Allele frequencies of 31 autosomal short tandem repeat (auSTR) loci obtained using the Precision ID GlobalFiler™ NGS STR Panel v2 in 322 individuals from the Japanese population.

In human identification methods that target short tandem repeats (STRs), massively parallel sequencing (MPS) technology has made it possible to genotype at the level of the specific sequence itself. This allows for the detection of repeat unit variants and single nucleotide polymorphisms (SNPs) adjacent to the STRs. Using the GlobalFiler™ NGS STR Panel v2, Ion S5, and Converge software, this study constructed a Japanese database of 31 autosomal STRs (auSTRs) and two sex markers from 322 individuals. After excluding some sequence errors and stutters, a total of 31 novel alleles were identified. Additionally, using the allele frequencies of 31 auSTR loci, the match probabilities for the length-based and sequence-based data were calculated to be 1.433 × 10-34 and 9.163 × 10-38, respectively. These values are at least nine orders of magnitude higher than that obtained from 21 auSTR loci in the Japanese population using the conventional capillary electrophoresis method. The database generated in this study is expected to be implemented in forensic practice and used to solve difficult casework.

Rapid semen identification from mixed body fluids using methylation-sensitive high-resolution melting analysis of the DACT1 gene.

In forensic genetics, a suspect is assigned to a component of a DNA mixture profile, and a probabilistic interpretation is then usually performed. However, it is difficult to determine what types of body fluid the component is from. Previous studies have reported that the fourth exon of the Dishevelled binding antagonist of beta catenin 1 (DACT1) gene is hypomethylated in a semen DNA-specific manner. In the present study, we evaluated whether the DACT1 gene could be effectively used to identify semen in body fluid mixtures and were able to semi-quantify the semen DNA content in mixed fluids. Our results showed that the DACT1 gene was useful in discriminating semen from venous blood and saliva. However, the amount of sperm in semen can affect semen identification. In addition, SI (the semen DNA content index), which we developed, was useful to determine whether the semen compromised majority, almost half, or was in the minority of the components in a mixed fluid. This technique is based on the methylation-sensitive high-resolution melting (MS-HRM) technology, which is time-, cost-, and labour-effective, and could be adopted in routine criminal investigations.

Development of a software for kinship analysis considering linkage and mutation based on a Bayesian network.

In forensic DNA testing, the number of tested short tandem repeat loci has increased owing to new multiplex kits with additional loci. Although this advancement provides improved discrimination power, the effects of linkage and mutation must be considered during kinship analysis. However, no software currently includes both of these effects. In this study, we developed new freeware called KinBN for kinship analysis based on a Bayesian network. The software is graphical-user-interface-based and calculates the likelihood ratios (LRs) at multiple loci considering the effects of linkage and mutation. In addition, the software can simulate the LR distribution according to the specified relationship. We confirmed the accuracy of KinBN by comparing its LRs with those of other software and evaluated the effects of linkage and mutation on the LRs. Our results indicate that KinBN is a useful tool for kinship analysis, particularly if expanded locus sets are used for DNA testing.

Distinct spectrum of microRNA expression in forensically relevant body fluids and probabilistic discriminant approach.

MicroRNA is attracting worldwide attention as a new marker for the identification of forensically relevant body fluids. A probabilistic discriminant model was constructed to identify venous blood, saliva, semen, and vaginal secretion, based on microRNA expression assessed via RT-qPCR. We quantified 15 candidate microRNAs in four types of body fluids by RT-qPCR and found that miR-144-3p, miR-451a-5p, miR-888-5p, miR-891a-5p, miR-203a-3p, miR-223-3p and miR-1260b were helpful to discriminate body fluids. Using the relative expression of seven candidate microRNAs in each body fluid, we implemented a partial least squares-discriminant analysis (PLS-DA) as a probabilistic discriminant model and distinguished four types of body fluids. Of 14 testing samples, 13 samples were correctly identified with >90% posterior probability. We also investigated the effects of microRNA expression in skin, semen infertility, and vaginal secretion during different menstrual phases. Semen infertility and menstrual phases did not affect our body fluid identification system. Therefore, the selected microRNAs were effective in identifying the four types of body fluids, indicating that probabilistic evaluation may be practical in forensic casework.