Population structure of Atlantic salmon (Salmo salar L.): a range-wide perspective from microsatellite DNA variation

Atlantic salmon (n = 1682) from 27 anadromous river populations and two nonanadromous strains ranging from south-central Maine, USA to northern Spain were genotyped at 12 microsatellite DNA loci. This suite of moderate to highly polymorphic loci revealed 266 alleles (5-37/locus) range-wide. Statistically significant allelic and genotypic heterogeneity was observed across loci between all but one pairwise comparison. Significant isolation by distance was found within and between North American and European populations, indicating reduced gene flow at all geographical scales examined. North American Atlantic salmon populations had fewer alleles, fewer unique alleles (though at a higher frequency) and a shallower phylogenetic structure than European Atlantic salmon populations. We believe these characteristics result from the differing glacial histories of the two continents, as the North American range of Atlantic salmon was glaciated more recently and more uniformly than the European range. Genotypic assignment tests based on maximum-likelihood provided 100% correct classification to continent of origin and averaged nearly 83% correct classification to province of origin across continents. This multilocus method, which may be enhanced with additional polymorphic loci, provides fishery managers the highest degree of correct assignment to management unit of any technique currently available.     

Novel set of multiplex assays (SalPrint15) for efficient analysis of 15 microsatellite loci of contemporary samples of the Atlantic salmon (Salmo salar)

We report the development of new PCR assays and loading panels for the Atlantic salmon using 15 microsatellite loci. A total of 8, 3 and 4 loci were coamplified in three separate PCRs using labelled primers and loaded on the ABI DNA analyzer in two separate panels. Amplified alleles were clearly typed, and easily interpretable results were obtained. The method was successfully applied in different laboratories, even when different types of DNA polymerase were employed. The method is useful for analysing paternity, population genetics and conservation as well as for selective breeding programmes.     

Assessing allelic dropout and genotype reliability using maximum likelihood.

A growing number of population genetic studies utilize nuclear DNA microsatellite data from museum specimens and noninvasive sources. Genotyping errors are elevated in these low quantity DNA sources, potentially compromising the power and accuracy of the data. The most conservative method for addressing this problem is effective, but requires extensive replication of individual genotypes. In search of a more efficient method, we developed a maximum-likelihood approach that minimizes errors by estimating genotype reliability and strategically directing replication at loci most likely to harbor errors. The model assumes that false and contaminant alleles can be removed from the dataset and that the allelic dropout rate is even across loci. Simulations demonstrate that the proposed method marks a vast improvement in efficiency while maintaining accuracy. When allelic dropout rates are low (0-30%), the reduction in the number of PCR replicates is typically 40-50%. The model is robust to moderate violations of the even dropout rate assumption. For datasets that contain false and contaminant alleles, a replication strategy is proposed. Our current model addresses only allelic dropout, the most prevalent source of genotyping error. However, the developed likelihood framework can incorporate additional error-generating processes as they become more clearly understood.     

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.     

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.     

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.     

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.     

Identification, Inheritance, and Variation of Microsatellite Markers in the Black Scallop Mimachlamys varia

Five polymorphic microsatellite loci were identified in the black scallop Mimachlamys varia after construction of a genomic library enriched for (GT)n. To examine the transmission pattern of microsatellite alleles, several families were created and genotypes scored for three loci. The expected Mendelian ratios were found in 12 of 14 segregations examined. Unexpected segregations may be explained by a genotyping error (allelic dropout), given that when a specific allele was treated as dominant, the phenotypic ratios conformed to Mendelian expectations. The five loci were also examined in two samples from the Spanish coast. The two localities displayed similar mean values for the number of alleles per locus (7.2-8.4), allelic richness (7.2-7.9), and observed (0.389-0.484) and expected heterozygosity (0.545-0.618). Significant Hardy-Weinberg deviations were observed at three loci, with heterozygote deficiency occurring in all cases. Global multilocus θ value and allele frequencies at one locus revealed significant differentiation between the two localities.     

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).     

A consensus list of microsatellite markers for olive genotyping

Cultivar identification is a primary concern for olive growers, breeders, and scientists. This study was aimed at examining the SSR markers retrieved from the literature and currently used in olive study, in order to select those most effective in characterizing the olive accessions and to make possible the comparison of data obtained by different laboratories. Olive microsatellite profiles were assessed by four independent laboratories, which analyzed 37 pre-selected SSR loci on a set of 21 cultivars. These SSR markers were initially tested for their reproducibility, power of discrimination and number of amplified loci/alleles. Independent segregation was tested for each pair of SSRs in a controlled cross and the allelic error rate was quantified. Some of them were finally selected as the most informative and reliable. Most of the alleles were sequenced and their sizes were determined. Profiles of the reference cultivars and a list of alleles with their sizes obtained by sequencing are reported. Several genetic parameters have been analysed on a larger set of cultivars allowing for a deeper characterization of the selected loci. Results of this study provide a list of recommended markers and protocols for olive genotyping as well as the allelic profile of a set of reference cultivars that would be useful for the establishment of a universal database of olive accessions.     

Microsatellite DNA markers for the study of Atlantic salmon (Salmo salar) kinship,population structure,and mixed‐fishery analyses

Eleven microsatellite DNA loci were identified and characterized for Atlantic salmon (Salmo salar) collected from the Penobscot River, Maine, USA and the River Nith, Scotland, UK. The markers revealed high levels of genetic diversity (seven to 48 alleles per locus), heterozygosity (to 100%), and allelic heterogeneity (all comparisons). Considerable differentiation was observed as the genetic distance (chord) between the two collections was 0.680 and the pairwise F_ST, 0.12, was highly significant. These findings are consistent with patterns of continental‐level differentiation observed previously using an alternate suite of microsatellite loci. Locus‐by‐locus analyses of molecular variance suggested that most markers were suitable for delineating kinships and population genetic structure.     

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.     

Quantitative PCR assessment of microsatellite and SNP genotyping with variable quality DNA extracts

In this study we developed eight quantitative PCR (qPCR) assays to evaluate the starting copy number of nuclear and mitochondrial DNA fragments ranging from 75 to 350 base-pairs in DNA extracts from Chinook salmon tissues with varying quality. Samples were genotyped with 13 microsatellite and 29 SNP assays and average genotyping success for good, intermediate, and poor quality samples was 96%, 24%, and 24% for microsatellite loci, and 98%, 97%, and 79% for SNPs, respectively. As measured by qPCR, good quality samples had a consistently high number of starting copies across all fragment sizes with little change between the smallest and largest size. In contrast, the intermediate and poor quality samples displayed decreases in starting copy number as fragment size increased, and was most pronounced with poor samples. Logistic regression of genotyping success by starting copy number indicated that in order to achieve at least 90% genotyping success, approximately 1,000 starting copies of nuclear DNA are necessary for microsatellite loci, and as few as 14 starting copies for SNP assays (but we recommend at least 50 copies to reduce genotyping error). While these guidelines apply specifically to Chinook salmon and the genetic markers included in this study, the principles are transferable to other species and markers due to the underlying process associated with template quantity and PCR amplification.     

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.     

Timing of first feeding and life-history strategies in salmon: genetic data

To investigate the relationship between genetic composition and some physiological traits of interest (age at smoltification, precocious maturation in male parr) in early and late first feeding Atlantic salmon, genetic variation at 6 isozyme and 8 microsatellite loci was examined. Early and late first feeding salmon showed different allelic and genotypic distributions at both isozyme and microsatellite loci. A positive relation between enzymatic loci heterozygosity and precocious active alimentation and earlier smoltification (S1 cf. S2) were also found.     

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.     

megasat: automated inference of microsatellite genotypes from sequence data

megasat is software that enables genotyping of microsatellite loci using next‐generation sequencing data. Microsatellites are amplified in large multiplexes, and then sequenced in pooled amplicons. megasat reads sequence files and automatically scores microsatellite genotypes. It uses fuzzy matches to allow for sequencing errors and applies decision rules to account for amplification artefacts, including nontarget amplification products, replication slippage during PCR (amplification stutter) and differential amplification of alleles. An important feature of megasat is the generation of histograms of the length–frequency distributions of amplification products for each locus and each individual. These histograms, analogous to electropherograms traditionally used to score microsatellite genotypes, enable rapid evaluation and editing of automatically scored genotypes. megasat is written in Perl, runs on Windows, Mac OS X and Linux systems, and includes a simple graphical user interface. We demonstrate megasat using data from guppy, Poecilia reticulata. We genotype 1024 guppies at 43 microsatellites per run on an Illumina MiSeq sequencer. We evaluated the accuracy of automatically called genotypes using two methods, based on pedigree and repeat genotyping data, and obtained estimates of mean genotyping error rates of 0.021 and 0.012. In both estimates, three loci accounted for a disproportionate fraction of genotyping errors; conversely, 26 loci were scored with 0–1 detected error (error rate ≤0.007). Our results show that with appropriate selection of loci, automated genotyping of microsatellite loci can be achieved with very high throughput, low genotyping error and very low genotyping costs.     

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.     

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.     

Quantifying genotyping errors in noninvasive population genetics

The use of noninvasively collected samples greatly expands the range of ecological issues that may be investigated through population genetics. Furthermore, the difficulty of obtaining reliable genotypes with samples containing low quantities of amplifiable DNA may be overcome by designing optimal genotyping schemes. Such protocols are mainly determined by the rates of genotyping errors caused by false alleles and allelic dropouts. These errors may not be avoided through laboratory procedure and hence must be quantified. However, the definition of genotyping error rates remains elusive and various estimation methods have been reported in the literature. In this paper we proposed accurate codification for the frequencies of false alleles and allelic dropouts. We then reviewed other estimation methods employed in hair- or faeces-based population genetics studies and modelled the bias associated with erroneous methods. It is emphasized that error rates may be substantially underestimated when using an erroneous approach. Genotyping error rates may be important determinants of the outcome of noninvasive studies and hence should be carefully computed and reported.