Allele Frequencies at Microsatellite Loci: The Stepwise Mutation Model Revisited

We summarize available data on the frequencies of alleles at microsatellite loci in human populations and compare observed distributions of allele frequencies to those generated by a simulation of the stepwise mutation model. We show that observed frequency distributions at 108 loci are consistent with the results of the model under the assumption that mutations cause an increase or decrease in repeat number by one and under the condition that the product Nu, where N is the effective population size and u is the mutation rate, is larger than one. We show that the variance of the distribution of allele sizes is a useful estimator of Nu and performs much better than previously suggested estimators for the stepwise mutation model. In the data, there is no correlation between the mean and variance in allele size at a locus or between the number of alleles and mean allele size, which suggests that the mutation rate at these loci is independent of allele size.     

Apolipoprotein E Gene Polymorphism and Allele Frequencies in the Lebanese Population

Apolipoprotein E (ApoE) genotypes were studied in order to determine the prevalence in the Lebanese population and compare it with other populations. DNA from 160 unrelated healthy donors from our HLA-bank was used. ApoE genotype was determined using the CardioVascular Disease (CVD) StripAssay (this assay is based on a Polymerase Chain Reaction-Reverse Hybridization technique). The prevalence of genotypes E3/3, E3/4, and E2/3 was found to be 69%, 26%, and 22%, respectively, and 0.6% for each of E2/4 and E4/4 genotypes. The Lebanese population tested showed similarities to earlier reported ApoE genotypic distributions (high E3 allele frequency) but also peculiar differences especially to some Arabic countries (total absence of E2 allele among Saudis) and other populations. This is the first report from Lebanon that will serve as a template for future investigations of the prevalence of ApoE alleles in association with various clinical entities.     

Using Allele Frequencies and Geographic Subdivision to Reconstruct Gene Trees within a Species: Molecular Variance Parsimony

We formalize the use of allele frequency and geographic information for the construction of gene trees at the intraspecific level and extend the concept of evolutionary parsimony to molecular variance parsimony. The central principle is to consider a particular gene tree as a variable to be optimized in the estimation of a given population statistic. We propose three population statistics that are related to variance components and that are explicit functions of phylogenetic information. The methodology is applied in the context of minimum spanning trees (MSTs) and human mitochondrial DNA restriction data, but could be extended to accommodate other tree-making procedures, as well as other data types. We pursue optimal trees by heuristic optimization over a search space of more than 1.29 billion MSTs. This very large number of equally parsimonious trees underlines the lack of resolution of conventional parsimony procedures. This lack of resolution is highlighted by the observation that equally parsimonious trees yield very different estimates of population genetic diversity and genetic structure, as shown by null distributions of the population statistics, obtained by evaluation of 10,000 random MSTs. We propose a non-parametric test for the similarity between any two trees, based on the distribution of a weighted coevolutionary correlation. The ability to test for tree relatedness leads to the definition of a class of solutions instead of a single solution. Members of the class share virtually all of the critical internal structure of the tree but differ in the placement of singleton branch tips.     

A Generic Estimation of Population Subdivision Using Distances between Alleles with Special Reference for Microsatellite Loci

Several estimators of population differentiation have been proposed in the recent past to deal with various types of genetic markers (i.e., allozymes, nucleotide sequences, restriction fragment length polymorphisms, or microsatellites). We discuss the relationships among these estimators and show how a single analysis of variance framework can accomodate these qualitatively different data types.     

Estimation of Allele Frequencies at Isoloci

In some polyploid animals and plants, pairs of duplicated loci occur that share alleles encoding proteins with identical electrophoretic mobilities. Except in cases where these ``isoloci' are known to be inherited tetrasomically, individual genotypes cannot be determined unambiguously, and there is no direct way to assign observed variation to a particular locus of the pair. For a pair of diallelic isoloci, nine genotypes are possible but only five phenotypes can be identified, corresponding to individuals with 0-4 doses of the variant allele. A maximum likelihood (ML) approach is used here to identify the set of allele frequencies (p, q) at the individual gene loci with the highest probability of producing the observed phenotypic distribution. A likelihood ratio test is used to generate the asymmetrical confidence intervals around ML estimates. Simulations indicate that the standard error of p is typically about twice the binomial sampling error associated with single locus allele frequency estimates. ML estimates can be used in standard indices of genetic diversity and differentiation and in goodness-of-fit tests of genetic hypotheses. The noncentral χ(2) distribution is used to evaluate the power of a test of apparent heterozygote deficiency that results from attributing all variation to one locus when both loci are polymorphic.     

Estimation of Allele Frequencies in Indigenous Populations of Siberia Based on Pedigree Data

Procedure is described to estimate allele frequencies in indigenous populations of Siberia using phenotype data not only for pure-blood representatives of the ethnic groups examined, but also for the descendants of mixed marriages. Implementation of the method requires reconstruction of the pedigree structure for the sample examined. Inclusion of the data on descendants of mixed marriages into the analysis increases the sample information content and decreases variance of the estimates obtained. The advantages of the method are illustrated using an example of Tundra Nentsy, for whom it was shown that variance of estimates at the analysis of the blood groups allele frequencies can be diminished approximately by a factor of 1.5.     

Microsatellite Analysis of Genetic Variation and Population Subdivision for the Black Muntjac, Muntiacus crinifrons

The black muntjac (Muntiacus crinifrons) is a rare deer found only in a restricted region in east China. Recent studies of mitochondrial DNA diversity have shown a markedly low level of nucleotide diversity for the species, and the Suichang population was genetically differentiated from the two other populations, in Huangshan and Tianmushan mountains. In this study, we extended the analysis of genetic diversity and population subdivision for the black muntjac using data from 11 highly polymorphic nuclear DNA microsatellite loci. Contrary to the results based on mtDNA data, the microsatellite loci revealed that the black muntjac retained a rather high nuclear genetic diversity (overall average H (E) = 0.78). Nevertheless, both types of markers supported the idea that the extant black muntjac population is genetically disrupted (overall phi (ST) = 0.16 for mtDNA and overall F (ST) = 0.053 for microsatellite, both P < 0.001). The correlation between genetic differentiation and geographic distance was not significant (Mantel test; P > 0.05), implying that the patterns of genetic differentiation observed in this study might result from recent habitat fragmentation or loss. Based on the results from the mtDNA and nuclear DNA data sets, two management units were defined for the species, Huangshan/Tianmushan and Suichang. We also recommend that a new captive population be established with individuals from the Suichang region as a founder source.     

Confidence Intervals for Population Allele Frequencies: The General Case of Sampling from a Finite Diploid Population of Any Size

The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (%), a sample size of is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive % confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint % confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a % confidence interval for Jost''s D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management.     

Estimation of Allele Frequencies From High-Coverage Genome-Sequencing Projects

A new generation of high-throughput sequencing strategies will soon lead to the acquisition of high-coverage genomic profiles of hundreds to thousands of individuals within species, generating unprecedented levels of information on the frequencies of nucleotides segregating at individual sites. However, because these new technologies are error prone and yield uneven coverage of alleles in diploid individuals, they also introduce the need for novel methods for analyzing the raw read data. A maximum-likelihood method for the estimation of allele frequencies is developed, eliminating both the need to arbitrarily discard individuals with low coverage and the requirement for an extrinsic measure of the sequence error rate. The resultant estimates are nearly unbiased with asymptotically minimal sampling variance, thereby defining the limits to our ability to estimate population-genetic parameters and providing a logical basis for the optimal design of population-genomic surveys.     

Robust Identification of Local Adaptation from Allele Frequencies

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to F_ST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.     

Sampling for Microsatellite-Based Population Genetic Studies: 25 to 30 Individuals per Population Is Enough to Accurately Estimate Allele Frequencies

One of the most common questions asked before starting a new population genetic study using microsatellite allele frequencies is “how many individuals do I need to sample from each population?” This question has previously been answered by addressing how many individuals are needed to detect all of the alleles present in a population (i.e. rarefaction based analyses). However, we argue that obtaining accurate allele frequencies and accurate estimates of diversity are much more important than detecting all of the alleles, given that very rare alleles (i.e. new mutations) are not very informative for assessing genetic diversity within a population or genetic structure among populations. Here we present a comparison of allele frequencies, expected heterozygosities and genetic distances between real and simulated populations by randomly subsampling 5–100 individuals from four empirical microsatellite genotype datasets (Formica lugubris, Sciurus vulgaris, Thalassarche melanophris, and Himantopus novaezelandia) to create 100 replicate datasets at each sample size. Despite differences in taxon (two birds, one mammal, one insect), population size, number of loci and polymorphism across loci, the degree of differences between simulated and empirical dataset allele frequencies, expected heterozygosities and pairwise F_ST values were almost identical among the four datasets at each sample size. Variability in allele frequency and expected heterozygosity among replicates decreased with increasing sample size, but these decreases were minimal above sample sizes of 25 to 30. Therefore, there appears to be little benefit in sampling more than 25 to 30 individuals per population for population genetic studies based on microsatellite allele frequencies.     

Estimation of Allele Frequencies in Ethnically Heterogeneous Populations

A method for reconstructing allele frequencies characteristic of an original ethnically homogeneous population before the start of migration processes is described. Information on both the ethnic group studied and offspring of interethnic marriages is used to estimate the allele frequencies. This makes it possible to increase the informativeness of the sample, which, in the case of ethnic heterogeneity, depends not only on allele frequencies and the total sample size, but also on the ethnic structure of the sample. The problem of estimating allele frequency in an ethnically heterogeneous sample has been solved analytically for diallelic loci. It has been demonstrated that, if offspring of interethnic marriages with the same degree of outbreeding is added to a sample of the ethnic group studied, the sample informativeness does not change. To utilize the information contained in the phenotypes of the offspring of interethnic marriages, representatives of the population from which migration occurs should be included into the sample. The size of the sample ensuring the preassigned accuracy of estimation is minimized at a certain ratio between the numbers of the offspring of interethnic marriages and the “immigrants.” To analyze polyallelic loci, a software package has been developed that allows estimating allele frequencies, determining the errors of these estimates, and planning the sample ensuring the preassigned accuracy of estimation. The package is available free at http://mga.bionet.nsc.ru/PopMixed/PopMixed.html.__________Translated from Genetika, Vol. 41, No. 7, 2005, pp. 990–996.Original Russian Text Copyright © 2005 by Axenovich, Kirichenko.     

Intracellular Population Genetics: Evidence for Random Drift of Mitochondrial Allele Frequencies in SACCHAROMYCES CEREVISIAE and SCHIZOSACCHAROMYCES POMBE

We report evidence for random drift of mitochondrial allele frequencies in zygote clones of Saccharomyces cerevisiae and Schizosaccharomyces pombe. Monofactorial and bifactorial crosses were done, using strains resistant or sensitive to erythromycin (alleles E^R, E^S), oligomycin (O^R, O^S), or diuron (D^R, D^S). The frequencies of resistant and sensitive cells (and thus the frequencies of the resistant and sensitive alleles) were determined for each of a number of clones of diploid cells arising from individual zygotes. Allele frequencies were extremely variable among these zygote clones; some clones were "uniparental," with mitochondrial alleles from only one parent present. These observations suggest random drift of the allele frequencies in the population of mitochondrial genes within an individual zygote and its diploid progeny. Drift would cease when all the cells in a clone become homoplasmic, due to segregation of the mitochondrial genomes during vegetative cell divisions. To test this, we delayed cell division (and hence segregation) for varying times by starving zygotes in order to give drift more time to operate. As predicted, delaying cell division resulted in an increase in the variance of allele frequencies among the zygote clones and an increase in the proportion of uniparental zygote clones. The changes in form of the allele frequency distributions resembled those seen during random drift in finite Mendelian populations. In bifactorial crosses, genotypes as well as individual alleles were fixed or lost in some zygote clones. However, the mean recombination frequency for a large number of clones did not increase when cell division was delayed. Several possible molecular mechanisms for intracellular random drift are discussed.     

Population Migration and the Variation of Dopamine D4 Receptor (DRD4) Allele Frequencies Around the Globe

This article reports an association between the variation of dopamine D4 receptor (DRD4) allele frequencies around the globe and population migration patterns in prehistoric times. After compiling existing data on DRD4 allele frequencies of 2,320 individuals from 39 populations and on the migration pattern of these groups, we found that, compared to sedentary populations, migratory populations showed a higher proportion of long alleles for DRD4. The correlation between macro-migration (long-distance group migration) and the proportion of long alleles of DRD4 was .85 (p < .001), and that between micro-migration (sedentary vs. nomadic settlement) and the proportion of long alleles was .52 (p = .001). We discussed the adaptive value of long alleles of DRD4—a genetic trait that has been linked in some studies to the personality trait of novelty-seeking and to hyperactivity— in migratory societies and the possibility of natural selection for a migration gene.     

Demographic Genetics of Brown Trout (Salmo Trutta) and Estimation of Effective Population Size from Temporal Change of Allele Frequencies

We studied temporal allele frequency shifts over 15 years and estimated the genetically effective size of four natural populations of brown trout (Salmo trutta L.) on the basis of the variation at 14 polymorphic allozyme loci. The allele frequency differences between consecutive cohorts were significant in all four populations. There were no indications of natural selection, and we conclude that random genetic drift is the most likely cause of temporal allele frequency shifts at the loci examined. Effective population sizes were estimated from observed allele frequency shifts among cohorts, taking into consideration the demographic characteristics of each population. The estimated effective sizes of the four populations range from 52 to 480 individuals, and we conclude that the effective size of natural brown trout populations may differ considerably among lakes that are similar in size and other apparent characteristics. In spite of their different effective sizes all four populations have similar levels of genetic variation (average heterozygosity) indicating that excessive loss of genetic variability has been retarded, most likely because of gene flow among neighboring populations.     

Constraints on Allele Size at Microsatellite Loci: Implications for Genetic Differentiation

Microsatellites are promising genetic markers for studying the demographic structure and phylogenetic history of populations. We present theoretical arguments indicating that the usefulness of microsatellite data for these purposes may be limited to a short time perspective and to relatively small populations. The evolution of selectively neutral markers is governed by the interaction of mutation and random genetic drift. Mutation pressure has the inherent tendency to shift different populations to the same distribution of alleles. Hence, mutation pressure is a homogenizing force, and population divergence is caused by random genetic drift. In case of allozymes or sequence data, the diversifying effect of drift is typically orders of magnitude larger than the homogenizing effect of mutation pressure. By a simple model, we demonstrate that the situation may be different for microsatellites where mutation rates are high and the range of alleles is limited. With the help of computer simulations, we investigate to what extent genetic distance measures applied to microsatellite data can nevertheless yield useful estimators for phylogenetic relationships or demographic parameters. We show that predictions based on microsatellite data are quite reliable in small populations, but that already in moderately sized populations the danger of misinterpretation is substantial.     

On Estimation of Allele Frequencies via Next-Generation DNA Resequencing with Barcoding

Next Generation Sequencing (NGS) has revolutionized biomedical research in recent years. It is now commonly used to identify rare variants through resequencing individual genomes. Due to the cost of NGS, researchers have considered pooling samples as a cost-effective alternative to individual sequencing. In this article, we consider the estimation of allele frequencies of rare variants through the NGS technologies with pooled DNA samples with or without barcodes. We consider three methods for estimating allele frequencies from such data, including raw sequencing counts, inferred genotypes, and expected minor allele counts, and compare their performance. Our simulation results suggest that the estimator based on inferred genotypes overall performs better than or as well as the other two estimators. When the sequencing coverage is low, biases and MSEs can be sensitive to the choice of the prior probabilities of genotypes for the estimators based on inferred genotypes and expected minor allele counts so that more accurate specification of prior probabilities is critical to lower biases and MSEs. Our study shows that the optimal number of barcodes in a pool is relatively robust to the frequencies of rare variants at a specific coverage depth. We provide general guidelines on using DNA pooling with barcoding for the estimation of allele frequencies of rare variants.