Estimation of mutation rates from parentage exclusion data: applications to STR and VNTR loci

Microsatellites' mutation modeling through the analysis of the Y-chromosomal transmission: Results of a GHEP-ISFG collaborative study

The Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) organized a collaborative study on mutations of Y-chromosomal short tandem repeats (Y-STRs). New data from 2225 father-son duos and data from 44 previously published reports, corresponding to 25,729 duos, were collected and analyzed. Marker-specific mutation rates were estimated for 33 Y-STRs. Although highly dependent on the analyzed marker, mutations compatible with the gain or loss of a single repeat were 23.2 times more likely than those involving a greater number of repeats. Longer alleles (relatively to the modal one) showed to be nearly twice more mutable than the shorter ones. Within the subset of longer alleles, the loss of repeats showed to be nearly twice more likely than the gain. Conversely, shorter alleles showed a symmetrical trend, with repeat gains being twofold more frequent than reductions. A positive correlation between the paternal age and the mutation rate was observed, strengthening previous findings. The results of a machine learning approach, via logistic regression analyses, allowed the establishment of algebraic formulas for estimating the probability of mutation depending on paternal age and allele length for DYS389I, DYS393 and DYS627. Algebraic formulas could also be established considering only the allele length as predictor for DYS19, DYS389I, DYS389II-I, DYS390, DYS391, DYS393, DYS437, DYS439, DYS449, DYS456, DYS458, DYS460, DYS481, DYS518, DYS533, DYS576, DYS626 and DYS627 loci. For the remaining Y-STRs, a lack of statistical significance was observed, probably as a consequence of the small effective size of the subsets available, a common difficulty in the modeling of rare events as is the case of mutations. The amount of data used in the different analyses varied widely, depending on how the data were reported in the publications analyzed. This shows a regrettable waste of produced data, due to inadequate communication of the results, supporting an urgent need of publication guidelines for mutation studies.

The sequence of the repetitive motif influences the frequency of multistep mutations in Short Tandem Repeats

Microsatellites, or Short Tandem Repeats (STRs), are subject to frequent length mutations that involve the loss or gain of an integer number of repeats. This work aimed to investigate the correlation between STRs' specific repetitive motif composition and mutational dynamics, specifically the occurrence of single- or multistep mutations. Allelic transmission data, comprising 323,818 allele transfers and 1,297 mutations, were gathered for 35 Y-chromosomal STRs with simple structure. Six structure groups were established: ATT, CTT, TCTA/GATA, GAAA/CTTT, CTTTT, and AGAGAT, according to the repetitive motif present in the DNA leading strand of the markers. Results show that the occurrence of multistep mutations varies significantly among groups of markers defined by the repetitive motif. The group of markers with the highest frequency of multistep mutations was the one with repetitive motif CTTTT (25% of the detected mutations) and the lowest frequency corresponding to the group with repetitive motifs TCTA/GATA (0.93%). Statistically significant differences (α = 0.05) were found between groups with repetitive motifs with different lengths, as is the case of TCTA/GATA and ATT (p = 0.0168), CTT (p < 0.0001) and CTTTT (p < 0.0001), as well as between GAAA/CTTT and CTTTT (p = 0.0102). The same occurred between the two tetrameric groups GAAA/CTTT and TCTA/GATA (p < 0.0001) - the first showing 5.7 times more multistep mutations than the second. When considering the number of repeats of the mutated paternal alleles, statistically significant differences were found for alleles with 10 or 12 repeats, between GATA and ATT structure groups. These results, which demonstrate the heterogeneity of mutational dynamics across repeat motifs, have implications in the fields of population genetics, epidemiology, or phylogeography, and whenever STR mutation models are used in evolutionary studies in general.

Estimations of Mutation Rates Depend on Population Allele Frequency Distribution: The Case of Autosomal Microsatellites

Microsatellites (or short-tandem repeats (STRs)) are widely used in anthropology and evolutionary studies. Their extensive polymorphism and rapid evolution make them the ideal genetic marker for dating events, such as the age of a gene or a population. This usage requires the estimation of mutation rates, which are usually estimated by counting the observed Mendelian incompatibilities in one-generation familial configurations (typically parent(s)–child duos or trios). Underestimations are inevitable when using this approach, due to the occurrence of mutational events that do not lead to incompatibilities with the parental genotypes (‘hidden’ or ‘covert’ mutations). It is known that the likelihood that one mutation event leads to a Mendelian incompatibility depends on the mode of genetic transmission considered, the type of familial configuration (duos or trios) considered, and the genotype(s) of the progenitor(s). In this work, we show how the magnitude of the underestimation of autosomal microsatellite mutation rates varies with the populations’ allele frequency distribution spectrum. The Mendelian incompatibilities approach (MIA) was applied to simulated parent(s)/offspring duos and trios in different populational scenarios. The results showed that the magnitude and type of biases depend on the population allele frequency distribution, whatever the type of familial data considered, and are greater when duos, instead of trios, are used to obtain the estimates. The implications for molecular anthropology are discussed and a simple framework is presented to correct the naïf estimates, along with an informatics tool for the correction of incompatibility rates obtained through the MIA.

Mutation Rate Model Used in the DNA VIEW Program

The first problem considered in this paper is the problem of correctness of a mutation model used in the DNA VIEW program. To this end, we theoretically predict population allele frequency changes in time according to this and similar models (we determine the limit frequencies of alleles—they are uniformly distributed). Furthermore, we evaluate the speed of the above changes using computer simulation applied to our DNA database. Comparing uniformly distributed allele frequencies with these existing in the population (for example, using entropy), we conclude that this mutation model is not correct. The evolution does not follow this direction (direction of uniformly distributed frequencies). The second problem relates to the determination of the extent to which an incorrect mutation model can disturb DNA VIEW program results. We show that in typical computations (simple paternity testing without maternal mutation) this influence is negligible, but in the case of maternal mutation, this should be taken into account. Furthermore, we show that this model is inconsistent from a theoretical viewpoint. Equivalent methods result in different error levels.

Comparison of southern Chinese Han and Brazilian Caucasian mutation rates at autosomal short tandem repeat loci used in human forensic genetics

The short tandem repeat (STR) loci used in human genetic studies are characterized by having relatively high mutation rates. In particular, to ensure an appropriate evaluation of genetic evidence in parentage and forensic analyses, it is essential to have accurate estimates of the mutation rates associated with the commonly used autosomal and sex chromosome STR loci. Differences in STR mutation rates between different ethnic groups should also be determined. Mutation data from two laboratories working with different ethnic groups were extracted from many meiotic transmissions ascertained for 15 autosomal STR loci currently used in forensic routine. Forty-five thousand and eighty-five trios were checked for the biological consistency of maternity and paternity through the analysis of a minimum of 15 loci. Mutations were scored as paternal, maternal, or ambiguous according to the most parsimonious explanation for the inconsistency, using always the least requiring hypothesis in terms of number of repeat differences. The main findings are: (a) the overall mutation rate across the 15 loci was 9.78 × 10(-4) per gamete per generation (95% CI = 9.30 × 10(-4)-1.03 × 10(-3)), and with just 48 (out of 1,587) exceptions, all of the mutations were single-step; (b) repeat gains were more frequent than losses; (c) longer alleles were found to be more mutable; and (d) the mutation rates differ at some loci between the two ethnic groups. Large worldwide meiotic transmission datasets are still needed to measure allele-specific mutation rates at the STR loci consensually used in forensic genetics.

DNA identification by pedigree likelihood ratio accommodating population substructure and mutations

DNA typing is an important tool in missing-person identification, especially in mass-fatality disasters. Identification methods comparing a DNA profile from unidentified human remains with that of a direct (from the person) or indirect (for example, from a biological relative) reference sample and ranking the pairwise likelihood ratios (LR) is straightforward and well defined. However, for indirect comparison cases in which several members from a family can serve as reference samples, the full power of kinship analysis is not entirely exploited. Because biologically related family members are not genetically independent, more information and thus greater power can be attained by simultaneous use of all pedigree members in most cases, although distant relationships may reduce the power. In this study, an improvement was made on the method for missing-person identification for autosomal and lineage-based markers, by considering jointly the DNA profile data of all available family reference samples. The missing person is evaluated by a pedigree LR of the probability of DNA evidence under alternative hypotheses (for example, the missing person is unrelated or if they belong to this pedigree with a specified biological relationship) and can be ranked for all pedigrees within a database. Pedigree LRs are adjusted for population substructure according to the recommendations of the second National Research Council (NRCII) Report. A realistic mutation model was also incorporated to accommodate the possibility of false exclusion. The results show that the effect of mutation on the pedigree LR is moderate, but LRs can be significantly decreased by the effect of population substructure. Finally, Y chromosome and mitochondrial DNA were integrated into the analysis to increase the power of identification. A program titled MPKin was developed, combining the aforementioned features to facilitate genetic analysis for identifying missing persons. The computational complexity of the algorithms is explained, and several ways to reduce the complexity are introduced.

Pedigree likelihood ratio for lineage markers

Lineage-based haplotype markers (e.g., Y chromosome STRs and mitochondrial DNA sequences) are important adjunct tools to the autosomal markers for kinship analysis and for specialized kinship applications such as database searching. Traditionally, the prosecution or kinship hypothesis considers the haplotypes in the same lineage and the probability of genotype data given the lineage hypothesis is simply set at 1 if the number of mismatched loci or nucleotides between the questioned person and the references is less than a predefined threshold. In this study, a kinship hypothesis based on a fixed relationship of the questioned person in the reference family is introduced. A graphical model is proposed to calculate the probability of the genotype data given the kinship hypothesis, which is the product of haplotype frequency of the founder in the pedigree and the transmission probability from the founder to all descendants. Proper mutation models are suggested for Y chromosome STRs and mitochondrial DNA sequence variants (i.e., SNPs) to calculate the transmission probability. The methods to infer the genotypes of the untyped individuals in the pedigree and the computational complexity of handling these untyped individuals are also addressed. Lastly, numerical examples of the applications are given to demonstrate the kinship hypothesis and the algorithms.

Estimating mutation rates from paternity casework

We present a statistical methodology for making inferences about mutation rates from paternity casework. This takes account of a number of sources of potential bias, including hidden mutation, incomplete family triplets, uncertain paternity status and differing maternal and paternal mutation rates, while allowing a wide variety of mutation models. An object-oriented Bayesian network is used to facilitate computation of the likelihood function for the mutation parameters. This can process either full or summary genotypic information, both from complete putative father-mother-child triplets and from defective cases where only the child and one of its parents are observed. We use a dataset from paternity casework to illustrate the effects on inferences about mutation parameters of various types of biases and the mutation model assumed. In particular, we show that there can be relevant information in cases of unconfirmed paternity, and that excluding these, as has generally been done, can lead to biased conclusions.

Minisatellite germline mutation rate in the Techa River population

Germline mutation at eight minisatellite loci has been studied among the irradiated families from the Techa River population and non-exposed families from the rural area of the Chelyabinsk and Kurgan Oblasts. The groups were matched by ethnicity, parental age, occupation and smoking habit. A statistically significant 1.7-fold increase in mutation rate was found in the germline of irradiated fathers, whereas maternal germline mutation rate in the exposed families was not elevated. Most of the minisatellite loci showed an elevated paternal mutation rate in the exposed group, indicating a generalised increase in minisatellite germline mutation rate in the Techa River population. These data suggest that the elevated minisatellite mutation rate can be attributed to radioactive exposure. The spectra of paternal mutation seen in the unexposed and exposed families were indistinguishable.

The mutational spectrum of human autosomal tetranucleotide microsatellites

We studied by multiplex amplification and single-run electrophoretic analysis 10 microsatellite loci, composed of nine tetranucleotide-repeats (D1S1612, D3S2387, D4S2431, D5S2501, D10S1237, D15S657, D16S2622, D18S1270, and IFNAR-ALU) and one trinucleotide repeat (D2S1353). After elimination of proven null allele events involving D1S1612 and D5S2501 and of all data of D3S2387, in which we suspected but could not prove the occurrence of null alleles, we were left with nine loci, encompassing 24,224 meioses and 23 mutations. Twenty-two of the mutations (96%) were single-step events. Moreover, 18 of the mutations were paternal, four were maternal, and one was indeterminate. There was no significant difference between the number of additions and deletions in the mutants. Our findings are compatible with a simple model in which tetranucleotide microsatellites mutate primarily in paternal germinative cells by DNA slippage, such that the vast majority of mutations are equiprobable additions or deletions of a single-repeat unit. By combining the data from our tetranucleotide loci with literature information of highly and lowly mutable microsatellites, we observed a very highly significant correlation between mutation rate and the geometric mean of the length of the longest perfect repeat region (LRPR), compatible with a power or exponential relationship. The variation of the length of the LRPR explained as much as 80% of the variance of the mutation rate of autosomal tetranucleotide microsatellites.

Elevated minisatellite mutation rate in the post-chernobyl families from ukraine

Germline mutation at eight human minisatellite loci has been studied among families from rural areas of the Kiev and Zhitomir regions of Ukraine, which were heavily contaminated by radionuclides after the Chernobyl accident. The control and exposed groups were composed of families containing children conceived before and after the Chernobyl accident, respectively. The groups were matched by ethnicity, maternal age, parental occupation, and smoking habits, and they differed only slightly by paternal age. A statistically significant 1.6-fold increase in mutation rate was found in the germline of exposed fathers, whereas the maternal germline mutation rate in the exposed families was not elevated. These data, together with the results of our previous analysis of the exposed families from Belarus, suggest that the elevated minisatellite mutation rate can be attributed to post-Chernobyl radioactive exposure. The mechanisms of mutation induction at human minisatellite loci are discussed.

Estimation of nonpaternity in the Mexican population of Nuevo Leon: a validation study with blood group markers

A method for estimating the general rate of nonpaternity in a population was validated using phenotype data on seven blood groups (A1A2BO, MNSs, Rh, Duffy, Lutheran, Kidd, and P) on 396 mother, child, and legal father trios from Nuevo León, Mexico. In all, 32 legal fathers were excluded as the possible father based on genetic exclusions at one or more loci (combined average exclusion probability of 0.694 for specific mother-child phenotype pairs). The maximum likelihood estimate of the general nonpaternity rate in the population was 0.118 +/- 0.020. The nonpaternity rates in Nuevo León were also seen to be inversely related with the socioeconomic status of the families, i.e., the highest in the low and the lowest in the high socioeconomic class. We further argue that with the moderately low (69.4%) power of exclusion for these seven blood group systems, the traditional critical values of paternity index (PI > or = 19) were not good indicators of true paternity, since a considerable fraction (307/364) of nonexcluded legal fathers had a paternity index below 19 based on the seven markers. Implications of these results in the context of genetic-epidemiological studies as well as for detection of true fathers for child-support adjudications are discussed, implying the need to employ a battery of genetic markers (possibly DNA-based tests) that yield a higher power of exclusion. We conclude that even though DNA markers are more informative, the probabilistic approach developed here would still be needed to estimate the true rate of nonpaternity in a population or to evaluate the precision of detecting true fathers.