A genotype likelihood function for DNA mixtures

The recent advent of genetic genealogy has brought about a renewed interest in genome-scale forensic analyses, of which kinship estimation is a critical component. Most genomic kinship estimators consider SNPs (single nucleotide polymorphisms), often leveraging the co-inheritance of shared alleles to inform their analyses. While current estimators cannot directly evaluate mixed samples, there exist well-established SNP-based kinship estimators tailored to considering challenged samples, including low-pass whole genome sequencing. As an example, several studies have shown remarkable success in imputing genotype posterior probabilities in low template samples when linked sites are considered. Critical to these approaches is the ability to account for genotype uncertainty; the lack of an expression for a genotype likelihood in imbalanced mixtures has prevented direct application. This work develops such an expression. The formulation is fully compatible with genotype imputation software, suggesting a genomic pipeline that estimates genotype likelihoods, performs imputation, and then estimates kinship when the sample is a mixture. Further, when framed as an imbalanced mixture, the problem of mixture deconvolution is reducible to the problem of genotyping mixed samples. Herein, the ability to genotype two-person mixtures is assessed through example and in silico settings. While certain mixture scenarios and classes of sites are inherently inseparable, simulations of read depths between 60 and 190 appear to produce likelihoods of sufficient magnitude to deconvolve two-person mixtures whenever the mixture fraction is moderately imbalanced. The described approach and results suggest a path forward for estimating the kinship coefficient (and similar inferences on relatedness) when the sample is a mixture.     

Fast and accurate kinship estimation using sparse SNPs in relatively large database searches

Forensic genetic genealogy (FGG) has primarily relied upon dense single nucleotide polymorphism (SNP) profiles from forensic samples or unidentified human remains queried against online genealogy database(s) of known profiles generated with SNP microarrays or from whole genome sequencing (WGS). In these queries, SNPs are compared to database samples by locating contiguous stretches of shared SNP alleles that allow for detection of genomic segments that are identical by descent (IBD) among biological relatives (kinship). This segment-based approach, while robust for detecting distant relationships, generally requires DNA quantity and/or quality that are sometimes not available in forensic casework samples. By focusing on SNPs with maximal discriminatory power and using an algorithm designed for a sparser SNP set than those from microarray typing, performance similar to segment matching was reached even in difficult casework samples. This algorithm locates shared segments using kinship coefficients in “windows” across the genome. The windowed kinship algorithm is a modification of the PC-AiR and PC-Relate tools for genetic relatedness inference, referred to here as the “whole genome kinship” approach, that control for the presence of unknown or unspecified population substructure. Simulated and empirical data in this study, using DNA profiles comprised of 10,230 SNPs (10K multiplex) targeted by the ForenSeq™ Kintelligence Kit demonstrate that the windowed kinship approach performs comparably to segment matching for identifying first, second and third degree relationships, reasonably well for fourth degree relationships, and with fewer false kinship associations. Selection criteria for the 10K SNP PCR-based multiplex and functionality of the windowed kinship algorithm are described.     

Effects of DNA degradation and genotype imputation on high-density SNP microarray in pairwise kinship analysis

High-density single nucleotide polymorphisms (SNPs) can detect distant relatives even in the context of pairwise kinship analysis. Although DNA microarrays conveniently generate genome-wide SNP data, they require large quantities of high-quality DNA. Genotyping data obtained from low-quantity and low-quality samples are likely unreliable owing to the incidence of no-called or mistyped SNPs. In this study, we examined the effects of insufficient sample densities and sample degradation on the efficacy of kinship analysis. While low DNA amounts had a minor effect, DNA degradation led to a significant increase in no-call rates and error rates. Posterior probabilities of kinship determination, calculated using the index of chromosomal sharing, were markedly lower in proportion to the no-call rates and error rates. We also investigated the effect of genotype imputation to complement the no-called genome data utilizing SNPs reference panels. We found that the posterior probability of the relative-assumed person increased with genotype complementation in case of mild degradation, even with mistyped genotypes. Therefore, DNA microarray with imputation is a promising method for analyzing forensic DNA samples taken from situations where DNA quantity and quality may be compromised, such as disaster victim identification using pairwise kinship analysis.     

Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences

Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.     

Current next generation sequencing technology may not meet forensic standards

In a Nature paper of 2010, the concern was raised that intra-individual mtDNA variation may be more pronounced than previously believed, in that heteroplasmies are common and vary markedly from tissue to tissue. This claim taken at face value would have considerable impact on forensic casework. It turns out however that the employed technology detected the germ-line variation relative to the reference sequence only incompletely: on average at least five mutations were missed per sample, as an in silico reassessment of the data reveals. Before one can really set out to access to entire mtDNA genome data with relative ease for forensic purposes, one needs careful calibration studies under strict forensic conditions-or might have to wait for another generation.     

Mitochondrial DNA heteroplasmy in the emerging field of massively parallel sequencing

Long an important and useful tool in forensic genetic investigations, mitochondrial DNA (mtDNA) typing continues to mature. Research in the last few years has demonstrated both that data from the entire molecule will have practical benefits in forensic DNA casework, and that massively parallel sequencing (MPS) methods will make full mitochondrial genome (mtGenome) sequencing of forensic specimens feasible and cost-effective. A spate of recent studies has employed these new technologies to assess intraindividual mtDNA variation. However, in several instances, contamination and other sources of mixed mtDNA data have been erroneously identified as heteroplasmy. Well vetted mtGenome datasets based on both Sanger and MPS sequences have found authentic point heteroplasmy in approximately 25% of individuals when minor component detection thresholds are in the range of 10–20%, along with positional distribution patterns in the coding region that differ from patterns of point heteroplasmy in the well-studied control region. A few recent studies that examined very low-level heteroplasmy are concordant with these observations when the data are examined at a common level of resolution. In this review we provide an overview of considerations related to the use of MPS technologies to detect mtDNA heteroplasmy. In addition, we examine published reports on point heteroplasmy to characterize features of the data that will assist in the evaluation of future mtGenome data developed by any typing method.     

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person’s relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log₁₀LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.     

Development and assessment of an optimized next-generation DNA sequencing approach for the mtgenome using the Illumina MiSeq

The development of molecular tools to detect and report mitochondrial DNA (mtDNA) heteroplasmy will increase the discrimination potential of the testing method when applied to forensic cases. The inherent limitations of the current state-of-the-art, Sanger-based sequencing, including constrictions in speed, throughput, and resolution, have hindered progress in this area. With the advent of next-generation sequencing (NGS) approaches, it is now possible to clearly identify heteroplasmic variants, and at a much lower level than previously possible. However, in order to bring these approaches into forensic laboratories and subsequently as accepted scientific information in a court of law, validated methods will be required to produce and analyze NGS data. We report here on the development of an optimized approach to NGS analysis for the mtDNA genome (mtgenome) using the Illumina MiSeq instrument. This optimized protocol allows for the production of more than 5 gigabases of mtDNA sequence per run, sufficient for detection and reliable reporting of minor heteroplasmic variants down to approximately 0.5–1.0% when multiplexing twelve samples. Depending on sample throughput needs, sequence coverage rates can be set at various levels, but were optimized here for at least 5000 reads. In addition, analysis parameters are provided for a commercially available software package that identify the highest quality sequencing reads and effectively filter out sequencing-based noise. With this method it will be possible to measure the rates of low-level heteroplasmy across the mtgenome, evaluate the transmission of heteroplasmy between the generations of maternal lineages, and assess the drift of variant sequences between different tissue types within an individual.     

Techniques for estimating genetically variable peptides and semi-continuous likelihoods from massively parallel sequencing data

Forensic genetic investigations typically rely on analysis of DNA for attribution purposes. There are times, however, when the amount and/or the quality of the DNA is limited, and thus little or no information can be obtained regarding the source of the sample. An alternative biochemical target that also contains genetic signatures is protein. One class of genetic signatures is protein polymorphisms that are a direct consequence of simple/single/short nucleotide polymorphisms (SNPs) in DNA. However, to interpret protein polymorphisms in a forensic context, certain complexities must be understood and addressed. These complexities include: 1) SNPs can generate 0, 1, or arbitrarily many polymorphisms in a polypeptide; and 2) as an object of expression that is modulated by alleles, genes and interactions with the environment, proteins may be present or absent in a given sample. To address these issues, a novel approach was taken to generate the expected protein alleles in a reference sample based on whole genome (or exome) sequence data and assess the significance of the evidence using a haplotype-based semi-continuous likelihood algorithm that leverages whole proteome data. Converting the genomic information into the proteomic information allows for the zero-to-many relationship between SNPs and GVPs to be abstracted away. When viewed as a haplotype, many GVPs that correspond to the same SNP is equivalent to many SNPs in perfect linkage disequilibrium (LD). As long as the likelihood formulation correctly accounts for LD, the correspondence between the SNP and the proteome can be safely neglected. Tests were performed on simulated samples, including single-source and two-person mixtures, and the power of using a classical semi-continuous likelihood versus one that has been adapted to neglect drop-out was compared. Additionally, summary statistics and a rudimentary set of decision guidelines were introduced to help identify mixtures from protein data.     

Sequence diversity of the uniparentally transmitted portions of the genome in the resident population of Catalonia

Genomic reference databases of residing populations are available in different countries and regions. Since they represent the whole genetic diversity of a geographical region, they have wide applications, from biomedical studies to forensic identifications. Uniparentally transmitted portions of the genome specifically are highly suitable for kinship analyses, mixed DNA cases and geographical ancestry inferences. We have sampled 808 individuals currently residing in Catalonia within the GCAT cohort, from which we have generated 808 high-quality whole mitochondrial DNA (mtDNA) genomes and 399 sequences of the male-specific part of the Y chromosome (MSY). We observe higher genetic diversity than in classical population genetics datasets. We test the robustness of whole sequences for unequivocal identifications, and we found that they have higher resolution than mitochondrial control region and Y chromosome short tandem repeats (Y-STRs), and that most of the variants they present are at low frequencies, increasing the discrimination capacity between individuals. These results confirm the forensic applicability of whole uniparental sequences and provide one of the largest high-quality reference datasets ever published.     

Forensic identity SNPs: Characterisation of flanking region variation using massively parallel sequencing

Single nucleotide polymorphisms (SNPs) can be analysed for identity or kinship applications in forensic genetics to either provide an adjunct to traditional STR typing or as a stand-alone approach. The advent of massively parallel sequencing technology (MPS) has provided a useful opportunity to more easily deploy SNP typing in a forensic context, given the ability to simultaneously amplify a large number of markers. Furthermore, MPS also provides valuable sequence data for the targeted regions, which enables the detection of any additional variation seen in the flanking regions of amplicons. In this study we genotyped 977 samples across five UK-relevant population groups (White British, East Asian, South Asian, North-East African and West African) for 94 identity-informative SNP markers using the ForenSeq DNA Signature Prep Kit. Examination of flanking region variation allowed for the identification of 158 additional alleles across all populations studied. Here we present allele frequencies for all 94 identity-informative SNPs, both including and excluding the flanking region sequence of these markers. We also present information on the configuration of these SNPs in the ForenSeq DNA Signature Prep Kit, including performance metrics for the markers and investigation of bioinformatic and chemistry-based discordances. Overall, the inclusion of flanking region variation in the analysing workflow for these markers reduced the average combined match probability 2175 times across all populations, with a maximum reduction of 675,000-fold in the West African population. The gain due to flanking region-based discrimination increased the heterozygosity of some loci above that of some of the least useful forensic STR loci; thus demonstrating the benefit of enhanced analysis of currently targeted SNP markers for forensic applications.     

Improving the system power of complex kinship analysis by combining multiple systems

Complex kinship analysis is a critical issue in forensic genetics. To address this issue, 55 STRs and 94 SNPs collected from four commercial forensic typing kits [three kits were based on a capillary electrophoresis (CE) platform and one was based on a next-generation sequencing (NGS) platform] were employed to test the system power for 2nd-degree and 3rd-degree kinship analysis. To measure the kinship index in related individuals, likelihood ratios (LRs) were calculated based on length and sequence polymorphism information (LR_length and LR_sequence, respectively) from simulation as well as true pedigree samples. LRs calculated based on sequence information are generally higher than those based on length information. The sensitivity, specificity, and effectiveness to distinguish the 2nd- and 3rd-degree kinship were estimated from four marker sets with different numbers of markers. As expected, system power for kinship analysis improved by increasing the number of markers and using LR_sequence, instead of LR_length. Furthermore, the system power based on 55 STRs from the CE platform is equal to the 40 STRs and 94 SNPs from one CE kit and the kit based on NGS platform for both 2nd-degree and 3rd-degree kinship analysis. For discrimination of 2nd-degree kinship, the system effectiveness is 86.63% with an error ratio < 0.01 using the 55 STRs from the CE platform. Using sequence information from the 55 STRs and 94 SNPs, the system effectiveness is 94.43%, with an error ratio < 0.001 for 2nd-degree kinship analysis and 64.34% with an error ratio < 0.05 for 3rd-degree kinship analysis, indicating that these markers are powerful for 2nd-degree kinship analysis and can be used for 3rd-degree kinship analysis.     

Practical forensic use of kinship determination using high-density SNP profiling based on a microarray platform,focusing on low-quantity DNA

Instead of traditional short tandem repeat (STR) profiling, the genetic genealogy method, which uses hundreds of thousands of single nucleotide polymorphisms (SNPs) spread across genome-wide, has emerged as a powerful kinship determination tool and recently attracted great attention in forensic genetics.In this study, we explored the tolerance and viability of kinship discrimination based on a high-density SNP profile for forensic DNA, especially focusing on low-quantity DNA. Using the Affymetrix Genome-Wide Human SNP Array 6.0 platform (Thermo Fisher Scientific), the influence of low-quantity DNA on SNP genotype determination was evaluated. The low-quantity DNA samples failed once every few samples, the generated SNP profile had low data quality. Our investigation revealed that the SNP profile with low data quality contained many genotyping errors in which the SNP genotype changed from homozygote to heterozygote. The kinship discrimination analysis using KING software was directly influenced by these genotyping errors, which was confirmed that some unrelated pairs were mis-specified as 4th-degree relatives. We confirmed that the false heterozygous SNPs resulted in an inflation of kinship coefficient and a decrease of non-shared allele between a tested pair.To eliminate the influence of these genotyping errors and acquire an accurate kinship discrimination result, we developed a novel method to select only the robust SNPs, which stably give the genotype determination with high accuracy even in SNP profiles with low data quality. The application of our novel method led to the improved results of kinship discrimination up to the same level as in the SNP profile with high data quality.In addition, this study demonstrated the advantage of kinship analysis using a high-density SNP profile in the forensic field. It is well known that likelihood ratio calculation based on autosomal STR profile, which is the most commonly applied approach, has difficulty in gaining true kinship analysis results, especially when the relationship between the tested two individuals is more biologically distant. We showed the kinship discrimination analysis with a high-density SNP profile is more suitable for the case without close relatives, using the real case data. Although further study with larger samples will be necessary, this study indicated that practical forensic use of kinship determination with a high-density SNP profile would bring benefits to the forensic field.     

An overview of SNP-SNP microhaplotypes in the 26 populations of the 1000 Genomes Project

Microhaplotypes (MHs) are a promising new type of forensic markers that are defined by the combinations of two- or more single-nucleotide polymorphisms (SNPs) within 200 bp. Their advantages, such as low mutation rates, lack of stutter artifacts, and short amplicons, have improved human identification, kinship analysis, ancestry prediction, and mixture deconvolution capabilities. Information on published MHs, e.g., allele frequencies, is available in widely used public databases, ALlele FREquency Database, and MicroHapDB. However, there are abundant non-published MHs spread over the whole genome, and those databases do not incorporate other databases (e.g., the SNP Database) to provide users with more integrated information. Therefore, it is essential to establish a robust, responsive, and comprehensive MHs database. In this study, we thoroughly screened for SNP-SNP MHs among 26 populations from the 1000 Genomes Project (Phase 3). All genotype data of SNPs in each MH were converted to PHASE input files, and allele frequencies were estimated using PHASE. We compiled a detailed summary of SNP-SNPs at the global, continental, and population levels focused on haplotypes and the A_e value and supplemented our database using dbSNP data (last updated in 2015). We have successfully established a dual-SNP MH database (D-SNPsDB) of MHs within 50 bp for 26 populations in the integration of basic data such as physical positions in the human genome, mapping of variant identifiers (rsIDs), allele frequencies, and basic variant information. For public database queries, the D-SNPsDB web app was developed with the R Shiny package to get integrated information.

     

Development and evaluation of a novel panel containing 188 microhaplotypes for 2nd-degree kinship testing in the Hebei Han population

Distant kinship identification is one of the critical problems in forensic genetics. As a new type of genetic marker defined and discussed in the last decade, the microhaplotype (MH) has drawn much attention in such identification owing to its specific advantages to traditional short tandem repeat (STR) or single nucleotide polymorphism (SNP) markers. In this study, MH markers were screened step by step from the 1000 Genomes Project database, and a novel multiplex panel containing 188 MHs (in which 181 are reported the first time, while 1 was reported in a previous study and the other 6 have partial overlaps with known markers) was constructed for application in 2nd- and 3rd-degree kinship identification. Along with the construction, a novel MH nomenclature was proposed, in which the SNP position information they contained was taken into account to eliminate the possibility that the same locus was named differently interlaboratory. After a series of evaluations, the panel was shown to have good sequencing accuracy, high sensitivity, species specificity, and resistance to anti-PCR inhibitors or degradation. Population data of the 188 MHs were calculated based on the genetic information of 221 unrelated Hebei Han individuals, and the effective number of alleles (Ae) ranged from 2.0925 to 8.2634 (with an average of 2.9267). For the whole system, the cumulative matching probability (CMP), the cumulative power of exclusion in paternity testing of duos (CPEduo) and that of trios (CPEtrio) reached 2.8422 × 10⁻¹³⁷, 1–1.3109 × 10⁻²¹, and 1–2.8975 × 10⁻³⁹, respectively, indicating that this panel was satisfactory for individual identification and paternity testing. Then, the efficiency of the 188 MHs in 2nd- and 3rd-degree kinship testing was studied based on 30 extended families consisting of 179 2nd-degree and 121 3rd-degree relatives, as well as simulations of 0.5 million pairs of those two kinships. The results showed that clear opinions would be given in 83.36% of 2nd-degree identifications with a false rate less than 10⁻⁵, when the confirming and excluding thresholds of cumulative likelihood ratio (CLR) were set as 10⁴ and 10⁻⁴, respectively. This panel is still not sufficient to solve the problem of 3rd-degree kinship identification alone, and approximately 300 or 870 MH loci would be needed in 2nd- or 3rd-degree kinship identification, respectively, to achieve a system efficiency not less than 0.99 with such a threshold set; such necessary numbers would be used only as a reference in further research.     

STRait Razor: A length-based forensic STR allele-calling tool for use with second generation sequencing data

Recent studies have demonstrated the capability of second generation sequencing (SGS) to provide coverage of short tandem repeats (STRs) found within the human genome. However, there are relatively few bioinformatic software packages capable of detecting these markers in the raw sequence data. The extant STR-calling tools are sophisticated, but are not always applicable to the analysis of the STR loci commonly used in forensic analyses. STRait Razor is a newly developed Perl-based software tool that runs on the Linux/Unix operating system and is designed to detect forensically-relevant STR alleles in FASTQ sequence data, based on allelic length. It is capable of analyzing STR loci with repeat motifs ranging from simple to complex without the need for extensive allelic sequence data. STRait Razor is designed to interpret both single-end and paired-end data and relies on intelligent parallel processing to reduce analysis time. Users are presented with a number of customization options, including variable mismatch detection parameters, as well as the ability to easily allow for the detection of alleles at new loci. In its current state, the software detects alleles for 44 autosomal and Y-chromosome STR loci. The study described herein demonstrates that STRait Razor is capable of detecting STR alleles in data generated by multiple library preparation methods and two Illumina^® sequencing instruments, with 100% concordance. The data also reveal noteworthy concepts related to the effect of different preparation chemistries and sequencing parameters on the bioinformatic detection of STR alleles.     

A performance evaluation of Nextera XT and KAPA HyperPlus for rapid Illumina library preparation of long-range mitogenome amplicons

Next-generation sequencing (NGS) facilitates the rapid and high-throughput generation of human mitochondrial genome (mitogenome) data to build population and reference databases for forensic comparisons. To this end, long-range amplification provides an effective method of target enrichment that is amenable to library preparation assays employing DNA fragmentation. This study compared the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA) and the KAPA HyperPlus Library Preparation Kit (Kapa Biosystems, Wilmington, MA) for enzymatic fragmentation and indexing of ∼8500 bp mitogenome amplicons for Illumina sequencing. The Nextera XT libraries produced low-coverage regions that were consistent across all samples, while the HyperPlus libraries resulted in uniformly high coverage across the mitogenome, even with reduced-volume reaction conditions. The balanced coverage observed from KAPA HyperPlus libraries enables not only low-level variant calling across the mitogenome but also increased sample multiplexing for greater processing efficiency.     

Concordance and reproducibility of a next generation mtGenome sequencing method for high-quality samples using the Illumina MiSeq

Sanger-type sequencing (STS) of mitochondrial DNA (mtDNA), specifically the control region (CR), is routinely employed in forensics in human identification and missing persons scenarios. Yet next-generation sequencing (NGS) has the potential to overcome some of the major limitations of STS processing, permitting reasonable paths forward for full mitochondrial genome (mtGenome) sequencing, while also offering higher-throughput and higher sensitivity capabilities. To establish the accuracy and reproducibility of NGS for the development of mtDNA data, 90 DNA extracts that were previously used to generate forensic quality full mtGenomes using STS were sequenced using Nextera XT library preparation and the Illumina MiSeq. Using the same amplicon product, replicate library sets were generated and sequenced at different laboratories, and analysis was performed in replicate using the CLC Genomics Workbench. Both sequencing sets resulted in 99.998% of positions with greater than 10X coverage when 96 samples (including controls) were multiplexed. Overall, 99.9996% concordance was observed between the NGS data and the STS data for the full mtGenome. The only “discordant” calls involved low level point heteroplasmies, with the differences resulting from stochastic variation and/or the increased sensitivity of NGS. Higher sensitivity also allowed for the detection of a mixed sample previously not detected with STS. Additionally, variant calls were reproducible between sequencing sets and between software analysis versions with the variant frequency only differing by 0.23% and 0.01%, respectively. Further validation studies and specialized software functionality tailored to forensic practice should facilitate the incorporation of NGS processing into standard casework applications. The data herein comprise the largest, and likely most thoroughly examined, complete mtGenome STS-NGS concordance dataset available.     

Schulterschluss zwischen forensischer Molekularbiologie und medizinischer Genetik

The high quality of forensic molecular biological methods is a preequisite for medico-legal applications and a valuable methodological repertoire in scientifically related disciplines. This is demonstrated by 2 studies which were conducted in cooperation within the medical genetics field and in both instances the forensic approach was the key to success. In the first example we identified the responsible stop-codon within the highly polymorphic repetitive repeat region of the apolipoprotein(a) gene by selective mutation analysis. The observed mutation leads to a truncated protein variant and is responsible for elevated plasma lipoprotein levels (arteriosclerosis risk factor). We developed a fast screening method for reliable detection of this polymorphism in genomic DNA. In the second example we applied multiplex STR (short tandem repeat) profiling to the identification of leukaemia cell lines. We evaluated and monitored STR typing in long-term cultures (350 generations), for sub-cloning and for the identification of drug-resistant subclones for quality assurance purposes. The results show that kinship analysis by means of STR profiles derived from cloning experiments needs to be performed with caution and that marker-specific mutation rates need to be taken into consideration. In some cases the additional analysis of more conservative markers may be necessary.     

Generating STR profile from "Touch DNA"

As forensic DNA technology has become a common tool in criminal investigations, scientists have attempted to obtain DNA evidence from what were once considered unlikely sources. “Touch DNA” refers to the DNA that is left behind from skin cells when a person touches or comes into contact with an item. This present study shows, DNA profiling of touched evidence materials is reported employing a combination of LCN typing and miniSTRs. The technology is highly valuable for increasing the scope of DNA profiling to large number touched evidence materials.