How to track and assess genotyping errors in population genetics studies

Genotyping errors occur when the genotype determined after molecular analysis does not correspond to the real genotype of the individual under consideration. Virtually every genetic data set includes some erroneous genotypes, but genotyping errors remain a taboo subject in population genetics, even though they might greatly bias the final conclusions, especially for studies based on individual identification. Here, we consider four case studies representing a large variety of population genetics investigations differing in their sampling strategies (noninvasive or traditional), in the type of organism studied (plant or animal) and the molecular markers used [microsatellites or amplified fragment length polymorphisms (AFLPs)]. In these data sets, the estimated genotyping error rate ranges from 0.8% for microsatellite loci from bear tissues to 2.6% for AFLP loci from dwarf birch leaves. Main sources of errors were allelic dropouts for microsatellites and differences in peak intensities for AFLPs, but in both cases human factors were non-negligible error generators. Therefore, tracking genotyping errors and identifying their causes are necessary to clean up the data sets and validate the final results according to the precision required. In addition, we propose the outline of a protocol designed to limit and quantify genotyping errors at each step of the genotyping process. In particular, we recommend (i) several efficient precautions to prevent contaminations and technical artefacts; (ii) systematic use of blind samples and automation; (iii) experience and rigor for laboratory work and scoring; and (iv) systematic reporting of the error rate in population genetics studies.     

Heterologous nuclear and chloroplast microsatellite amplification and variation in tea, Camellia sinensis.

The advantage of the cross transferability of heterologous chloroplast and nuclear microsatellite primers was taken to detect polymorphism among 24 tea (Camellia sinensis (L.) O. Kuntze) genotypes, including both the assamica and the sinensis varieties. Primer information was obtained from the closely related Camellia japonica species for four nuclear microsatellites, and from Nicotiana tabaccum for seven universal chloroplast microsatellites. All of the nuclear microsatellite loci tested generated an expected DNA fragment in tea, revealing between three and five alleles per locus. Four out of the seven chloroplast microsatellites primers amplified positively, and of these only one was polymorphic with three alleles, which is in agreement with the conserved nature of chloroplast microsatellites at the intraspecific level. A factorial correspondence analysis carried out on all genotypes and nuclear microsatellite alleles separated the assamica and sinensis genotypes into two groups, thus demonstrating the value of these markers in establishing the genetic relationship between tea varieties. Genetic diversity measured with nuclear microsatellites was higher than that measured with other types of molecular markers, offering prospects for their use in fingerprinting, mapping, and population genetic studies, whereas polymorphisms detected at a cpSSR locus will allow the determination of plastid inheritance in the species.     

micro‐checker: software for identifying and correcting genotyping errors in microsatellite data

DNA degradation, low DNA concentrations and primer‐site mutations may result in the incorrect assignment of microsatellite genotypes, potentially biasing population genetic analyses. micro ‐checker is windows ®‐based software that tests the genotyping of microsatellites from diploid populations. The program aids identification of genotyping errors due to nonamplified alleles (null alleles), short allele dominance (large allele dropout) and the scoring of stutter peaks, and also detects typographic errors. micro ‐checker estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis. micro ‐checker can be freely downloaded from http://www.microchecker.hull.ac.uk/ .     

An empirical exploration of data quality in DNA-based population inventories

I present data from 21 population inventory studies - 20 of them on bears - that relied on the noninvasive collection of hair, and review the methods that were used to prevent genetic errors in these studies. These methods were designed to simultaneously minimize errors (which can bias estimates of abundance) and per-sample analysis effort (which can reduce the precision of estimates by limiting sample size). A variety of approaches were used to probe the reliability of the empirical data, producing a mean, per-study estimate of no more than one undetected error in either direction (too few or too many individuals identified in the laboratory). For the type of samples considered here (plucked hair samples), the gain or loss of individuals in the laboratory can be reduced to a level that is inconsequential relative to the more universal sources of bias and imprecision that can affect mark-recapture studies, assuming that marker systems are selected according to stated guidelines, marginal samples are excluded at an early stage, similar pairs of genotypes are scrutinized, and laboratory work is performed with skill and care.     

鲤鱼微卫星突变速率和模式(英文)

利用150个微卫星分子标记在F1代家系的基因型分析过程中,共有27600个等位基因从亲本向子代传递,其中在5个微卫星座位上检测到6个突变的等位基因。对突变的等位基因数目进行统计分析后得出:鲤鱼平均每个世代每个微卫星座位的突变速率为2.53×10-4。在发现突变的5个位点中,经测序发现,突变序列中插入1个以上的重复单元就导致了突变的发生。这些突变表明,鲤鱼的微卫星突变没有遵循严格的渐变突变模型(stepwise mutation model,SMM)。该文关于鲤鱼微卫星突变速率和模式的研究将会对统计鲤鱼有效群体的统计提供有效参数。     

The in vitro fidelity of yeast DNA polymerase δ and polymerase ε holoenzymes during dinucleotide microsatellite DNA synthesis

Elucidating the sources of genetic variation within microsatellite alleles has important implications for understanding the etiology of human diseases. Mismatch repair is a well described pathway for the suppression of microsatellite instability. However, the cellular polymerases responsible for generating microsatellite errors have not been fully described. We address this gap in knowledge by measuring the fidelity of recombinant yeast polymerase δ (Pol δ) and ? (Pol ?) holoenzymes during synthesis of a [GT/CA] microsatellite. The in vitro HSV-tk forward assay was used to measure DNA polymerase errors generated during gap-filling of complementary GT(10) and CA(10)-containing substrates and ～90 nucleotides of HSV-tk coding sequence surrounding the microsatellites. The observed mutant frequencies within the microsatellites were 4 to 30-fold higher than the observed mutant frequencies within the coding sequence. More specifically, the rate of Pol δ and Pol ? misalignment-based insertion/deletion errors within the microsatellites was ～1000-fold higher than the rate of insertion/deletion errors within the HSV-tk gene. Although the most common microsatellite error was the deletion of a single repeat unit, ～ 20% of errors were deletions of two or more units for both polymerases. The differences in fidelity for wild type enzymes and their exonuclease-deficient derivatives were ～2-fold for unit-based microsatellite insertion/deletion errors. Interestingly, the exonucleases preferentially removed potentially stabilizing interruption errors within the microsatellites. Since Pol δ and Pol ? perform not only the bulk of DNA replication in eukaryotic cells but also are implicated in performing DNA synthesis associated with repair and recombination, these results indicate that microsatellite errors may be introduced into the genome during multiple DNA metabolic pathways.     

Estimation of the number of genetic markers required for individual animal identification accounting for genotyping errors

Nearly all studies that consider the power of exclusion for individual identification using genetic markers ignore the possibility of erroneous genotypes, although individual genotype error rates are approximately 1% for microsatellites. Single nucleotide polymorphisms (SNPs) have lower error rates, but because of their lower information content, more SNPs than microsatellites will be required to obtain the same power of exclusion for traceability. In this study, we accounted for genotyping mistakes by requiring at least two discrepancies to reject a match. Exclusion probabilities were computed analytically and by simulation. A microsatellite with five alleles was approximately comparable in exclusion power to 2-2.25 SNPs. At least eight SNPs were required to achieve a 99% probability of rejection for a match between two individuals, while with 25 SNPs there was a <1% chance for a match between any of five million individuals.     

Microsatellite evidence for high clonality and limited genetic diversity in Ziziphus celata (Rhamnaceae), an endangered, self-incompatible shrub endemic to the Lake Wales Ridge, Florida, USA

Genetic data are often crucial for designing management strategies for rare and endangered species. Ziziphus celata is an endangered sandhill shrub endemic to the Lake Wales Ridge of central Florida. This self-incompatible clonal species is known from only 14 wild populations, most of which are small (under 100 plants). Focusing on the five populations discovered in 2007, we evaluate the level of genetic diversity and identify clonal lineages within the wild populations of the species with a set of microsatellite loci. To account for somatic mutations and genotyping errors, we identified clonal lineages using a threshold cutoff for pair-wise genetic distances among samples. The microsatellites had up to 18 alleles/locus, and, consistent with outcrossing, samples were highly heterozygous (average population level H _o  = 0.69). Most populations of Z. celata consist of a single clone, and the most diverse population has only 10 clones. Overall Z. celata comprises 41 multi-locus genotypes, and 30 clonal lineages. With nearly 1,000 recorded plants (595 genotyped) and only 30 clonal lineages, Ziziphus celata is highly clonal: clonal richness, R = 0.049. The pair-wise distance method facilitates identification of clonal lineages, avoiding overestimation of clonal diversity. In most cases, the samples that grouped into a lineage were one to four plants differing from a surrounding genotype by a single microsatellite repeat insertion/deletion mutation, consistent with these having arisen via somatic mutations. Our data will enable managers to incorporate extant diversity from wild populations into ex situ collections. Additionally, our research demonstrates the utility of microsatellites for conservation of imperiled species, identifying genotypes of high priority for preservation.     

Population size estimation in Yellowstone wolves with error-prone noninvasive microsatellite genotypes

Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the 'worst-case threshold' suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a 'matching approach' to eliminate this overestimation bias.     

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.     

Likelihood-based estimation of microsatellite mutation rates

Microsatellites are widely used in genetic analyses, many of which require reliable estimates of microsatellite mutation rates, yet the factors determining mutation rates are uncertain. The most straightforward and conclusive method by which to study mutation is direct observation of allele transmissions in parent-child pairs, and studies of this type suggest a positive, possibly exponential, relationship between mutation rate and allele size, together with a bias toward length increase. Except for microsatellites on the Y chromosome, however, previous analyses have not made full use of available data and may have introduced bias: mutations have been identified only where child genotypes could not be generated by transmission from parents' genotypes, so that the probability that a mutation is detected depends on the distribution of allele lengths and varies with allele length. We introduce a likelihood-based approach that has two key advantages over existing methods. First, we can make formal comparisons between competing models of microsatellite evolution; second, we obtain asymptotically unbiased and efficient parameter estimates. Application to data composed of 118,866 parent-offspring transmissions of AC microsatellites supports the hypothesis that mutation rate increases exponentially with microsatellite length, with a suggestion that contractions become more likely than expansions as length increases. This would lead to a stationary distribution for allele length maintained by mutational balance. There is no evidence that contractions and expansions differ in their step size distributions.     

Reconstruction of microsatellite mutation history reveals a strong and consistent deletion bias in invasive clonal snails,Potamopyrgus antipodarum

Direct observations of mutations and comparative analyses suggest that nuclear microsatellites show a tendency to expand, with reports of deletion biases limited to very long alleles or a few loci in multilocus studies. Here we investigate microsatellite evolution in clonal snails, Potamopyrgus antipodarum, since their introduction to Britain in the 19th century, using an analysis based on minimum spanning networks of multilocus microsatellite genotypes. British populations consist of a small number of highly distinct genotype groups with very few outlying genotypes, suggesting clonal lineages containing minor variation generated by mutation. Network patterns suggest that a single introduced genotype was the ancestor of all extant variation and also provide support for wholly apomictic reproduction within the most common clonal lineage (group A). Microsatellites within group A showed a strong tendency to delete repeats, with an overall bias exceeding 88%, irrespective of the exact method used to infer mutations. This highly unusual pattern of deletion bias is consistent across populations and loci and is unrelated to allele size. We suggest that for persistence of microsatellites in this clone, some change in the mutation mechanism must have occurred in relatively recent evolutionary time. Possible causes of such a change in mechanism are discussed.     

微卫星标记在种群生物学研究中的应用

微卫星是以几个碱基 (一般为 1～ 6个 )为重复单位组成的简单的串联重复序列 ,具有丰度高、多态性高、共显性标记、选择中性、可自动检测等优点。本文着重介绍了微卫星在种群生物学研究中的应用。微卫星位点可以提供具高分辨率的遗传信息 ,这一特点使微卫星既适合于个体水平上的研究 ,又适合于种群水平上的研究。在个体水平上包括个体识别、交配系统和亲本分析、基因流等研究。微卫星是常用的个体识别手段 ,但在克隆植物遗传结构研究方面的应用还很有限 ;微卫星提高了交配系统和亲本分析、基因流等研究的准确性。在种群水平上微卫星可用于遗传结构、有效种群大小、种群的系统发育重建等研究。微卫星在很多物种 (包括珍稀物种 )的遗传结构研究中得到应用 ;利用微卫星标记确定有效种群大小、检测有效种群大小的波动可以促使我们正确理解种群遗传结构动态和种群进化过程 ;微卫星在种群的系统发育重建研究方面有很大的应用潜力。然而微卫星并不是研究所有问题的唯一选择。文中还讨论了在实际工作中应如何正确利用分子标记等问题     

Microsatellite Interruptions Stabilize Primate Genomes and Exist as Population-Specific Single Nucleotide Polymorphisms within Individual Human Genomes

Interruptions of microsatellite sequences impact genome evolution and can alter disease manifestation. However, human polymorphism levels at interrupted microsatellites (iMSs) are not known at a genome-wide scale, and the pathways for gaining interruptions are poorly understood. Using the 1000 Genomes Phase-1 variant call set, we interrogated mono-, di-, tri-, and tetranucleotide repeats up to 10 units in length. We detected ∼26,000–40,000 iMSs within each of four human population groups (African, European, East Asian, and American). We identified population-specific iMSs within exonic regions, and discovered that known disease-associated iMSs contain alleles present at differing frequencies among the populations. By analyzing longer microsatellites in primate genomes, we demonstrate that single interruptions result in a genome-wide average two- to six-fold reduction in microsatellite mutability, as compared with perfect microsatellites. Centrally located interruptions lowered mutability dramatically, by two to three orders of magnitude. Using a biochemical approach, we tested directly whether the mutability of a specific iMS is lower because of decreased DNA polymerase strand slippage errors. Modeling the adenomatous polyposis coli tumor suppressor gene sequence, we observed that a single base substitution interruption reduced strand slippage error rates five- to 50-fold, relative to a perfect repeat, during synthesis by DNA polymerases α, β, or η. Computationally, we demonstrate that iMSs arise primarily by base substitution mutations within individual human genomes. Our biochemical survey of human DNA polymerase α, β, δ, κ, and η error rates within certain microsatellites suggests that interruptions are created most frequently by low fidelity polymerases. Our combined computational and biochemical results demonstrate that iMSs are abundant in human genomes and are sources of population-specific genetic variation that may affect genome stability. The genome-wide identification of iMSs in human populations presented here has important implications for current models describing the impact of microsatellite polymorphisms on gene expression.     

Incorporating Genotyping Error Into Non-Invasive DNA-Based Mark—Recapture Population Estimates

ABSTRACT Use of non-invasive sources of DNA, such as hair or scat, to obtain a genetic mark for population estimates is becoming commonplace. Unfortunately, with such marks, potentials for genotyping errors and for the shadow effect have resulted in use of many loci and amplification of each specimen many times at each locus, drastically increasing time and cost of obtaining a population estimate. We proposed a method, the Genotyping Uncertainty Added Variance Adjustment (GUAVA), which statistically adjusts for genotyping errors and the shadow effect, thereby allowing use of fewer loci and one amplification of each specimen per locus. Using allele frequencies and estimates of genotyping error rates, we determined, for each pair of specimens, the probability that the pair was obtained from the same individual, whether or not their observed genotypes match. Using these probabilities, we reconstructed possible capture history matrices and used this distribution to obtain a population estimate. With simulated data, we consistently found our estimates had lower bias and smaller variance than estimates based on single amplifications in which genotyping error was ignored and that were comparable to estimates based on data free of genotyping errors. We also demonstrated the method on a fecal DNA data set from a population of red wolves (Canis rufus). The GUAVA estimate based on only one amplification genotypes compares favorably to the estimate based on consensus genotypes. A program to conduct the analysis is available from the first author for UNIX or Windows platforms. Application of GUAVA may allow for increased accuracy in population estimates at reduced cost.     

Development of microsatellite markers in potato and their transferability in some members of Solanaceae

We have developed thirty new microsatellite markers in potato by screening genomic libraries and ESTs. Genomic libraries of potato cultivar Kufri Bahar were screened for sequences containing microsatellite motifs GA, GT, ACA, ATC, GAA, TAA and GATA. Using flanking sequences, PCR primers were designed for microsatellites identified from genomic libraries and ESTs. Sixteen new primer pairs from genomic libraries and fourteen from ESTs along with seven previously published primer pairs amplified PCR products in the selected genotypes comprising of 65 Solanum tuberosum lines and 14 other species of the potato gene pool. Neighbor-joining tree based on genetic distance matrix developed using microsatellite markers successfully distinguished all these genotypes in the expected size range. Seventeen microsatellites could also be cross-amplified in at least one of the five members of solanaceae, namely tomato, eggplant, pepper, petunia and tobacco. The new microsatellite markers obtained in this study will be useful in various genetic and taxonomic studies in potato and related genomes.     

Characteristics of loci and individuals are associated with germline microsatellite mutation rates in lesser kestrels (Falco naumanni)

Although microsatellites are one of the most popular tools in genetic studies, their mutational dynamics and evolution remain unclear. Here, we apply extensive pedigree genotyping to identify and analyze the patterns and factors associated with de novo germline mutations across nine microsatellite loci in a wild population of lesser kestrels (Falco naumanni). A total of 10 germline mutations events were unambiguously identified in four loci, yielding an average mutation rate of 2.96x10(-3). Across loci, mutation rate was positively correlated with locus variability and average allele size. Mutations were primarily compatible with a stepwise mutation model, although not exclusively involved single-step changes. Unexpectedly, we found an excess of maternally transmitted mutations (male-to-female ratio of 0.1). One of the analyzed loci (Fn2.14) resulted hypermutable (mutation rate=0.87%). This locus showed a size-dependent mutation bias, with longer alleles displaying deletions or additions of a small number of repeat than shorter alleles. Mutation probability at Fn2.14 was higher for females and increased with parental (maternal) age but was not associated with individual physical condition, multilocus heterozygosity, allele length or allele span. Overall, our results do not support the male-biased mutation rate described in other organisms and suggest that mutation dynamics at microsatellite loci are a complex process which requires further research.     

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.     

Description of microsatellite markers and genotyping performances using feathers and buccal swabs for the Ivory gull (Pagophila eburnea)

We report 22 new polymorphic microsatellites for the Ivory gull (Pagophila eburnea), and we describe how they can be efficiently co-amplified using multiplexed polymerase chain reactions. In addition, we report DNA concentration, amplification success, rates of genotyping errors and the number of genotyping repetitions required to obtain reliable data with three types of noninvasive or nondestructive samples: shed feathers collected in colonies, feathers plucked from living individuals and buccal swabs. In two populations from Greenland (n=21) and Russia (Severnaya Zemlya Archipelago, n=21), the number of alleles per locus varied between 2 and 17, and expected heterozygosity per population ranged from 0.18 to 0.92. Twenty of the markers conformed to Hardy-Weinberg and linkage equilibrium expectations. Most markers were easily amplified and highly reliable when analysed from buccal swabs and plucked feathers, showing that buccal swabbing is a very efficient approach allowing good quality DNA retrieval. Although DNA amplification success using single shed feathers was generally high, the genotypes obtained from this type of samples were prone to error and thus need to be amplified several times. The set of microsatellite markers described here together with multiplex amplification conditions and genotyping error rates will be useful for population genetic studies of the Ivory gull.     

Identification and analysis of error types in high-throughput genotyping

Although it is clear that errors in genotyping data can lead to severe errors in linkage analysis, there is as yet no consensus strategy for identification of genotyping errors. Strategies include comparison of duplicate samples, independent calling of alleles, and Mendelian-inheritance-error checking. This study aimed to develop a better understanding of error types associated with microsatellite genotyping, as a first step toward development of a rational error-detection strategy. Two microsatellite marker sets (a commercial genomewide set and a custom-designed fine-resolution mapping set) were used to generate 118,420 and 22,500 initial genotypes and 10,088 and 8,328 duplicates, respectively. Mendelian-inheritance errors were identified by PedManager software, and concordance was determined for the duplicate samples. Concordance checking identifies only human errors, whereas Mendelian-inheritance-error checking is capable of detection of additional errors, such as mutations and null alleles. Neither strategy is able to detect all errors. Inheritance checking of the commercial marker data identified that the results contained 0.13% human errors and 0.12% other errors (0.25% total error), whereas concordance checking found 0.16% human errors. Similarly, Mendelian-inheritance-error checking of the custom-set data identified 1.37% errors, compared with 2.38% human errors identified by concordance checking. A greater variety of error types were detected by Mendelian-inheritance-error checking than by duplication of samples or by independent reanalysis of gels. These data suggest that Mendelian-inheritance-error checking is a worthwhile strategy for both types of genotyping data, whereas fine-mapping studies benefit more from concordance checking than do studies using commercial marker data. Maximization of error identification increases the likelihood of linkage when complex diseases are analyzed.