between laboratories presented here will be especially important for genetic assignment of marine-caught Atlantic salmon, enabling analysis of marine mortality, a major factor in the observed declines of this highly valued species.