Empirical evaluation reveals best fit of a logistic mutation model for human Y-chromosomal microsatellites

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.

Considerations on the application of a mutation model for Y-STR interpretation

If Y-STR profiling is to be more effective in criminal casework, the methods used to evaluate evidential weight require improvement. Many forensic scientists assign an evidential weight by estimating the number of times a Y-STR profile obtained from a questioned sample has been observed in YHRD datasets. More sophisticated models have been suggested but not yet implemented into routine casework, e.g. Andersen & Balding [1]. Mutation is inherent to STR meiosis (or inheritance) and is encountered in practice. We evaluated a mutation model that can be incorporated into a method for assigning evidential weight to Y-STR profiles, an essential part of bringing any method into practice. Since an important part of implementation to casework is communication, the article is written in an accessible format for practitioners as well as statisticians. The mutation component within the MUTEA model by Willems et al. [2] incorporates the potential for multistep mutations and a tendency for alleles to revert towards a central length, reflecting observed mutation data, e.g. [3]. We have estimated the parameters in this model and in a simplified symmetric version of this model, using sequence data from father/son pairs [4] and deep-rooted pedigrees [5]. Both datasets contain multistep mutations, which may have an effect on models based on simulations [1]. We introduce Beta-Binomial and Beta-Geometric conjugate analyses for estimating rate and step parameters for the mutation models presented here, which require only summations and multiplications. We proved mathematically that the parameters can be estimated independently. We show the importance of reporting the variability of the parameters and not only a point estimate. The parameters can be easily incorporated into statistical models, and updated sequentially as more data becomes available. We recommend fuller publication of data to enable the development and evaluation of a wider range of mutation models.

Large-scale pedigree analysis highlights rapidly mutating Y-chromosomal short tandem repeats for differentiating patrilineal relatives and predicting their degrees of consanguinity

Rapidly mutating Y-chromosomal short tandem repeats (RM Y-STRs) were suggested for differentiating patrilineally related men as relevant in forensic genetics, anthropological genetics, and genetic genealogy. Empirical data are available for closely related males, while differentiation rates for more distant relatives are scarce. Available RM Y-STR mutation rate estimates are typically based on father-son pair data, while pedigree-based studies for efficient analysis requiring less samples are rare. Here, we present a large-scale pedigree analysis in 9379 pairs of men separated by 1-34 meioses on 30 Y-STRs with increased mutation rates including all known RM Y-STRs (RMplex). For comparison, part of the samples were genotyped at 25 standard Y-STRs mostly with moderate mutation rates (Yfiler Plus). For 43 of the 49 Y-STRs analyzed, pedigree-based mutation rates were similar to previous father-son based estimates, while for six markers significant differences were observed. Male relative differentiation rates from the 30 RMplex Y-STRs were 43%, 84%, 96%, 99%, and 100% for relatives separated by one, four, six, nine, and twelve meioses, respectively, which largely exceeded rates obtained by 25 standard Y-STRs. Machine learning based models for predicting the degree of patrilineal consanguinity yielded accurate and reasonably precise predictions when using RM Y-STRs. Fully matching haplotypes resulted in a 95% confidence interval of 1-6 meioses with RMplex compared to 1-25 with Yfiler Plus. Our comprehensive pedigree study demonstrates the value of RM Y-STRs for differentiating male relatives of various types, in many cases achieving individual identification, thereby overcoming the largest limitation of forensic Y-chromosome analysis.

Assessing the Forensic Value of DNA Evidence from Y Chromosomes and Mitogenomes

Y chromosome and mitochondrial DNA profiles have been used as evidence in courts for decades, yet the problem of evaluating the weight of evidence has not been adequately resolved. Both are lineage markers (inherited from just one parent), which presents different interpretation challenges compared with standard autosomal DNA profiles (inherited from both parents). We review approaches to the evaluation of lineage marker profiles for forensic identification, focussing on the key roles of profile mutation rate and relatedness (extending beyond known relatives). Higher mutation rates imply fewer individuals matching the profile of an alleged contributor, but they will be more closely related. This makes it challenging to evaluate the possibility that one of these matching individuals could be the true source, because relatives may be plausible alternative contributors, and may not be well mixed in the population. These issues reduce the usefulness of profile databases drawn from a broad population: larger populations can have a lower profile relative frequency because of lower relatedness with the alleged contributor. Many evaluation methods do not adequately take account of distant relatedness, but its effects have become more pronounced with the latest generation of high-mutation-rate Y profiles.

A Y-chromosomal survey of Ecuador's multi-ethnic population reveals new insights into the tri-partite population structure and supports an early Holocene age of the rare Native American founder lineage C3-MPB373

Ecuador is a multiethnic and pluricultural country with a complex history defined by migration and admixture processes. The present study aims to increase our knowledge on the Ecuadorian Native Amerindian groups and the unique South American Y-chromosome haplogroup C3-MPB373 through the analysis of up to 23 Y-chromosome STRs (Y-STRs) and several Y-SNPs in a sample of 527 Ecuadorians from 7 distinct populations and geographic areas, including Kichwa and non-Kichwa Native Amerindians, Mestizos and Afro-Ecuadorians. Our results reveal the presence of C3-MPB373 both in the Amazonian lowland Kichwa with frequencies up to 28 % and, for the first time, in notable proportions in Kichwa populations from the Ecuadorian highlands. The substantially higher frequencies of C3-MPB373 in the Amazonian lowlands found in Kichwa and Waorani individuals suggest a founder effect in that area. Notably, estimates for the time to the most recent common ancestor (TMRCA) in the range of 7.2-9.0 kya point to an ancient origin of the haplogroup and suggest an early Holocene expansion of C3-MPB373 into South America. Finally, the pairwise genetic distances (R_ST) separate the Kichwa Salasaka from all the other Native Amerindian and Ecuadorian groups, indicating a so far hidden diversity among the Kichwa-speaking populations and suggesting a more southern origin of this population. In sum, our study provides a more in-depth knowledge of the male genetic structure of the multiethnic Ecuadorian population, as well as a valuable reference dataset for forensic use.

Mutation analysis of 21 autosomal short tandem repeats in Han population from Hunan, China

Background: Short tandem repeats (STRs) are powerful genetic markers widely used in human genetics. Population data and locus-specific mutation rates of STRs are crucial for the evaluation and interpretation of genetic evidence in forensic and population genetics.Aim: To investigate the mutation rates of 21 autosomal STRs in a population from central south China.Subjects and methods: This study analysed 3420 paternity cases with a Combined Paternity Index >10,000 from Han population in Hunan. A total of 68,743 meiotic transfers were analysed and 62 mutations were identified.Results: The overall mutation rate of STR loci was 0.9 × 10^-3 (95% CI, 0.0007-0.0011) and the locus-specific mutation rates were estimated ranging from 0.0000-0.0023. Locus D1S1656 exhibited the highest mutation rate of 2.3 × 10^-3 (95% CI, 0.0005-0.0006), followed by D12S391 with a mutation rate of 2.0 × 10^-3 (95% CI, 0.0007-0.0044). No mutation was observed at TPOX, D2S1338 or Penta D. One-step mutation cases accounted for 96.77% of total mutations and the ratio of paternal vs maternal mutations was ∼4.85:1. Inter-population comparisons of locus-specific mutation rates of several STRs revealed significant differences between Han in Hunan and Han in other regions of China. Conclusion: The data justified the use of geographical data in further genetic applications.

Comparison of Markov Chain Monte Carlo Software for the Evolutionary Analysis of Y-Chromosomal Microsatellite Data

The evolutionary analysis of genetic data is an important subject of modern bioscience, with practical applications in diverse fields. Parameters of interest in this context include effective population sizes, mutation rates, population growth rates and the times to most recent common ancestors. Studying Y-chromosomal microsatellite data, in particular, has proven useful to unravel the recent patrilineal history of Homo sapiens populations. We compared the individual analysis options and technical details of four software tools that are widely used for this purpose, namely BATWING, BEAST, IMa2 and LAMARC, all of which use Bayesian coalescent-based Markov chain Monte Carlo (MCMC) methods for parameter estimation. More specifically, we simulated datasets for either eight or 20 hypothetical Y-chromosomal microsatellites, assuming a mutation rate of 0.0030 per generation and a constant or exponentially increasing population size, and used these data to evaluate the parameter estimation capacity of each tool. The datasets comprised between 100 and 1000 samples. In addition to runtime, the practical utility of the tools of interest can also be expected to depend critically upon the convergence behavior of the actual MCMC implementation. In fact, we found that runtime increased, and convergence rate decreased, with increasing sample size as expected. BATWING performed best with respect to runtime and convergence behavior, but only supports simple evolutionary models. As regards the spectrum of evolutionary models covered, and also in terms of cross-platform usability, BEAST provided the greatest flexibility. Finally, IMa2 and LAMARC turned out best to incorporate elaborate migration models in the analysis process.

Evolution of Variable Number Tandem Repeats and Its Relationship with Genomic Diversity in Salmonella Typhimurium

Salmonella enterica serovar Typhimurium is the most common Salmonella serovar causing human infections in Australia and many other countries. A total of 12,112 S. Typhimurium isolates from New South Wales were analyzed by multi-locus variable number of tandem repeat (VNTR) analysis (MLVA) using five VNTRs from 2007 to 2014. We found that mid ranges of repeat units of 8–14 in VNTR locus STTR5, 6–13 in STTR6, and 9–12 in STTR10 were always predominant in the population (>50%). In vitro passaging experiments using MLVA type carrying extreme length alleles found that the majority of long length alleles mutated to short ones and short length alleles mutated to longer ones. Both data suggest directional mutability of VNTRs toward mid-range repeats. Sequencing of 28 isolates from a newly emerged MLVA type and its five single locus variants revealed that single nucleotide variation between isolates with up to two MLVA differences ranged from 0 to 12 single nucleotide polymorphisms (SNPs). However, there was no relationship between SNP and VNTR differences. A population genetic model of the joint distribution of VNTRs and SNPs variations was used to estimate the mutation rates of the two markers, yielding a ratio of 1 VNTR change to 6.9 SNP changes. When only one VNTR repeat difference was considered, the majority of pairwise SNP difference between isolates were 4 SNPs or fewer. Based on this observation and our previous findings of SNP differences of outbreak isolates, we suggest that investigation of S. Typhimurium community outbreaks should include cases of 1 repeat difference to increase sensitivity. This study offers new insights into the short-term VNTR evolution of S. Typhimurium and its application for epidemiological typing.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.