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Paternity testing and sibling testing become more complex and difficult when samples degrade. But the commonly used genetic markers (STR and SNP) cannot completely solve this problem due to some disadvantages. The novel genetic marker microhaplotype proposed by Kidd’s research group combines the advantages of STR and SNP and is expected to become a promising genetic marker for kinship testing in degraded samples. Therefore, in this study, we intended to select an appropriate number of highly polymorphic SNP-based microhaplotype loci, detect them by the next-generation sequencing technology, analyze their ability to detect degraded samples, calculate their forensic parameters based on the collected 96 unrelated individuals, and evaluate their effectiveness in paternity testing and sibling testing by simulating kinship relationship pairs, which were also compared to 15 STR loci. Finally, a short and highly polymorphic microhaplotype panel was developed, containing 36 highly polymorphic SNP-based microhaplotype loci with lengths smaller than 100 bp and Ae greater than 3.00, of which 29 microhaplotype loci could not reject the Hardy-Weinberg equilibrium and linkage equilibrium after the Bonferroni correction. The CPD and CPE of these 29 microhaplotype loci were 1-2.96E-26 and 1-5.45E-09, respectively. No allele dropout was observed in degraded samples incubated with 100°C hot water for 40min and 60min. According to the simulated kinship analysis, the effectiveness at the threshold of 4/−4 reached 98.39% for relationship parent-child vs. unrelated individuals, and the effectiveness at the threshold of 2/−2 for relationship full-sibling vs. unrelated individuals was 93.01%, which was greater than that of 15 STR loci (86.75% for relationship parent-child vs. unrelated individuals and 81.73% for relationship full-sibling vs. unrelated individuals). After combining our 29 microhaplotype loci with other 50 short and highly polymorphic microhaplotype loci, the effectiveness values at the threshold of 2/−2 were 82.42% and 90.89% for relationship half-sibling vs. unrelated individuals and full-sibling vs. half-sibling. The short and highly polymorphic microhaplotype panel we developed may be very useful for paternity testing and full sibling testing in degraded samples, and in combination with short and highly polymorphic microhaplotype loci reported by other researchers, may be helpful to analyze more distant kinship relationships.

Bacteria acts as the main decomposer during the process of biodegradation by microbial communities in the ecosystem. Numerous studies have revealed the bacterial succession patterns during carcass decomposition in the terrestrial setting. The machine learning algorithm-generated models based on such temporal succession patterns have been developed for the postmortem interval (PMI) estimation. However, the bacterial succession that occurs on decomposing carcasses in the aquatic environment is poorly understood. In the forensic practice, the postmortem submersion interval (PMSI), which approximately equals to the PMI in most of the common drowning cases, has long been problematic to determine. In the present study, bacterial successions in the epinecrotic biofilm samples collected from the decomposing swine cadavers submerged in water were analyzed by sequencing the variable region 4 (V4) of 16S rDNA. The succession patterns between the repeated experimental settings were repeatable. Using the machine learning algorithm for establishing random forest (RF) models, the microbial community succession patterns in the epinecrotic biofilm samples taken during the 56-day winter trial and 21-day summer trial were determined to be used as the PMSI predictors with the mean absolute error (MAE) of 17.87 ± 2.48 ADD (≈1.3 day) and 20.59 ± 4.89 ADD (≈0.7 day), respectively. Significant differences were observed between the seasons and between the substrates. The data presented in this research suggested that the influences of the environmental factors and the aquatic bacterioplankton on succession patterns of the biofilm bacteria were of great significance. The related mechanisms of such influence need to be further studied and clarified in depth to consider epinecrotic biofilm as a reliable predictor in the forensic investigations.

Various compound markers encompassing two or more variants within a small region can be regarded as generalized microhaplotypes. Many of these markers have been investigated for various forensic purposes, such as individual identification, deconvolution of DNA mixtures, or forensic ancestry inference. SNP-STR is a compound biomarker composed of a single nucleotide polymorphism (SNP) and a closely linked short tandem repeat polymorphism (STR), and possess the advantages of both SNPs and STRs. In addition, in conjunction with a polymerase chain reaction (PCR) technique based on the amplification refractory mutation system (ARMS), SNP-STRs can be used for forensic unbalanced DNA mixture analysis based on capillary electrophoresis (CE), which is the most commonly used platform in worldwide forensic laboratories. Our previous research reported 11 SNP-STRs, but few of them are derived from the commonly used STR loci, for which existing STR databases can be used as a reference. For maximum compatibility with existing DNA databases, in this study, we screened 18 SNP-STR loci, of which 14 were derived from the expanded CODIS core loci set. Stable and sensitive SNP-STR multiplex PCR panels based on the CE platform were established. Assays on simulated two-person DNA mixtures showed that all allele-specific primers could detect minor DNA components in 1:500 mixtures. Population data based on 113 unrelated Chengdu Han individuals were investigated. A Bayesian framework was developed for the likelihood ratio (LR) evaluation of SNP-STR profiling results obtained from two-person mixtures. Furthermore, we report on the first use of SNP-STRs in casework to show the advantages and limitations for use in practice. Compared to 2.86 × 103 for autosomal STR kits, the combined LR reached 7.14 × 107 using the SNP-STR method in this casework example.

Since the concept of microhaplotypes was proposed by Kidd in 2013, various microhaplotype markers have been investigated for various forensic purposes, such as individual identification, deconvolution of DNA mixtures, or forensic ancestry inference. In our opinion, various compound markers are also regarded as generalized microhaplotypes, encompassing two or more variants in a short segment of DNA (e.g., 200 bp). That is, a set of variants (referred to herein as multi-variants) within a certain length includes single nucleotide polymorphisms (SNP), insertion/deletion polymorphisms (Indels), or short tandem repeat polymorphisms (STRs). At present, multi-variant is mainly aimed at multi-SNPs. However, the haplotype genotyping of multi-variants relies on single-strand analysis, mainly using massively parallel sequencing (MPS). Here, we describe a method based on a capillary electrophoresis (CE) platform that can directly obtain haplotypes of individuals. Several microhaplotypes consisting of three or more Indels with different insertion or deletion lengths in the range of less than 200 bp were screened out, each of which had at least three haplotypes. As a result, the haplotype of an individual was reflected by the length of its polymorphism. Finally, we established a multiplex amplification system containing 18 multi-Indel markers that could identify haplotypes on each chromosome of an individual. The combined power of discrimination (CPD) and the cumulative probability of exclusion (CPE) were 0.999999999997234 and 0.9984, respectively.

Bacteria acts as the main decomposer during the process of biodegradation by microbial communities in the ecosystem. Numerous studies have revealed the bacterial succession patterns during carcass decomposition in the terrestrial setting. The machine learning algorithm-generated models based on such temporal succession patterns have been developed for the postmortem interval (PMI) estimation. However, the bacterial succession that occurs on decomposing carcasses in the aquatic environment is poorly understood. In the forensic practice, the postmortem submersion interval (PMSI), which approximately equals to the PMI in most of the common drowning cases, has long been problematic to determine. In the present study, bacterial successions in the epinecrotic biofilm samples collected from the decomposing swine cadavers submerged in water were analyzed by sequencing the variable region 4 (V4) of 16S rDNA. The succession patterns between the repeated experimental settings were repeatable. Using the machine learning algorithm for establishing random forest (RF) models, the microbial community succession patterns in the epinecrotic biofilm samples taken during the 56- day winter trial and 21-day summer trial were determined to be used as the PMSI predictors with the mean absolute error (MAE) of 17.87 ± 2.48 ADD (≈1.3 day) and 20.59 ± 4.89 ADD (≈0.7 day), respectively. Significant differences were observed between the seasons and between the substrates. The data presented in this research suggested that the influences of the environmental factors and the aquatic bacterioplankton on succession patterns of the biofilm bacteria were of great significance. The related mechanisms of such influence need to be further studied and clarified in depth to consider epinecrotic biofilm as a reliable predictor in the forensic investigations. [ABSTRACT FROM AUTHOR]