What is the magnitude of the subpopulation effect?

The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity

Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.

Population structure of Han nationality in Central-Southern China

Knowledge of population structure is very important for forensic genetics. However, the population substructure in Central-Southern China Han nationality has still not been fully described. In this study, we investigated the genetic diversity of 15 forensic autosomal STR loci from 6879 individuals in 12 Han populations subdivided by administrative provinces in Central-Southern China. The statistical analysis of genetic variation showed that genetic differentiation among these populations was very small with a F_st value of 0.0009. The Discriminant Analysis of Principal Components (DAPC) showed that there were no obvious population clusters in Central-Southern China Han population. In practice, the population structure effect in Central-Southern China Han population can be negligible in forensic identification and paternity testing.

Forensic genetic analyses in isolated populations with examples of central European Valachs and Roma

Isolated populations present a constant threat to the correctness of forensic genetic casework. In this review article we present several examples of how analyzing samples from isolated populations can bias the results of the forensic statistics and analyses. We select our examples from isolated populations from central and southeastern Europe, namely the Valachs and the European Roma. We also provide the reader with general strategies and principles to improve the laboratory practice (best practice) and reporting of samples from supposedly isolated populations. These include reporting the precise population data used for computing the forensic statistics, using the appropriate θ correction factor for calculating allele frequencies, typing ancestry informative markers in samples of unknown or uncertain ethnicity and establishing ethnic-specific forensic databases.

The factor of 10 in forensic DNA match probabilities

An update was performed of the classic experiments that led to the view that profile probability assignments are usually within a factor of 10 of each other. The data used in this study consist of 15 Identifiler loci collected from a wide range of forensic populations. Following Budowle et al. [1], the terms cognate and non-cognate are used. The cognate database is the database from which the profiles are simulated. The profile probability assignment was usually larger in the cognate database. In 44%-65% of the cases, the profile probability for 15 loci in the non-cognate database was within a factor of 10 of the profile probability in the cognate database. This proportion was between 60% and 80% when the FBI and NIST data were used as the non-cognate databases. A second experiment compared the match probability assignment using a generalised database and recommendation 4.2 from NRC II (the 4.2 assignment) with a proxy for the matching proportion developed using subpopulation allele frequencies and the product rule. The findings support that the 4.2 assignment has a large conservative bias. These results are in agreement with previous research results.

Fitting the Balding-Nichols model to forensic databases

Large forensic databases provide an opportunity to compare observed empirical rates of genotype matching with those expected under forensic genetic models. A number of researchers have taken advantage of this opportunity to validate some forensic genetic approaches, particularly to ensure that estimated rates of genotype matching between unrelated individuals are indeed slight overestimates of those observed. However, these studies have also revealed systematic error trends in genotype probability estimates. In this analysis, we investigate these error trends and show how they result from inappropriate implementation of the Balding-Nichols model in the context of database-wide matching. Specifically, we show that in addition to accounting for increased allelic matching between individuals with recent shared ancestry, studies must account for relatively decreased allelic matching between individuals with more ancient shared ancestry.

Evaluating methods to correct for population stratification when estimating paternity indexes

The statistical interpretation of the forensic genetic evidence requires the use of allelic frequency estimates in the reference population for the studied markers. Differences in the genetic make up of the populations can be reflected in statistically different allelic frequency distributions. One can easily figure out that collecting such information for any given population is not always possible. Therefore, alternative approaches are needed in these cases in order to compensate for the lack of information. A number of statistics have been proposed to control for population stratification in paternity testing and forensic casework, Fst correction being the only one recommended by the forensic community. In this study we aimed to evaluate the performance of Fst to correct for population stratification in forensics. By way of simulations, we first tested the dependence of Fst on the relative sizes of the sub-populations, and second, we measured the effect of the Fst corrections on the Paternity Index (PI) values compared to the ones obtained when using the local reference database. The results provide clear-cut evidence that (i) Fst values are strongly dependent on the sampling scheme, and therefore, for most situations it would be almost impossible to estimate real values of Fst; and (ii) Fst corrections might unfairly correct PI values for stratification, suggesting the use of local databases whenever possible to estimate the frequencies of genetic profiles and PI values.

Use of DNA profiles for investigation using a simulated national DNA database: Part I. Partial SGM Plus profiles

In traditional criminal investigation, uncertainties are often dealt with using a combination of common sense, practical considerations and experience, but rarely with tailored statistical models. For example, in some countries, in order to search for a given profile in the national DNA database, it must have allelic information for six or more of the ten SGM Plus loci for a simple trace. If the profile does not have this amount of information then it cannot be searched in the national DNA database (NDNAD). This requirement (of a result at six or more loci) is not based on a statistical approach, but rather on the feeling that six or more would be sufficient. A statistical approach, however, could be more rigorous and objective and would take into consideration factors such as the probability of adventitious matches relative to the actual database size and/or investigator's requirements in a sensible way. Therefore, this research was undertaken to establish scientific foundations pertaining to the use of partial SGM Plus loci profiles (or similar) for investigation.

A universal strategy to interpret DNA profiles that does not require a definition of low-copy-number

In this paper we critically examine the causes of the underlying confusion that relates to the issue of low-template (LT) DNA profile interpretation. Firstly, there is much difficulty in attempting to distinguish between LT-DNA vs. conventional DNA because there is no discrete 'cut-off' point that can be reasonably defined or evaluated. LT-DNA is loosely characterised by drop-out (where alleles may be missing) and drop-in (where additional alleles may be present). We have previously described probabilistic methods that can be used to incorporate these phenomena using likelihood ratio (LR) principles. This is preferred to the random man not excluded (RMNE) method, because we cannot identify a coherent way forward within the restrictions provided by this framework. Most LT-DNA profiles are interpreted using a 'consensus' profile method, we called this the 'biological model', where only those alleles that are duplicated in consecutive tests are reported. We recognise that there is an increased need for probabilistic models to take precedence over the biological model. These models are required for all kinds of DNA profiles, not just those that are believed to be low-template. We also recognise that there is a need for education and training if the methods we recommend are to be widely introduced.

Object-oriented Bayesian networks for paternity cases with allelic dependencies

This study extends the current use of Bayesian networks by incorporating the effects of allelic dependencies in paternity calculations. The use of object-oriented networks greatly simplify the process of building and interpreting forensic identification models, allowing researchers to solve new, more complex problems. We explore two paternity examples: the most common scenario where DNA evidence is available from the alleged father, the mother and the child; a more complex casewhere DNA is not available from the alleged father, but is available from the alleged father's brother. Object-oriented networks are built, using HUGIN, for each example which incorporate the effects of allelic dependence caused by evolutionary relatedness.

Database of genetic profiles at the Department of Forensic Medicine, Medical University of Bialystok

PURPOSE

The objective of this project was to establish an 'in-house' DNA database to store and compare profiles genotyped in the Department of Forensic Medicine, Medical University of Bialystok.

MATERIAL AND METHODS

DNA was extracted using Chelex-100, an organic procedure, or commercial kits. Genetic profiles were obtained using AmpFISTR SGM Plus, AmpFISTR Profiler, or AmpFISTR Identifiler and 310 ABI Prism Genetic Analyzer (Applera). DNA Stat v. 1. 2 software was used to construct the database.

RESULTS

As of the end of 2006 our forensic database stored 1,595 profiles genotyped in criminal cases in the years 2000-2006, including 398 non-match samples, 2 non-match fetuses, 5 non-match newborns and 4 non-match corpses.

CONCLUSION

A DNA database was established that may be used for the purpose of genetic profile comparison in criminal cases.

Use of subpopulation data in Australian forensic DNA casework

DNA profiling evidence presented in court should be accompanied by a reliable estimate of its evidential weight. In calculating such statistics, allele frequencies from commonly employed autosomal microsatellite loci are required. These allele frequencies should be collected at a level that appropriately represents the genetic diversity that exists in the population. Typically this occurs at broadly defined bio-geographic categories, such as Caucasian or Asian. Datasets are commonly administered at the jurisdictional level. This paper focuses on Australian jurisdictions and assesses whether this current practice is appropriate for Aboriginal Australian and Caucasian populations alike. In keeping with other studies we observe negligible differences between Caucasian populations within Australia when segregated geographically. However segregation of Aboriginal Australian population data along contemporary State and Territory lines appears to mask the diversity that exists within this subpopulation. For this reason datasets collated along more traditional lines may be more appropriate, particularly to distinguish the most genetically differentiated populations residing in the north of the continent.

Implication of Population Structure in the Resolution of Cattle Stealing Cases

Estimation of population subdivision using genetic markers shows that genetic differentiation in livestock and pet breeds is significantly higher than in human populations. Nevertheless, the influence of population substructure and sample size on match probability has not been extensively analyzed in domestic species. To evaluate the magnitude of the subpopulation effect on estimation of match probabilities in bovine robbery cases, we calculated and compared the match probabilities obtained from cattle breed databases using both real, adjudicated cases from the Buenos Aires Province (Argentina), as well as simulated data. While the Balding and Nichols' correction, when applied to the population database used in the case, produce a more conservative value favorable to the defendant, the match probabilities calculated using the simple product estimator produce a value favorable to the prosecution. We suggest an alternative procedure that can be used. The method consists of choosing the highest value from all match probabilities calculated from the database of each breed. This approach represents an intermediate and more accurate estimation of match probability, although it still produces a slight conservative value favorable to the defense.

A comprehensive analysis of microsatellite diversity in Aboriginal Australians

Indigenous Australians have a unique evolutionary history that has resulted in a complex system of inter and intra-tribal relationships. While a number of studies have examined the population genetics of indigenous Australians, most have used a single sample to illuminate details of the global dispersal of modern humans and few studies have focussed on the population genetic features of the widely dispersed communities of the indigenous population. In this study we examine the largest Aboriginal Australian sample yet analysed (N = 8,868) at fifteen hypervariable autosomal microsatellite loci. A comprehensive analysis of differentiation indicates different levels of heterogeneity among indigenous peoples from traditional regions of Aboriginal Australia. The most genetically differentiated populations inhabit the North of the country, in particular the Tiwi of Melville and Bathurst islands, Arnhem Land (itself divided into West and East Arnhem), and Fitzmaurice regions. These tribal groups are most differentiated from other Aboriginal Australian tribes, especially those of the Central Desert regions, and also show marked heterogeneity from one another. These genetic findings are supportive of observations of body measurements, skin colour, and dermatoglyphic features which also vary substantially between tribes of the North (e.g. Arnhem Land) and Central Australian regions and, more specifically, between the Tiwi and West and East Arnhem tribes. This study provides the most comprehensive survey of the population genetics of Aboriginal Australia.

Population Substructure Can Significantly Affect Reliability of a DNA-led Process of Identification of Mass Fatality Victims

Aiming to evaluate the effects of population substructure on the reliability of a DNA correspondence in the process of human identification, we used the model of "in silico" constructed populations with and without substructure. Effects of population substructure were evaluated at the level of locus heterozygosity, Hardy-Weinberg equilibrium and mini-haplotype distribution. Inbreeding in a subpopulation of 100 individuals through 10 generations did not significantly alter the level of heterozygosity and Hardy-Weinberg equilibrium. However, analysis of mini-haplotype distribution revealed a significant homogenization in separated subpopulations. Average observed mini-haplotype frequency (f(o)) increased to threefold from expected values (f(e)), and the number of mini-haplotypes with f(o)/f(e) above 10 increased over sixfold, suggesting that the effects of population substructure on calculated likelihood ratios (LR) might be larger than previously estimated. In most criminal cases, this would not represent a problem, whereas for identifications in large-scale mass fatality events, population substructure might considerably increase the risk of false identification.

Dealing with allelic dropout when reporting the evidential value in DNA relatedness analysis

A method is suggested that allows the use of loci that have shown allelic dropout in kinship analysis as used for disaster victim identification (DVI) and missing person work (MP). This approach uses an extension of a previously published approach to modelling allelic dropout. This method may salvage some information in cases where allelic dropout is hindering DVI or MP work particularly in reconciliations involving a large number of bodies and pedigrees. It should not replace the pursuit of more complete DNA profiles by the normal rework process for such samples.

How reliable is the sub-population model in DNA testimony?

The performance of the sub-population model first proposed by Balding and Nichols [D.J. Balding, R.A. Nichols, DNA profile match probability calculation: how to allow for population stratification, relatedness, database selection and single bands. Forensic Sci. Int. 64 (1994) 125-140] is examined using a simulation approach. This work extends the investigations of Curran et al. [J.M. Curran, J.S. Buckleton, and C.M. Triggs, What is the magnitude of the sub-population effect? Forensic Sci. Int. 135 (2003) 1-8]. In particular the effect of underestimating the coancestry coefficient, theta, and the effect of departures from the modelling assumptions were investigated. The model tends to give strongly conservative estimates if the estimate for the coancestry coefficient is accurate. If this coefficient is underestimated then a larger fraction of cases give non-conservative estimates. Departures from the modelling assumption that the sub-population is in Hardy-Weinberg and linkage equilibria appear to have very little effect.