Statistical Genetics and Genetical Statistics: a Forensic Perspective*

Utilizing Massively Parallel Sequencing (MPS) of Human Leukocyte Antigen (HLA) Gene Polymorphism to Assess Relatedness in Deficiency Parentage Testing

In the realm of DNA testing with legal implications, the reliability and precision of genetic markers play a pivotal role in confirming or negating paternity claims. This study aimed to assess the potential utility of human leukocyte antigen (HLA) gene polymorphism through massively parallel sequencing (MPS) technology as robust forensic markers for parentage testing involving genetic deficiencies. It sought to redefine the significance of HLA genes in this context. Data on autosomal short tandem repeat (aSTR) mutational events across 18 paternity cases involving 16 commonly employed microsatellite loci were presented. In instances where traditional aSTR analysis failed to establish statistical certainty, kinship determination was pursued via HLA genotyping, encompassing the amplification of 17 linked HLA loci. Within the framework of this investigation, phase-resolved genotypes for HLA genes were meticulously generated, resulting in the definition of 34 inherited HLA haplotypes. An impressive total of 274 unique HLA alleles, which were classified at either the field 3 or 4 level, were identified, including the discovery of four novel HLA alleles. Likelihood ratio (LR) values, which indicated the likelihood of the observed data under a true biological relationship versus no relationship, were subsequently calculated. The analysis of the LR values demonstrated that the HLA genes significantly enhanced kinship determination compared with the aSTR analysis. Combining LR values from aSTR markers and HLA loci yielded conclusive outcomes in duo paternity cases, showcasing the potential of HLA genes and MPS technology for deeper insights and diversity in genetic testing. Comprehensive reference databases and high-resolution HLA typing across diverse populations are essential. Reintegrating HLA alleles into forensic identification complements existing markers, creating a potent method for future forensic analysis.

Classical and Non-Classical HLA Alleles as Supplementary Markers in Indirect Kinship Parentage Testing

A civil paternity investigation involving the parents of the deceased alleged father in order to establish a family relationship is presented. On the basis of the 23 autosomal short tandem repeat (aSTR) genotyping results, conclusive proof of paternity was not achieved, as the probability of paternity (W) was calculated to 0.99988. Additional genetic data of 17 classical and non-classical human leukocyte alleles (HLA) typing by next-generation sequencing (NGS) at a high-resolution level supported the hypothesis of grandpaternity over the hypothesis of coincidental paternal obligate allele (POA) sharing (total WaSTR&HLA = 0.9999998). The present study demonstrates the utility of 17 HLA genetic markers-typing in the solution of deficiency cases of disputed parentage.

Kinship and the familial occurrence of skeletal developmental anomalies in the noble Swéerts-Sporck family (Bohemia, 17th to 20th centuries)

OBJECTIVE

To determine the degree of similarity of biologically related individuals according to the occurrence of skeletal developmental anomalies (SDA), to see whether these anomalies reflect documented biological relationships.

MATERIAL AND METHODS

The sample consists of the skeletal remains of seven members of the noble Swéerts-Sporck family from the 17th-20th centuries. Eighty-nine SDA were examined using morphological assessment, X-ray and CT. The degree of similarity was calculated using a similarity coefficient (Cvrček et al., 2018).

RESULTS

There were three shared SDA in the sample (cranial shift at the C-T border, cervical ribs, hypoplasia of rib 12), and another fifteen individual SDA were reported. The degree of similarity between individuals supports their documented relationships. The greatest similarity was found in closely related individuals such as father/son or siblings, and the least between unrelated individuals.

CONCLUSIONS

SDA can be used as a supportive tool for detecting family relationships. The results correspond to the conclusions of earlier analyses of non-metric traits and frontal sinuses in the same sample: the smaller the biological distance between individuals, the greater the degree of their similarity.

SIGNIFICANCE

Using unique human skeletal collections, this communication contributes to the expansion of knowledge about the familial occurrence of SDA.

LIMITATIONS

The small number of individuals limits the use of statistical approaches.

SUGGESTIONS FOR FURTHER RESEARCH

The results call for research on this topic using a larger sample with known genealogical data and the same approaches, to confirm our conclusions.

Bayesian approach to discriminant problems for count data with application to multilocus short tandem repeat dataset

Short Tandem Repeats (STRs) are a type of DNA polymorphism. This study considers discriminant analysis to determine the population of test individuals using an STR database containing the lengths of STRs observed at more than one locus. The discriminant method based on the Bayes factor is discussed and an improved method is proposed. The main issues are to develop a method that is relatively robust to sample size imbalance, identify a procedure to select loci, and treat the parameter in the prior distribution. A previous study achieved a classification accuracy of 0.748 for the g-mean (geometric mean of classification accuracies for two populations) and 0.867 for the AUC (area under the receiver operating characteristic curve). We improve the maximum values for the g-mean to 0.830 and the AUC to 0.935. Computer simulations indicate that the previous method is susceptible to sample size imbalance, whereas the proposed method is more robust while achieving almost identical classification accuracy. Furthermore, the results confirm that threshold adjustment is an effective countermeasure to sample size imbalance.

Multiple deaths caused by a fire in a factory: identification and investigative issues

The article presents a case of multiple casualties following a textile factory fire. The incident required a full DVI team similar to large mass-disaster because of the specific operational aspects and identification difficulties. The autopsy results were consistent with death by fire and the toxicological investigations revealed carbon monoxide poisoning in four cases (HbCO% ranging between 88,05 and 95,77), two deaths by cyanide intoxication (with concentrations between 5,17 and 8,85 mcg/ml), and in one case there was a synergistic effect of the two substances (carbon monoxide and cyanide). The identification, carried out in accordance with INTERPOL protocols, encountered serious difficulties in the AM phase primarily due to a language barrier and the lack of any dental or medical information relating to the victims. Secondary identifiers proved to be very useful in corroborating possible identities. As a result of the combined efforts of a team of experts the identity of each victim was determined and in all cases at least one primary identifier was used in the identification process. The deployment of DVI teams composed of forensic experts from different fields of expertise and well acquainted with DVI procedures, is essential in events involving multiple casualties that may also include foreign victims. The DVI team should intervene not only in PM examinations but also in the collection of AM data for those individuals not accounted for and by helping police in contacting families of missing people.

Response to: DNA identification by pedigree likelihood ratio accommodating population substructure and mutations

Mutation models are important in many areas of genetics including forensics. This letter criticizes the model of the paper 'DNA identification by pedigree likelihood ratio accommodating population substructure and mutations' by Ge et al. (2010). Furthermore, we argue that the paper in some cases misrepresents previously published papers.

Please see related letter: http://www.investigativegenetics.com/content/2/1/8.

Population stratification in Argentina strongly influences likelihood ratio estimates in paternity testing as revealed by a simulation-based approach

A simulation-based analysis was carried out to investigate the potential effects of population substructure in paternity testing in Argentina. The study was performed by evaluating paternity indexes (PI) calculated from different simulated pedigree scenarios and using 15 autosomal short tandem repeats (STRs) from eight Argentinean databases. The results show important statistically significant differences between PI values depending on the dataset employed. These differences are more dramatic when considering Native American versus urban populations. This study also indicates that the use of Fst to correct for the effect of population stratification on PI might be inappropriate because it cannot account for the particularities of single paternity cases.

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.

Structured Incorporation of Prior Information in Relationship Identification Problems

The objective of this paper is to show how various sources of information can be modelled and integrated to address relationship identification problems. Applications come from areas as diverse as evolution and conservation research, genealogical research in human, plant and animal populations, and forensic problems including paternity cases, identification following disasters, family reunions and immigration issues. We propose assigning a prior probability distribution to the sample space of pedigrees, calculating the likelihood based on DNA data using available software and posterior probabilities using Bayes' Theorem. Our emphasis here is on the modelling of this prior information in a formal and consistent manner. We introduce the distinction between local and global prior information, whereby local information usually applies to particular components of the pedigree and global prior information refers to more general features. When it is difficult to decide on a prior distribution, robustness to various choices should be studied. When suitable prior information is not available, a flat prior can be used which will then correspond to a strict likelihood approach. In practice, prior information is often considered for these problems, but in a generally ad hoc manner. This paper offers a consistent alternative. We emphasise that many practical problems can be addressed using freely available software.

Non-fatherhood or mutation? A probabilistic approach to parental exclusion in paternity testing

The occurrence of germline mutations at microsatellite loci poses problems in ascertaining non-fatherhood status in paternity testing. We describe the appropriate probabilistic analysis for computing the likelihood ratio in favour of paternity while allowing for mutation, for all 18 relevant combinations of seemingly incompatible parental genotypes. We allow arbitrary and possibly different mutation rates in paternal and maternal germlines. We describe a stationary mutation model for expressing the required allele-specific transition mutation rates in terms of overall mutation rates, and compare the likelihood ratios calculated from this and from other mutation models suggested in the literature. We also show how to derive an upper bound on the likelihood ratio, depending only on the overall mutation rate.