A general model for likelihood computations of genetic marker data accounting for linkage, linkage disequilibrium, and mutations

Determining the effects of genetic linkage when using a combination of STR and SNP loci for kinship testing

The pedigree likelihood ratio (LR) can be used for determining kinship in the forensic kinship testing. LR can be obtained by analyzing the DNA data of Short tandem repeat (STR) and single nucleotide polymorphism (SNP) loci. With the advancement of biotechnology, increasing number of genetic markers have been identified, thereby expanding the pedigree range of kinship testing. Moreover, some of the loci are physically closer to each other and genetic linkage between loci is inevitable. LRs can be calculated by accounting for linkage or ignoring linkage (LRlinkage and LRignore, respectively). GeneVisa is a software for kinship testing (www.genevisa.net) and adopts the Lander-Green algorithm to deal with genetic linkage. Herein, we used the simulation program of the software GeneVisa to investigate the effects of genetic linkage on 1st-degree, 2nd-degree, and 3rd-degree kinship testing. We used this software to simulate LRlinkage and LRignore values based on 43 STRs and 134 SNPs in commercial kits by using the allele frequency rate and genetic distance data of the European population. The effects of linkage on LR distribution and LRs of routine cases were investigated by comparing the LRlinkage values with the LRignore values. Our results revealed that the linkage effect on LR distributions is small, but the effect on LRs of routine cases may be large. Moreover, the results indicated that the discriminatory power of genetic markers for kinship testing can be improved by accounting for linkage.

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices.

Pedigree likelihood formulae based on founder and founder couple symmetry and validation of DNA testing software

Pedigree likelihood ratios are widely used in forensic genetics. Linkage of genetic markers affects the pedigree likelihood ratio. In this study, a series of novel formulae was established based on simplification due to founder and founder couple symmetry of the Lander-Green algorithm for dealing with linkage. These new formulae are based on the inheritance vectors and differ from existing formulae that are based on the number of alleles shared identical-by-descent. In contrast to previous formulae, the formulae of this study expand the calculation to more general relationships, which enables specifying the number of typed individuals in pedigrees, and the new formulae are no longer limited to calculation of pairs of linked markers. Alternatively, pedigree likelihood values incorporating multiple linked markers could be obtained by iterating the vector transition probability between pairs of linkage markers and the probability of genotypes of typed individuals given inheritance vectors; the vector transition probability formulae are provided in a table form. To demonstrate utilization of the proposed formulae system, a series of cases were designed based on the relationships to validate GeneVisa software (www.genevisa.net) with frequency data of three linked markers, SE33-D6S1043-D6S474, on chromosome 6. The calculation results were verified with the FamLink software. The results demonstrated that the proposed formulae can correctly obtain the pedigree likelihood ratio, demonstrating the application potential of these formulae to verify effectiveness of DNA testing software.

Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers

The inference of ancestry has become a part of the services many forensic genetic laboratories provide. Interest in ancestry may be to provide investigative leads or identify the region of origin in cases of unidentified missing persons. There exist many biostatistical methods developed for the study of population structure in the area of population genetics. However, the challenges and questions are slightly different in the context of forensic genetics, where the origin of a specific sample is of interest compared to the understanding of population histories and genealogies. In this paper, the methodologies for modelling population admixture and inferring ancestral populations are reviewed with a focus on their strengths and weaknesses in relation to ancestry inference in the forensic context.

A reference database of forensic autosomal and gonosomal STR markers in the Tigray population of Ethiopia

Allele frequencies of 21 autosomal STR markers (AmpF/STR GlobalFiler) and haplotype frequencies of 27 Y- and 12 X-STR markers (AmpF/STR YFiler Plus and Investigator Argus X-12, respectively) were investigated in the Tigray population of Ethiopia, representing the main population group in the Tigray regional state of Ethiopia and neighboring Eritrea. For autosomal STR allele frequencies, the average random match probability in the Tigray sample was 2.1 × 10^-27. The average locus by locus F_ST distance calculated comparing autosomal STR allele frequencies from Tigray and from a broad regional reference dataset currently available for the Horn of Africa was 0.003. The Tigray male sample displayed high Y-STR diversity, with complete individualization of haplotypes using the AmpF/STR YFiler Plus panel. Analysis of molecular variance did not detect significant heterogeneity between Y-STR haplotypes observed in the present study and those previously reported in the literature for other Tigray population samples from Ethiopia and Eritrea. Study of the X-STR landscape in Tigray evidenced several distinctive features including: the molecular characterization of a novel null allele at locus DXS10146 with frequency > 1%; allele dependency between loci within linkage groups I and III; significant differences in haplotype distribution compared to other Horn of Africa populations, that should be taken into account in kinship analysis. The collected data can be used as a reference STR database by local forensic genetics services and in genetic identification procedures of victims of human trafficking in the Mediterranean Sea, which frequently involve individuals originating from the Horn of Africa.

Strategies for pairwise searches in forensic kinship analysis

Testing kinship between pairs of individuals is central to a wide range of applications. We focus on cases where many tests are done jointly. Typical examples include cases where DNA profiles are available from a burial site, a plane crash or a database of convicted offenders. The task is to determine the relationships between DNA profiles or individuals. Our approach generalises previous methods and implementations in several respects. We model general, possibly inbred, pairwise relationships which is important for non-human applications and in archaeological studies of ancient inbred populations. Furthermore, we do not restrict attention to autosomal markers. Some cases, such as distinguishing between maternal and paternal half siblings, can be solved using X-chromosomal markers. When many tests are done, the risk of errors increases. We address this problem by building on the theory of multiple testing and show how optimal thresholds for tests can be determined. We point out that the likelihood ratios in a blind search may be dependent so multiple testing methods and interpretation need to account for this. In addition, we show how a Bayesian approach can be helpful. Our examples, using simulated and real data, demonstrate the practical importance of the methods and implementation is based on freely available software.

Evaluating DNA evidence possibly involving multiple (mixed) samples, common donors and related contributors

Forensic DNA profiling is used in various circumstances to evaluate support for two competing propositions with the assignment of a likelihood ratio. Many software implementations exist that tackle a range of inference problems spanning identification and relationship testing. We propose a flexible likelihood ratio framework that caters to inference problems in forensic genetics. The framework allows for investigation of the degree of support for the contribution of multiple persons to multiple samples allowing for persons to be related according to a pedigree, including inbred relationships. We explain how a number of routine as well as more complex problems can be treated within this framework.

A likelihood ratio approach for identifying three-quarter siblings in genetic databases

The detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent-offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent-grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

Evaluation of a custom GeneRead™ massively parallel sequencing assay with 210 ancestry informative SNPs using the Ion S5™ and MiSeq platforms

A custom GeneRead DNAseq SNP panel with 210 markers was evaluated using the Ion S5 and MiSeq sequencing platforms. Sensitivity, PCR cycle number, and the use of half volume of reagents for target enrichment and library preparation were tested. Furthermore, genotype concordance between results obtained with the different sequencing platforms and with known profiles generated using other sequencing assays was analysed. The GeneRead DNASeq SNP assay gave reproducible results with an input of 200 pg DNA on both platforms. A total of 204 loci were successfully sequenced. Three loci failed completely in the PCR amplification, and three additional loci displayed frequent locus drop-outs due to low read depth or high heterozygote imbalance. Overall, the read depth across the loci was more well-balanced with the MiSeq, while the heterozygote balance was less variable with the Ion S5. Noise levels were low on both platforms (median< 0.2 %). Two simple criteria for genotyping were applied: A minimum threshold of 45 reads and an acceptable heterozygote balance range of 0.3-3.0. Complete concordance between platforms was observed except for three genotypes in one of the poorly performing loci, rs1470637. This locus had relatively low read depths on both platforms, skewed heterozygote balance, and frequent locus drop-outs. There was also full genotype concordance between the results from the GeneRead assay and known profiles generated with the QIAseq and Ion AmpliSeq assays. The few discordant results were either due to locus drop-outs in the poorly performing loci or allele drop-outs in the QIAseq assay. Profiles with a minimum of 179 SNPs were obtained from four challenging case work samples (blood swabs, bone, or blood from a corpse). Overall, the GeneRead DNASeq assay showed considerable potential and could provide a reliable method for SNP genotyping in cases involving identification of individuals, prediction of phenotypic traits, and ancestry inference.

Twenty Years Later: A Comprehensive Review of the X Chromosome Use in Forensic Genetics

The unique structure of the X chromosome shaped by evolution has led to the present gender-specific genetic differences, which are not shared by its counterpart, the Y chromosome, and neither by the autosomes. In males, recombination between the X and Y chromosomes is limited to the pseudoautosomal regions, PAR1 and PAR2; therefore, in males, the X chromosome is (almost) entirely transmitted to female offspring. On the other hand, the X chromosome is present in females with two copies that recombine along the whole chromosome during female meiosis and that is transmitted to both female and male descendants. These transmission characteristics, besides the obvious clinical impact (sex chromosome aneuploidies are extremely frequent), make the X chromosome an irreplaceable genetic tool for population genetic-based studies as well as for kinship and forensic investigations. In the early 2000s, the number of publications using X-chromosomal polymorphisms in forensic and population genetic applications increased steadily. However, nearly 20 years later, we observe a conspicuous decrease in the rate of these publications. In light of this observation, the main aim of this article is to provide a comprehensive review of the advances and applications of X-chromosomal markers in population and forensic genetics over the last two decades. The foremost relevant topics are addressed as: (i) developments concerning the number and types of markers available, with special emphasis on short tandem repeat (STR) polymorphisms (STR nomenclatures and practical concerns); (ii) overview of worldwide population (frequency) data; (iii) the use of X-chromosomal markers in (complex) kinship testing and the forensic statistical evaluation of evidence; (iv) segregation and mutation studies; and (v) current weaknesses and future prospects.

Paternal and maternal mutations in X-STRs: A GHEP-ISFG collaborative study

The GHEP-ISFG organized a collaborative study to estimate mutation rates for the markers included in the Investigator Argus X-12 QS kit Qiagen. A total of 16 laboratories gathered data from 1,612 father/mother/daughter trios, which were used to estimate both maternal and paternal mutation rates, when pooled together with other already published data. Data on fathers and mothers' age at the time of birth of the daughter were also available for ∼93 % of the cases. Population analyses were computed considering the genetic information of a subset of 1,327 unrelated daughters, corresponding to 2,654 haplotypes from residents in several regions of five countries: Argentina, Brazil, Ecuador, Portugal and Spain. Genetic differentiation analyses between the population samples from the same country did not reveal signs of significant stratification, although results from Hardy-Weinberg and linkage disequilibrium tests indicated the need of larger studies for Ecuador and Brazilian populations. The high genetic diversity of the markers resulted in a large number of haplotype combinations, showing the need of huge databases for reliable estimates of their frequencies. It should also be noted the high number of new alleles found, many of them not included in the allelic ladders provided with the kit, as very diverse populations were analyzed. The overall estimates for locus specific average mutation rates varied between 7.5E-04 (for DXS7423) and 1.1E-02 (for DXS10135), the latter being a troublesome figure for kinship analyses. Most of the found mutations (∼92 %) are compatible with the gain or loss of a single repeat. Paternal mutation rates showed to be 5.2 times higher than maternal ones. We also found that older fathers were more prone to transmit mutated alleles, having this trend not been observed in the case of the mothers.

Genetic variation of 17 X-chromosome STR loci in Tunisian population of Nabeul

In the present study, the genetic variations of 17 X-STR markers (DXS8378, DXS9898, DXS7133, GATA31E08, GATA172D05, DXS6801, DXS7423, DXS6809, DXS6799, DXS7132, DXS9902, DXS6800, DXS6789, DXS10075, DXS10079, DXS6807, and DXS6803) were analyzed in 139 unrelated individuals in Nabeul, aiming to perform an X-STR database for anthropological and forensic purposes. Our results indicate that DXS6809 was the most polymorphic locus, whereas DXS6807 was the least informative marker. In addition, the obtained values for the statistical parameters of forensic interest, i.e., the power of discrimination in males (PD_M) and females (PD_F), as well as the mean exclusion chance in duos (MEC_D) and trios (MEC_T) have demonstrated that this panel of 17 X-STRs is highly informative and useful for forensic application and anthropological research. Additionally, pairwise genetic distances based on F_ST were calculated between Nabeul population and other populations extracted from the literature. Genetic distances were represented in a non-metric MDS plot and clustering of populations according to their geographic locations and their historical relationship was detected.

DNA Commission of the International Society for Forensic Genetics (ISFG): Guidelines on the use of X-STRs in kinship analysis

Forensic genetic laboratories perform an increasing amount of genetic analyses of the X chromosome, in particular to solve complex cases of kinship analysis. For some biological relationships X-chromosomal markers can be more informative than autosomal markers, and there are a large number of markers, methods and databases that have been described for forensic use. Due to their particular mode of inheritance, and their physical location on a single chromosome, some specific considerations are required when estimating the weight of evidence for X-chromosomal marker DNA data. The DNA Commission of the International Society for Forensic Genetics (ISFG) hereby presents guidelines and recommendations for the use of X-chromosomal markers in kinship analysis with a special focus on the biostatistical evaluation. Linkage and linkage disequilibrium (association of alleles) are of special importance for such evaluations and these concepts and the implications for likelihood calculations are described in more detail. Furthermore it is important to use appropriate computer software that accounts for linkage and linkage disequilibrium among loci, as well as for mutations. Even though some software exist, there is still a need for further improvement of dedicated software.

Combined effects of multiple linked loci on pairwise sibling tests

The advanced multiplex STR system, PowerPlex Fusion, includes four linked locus pairs. The conventional Identifiler system has one pair of linked loci. Therefore, sibling tests conducted using the advanced system might be more affected by linkage than those conducted using the conventional system. This study simulated single and combined effects of the four linked locus pairs on pairwise sibling tests. Simulated genotypes of 100,000 pairs of full siblings and nonrelatives were constructed according to allele frequencies of the Japanese population. The single linkage effect was evaluated for simulated genotype data by calculating both the likelihood ratio accounting for the linkage between two loci and the likelihood ratio ignoring the linkage. The combined effect was obtained by multiplication of the respective single effects. Furthermore, we investigated the possibility that ignoring the linkage affects subject classification by introducing a scale of the likelihood ratio into sibling tests. The single effect in the Identifiler analysis was 0.645-1.746 times if the linkage was ignored. Overestimations and underestimations were predictable from the identical-by-state status at two linked loci. The combined effect in the PowerPlex Fusion analysis was 0.217-7.390 times. Ignoring the linkage rarely caused a false conclusive or inconclusive result, even from PowerPlex Fusion analysis. Application of the advanced system improved sibling tests considerably. The additional examined loci were more beneficial than the adverse effect of the linkage derived from the four linked locus pairs.

Evaluation of the impact of genetic linkage in forensic identity and relationship testing for expanded DNA marker sets

Advances in massively parallel sequencing technology have enabled the combination of a much-expanded number of DNA markers (notably STRs and SNPs in one or combined multiplexes), with the aim of increasing the weight of evidence in forensic casework. However, when data from multiple loci on the same chromosome are used, genetic linkage can affect the final likelihood calculation. In order to study the effect of linkage for different sets of markers we developed the biostatistical tool ILIR, (Impact of Linkage on forensic markers for Identity and Relationship tests). The ILIR tool can be used to study the overall impact of genetic linkage for an arbitrary set of markers used in forensic testing. Application of ILIR can be useful during marker selection and design of new marker panels, as well as being highly relevant for existing marker sets as a way to properly evaluate the effects of linkage on a case-by-case basis. ILIR, implemented via the open source platform R, includes variation and genomic position reference data for over 40 STRs and 140 SNPs, combined with the ability to include additional forensic markers of interest. The use of the software is demonstrated with examples from several different established marker sets (such as the expanded CODIS core loci) including a review of the interpretation of linked genetic data.