Discovery and identification of new D13S317 primer binding site mutations

The (in)dependence of single-cell data inferences on model constructs

Recent developments in single-cell analysis have revolutionized basic research and have garnered the attention of the forensic domain. Though single-cell analysis is not new to forensics, the ways in which these data can be generated and interpreted are. Modern interpretation strategies report likelihood ratios that rely on a model of the world that is a simplification of it. It is, therefore, plausible that different reasonable models will assign noticeably different weights of evidence (WoEs) to some of these data, resulting in inconsistent reports and protracted reviews of that evidence, potentially across years. With one goal of research being to identify and understand sources of inconsistencies during early stages, we undertake a study that evaluates WoE at the limit of one single-cell electropherogram (scEPG) across three architecturally distinct probabilistic models. The three are named EESCIt (Evidentiary Evaluation of Single Cells), TD (Top-Down), and DCM (Discrete Cell Model). To do this, we performance test the three models on a set of 996 individual scEPGs and conduct one H1-true, i.e., true contributor, and 201 H2-true, i.e., false contributor, tests, per scEPG. With the 201,192 outcomes per model, we confirm that scEPGs well resolve the hypotheses, regardless of what model was applied. We also observe that WoEs increase, on average, by 1 for every 1000 RFU of total intensity added until a plateau near the logarithm of the inverse of the random match probability is reached at ca. 22,000 RFU. By querying WoE calibration for each model, we determine if the evidence is over- or under-stated for any one of them. We find that for WoE ≥ -1 hardly any calibration discrepancy is observed. There were rare instances, however, for which WoEs that were ≤ -1 too strongly pointed in the negative direction, though H1 was true. This was the result of five scEPGs that not only exhibited extreme signal in stutter positions, but also carried little information in other loci. These findings show that all three models appropriately stated WoEs for scEPGs when reporting positive WoE, and the two continuous model's WoE reasonably represented the findings when WoE < -1 for most loci. To further explore, we continued with paired analyses that evaluated the agreement in WoE, per scEPG, across models. Unlike unpaired analyses, this evaluation determines if well performing models return equivalent results for the same scEPG. The paired analysis was summarized by way of intraclass correlations, which were at least 0.99997. Further, we found that 762 of 996 WoEs were within a range of 3 orders of magnitude of each other, though many of these were associated with WoEs that were large, i.e., > 9, in the first instance. When we more closely focus on scEPGs giving ranges ≥ 3, but whose WoE ≤ 9 for at least one of the models, we find there are 21 of them. When we perform a locus-by-locus investigation of these 21 and of the five scEPGs returning too strong negative WoE for true contributors we find that extreme stutter is usually the cause of the challenges. To ameliorate differences in predicting rare, though impactful, events we proffer interpretive adaptions that extend beyond manually addressing the phenomena. With the WoE being calibrated within their relevant regions across EESCIt, TD and DCM, we categorize each as meeting the pillar of legitimacy for single-cell data within their intended WoE ranges.

Estimation of population specific values of theta for sequence-based STR profiles

We describe the estimation of θ (theta) values from autosomal STR sequencing data for five metapopulations. The data were compiled from 20 publications and included 39 datasets comprising a total of 7005 samples. The estimates are suitable for use within the calculation of match probabilities in forensic casework. We also have constructed a phylogenetic tree using this data that aligns with our understanding of human evolution.

Identification of the sequence variations of 15 autosomal STR loci in a Chinese population

BACKGROUND

DNA sequence variation including base(s) changes and insertion or deletion in the primer binding region may cause a null allele and, if this changes the length of the amplified fragment out of the allelic ladder, off-ladder (OL) alleles may be detected.

AIM

In order to provide accurate and reliable DNA evidence for forensic DNA analysis, it is essential to clarify sequence variations in prevalently used STR loci.

SUBJECTS AND METHODS

Suspected null alleles and OL alleles of PlowerPlex16® System from 21,934 unrelated Chinese individuals were verified by alternative systems and sequenced.

RESULTS

A total of 17 cases with null alleles were identified, including 12 kinds of point mutations in 16 cases and a 19-base deletion in one case. The total frequency of null alleles was 7.751 × 10(-4). Eight hundred and forty-four OL alleles classified as being of 97 different kinds were observed at 15 STR loci of the PowerPlex®16 system except vWA. All the frequencies of OL alleles were under 0.01.

CONCLUSION

Null alleles should be confirmed by alternative primers and OL alleles should be named appropriately. Particular attention should be paid to sequence variation, since incorrect designation could lead to false conclusions.

Identification of new primer binding site mutations at TH01 and D13S317 loci and determination of their corresponding STR alleles by allele-specific PCR

Several commercial multiplex PCR kits for the amplification of short tandem repeat (STR) loci have been extensively applied in forensic genetics. Consequently, large numbers of samples have been genotyped, and the number of discordant genotypes observed has also increased. We observed allele dropout with two novel alleles at the STR loci TH01 and D13S317 during paternity testing using the AmpFℓSTR Identifiler PCR Amplification Kit. The lost alleles reappeared when alternative PCR primer pairs were used. A sequence analysis revealed a G-to-A substitution 82 bases downstream of the last TCAT motif of the repeat region at the TH01 locus (GenBank accession: D00269) and a G-to-T substitution 90 bases upstream of the first TATC motif of the repeat region at the D13S317 locus (GenBank accession: G09017). The frequencies of these two point mutations were subsequently investigated in the Chinese population using sequence-specific primer PCR (SSP-PCR), but neither of these mutations was detected in any of the samples tested. In addition, the DNA samples in which the mutations were identified were amplified to type the point mutations by SSP-PCR to determine the corresponding STR alleles at the two loci. Subsequently, the amplified PCR products with different point mutations and STR repeat numbers were directly sequenced because this strategy overcomes the appearance overlapping peaks generated by different STR alleles and accurately characterizes genotypes. Thus, our findings not only provide useful information for DNA databases and forensic identification but also establish an effective strategy for typing STR alleles with primer binding site mutations.

Familial identification: population structure and relationship distinguishability

With the expansion of offender/arrestee DNA profile databases, genetic forensic identification has become commonplace in the United States criminal justice system. Implementation of familial searching has been proposed to extend forensic identification to family members of individuals with profiles in offender/arrestee DNA databases. In familial searching, a partial genetic profile match between a database entrant and a crime scene sample is used to implicate genetic relatives of the database entrant as potential sources of the crime scene sample. In addition to concerns regarding civil liberties, familial searching poses unanswered statistical questions. In this study, we define confidence intervals on estimated likelihood ratios for familial identification. Using these confidence intervals, we consider familial searching in a structured population. We show that relatives and unrelated individuals from population samples with lower gene diversity over the loci considered are less distinguishable. We also consider cases where the most appropriate population sample for individuals considered is unknown. We find that as a less appropriate population sample, and thus allele frequency distribution, is assumed, relatives and unrelated individuals become more difficult to distinguish. In addition, we show that relationship distinguishability increases with the number of markers considered, but decreases for more distant genetic familial relationships. All of these results indicate that caution is warranted in the application of familial searching in structured populations, such as in the United States.

Identification and sequence analysis of discordant phenotypes between AmpFlSTR SGM Plus and PowerPlex 16

During duplicate analysis of buccal swabs from 1,377 individuals with 2 commercial short tandem repeat (STR) kits, we observed 8 discordant phenotypes with SGM Plus (SGM, second generation multiplex) for the STRs THO1 (2), vWA (4) and D18S51 (2), and 1 discrepancy with PowerPlex 16 for D18S51. One individual even showed two discrepancies (vWA and THO1) for SGM Plus. In each case, the difference observed was due to the non-amplification or allele dropout of the second allele in a heterozygous genotype. Sequence analysis revealed each time the presence of a mutation that probably coincided with the primer-binding site. Primer-binding site mutations for vWA and D18S51 have been reported previously, while the mutation for THO1 (C-to-T substitution at position 1286 of GenBank sequence D00269) is reported here for the first time. While the frequency of these silent alleles remains low (0.58% in our study), it is suggested that appropriate measures should be taken for database comparisons and that allelic dropout should be further investigated by sequence analysis and be reported to the forensic community.