DNA commission of the International Society of Forensic Genetics: Recommendations on the evaluation of STR typing results that may include drop-out and/or drop-in using probabilistic methods

Genotyping and interpretation of STR-DNA: Low-template, mixtures and database matches-Twenty years of research and development

The introduction of Short Tandem Repeat (STR) DNA was a revolution within a revolution that transformed forensic DNA profiling into a tool that could be used, for the first time, to create National DNA databases. This transformation would not have been possible without the concurrent development of fluorescent automated sequencers, combined with the ability to multiplex several loci together. Use of the polymerase chain reaction (PCR) increased the sensitivity of the method to enable the analysis of a handful of cells. The first multiplexes were simple: 'the quad', introduced by the defunct UK Forensic Science Service (FSS) in 1994, rapidly followed by a more discriminating 'six-plex' (Second Generation Multiplex) in 1995 that was used to create the world's first national DNA database. The success of the database rapidly outgrew the functionality of the original system - by the year 2000 a new multiplex of ten-loci was introduced to reduce the chance of adventitious matches. The technology was adopted world-wide, albeit with different loci. The political requirement to introduce pan-European databases encouraged standardisation - the development of European Standard Set (ESS) of markers comprising twelve-loci is the latest iteration. Although development has been impressive, the methods used to interpret evidence have lagged behind. For example, the theory to interpret complex DNA profiles (low-level mixtures), had been developed fifteen years ago, but only in the past year or so, are the concepts starting to be widely adopted. A plethora of different models (some commercial and others non-commercial) have appeared. This has led to a confusing 'debate' about the 'best' to use. The different models available are described along with their advantages and disadvantages. A section discusses the development of national DNA databases, along with details of an associated controversy to estimate the strength of evidence of matches. Current methodology is limited to searches of complete profiles - another example where the interpretation of matches has not kept pace with development of theory. STRs have also transformed the area of Disaster Victim Identification (DVI) which frequently requires kinship analysis. However, genotyping efficiency is complicated by complex, degraded DNA profiles. Finally, there is now a detailed understanding of the causes of stochastic effects that cause DNA profiles to exhibit the phenomena of drop-out and drop-in, along with artefacts such as stutters. The phenomena discussed include: heterozygote balance; stutter; degradation; the effect of decreasing quantities of DNA; the dilution effect.

The ancient Yakuts: a population genetic enigma

This study is part of an ongoing project aiming at determining the ethnogenesis of an eastern Siberian ethnic group, the Yakuts, on the basis of archaeological excavations carried out over a period of 10 years in three regions of Yakutia: Central Yakutia, the Vilyuy River basin and the Verkhoyansk area. In this study, genetic analyses were carried out on skeletal remains from 130 individuals of unknown ancestry dated mainly from the fifteenth to the nineteenth century AD. Kinship studies were conducted using sets of commercially available autosomal and Y-chromosomal short tandem repeats (STRs) along with hypervariable region I sequences of the mitochondrial DNA. An unexpected and intriguing finding of this work was that the uniparental marker systems did not always corroborate results from autosomal DNA analyses; in some cases, false-positive relationships were observed. These discrepancies revealed that 15 autosomal STR loci are not sufficient to discriminate between first degree relatives and more distantly related individuals in our ancient Yakut sample. The Y-STR analyses led to similar conclusions, because the current Y-STR panels provided the limited resolution of the paternal lineages.

Inclusion probability with dropout: an operational formula

In forensic genetics, a mixture of two or more contributors to a DNA profile is often interpreted using the inclusion probabilities theory. In this paper, we present a general formula for estimating the probability of inclusion (PI, also known as the RMNE probability) from a subset of visible alleles when dropouts are possible. This one-locus formula can easily be extended to multiple loci using the cumulative probability of inclusion. We show that an exact formulation requires fixing the number of contributors, hence to slightly modify the classic interpretation of the PI. We discuss the implications of our results for the enduring debate over the use of PI vs likelihood ratio approaches within the context of low template amplifications.

Complex DNA mixture analysis in a forensic context: evaluating the probative value using a likelihood ratio model

The interpretation of mixed DNA profiles obtained from low template DNA samples has proven to be a particularly difficult task in forensic casework. Newly developed likelihood ratio (LR) models that account for PCR-related stochastic effects, such as allelic drop-out, drop-in and stutters, have enabled the analysis of complex cases that would otherwise have been reported as inconclusive. In such samples, there are uncertainties about the number of contributors, and the correct sets of propositions to consider. Using experimental samples, where the genotypes of the donors are known, we evaluated the feasibility and the relevance of the interpretation of high order mixtures, of three, four and five donors. The relative risks of analyzing high order mixtures of three, four, and five donors, were established by comparison of a 'gold standard' LR, to the LR that would be obtained in casework. The 'gold standard' LR is the ideal LR: since the genotypes and number of contributors are known, it follows that the parameters needed to compute the LR can be determined per contributor. The 'casework LR' was calculated as used in standard practice, where unknown donors are assumed; the parameters were estimated from the available data. Both LRs were calculated using the basic standard model, also termed the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim. We show how our results furthered the understanding of the relevance of analyzing high order mixtures in a forensic context. Limitations are highlighted, and it is illustrated how our study serves as a guide to implement likelihood ratio interpretation of complex DNA profiles in forensic casework.

Development of an Italian RM Y-STR haplotype database: Results of the 2013 GEFI collaborative exercise

Recently introduced rapidly mutating Y-chromosomal short tandem repeat (RM Y-STR) loci, displaying a multiple-fold higher mutation rate relative to any other Y-STRs, including those conventionally used in forensic casework, have been demonstrated to improve the resolution of male lineage differentiation and to allow male relative separation usually impossible with standard Y-STRs. However, large and geographically-detailed frequency haplotype databases are required to estimate the statistical weight of RM Y-STR haplotype matches if observed in forensic casework. With this in mind, the Italian Working Group (GEFI) of the International Society for Forensic Genetics launched a collaborative exercise aimed at generating an Italian quality controlled forensic RM Y-STR haplotype database. Overall 1509 male individuals from 13 regional populations covering northern, central and southern areas of the Italian peninsula plus Sicily were collected, including both "rural" and "urban" samples classified according to population density in the sampling area. A subset of individuals was additionally genotyped for Y-STR loci included in the Yfiler and PowerPlex Y23 (PPY23) systems (75% and 62%, respectively), allowing the comparison of RM and conventional Y-STRs. Considering the whole set of 13 RM Y-STRs, 1501 unique haplotypes were observed among the 1509 sampled Italian men with a haplotype diversity of 0.999996, largely superior to Yfiler and PPY23 with 0.999914 and 0.999950, respectively. AMOVA indicated that 99.996% of the haplotype variation was within populations, confirming that genetic-geographic structure is almost undetected by RM Y-STRs. Haplotype sharing among regional Italian populations was not observed at all with the complete set of 13 RM Y-STRs. Haplotype sharing within Italian populations was very rare (0.27% non-unique haplotypes), and lower in urban (0.22%) than rural (0.29%) areas. Additionally, 422 father-son pairs were investigated, and 20.1% of them could be discriminated by the whole set of 13 RM Y-STRs, which was very close to the theoretically expected estimate of 19.5% given the mutation rates of the markers used. Results obtained from a high-coverage Italian haplotype dataset confirm on the regional scale the exceptional ability of RM Y-STRs to resolve male lineages previously observed globally, and attest the unsurpassed value of RM Y-STRs for male-relative differentiation purposes.

Verifying likelihoods for low template DNA profiles using multiple replicates

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The behaviour of multi-replicate LRs with respect to the inverse match probability is proposed as a method to validate forensic LR software.

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We perform lab-based and simulated experiments of one-, two- and three-contributor CSPs, as well as investigating a real-world CSP.

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LRs rise towards the IMP with additional replicates, while never exceeding it. Additionally, the LR from multiple low-template replicates can exceed that from a single good-quality sample.

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We validate likeLTD by demonstrating that it adheres to the expected behaviours.

To date there is no generally accepted method to test the validity of algorithms used to compute likelihood ratios (LR) evaluating forensic DNA profiles from low-template and/or degraded samples. An upper bound on the LR is provided by the inverse of the match probability, which is the usual measure of weight of evidence for standard DNA profiles not subject to the stochastic effects that are the hallmark of low-template profiles. However, even for low-template profiles the LR in favour of a true prosecution hypothesis should approach this bound as the number of profiling replicates increases, provided that the queried contributor is the major contributor. Moreover, for sufficiently many replicates the standard LR for mixtures is often surpassed by the low-template LR. It follows that multiple LTDNA replicates can provide stronger evidence for a contributor to a mixture than a standard analysis of a good-quality profile. Here, we examine the performance of the likeLTD software for up to eight replicate profiling runs. We consider simulated and laboratory-generated replicates as well as resampling replicates from a real crime case. We show that LRs generated by likeLTD usually do exceed the mixture LR given sufficient replicates, are bounded above by the inverse match probability and do approach this bound closely when this is expected. We also show good performance of likeLTD even when a large majority of alleles are designated as uncertain, and suggest that there can be advantages to using different profiling sensitivities for different replicates. Overall, our results support both the validity of the underlying mathematical model and its correct implementation in the likeLTD software.

Analysis of allelic drop-out using the Identifiler(®) and PowerPlex(®) 16 forensic STR typing systems

Low-template (LT) DNA profiles continue to present interpretational challenges to the forensic community. Whether the LT contribution comprises the main profile, or whether it is present as the minor component of a mixture, ambiguity arises from the possibility that alleles present in the biological sample may not be detected in the resulting DNA profile. This phenomenon is known as allelic drop-out. This ambiguity complicates both the assessment of the potential number of contributors and estimation of the weight of the DNA evidence for or against specific propositions. One solution to estimating the weight of the evidence is to use a likelihood ratio (LR) that incorporates the probability of allelic drop-out P(DO) estimated for the specific evidence sample under consideration. However, although a vast repository of data exists, few empirical studies to determine allelic drop-out probabilities have been performed to date. Here we characterized patterns of allelic drop-out in single-source samples using both universal and run-specific analytical thresholds. Not surprisingly, we found fewer instances of apparent drop-out when using a lower (run-specific) detection threshold. Also, unsurprisingly, a positive correlation exists between allele drop-out and allele length, even in good quality samples. We used logistic regression to model the fraction of alleles that dropped out of a profile as a function of the average height of the detected peaks. The equation derived from the logistic regression model allowed us to estimate the expected drop-out probability for an evidentiary sample based on the average peak height of the profile. We show that the LRs calculated using the estimated drop-out probabilities were similar to those calculated using the benchmark drop-out probabilities, suggesting that the estimates of the drop-out probability are accurate and useful. This trend holds even when using the data from the PowerPlex(®) 16 typing system to estimate the drop-out probability for an Identifiler(®) profile, and vice versa. Thus we demonstrate that use of a LR that incorporates empirically estimated allelic drop-out probabilities provides a reliable means for extracting additional information from LT forensic DNA profiles.

Stochastic sampling effects in STR typing: Implications for analysis and interpretation

The analysis and interpretation of forensic STR typing results can become more complicated when reduced template amounts are used for PCR amplification due to increased stochastic effects. These effects are typically observed as reduced heterozygous peak-height balance and increased frequency of undetected alleles (allelic "dropout"). To investigate the origins of these effects, a study was performed using the AmpFlSTR(®) Identifiler Plus(®) and MiniFiler(®) kits to amplify replicates from a dilution series of NIST Human DNA Quantitation Standard (SRM(®) 2372A). The resulting amplicons were resolved and detected on two different genetic analyzer platforms, the Applied Biosystems 3130xL and 3500 analyzers. Results from our study show that the four different STR/genetic analyzer combinations exhibited very similar peak-height ratio statistics when normalized for the amount of template DNA in the PCR. Peak-height ratio statistics were successfully modeled using the Poisson distribution to simulate pre-PCR stochastic sampling of the alleles, confirming earlier explanations that sampling is the primary source for peak-height imbalance in reduced template dilutions. In addition, template-based pre-PCR sampling simulations also successfully predicted allelic dropout frequencies, as modeled by logistic regression methods, for the low-template DNA dilutions. We discuss the possibility that an accurately quantified DNA template might be used to characterize the linear signal response for data collected using different STR kits or genetic analyzer platforms, so as to provide a standardized approach for comparing results obtained from different STR/CE combinations and to aid in validation studies.

Evaluating the X chromosome-specific diversity of Colombian populations using insertion/deletion polymorphisms

The European and African contribution to the pre-existing Native American background has influenced the complex genetic pool of Colombia. Because colonisation was not homogeneous in this country, current populations are, therefore, expected to have different proportions of Native American, European and African ancestral contributions. The aim of this work was to examine 11 urban admixed populations and a Native American group, called Pastos, for 32 X chromosome indel markers to expand the current knowledge concerning the genetic background of Colombia. The results revealed a highly diverse genetic background comprising all admixed populations, harbouring important X chromosome contributions from all continental source populations. In addition, Colombia is genetically sub-structured, with different proportions of European and African influxes depending on the regions. The samples from the North Pacific and Caribbean coasts have a high African ancestry, showing the highest levels of diversity. The sample from the South Andean region showed the lowest diversity and significantly higher proportion of Native American ancestry than the other samples from the North Pacific and Caribbean coasts, Central-West and Central-East Andean regions, and the Orinoquian region. The results of admixture analysis using X-chromosomal markers suggest that the high proportion of African ancestry in the North Pacific coast was primarily male driven. These men have joined to females with higher Native American and European ancestry (likely resulting from a classic colonial asymmetric mating type: European male x Amerindian female). This high proportion of male-mediated African contributions is atypical of colonial settings, suggesting that the admixture occurred during a period when African people were no longer enslaved. In the remaining regions, the African contribution was primarily female-mediated, whereas the European counterpart was primarily male driven and the Native American ancestry contribution was not gender biased.

Panel of polymorphic heterologous microsatellite loci to genotype critically endangered Bengal tiger: a pilot study

In India, six landscapes and source populations that are important for long-term conservation of Bengal tigers (Panthera tigris tigris) have been identified. Except for a few studies, nothing is known regarding the genetic structure and extent of gene flow among most of the tiger populations across India as the majority of them are small, fragmented and isolated. Thus, individual-based relationships are required to understand the species ecology and biology for planning effective conservation and genetics-based individual identification has been widely used. But this needs screening and describing characteristics of microsatellite loci from DNA from good-quality sources so that the required number of loci can be selected and the genotyping error rate minimized. In the studies so far conducted on the Bengal tiger, a very small number of loci (n = 35) have been tested with high-quality source of DNA, and information on locus-specific characteristics is lacking. The use of such characteristics has been strongly recommended in the literature to minimize the error rate and by the International Society for Forensic Genetics (ISFG) for forensic purposes. Therefore, we describe for the first time locus-specific genetic and genotyping profile characteristics, crucial for population genetic studies, using high-quality source of DNA of the Bengal tiger. We screened 39 heterologous microsatellite loci (Sumatran tiger, domestic cat, Asiatic lion and snow leopard) in captive individuals (n = 8), of which 21 loci are being reported for the first time in the Bengal tiger, providing an additional choice for selection. The mean relatedness coefficient (R = -0.143) indicates that the selected tigers were unrelated. Thirty-four loci were polymorphic, with the number of alleles ranging from 2 to 7 per locus, and the remaining five loci were monomorphic. Based on the PIC values (> 0.500), and other characteristics, we suggest that 16 loci (3 to 7 alleles) be used for genetic and forensic study purposes. The probabilities of matching genotypes of unrelated individuals (3.692 × 10(-19)) and siblings (4.003 × 10(-6)) are within the values needed for undertaking studies in population genetics, relatedness, sociobiology and forensics.

Genetic association between the dopamine D1-receptor gene and paranoid schizophrenia in a northern Han Chinese population

OBJECTIVE

Dysregulation of dopaminergic neurotransmission at the D1 receptor in the prefrontal cortex has been implicated in the pathogenesis of schizophrenia. Genetic polymorphisms of the dopamine D1-receptor gene have a plausible role in modulating the risk of schizophrenia. To determine the role of DRD1 genetic polymorphisms as a risk factor for schizophrenia, we undertook a case-control study to look for an association between the DRD1 gene and schizophrenia.

MATERIALS AND METHODS

We genotyped eleven single-nucleotide polymorphisms within the DRD1 gene by deoxyribonucleic acid sequencing involving 173 paranoid schizophrenia patients and 213 unrelated healthy individuals. Statistical analysis was performed to identify the difference of genotype, allele, or haplotype distribution between cases and controls.

RESULTS

A significantly lower risk of paranoid schizophrenia was associated with the AG + GG genotype of rs5326 and the AG + GG genotype of rs4532 compared to the AA genotype and the AA genotype, respectively. Distribution of haplotypes was no different between controls and paranoid schizophrenia patients. In the males, the genotype distribution of rs5326 was statistically different between cases and controls. In the females, the genotype distribution of rs4532 was statistically different between cases and controls. However, the aforementioned statistical significances were lost after Bonferroni correction.

CONCLUSION

It is unlikely that DRD1 accounts for a substantial proportion of the genetic risk for schizophrenia. As an important dopaminergic gene, DRD1 may contribute to schizophrenia by interacting with other genes, and further relevant studies are warranted.

Exact computation of the distribution of likelihood ratios with forensic applications

If complex DNA profiles, conditioned on multiple individuals are evaluated, it may be difficult to assess the strength of the evidence based on the likelihood ratio. A likelihood ratio does not give information about the relative weights that are provided by separate contributors. Alternatively, the observed likelihood ratio can be evaluated with respect to the distribution of the likelihood ratio under the defense hypothesis. We present an efficient algorithm to compute an exact distribution of likelihood ratios that can be applied to any LR-based model. The distribution may have several applications, but is used here to compute a p-value that corresponds to the observed likelihood ratio. The p-value is the probability that a profile under the defense hypothesis, substituted for a questioned contributor e.g. suspect, would attain a likelihood ratio which is at least the same magnitude as that observed. The p-value can be thought of as a scaled version of the likelihood ratio, giving a quantitative measure of the strength of the evidence relative to the specified hypotheses and the model used for the analysis. The algorithm is demonstrated on examples based on real data. R code for the algorithm is freely available in the R package euroMix.

The National DNA Data Bank of Canada: a Quebecer perspective

The Canadian National DNA Database was created in 1998 and first used in the mid-2000. Under management by the RCMP, the National DNA Data Bank of Canada offers each year satisfactory reported statistics for its use and efficiency. Built on two indexes (convicted offenders and crime scene indexes), the database not only provides increasing matches to offenders or linked traces to the various police forces of the nation, but offers a memory repository for cold cases. Despite these achievements, the data bank is now facing new challenges that will inevitably defy the way the database is currently used. These arise from the increasing power of detection of DNA traces, the diversity of demands from police investigators and the growth of the bank itself. Examples of new requirements from the database now include familial searches, low-copy-number analyses and the correct interpretation of mixed samples. This paper aims to develop on the original way set in Québec to address some of these challenges. Nevertheless, analytic and technological advances will inevitably lead to the introduction of new technologies in forensic laboratories, such as single cell sequencing, phenotyping, and proteomics. Furthermore, it will not only request a new holistic/global approach of the forensic molecular biology sciences (through academia and a more investigative role in the laboratory), but also new legal developments. Far from being exhaustive, this paper highlights some of the current use of the database, its potential for the future, and opportunity to expand as a result of recent technological developments in molecular biology, including, but not limited to DNA identification.

Modeling one complete versus triplicate analyses in low template DNA typing

There are generally two strategies for low template DNA typing: the complete strategy, which uses all available DNA in a single PCR and subsequent typing, and the consensus strategy, in which the biological sample is divided into two or more aliquots and the genotype profile is determined by consensus from these "replicates." In this study, the consensus and complete strategies are compared by a statistical approach in terms of the accuracy of obtaining the correct genotype at a single locus for single source samples. Logistic models were employed to describe the allele drop-out and drop-in events. The parameters of the models were estimated with empirical or hypothetical data. The probabilities of obtaining the true genotype and the chances to observe drop-out and drop-in alleles were estimated and compared for both strategies. Consistent with a previous experimental study, this study found that, with relatively high input DNA (e.g., ≥ 100 pg), the complete strategy performs better than the consensus strategy to obtain the true genotype and the complete strategy will display less dropped out alleles. The consensus strategy had less drop-in alleles for ≤ 100 pg DNA samples. Moreover, the limitations of the logistic models were discussed. Ideal models with better fit of empirical data approximating casework conditions were proposed for future studies.

Evaluation of mixed-source, low-template DNA profiles in forensic science

Enhancements in sensitivity now allow DNA profiles to be obtained from only tens of picograms of DNA, corresponding to a few cells, even for samples subject to degradation from environmental exposure. However, low-template DNA (LTDNA) profiles are subject to stochastic effects, such as "dropout" and "dropin" of alleles, and highly variable stutter peak heights. Although the sensitivity of the newly developed methods is highly appealing to crime investigators, courts are concerned about the reliability of the underlying science. High-profile cases relying on LTDNA evidence have collapsed amid controversy, including the case of Hoey in the United Kingdom and the case of Knox and Sollecito in Italy. I argue that rather than the reliability of the science, courts and commentators should focus on the validity of the statistical methods of evaluation of the evidence. Even noisy DNA evidence can be more powerful than many traditional types of evidence, and it can be helpful to a court as long as its strength is not overstated. There have been serious shortcomings in statistical methods for the evaluation of LTDNA profile evidence, however. Here, I propose a method that allows for multiple replicates with different rates of dropout, sporadic dropins, different amounts of DNA from different contributors, relatedness of suspected and alternate contributors, "uncertain" allele designations, and degradation. R code implementing the method is open source, facilitating wide scrutiny. I illustrate its good performance using real cases and simulated crime scene profiles.