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

A novel mathematical framework for pedigree-based calculation of Y-STR match probabilities

Y-chromosomal short tandem repeat (Y-STR) markers are routinely used in forensic casework to identify male donors of biological traces left at crime scenes, particularly in sexual assault cases. However, the evidential value of a match between the Y-STR profile of a trace and a potential donor, usually a crime suspect, is difficult to quantify, and the common albeit inappropriate practise to equate Y-STR match probabilities with Y-STR profile frequencies estimated from population databases has been subject to scientific debate for decades. As a solution to this long-standing problem, we suggest an alternative approach to the calculation of Y-STR match probabilities that involves splitting the group of potential donors other than the suspect into two: (i) his close male relatives (termed his 'pedigree') and (ii) all other males. While an upper limit to the match probability is easily calculated for the second group, it is computationally challenging to derive for the first. We therefore developed a mathematical framework that uses importance sampling to reconstruct and evaluate the Y-STR profiles of untyped members of the suspect's pedigree by way of simulation. Extensive testing with elementary pedigrees of different structure and complexity confirmed that both, the framework and its Python-based software implementation yield match probability estimates that approximate well the correct analytical results, depending upon the number of simulations performed. Our methodology thus facilitates a more appropriate and valid solution to the long-standing problem of interpreting Y-STR profile matches in forensic casework.

Impact of theta correction in siblingship testing

Genetic relationship testing is dependent on appropriate population data, for which there has been a considerable amount of effort invested over the past three decades. This can be evidenced by the large number of population genetic studies that have presented short tandem repeat (STR) data for a wide range of population groups worldwide. However, comparatively little effort has been invested in the measurement of population substructure at various geographical levels and in the investigation of its effect on genetic relationship testing. The concept of population substructure is utilized as a proxy for co-ancestry in kinship calculations and is often corrected for by introducing the co-ancestry coefficient theta (θ). In practice, it is frequently assessed at the national level or for entire subpopulations. However, infrastructure, geographic and sociocultural factors have the potential to significantly impact the estimation of co-ancestry at the local level, leading to larger population substructure in smaller local communities, which may not be adequately addressed by large-scale population studies. Consequently, it can be challenging to accurately estimate the appropriate degree of co-ancestry for a specific genetic relationship testing case. In contrast to the calculations of DNA match probabilities in forensics, there is no conservative approach to account for this uncertainty in genetic kinship testing. In the present paper, we demonstrate that the incorrect choice of the theta correction factor for co-ancestry can have a substantial impact on the outcome of the calculations and therefore potentially on the life of the concerned individuals. The findings of this study have been used to formulate recommendations for the communication of results, with a particular focus on cases where private individuals are involved in administrative or legal proceedings facing state authorities, such as immigration cases.

X-chromosomal STRs: Metapopulations and mutation rates

The analysis of STRs located on the X chromosome has been one of the strategies used to address complex kinship cases. Its usefulness is, however, limited by the low availability of population haplotype frequency data and lack of knowledge on the probability of mutations. Due to the large amount of data required to obtain reliable estimates, it is important to investigate the possibility of grouping data from populations with similar profiles when calculating these parameters. To better understand the partition of genetic diversity among human populations for the X-STRs most used in forensics, an analysis was carried out based on data available in the literature and new data (23,949 haplotypes in total; from these 10,445 new) obtained through collaborative exercises within the Spanish and Portuguese Working Group of the International Society for Forensic Genetics. Based on the available population data, a similarity in X-STR profiles was found in European populations, and in East Asian populations, except for some isolates. A greater complexity was found for African, South American, and South and Southeast Asian populations, preventing their grouping into large metapopulations. New segregation data on 2273 father/mother/daughter trios were also obtained, aiming for a more thorough analysis of X-STR mutation rates. After combining our data with published information on father/mother/daughter trios, no mutations were detected in 13 out of 37 loci analyzed. For the remaining loci, mutation rates varied between 2.68 × 10-4 (DXS7133) and 1.07x10-2 (DXS10135), being 5.2 times higher in the male (4.16 ×10-3) than in the female (8.01 ×10-4) germline.

Relevant propositions for Y chromosome interpretation

The Y chromosomal haplotype is expected to be identical (or close to, depending on the mutation rate) among a male and many of his paternal relatives. This means that often the same evidential value for the DNA evidence is obtained, whether the true donor or one of his close paternal relatives is compared to a crime sample. Commentators (see for example the UK Forensic Science Regulator or Amorim) have suggested to change the proposition pair to compare the probability of the evidence if the Person of Interest (POI) or one of his close paternal relatives left the DNA to the probability of the evidence if an unrelated male from the population left the DNA. We argue that this is problematic because there is no clear definition of close paternal relatives and truly unrelated males do not exist. Instead, we take a starting point in the traditional proposition pair "The source of the male DNA is the POI" versus "The source of the male DNA is not the POI" and make the latter one operational by suggesting that it is formulated as "The source of the male DNA is a random man from the population". The issue of matching males in the POI's lineage is then addressed either in a comment in the statement or directly through a probability model.

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.

Complete Mitochondrial DNA Genome Variation in the Swedish Population

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.

Extending the discrete Laplace method: incorporating multi-copy loci, partial repeats and null alleles

The discrete Laplace method can be used to estimate the frequency of a Y-chromosomal STR haplotype using a random sample from the population. Two limitations of the method are the assumptions that each profile has exactly one allele at every locus and that this allele has an integer repeat number. We relax these assumptions to allow for multi-copy loci, partial repeats and null alleles. We show how the parameters to the extension of the model can be estimated by numerical optimisation using an off-the-shelf solver. Concordance with the discrete Laplace method is obtained when the data satisfy the more stringent assumptions of the original method. We also investigate the performance of the (extended) discrete Laplace method when used to assign match probabilities for haplotypes. A simulation study shows that as more loci are used, match probabilities are underestimated more severely. This is consistent with the hypothesis that the discrete Laplace method cannot model the matches that arise by being identical by descent (IBD). As the number of loci increases the fraction of matches that are IBD increases. Simulation provides support that the discrete Laplace can model those matches that arise from identity by state (IBS) only.

Weight of evidence of Y-STR matches computed with the discrete Laplace method: Impact of adding a suspect's profile to a reference database

The discrete Laplace method is recommended by multiple parties (including the International Society for Forensic Genetics, ISFG) to estimate the weight of evidence in criminal cases when a suspect's Y-STR profile matches the crime scene Y-STR profile. Unfortunately, modelling the distribution of Y-STR profiles in the population reference database is time-consuming and requires expert knowledge. When the suspect's Y-STR profile is added to the database, as would be the protocol in many cases, the parameters of the discrete Laplace model must be re-estimated. We found that the likelihood ratios with and without adding the suspect's Y-STR profile were almost identical with 1,000 or more Y-STR profiles in the database for Y-STR profiles with 8, 12, and 17 loci. Thus, likelihood ratio calculations can be performed in seconds if an established discrete Laplace model based on at least 1,000 Y-STR profiles is used. A match in a population reference database with 17 Y-STR loci from at least 1,000 male individuals results in a likelihood ratio above 10,000 in approximately 94% of the cases, and above 100,000 in approximately 82% of the cases. We offer free software accessible without restrictions to estimate a discrete Laplace model using a Y-STR reference database and subsequently to calculate likelihood ratios.

Recent advances in forensic biology and forensic DNA typing: INTERPOL review 2019-2022

This review paper covers the forensic-relevant literature in biological sciences from 2019 to 2022 as a part of the 20th INTERPOL International Forensic Science Managers Symposium. Topics reviewed include rapid DNA testing, using law enforcement DNA databases plus investigative genetic genealogy DNA databases along with privacy/ethical issues, forensic biology and body fluid identification, DNA extraction and typing methods, mixture interpretation involving probabilistic genotyping software (PGS), DNA transfer and activity-level evaluations, next-generation sequencing (NGS), DNA phenotyping, lineage markers (Y-chromosome, mitochondrial DNA, X-chromosome), new markers and approaches (microhaplotypes, proteomics, and microbial DNA), kinship analysis and human identification with disaster victim identification (DVI), and non-human DNA testing including wildlife forensics. Available books and review articles are summarized as well as 70 guidance documents to assist in quality control that were published in the past three years by various groups within the United States and around the world.

On the Forensic Use of Y-Chromosome Polymorphisms

Nowadays, the use of Y-chromosome polymorphisms forms an essential part of many forensic DNA investigations. However, this was not always the case. Only since 1992 have we seen that some forensic scientists started to have an interest in this chromosome. In this review, I will sketch a brief history focusing on the forensic use of Y-chromosome polymorphisms. Before describing the various applications of short-tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) on the Y-chromosome, I will discuss a few often ignored aspects influencing proper use and interpretation of Y-chromosome information: (i) genotyping Y-SNPs and Y-STRs, (ii) Y-STR haplotypes shared identical by state (IBS) or identical by descent (IBD), and (iii) Y-haplotype database frequencies.