Joint application of A-InDels and miniSTRs for forensic personal, full and half sibling identifications, and genetic differentiation analyses in two populations from China.

BACKGROUND: Previously, a novel multiplex system of 64 loci was constructed based on capillary electrophoresis platform, including 59 autosomal insertion/deletions (A-InDels), two Y-chromosome InDels, two mini short tandem repeats (miniSTRs), and an Amelogenin gene. The aim of this study is to evaluate the efficiencies of this multiplex system for individual identification, paternity testing and biogeographic ancestry inference in Chinese Hezhou Han (CHH) and Hubei Tujia (CTH) groups, providing valuable insights for forensic anthropology and population genetics research. RESULTS: The cumulative values of power of discrimination (CDP) and probability of exclusion (CPE) for the 59 A-InDels and two miniSTRs were 0.99999999999999999999999999754, 0.99999905; and 0.99999999999999999999999999998, 0.99999898 in CTH and CHH groups, respectively. When the likelihood ratio thresholds were set to 1 or 10, more than 95% of the full sibling pairs could be identified from unrelated individual pairs, and the false positive rates were less than 1.2% in both CTH and CHH groups. Biogeographic ancestry inference models based on 35 populations were constructed with three algorithms: random forest, adaptive boosting and extreme gradient boosting, and then 10-fold cross-validation analyses were applied to test these three models with the average accuracies of 86.59%, 84.22% and 87.80%, respectively. In addition, we also investigated the genetic relationships between the two studied groups with 33 reference populations using population statistical methods of FST, DA, phylogenetic tree, PCA, STRUCTURE and TreeMix analyses. The present results showed that compared to other continental populations, the CTH and CHH groups had closer genetic affinities to East Asian populations. CONCLUSIONS: This novel multiplex system has high CDP and CPE in CTH and CHH groups, which can be used as a powerful tool for individual identification and paternity testing. According to various genetic analysis methods, the genetic structures of CTH and CHH groups are relatively similar to the reference East Asian populations.

A novel 193-plex MPS panel integrating STRs and SNPs highlights the application value of forensic genetics in individual identification and paternity testing.

Massively parallel sequencing (MPS) has emerged as a promising technology for targeting multiple genetic loci simultaneously in forensic genetics. Here, a novel 193-plex panel was designed to target 28 A-STRs, 41 Y-STRs, 21 X-STRs, 3 sex-identified loci, and 100 A-SNPs by employing a single-end 400 bp sequencing strategy on the MGISEQ-2000™ platform. In the present study, a series of validations and sequencing of 1642 population samples were performed to evaluate the overall performance of the MPS-based panel and its practicality in forensic application according to the SWGDAM guidelines. In general, the 193-plex markers in our panel showed good performance in terms of species specificity, stability, and repeatability. Compared to commercial kits, this panel achieved 100% concordance for standard gDNA and 99.87% concordance for 14,560 population genotypes. Moreover, this panel detected 100% of the loci from 0.5 ng of DNA template and all unique alleles at a 1:4 DNA mixture ratio (0.2 ng minor contributor), and the applicability of the proposed approach for tracing and degrading DNA was further supported by case samples. In addition, several forensic parameters of STRs and SNPs were calculated in a population study. High CPE and CPD values greater than 0.9999999 were clearly demonstrated and these results could be useful references for the application of this panel in individual identification and paternity testing. Overall, this 193-plex MPS panel has been shown to be a reliable, repeatable, robust, inexpensive, and powerful tool sufficient for forensic practice.

Epigenetic-based age prediction in blood samples: Model development.

Aging is a complex process influenced by genetic, epigenetic, and environmental factors that lead to tissue deterioration and frailty. Epigenetic mechanisms, such as DNA methylation, play a significant role in gene expression regulation and aging. This study presents a new age estimation model developed for the Turkish population using blood samples. Eight CpG sites in loci TOM1L1, ELOVL2, ASPA, FHL2, C1orf132, CCDC102B, cg07082267, and RASSF5 were selected based on their correlation with age. Methylation patterns of these sites were analyzed in blood samples from 100 volunteers, grouped into age categories (20-35, 36-55, and ≥56). Sensitivity analysis indicated a reliable performance with DNA inputs ≥1 ng. Statistical modeling, utilizing Multiple Linear Regression, underscores the reliability of the primary 6-CpG model, excluding cg07082267 and TOM1L1. This model demonstrates strong correlations with chronological age (r = 0.941) and explains 88% of the age variance with low error rates (MAE = 4.07, RMSE = 5.73 years). Validation procedures, including a training-test split and fivefold cross-validation, consistently confirm the model's accuracy and consistency. The study indicates minimal variation in error scores across age cohorts and no significant gender differences. The developed model showed strong predictive accuracy, with the ability to estimate age within certain prediction intervals. This study contributes to the age prediction by using DNA methylation patterns, which can have disparate applications, including forensic and clinical assessments.

Predicting age from blood by droplet digital PCR using a set of three DNA methylation markers.

Evaluation of DNA methylation (DNAm) patterns is a promising tool for age estimation. The duplex droplet digital PCR (ddPCR) method has been recently investigated for DNAm evaluation, revealing to be a potential methodology for DNAm evaluation and molecular age estimation. In this study, we evaluated DNAm levels of CpGs located at the three age-associated genes ELOVL2, FHL2 and PDE4C using ddPCR to develop an age prediction model. Blood-derived DNA samples from 58 healthy individuals (42 women and 16 men; aged 1-93 years old) were submitted to bisulfite conversion followed by ddPCR using dual-labeled probes targeting methylated and unmethylated DNA sequences. Simple linear regression statistics revealed a strong correlation between DNAm levels and chronological age for FHL2 (R = 0.948; P = 1.472 × 10-29) and PDE4C (R = 0.819; P = 3.917 × 10-15), addressing only one CpG for each gene. For the ELOVL2 gene, evaluating five CpG sites in simultaneous, revealed a strong age correlation (R = 0.887; P = 2.099 × 10-20) in a simple linear regression statistics and very strong age correlation (R = 0.926; P = 2.202 × 10-25) when using quadratic regression statistics. The multivariable regression analysis, using methylation information captured on ELOVL2 (squared), FHL2 and PDE4C genes, revealed a very strong age correlation (R = 0.970; P = 5.356 ×10-33), explaining 93.7 % of age variance, displaying a mean absolute deviation (MAD) between chronological and predicted age of 4.657 years (RMSE = 6.044). We postulate that the ddPCR method should be further investigated for DNAm-based age prediction, because it is a relatively simple and an accurate method that can be routinely used in forensic laboratories for testing a few numbers of markers.

Sequence-based population structure, relatedness, and inbreeding estimates for forensic autosomal STR markers.

Population data have become available for sequence data to aid forensic investigations and prepare the forensic community in the move towards implementing NGS methods. This comes with a need for updated population genetic parameters estimates to allow DNA evidence evaluations using sequence data. Initial work has been done on a small sample and here we expand this work by providing estimates of population structure and relatedness for autosomal STR data generated by sequencing technologies. We also discuss the effect of inbreeding on forensic calculations and discuss why the use of genotypic-based estimates may be preferred over allelic-based estimates.

DNA methylation-based age estimation and quantification of the degradation levels of bisulfite-converted DNA.

DNA methylation modifications are known to influence epigenetic phenomena and have been a focus of forensic science research for some time. Degraded DNA after bisulfite treatment is widely used in DNA methylation analysis. In this study, we analyzed methylation levels at 12 CpG sites of four selected genomic regions by pyrosequencing after bisulfite treatment. DNA was extracted from buccal swab samples collected from 102 Japanese individuals who were 21-77 years old. We also developed a simple method to quantify the degradation levels of bisulfite-converted DNA by real-time PCR, and evaluated the effect of DNA degradation on age estimation. We found that the methylation levels and chronological ages were highly correlated in the four selected regions, and the mean absolute deviation (MAD) between chronological and estimated ages was low at 3.88 years. These results indicated that pyrosequencing analysis at the 12 CpGs was useful for age estimation in the Japanese population. To develop a sensitive quantification method, we analyzed the amplification efficiency of short and long fragments from 10 regions by real-time PCR. The amplification efficiency was highest for CCDC102B, and the degradation levels of bisulfite-converted DNA for the 102 samples were categorized as moderately or heavily degraded. For the younger age groups (20-49 years), the MADs were lower for moderately degraded DNA than they were for heavily degraded DNA. This finding indicates that degradation levels affected the accuracy of age estimation in most of the samples; the exception was the samples from the 50-77 years age group.

A combined molecular approach utilizing microbial DNA and microRNAs in a qPCR multiplex for the classification of five forensically relevant body fluids.

Body fluid identification is an essential step in the forensic biology workflow that can assist DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the specificity that molecular techniques can achieve; therefore, molecular methods, including microRNA (miRNA) and microbial signature characterization, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase the discrimination efficiency of multiple body fluids from a single assay. While microbial signatures have been successful in identifying fluids with high bacterial abundances, microRNAs have shown promise in fluids with low microbial abundance (blood and semen). This project synergized the benefits of microRNAs and microbial DNA to identify multiple body fluids using DNA extracts. A reverse transcription (RT)-qPCR duplex targeting miR-891a and let-7g was validated, and miR-891a differential expression was significantly different between blood and semen. The miRNA duplex was incorporated into a previously reported qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius to presumptively identify vaginal/menstrual secretions, feces, and saliva, respectively. The combined classification regression tree model resulted in the presumptive classification of five body fluids with 94.6% overall accuracy, now including blood and semen identification. These results provide proof of concept that microRNAs and microbial DNA can classify multiple body fluids simultaneously at the quantification step of the current forensic DNA workflow.

An mRNA profiling assay incorporating coding region InDels for body fluid identification and the inference of the donor in mixed samples.

Biological traces discovered at crime scenes hold significant significance in forensic investigations. In cases involving mixed body fluid stains, the evidentiary value of DNA profiles depends on the type of body fluid from which the DNA was obtained. Recently, coding region polymorphism analysis has proved to be a promising method for directly linking specific body fluids to their respective DNA contributors in mixtures, which may help to avoid "association fallacy" between separate DNA and RNA evidence. In this study, we present an update on previously reported coding region Single Nucleotide Polymorphisms (cSNPs) by exploring the potential application of coding region Insertion/Deletion polymorphisms (cInDels). Nine promising cInDels, selected from 70 mRNA markers based on stringent screening criteria, were integrated into an existing mRNA profiling assay. Subsequently, the body fluid specificity of our cInDel assay and the genotyping consistency between complementary DNA (cDNA) and genomic DNA (gDNA) were examined. Our study demonstrates that cInDels can function as important multifunctional genetic markers, as they provide not only the ability to confirm the presence of forensically relevant body fluids, but also the ability to associate/dissociate specific body fluids with particular donors.

Review: Wildlife forensic genetics-Biological evidence, DNA markers, analytical approaches, and challenges.

Wildlife-related crimes are the second most prevalent lawbreaking offense globally. This illicit trade encompasses hunting, breeding and trafficking. Besides diminishing many species and their habitats and ecosystems, hindering the economic development of local communities that depend on them, undermining the rule of law and financing terrorism, various cross-species transmissions (zoonoses) of pathogens, including COVID-19, can be attributed to wildlife crimes. Wildlife forensics applies interdisciplinary scientific analyses to support law enforcement in investigating wildlife crimes. Its main objectives are to identify the taxonomic species in question, determine if a crime has been committed, link a suspect to the crime and support the conviction and prosecution of the perpetrator. This article reviews wildlife crime and its implications, wildlife forensic science investigation, common forms of wildlife biological evidence, including DNA, wildlife DNA techniques and challenges in wildlife forensic genetics. The article also reviews the contributions of genetic markers such as short tandem repeat (STR) and mitochondrial DNA (mtDNA) markers, which provide the probative genetic data representing the bulk of DNA evidence for solving wildlife crime. This review provides an overview of wildlife DNA databases, which are critical for searching and matching forensic DNA profiles and sequences and establishing how frequent forensic DNA profiles and sequences are in a particular population or geographic region. As such, this review will contain an in-depth analysis of the current status of wildlife forensic genetics, and it will be of general interest to wildlife and conservation biologists, law enforcement officers, and academics interested in combating crimes against wildlife using animal forensic DNA methods.

A proof-of-principle study: The potential application of MiniHap biomarkers in ancestry inference based on the QNome nanopore sequencing.

Haplotyped SNPs convey forensic-related information, and microhaplotypes (MHs), as the most representative of this kind of marker, have proved the potential value for human forensics. In recent years, nanopore sequencing technology has developed rapidly, with its outstanding ability to sequence long continuous DNA fragments and obtain phase information, making the detection of longer haplotype marker possible. In this proof-of-principle study, we proposed a new type of forensic marker, MiniHap, based on five or more SNPs within a molecular distance less than 800 bp, and investigated the haplotype data of 56 selected MiniHaps in five Chinese populations using the QNome nanopore sequencing. The sequencing performance, allele (haplotype) frequencies, forensic parameters, effective number of alleles (Ae), and informativeness (In) were subsequently calculated. In addition, we performed principal component analysis (PCA), phylogenetic tree, and structure analysis to investigate the population genetic relationships and ancestry components among the five investigated populations and 26 worldwide populations. MiniHap-04 exhibited remarkable forensic efficacy, with 148 haplotypes reported and the Ae was 66.9268. In addition, the power of discrimination (PD) was 0.9934, the probability of exclusion (PE) was 0.9898, and the In value was 0.7893. Of the 56 loci, 85.71% had PD values above 0.85, 66.07% had PE values above 0.54, 67.86% had Ae values over 7.0%, and 55.36% were with In values above 0.2 across all samples, indicating that most of the MiniHaps are suitable for individual identification, paternity testing, mixture deconvolution, and ancestry inference. Moreover, the results of PCA, phylogenetic tree and structure analysis demonstrated that this MiniHap panel had the competency in continental population ancestry inference, but the differentiation within intracontinental/linguistically restricted subpopulations was not ideal. Such findings suggested that the QNome device for MiniHap detection was feasible and this novel marker has the potential in ancestry inference. Yet, the establishment of a more comprehensive database with sufficient reference population data remains necessary to screen more suitable MiniHaps.

Operationalisation of the ForenSeq® Kintelligence Kit for Australian unidentified and missing persons casework.

Single nucleotide polymorphism (SNP) genotyping technologies can generate investigative leads for human remains identification, including estimation of biological sex, biogeographical ancestry (BGA), externally visible characteristics (EVCs), identity, uniparental lineage and extended kinship. The ForenSeq® Kintelligence Kit provides forensic laboratories with the ability to apply this suite of genetic tools to forensic samples using one panel targeting 10,230 SNPs (including 56 ancestry-informative, 24 phenotype-informative, 94 identity-informative, 106 X chromosome, 85 Y chromosome and 9867 kinship-informative SNPs) sequenced on the MiSeq FGx® Sequencing System. The ForenSeq® Kintelligence Kit has been internally validated, optimised and operationalised by the Australian Federal Police National DNA Program for Unidentified and Missing Persons (AFP Program) for coronial casework. The internal validation was conducted according to the Scientific Working Group on DNA Analysis Methods guidelines (excluding mixture analysis), focussing on sample types typically encountered in human remains identification casework, such as bones, teeth, nail, blood and hair. The workflow was optimised for a high throughput library preparation and sequencing workflow, and additional analytical thresholds were developed to improve genotyping accuracy for low DNA input samples. Additionally, the genetic intelligence generated from the kit was compared to the self-declared biological sex, EVCs and BGA of the DNA donors to assess concordance. The kit was able to produce high quality SNP profiles from 1.0 ng down to 0.1 ng of DNA, with high repeatability and reproducibility, and minimal background noise. The prediction accuracy for biological sex (95%), hair colour (58%), eye colour (74%) and BGA inferences (consistent: 74%; partially consistent: 10%; inconclusive: 16%) was determined based on self-declared data. Additionally, SNP profiles from a volunteer family group of ten related individuals were uploaded to GEDmatch PRO™ to assess kinship accuracy. The kit was capable of detecting (97%) and accurately classifying (90%) genetic relationships spanning from first to fifth degree. The Kintelligence Kit provides the AFP Program with a robust and reliable genetic intelligence tool for unidentified and missing persons investigations, which has been designed to sequence multiple challenging samples in a single multiplexed assay using existing laboratory instrumentation.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Development and comparison of forensic interval age prediction models by statistical and machine learning methods based on the methylation rates of ELOVL2 in blood DNA.

Age estimation can be useful information for narrowing down candidates of unidentified donors in criminal investigations. Various age estimation models based on DNA methylation biomarkers have been developed for forensic usage in the past decade. However, many of these models using ordinary least squares regression cannot generate an appropriate estimation due to the deterioration in prediction accuracy caused by an increased prediction error in older age groups. In the present study, to address this problem, we developed age estimation models that set an appropriate prediction interval for all age groups by two approaches: a statistical method using quantile regression (QR) and a machine learning method using an artificial neural network (ANN). Methylation datasets (n = 1280, age 0-91 years) of the promoter for the gene encoding ELOVL fatty acid elongase 2 were used to develop the QR and ANN models. By validation using several test datasets, both models were shown to enlarge prediction intervals in accordance with aging and have a high level of correct prediction (>90 %) for older age groups. The QR and ANN models also generated a point age prediction with high accuracy. The ANN model enabled a prediction with a mean absolute error (MAE) of 5.3 years and root mean square error (RMSE) of 7.3 years for the test dataset (n = 549), which were comparable to those of the QR model (MAE = 5.6 years, RMSE = 7.8 years). Their applicability to casework was also confirmed using bloodstain samples stored for various periods of time (1-14 years), indicating the stability of the models for aged bloodstain samples. From these results, it was considered that the proposed models can provide more useful and effective age estimation in forensic settings.

Partial validation of multiplexed real-time quantitative PCR assays for forensic body fluid identification.

Confirmatory body fluid identification using messenger RNA (mRNA) is a well-established technique to address issues encountered with conventional testing - such as poor sensitivity, specificity, and a lack of available tests for all body fluids of interest. For over a decade, endpoint reverse-transcription polymerase chain reaction (RT-PCR) assays have been used in forensic casework for such purposes. However, in comparison with real-time quantitative RT-PCR (RT-qPCR), endpoint RT-PCR has lower sensitivity, precision, and linear dynamic range. This research details the multiplexing and partial validation of confirmatory RT-qPCR assays. We have previously described novel assays for a range of body fluid targets and identified an optimal commercial kit for their amplification. Here, multiplexing was undertaken to form three assays: circulatory blood (SLC4A1) and menstrual fluid (STC1), saliva (HTN3) and vaginal material (CYP2B7P), and spermatozoa (PRM1) and seminal fluid (KLK2), all including a synthetic internal control RNA. Partial validation of the multiplexed assays incorporated the MIQE guidelines, ISO requirements, and SWGDAM guidelines. Using receiver operating characteristic (ROC) curves, each marker was significantly different from an uninformative assay and optimal cut-offs were all above 35 cycles. All assays showed a wide LDR (ranging from 3 to 5 logs with most R2 > 0.99), and high precision (most mean CV < 1 %). STC1 showed some instances of sporadic expression in blood, semen, and vaginal material at high CT values. CYP2B7P showed off-target expression in semen and blood. The sensitivities were approximated as; saliva: 1 in 1,000 dilution of a whole buccal swab, circulatory blood: 0.01-0.1 µL blood, menstrual fluid: 1 in 10,000 dilution of a whole menstrual swab, spermatozoa: 0.001 µL semen, seminal fluid: 0.01 µL semen, and vaginal material: 1 in 1,000 dilution of a whole vaginal swab. A total of 16 mock body fluid extract mixtures and 18 swab mixtures were tested and had 100% and 99% detection of target markers below each specific cut-off, respectively. Some mixtures containing high volumes of blood and semen showed off-target CYP2B7P expression. The successful application of a probabilistic model to the RT-qPCR data was also demonstrated. Further work will involve full developmental validation.

Cross-Platform Application of DNA Methylation Age Estimation Model in Eastern Chinese Han Population.

OBJECTIVES: To evaluate the forensic application value of an age estimation model based on DNA methylation in eastern Chinese Han population, and to provide a theoretical basis for exploring age estimation models suitable for different detection platforms. METHODS: According to the 6 age-related methylation sites in the published blood DNA methylation age estimation models of Chinese Han population, the DNA methylation level of 48 samples was detected by pyrosequencing and next-generation sequencing (NGS). After submitting DNA methylation levels to the age estimation model, the DNA methylation ages were predicted and compared with their real ages. RESULTS: The 6 DNA methylation sites in both detection techniques were age-related, with an R2 of 0.85 and a median absolute deviation (MAD) of 4.81 years when using pyrosequencing；with an R2 of 0.84 and MAD of 4.41 years when using NGS. CONCLUSIONS: The blood DNA methylation age estimation model can be used under pyrosequencing and multi-purpose regional methylation enrichment sequencing technology based on NGS and it can accurately estimate the age.

Construction of an Analysis Model of mRNA Markers in Menstrual Blood Based on Naïve Bayes and Multivariate Logistic Regression Methods.

OBJECTIVES: To establish the menstrual blood identification model based on Naïve Bayes and multivariate logistic regression methods by using specific mRNA markers in menstrual blood detection technology combined with statistical methods, and to quantitatively distinguish menstrual blood from other body fluids. METHODS: Body fluids including 86 menstrual blood, 48 peripheral blood, 48 vaginal secretions, 24 semen and 24 saliva samples were collected. RNA of the samples was extracted and cDNA was obtained by reverse transcription. Five menstrual blood-specific markers including members of the matrix metalloproteinase (MMP) family MMP3, MMP7, MMP11, progestogens associated endometrial protein (PAEP) and stanniocalcin-1 (STC1) were amplified and analyzed by electrophoresis. The results were analyzed by Naïve Bayes and multivariate logistic regression. RESULTS: The accuracy of the classification model constructed was 88.37% by Naïve Bayes and 91.86% by multivariate logistic regression. In non-menstrual blood samples, the distinguishing accuracy of peripheral blood, saliva and semen was generally higher than 90%, while the distinguishing accuracy of vaginal secretions was lower, which were 16.67% and 33.33%, respectively. CONCLUSIONS: The mRNA detection technology combined with statistical methods can be used to establish a classification and discrimination model for menstrual blood, which can distignuish the menstrual blood and other body fluids, and quantitative description of analysis results, which has a certain application value in body fluid stain identification.

Application of SNaPshot Technology in Semen-Specific cSNP Genetic Marker.

OBJECTIVES: To explore the feasibility of genetic marker detection of semen-specific coding region single nucleotide polymorphism (cSNP) based on SNaPshot technology in semen stains and mixed body fluid identification. METHODS: Genomic DNA (gDNA) and total RNA were extracted from 16 semen stains and 11 mixtures composed of semen and venous blood, and the total RNA was reverse transcribed into complementary DNA (cDNA). The cSNP genetic markers were screened on the validated semen-specific mRNA coding genes. The cSNP multiplex detection system based on SNaPshot technology was established, and samples were genotyped by capillary electrophoresis (CE). RESULTS: A multiplex detection system containing 5 semen-specific cSNPs was successfully established. In 16 semen samples, except the cSNP located in the TGM4 gene showed allele loss in cDNA detection results, the gDNA and cDNA typing results of other cSNPs were highly consistent. When detecting semen-venous blood mixtures, the results of cSNP typing detected were consistent with the genotype of semen donor and were not interfered by the genotype of venous blood donor. CONCLUSIONS: The method of semen-specific cSNPs detection by SNaPshot technology method can be applied to the genotyping of semen (stains) and provide information for determining the origin of semen in mixed body fluids (stains).

Research Progress on Molecular Biology of Human Height Estimation.

As an important anthropometric characteristic, human height not only contributes to the recognition of other anthropological characteristics and genetic risk factors, but also is an important part of forensic DNA phenotyping studies. Accurate estimation of height can provide more complete information about the phenotype of suspects and provide help to solve cases. In recent years, having benefited from the rapid development of molecular biological techniques and bioinformatics, height-related genetics research has made some progress. This paper describes the research progress of human height estimation from the genetic variation and the epigenetic inheritance perspectives and looks into the future research direction.

Targeted sequencing of high-density SNPs provides an enhanced tool for forensic applications and genetic landscape exploration in Chinese Korean ethnic group.

BACKGROUND: In this study, we present a NGS-based panel designed for sequencing 1993 SNP loci for forensic DNA investigation. This panel addresses unique challenges encountered in forensic practice and allows for a comprehensive population genetic study of the Chinese Korean ethnic group. To achieve this, we combine our results with datasets from the 1000 Genomes Project and the Human Genome Diversity Panel. RESULTS: We demonstrate that this panel is a reliable tool for individual identification and parentage testing, even when dealing with degraded DNA samples featuring exceedingly low SNP detection rates. The performance of this panel for complex kinship determinations, such as half-sibling and grandparent-grandchild scenarios, is also validated by various kinship simulations. Population genetic studies indicate that this panel can uncover population substructures on both global and regional scales. Notably, the Han population can be distinguished from the ethnic minorities in the northern and southern regions of East Asia, suggesting its potential for regional ancestry inference. Furthermore, we highlight that the Chinese Korean ethnic group, along with various Han populations from different regional areas and certain northern ethnic minorities (Daur, Tujia, Japanese, Mongolian, Xibo), exhibit a higher degree of genetic affinities when examined from a genomic perspective. CONCLUSION: This study provides convincing evidence that the NGS-based panel can serve as a reliable tool for various forensic applications. Moreover, it has helped to enhance our knowledge about the genetic landscape of the Chinese Korean ethnic group.

Forensic validation of a combined analysis of mRNA and miRNA markers for precise tissue origin inferences of five kinds of body fluids by RT-qPCR.

Correctly inferring the tissue origin types of forensic-relevant body fluids left at a crime scene is beneficial for reconstructing a crime scene. However, it is still a challenge to accurately identify different kinds of body fluids at a crime scene. Shorter sequence length and anti-degradation microRNA (miRNA) can be used to infer the tissue sources of biological fluid traces, but a limited number of miRNAs are tissue specific. The application of messenger RNA (mRNA) has been confirmed by different studies based on its high tissue specificity. According to the differential expression features of mRNA or miRNA in forensically relevant body fluids, this study developed a simultaneously reversed mRNA and miRNA system and then used these two types of RNAs for the determinations of five common kinds of body fluids. Compared with previously reported single kind of mRNA or miRNA assay, the combined mRNA and miRNA system showed good advantages for human body fluid identifications, especially it could be applied in mixed samples. In conclusion, the obtained results indicated that this combined mRNA and miRNA system might provide a scientific and accurate reference for body fluid identifications.