Forensic Scenarios Research Articles

DNA Methylation: Bridging life’s experience and genetics within forensic scenario

DNA serving as the “blueprints of life” is a complex found in all biological cells carrying the genetic instructions for development and functioning of the organism. Inheritance of unique combination of genetic polymorphism results in DNA profile. In past few decades, the field of forensic genetics has witnessed several advancements from the radio-labelled DNA probes to the Short Tandem Repeats (STR) and Single Nucleotide Polymorphism (SNP) that have fostered the emergence of biological materials as most reliable evidences at a crime scene for the purpose of human identification but then, are inadequate in distinguishing monozygotic twins. Also, these techniques are of unavailing in providing informations such as tissue-specificity of the DNA source, phenotypic identification, and age estimation. Epigenetics, particularly DNA methylation is evolving as a promising technique to overcome such drawbacks of conventional profiling techniques.

Age estimation by evaluation of obliteration of the palatine sutures: a scoping review.

The age estimation (AE) of human remains is a challenging task since it is dependent on the state in which these remains are found. Since the macroscopic evaluation of palatal sutures has been proposed as a method for AE, the aim of this study was to review the literature on this method, considering that the cases of edentulous elderly are among the greatest challenges in anthropological and forensic contexts. A scoping review was performed using a specific search strategy in PubMed, Web of Science, SciELO, LILACS, and Google Scholar. The search identified 13 articles, among which the USA yielded the most information with 3 articles. Only 1 study was identified in Latin America (Peru). There was great diversity regarding the origin of samples, and the studies were carried out on both historical and modern populations. Only 6 articles exceeded the average sample size (168.08) and 4 articles studied samples of fewer than 100 individuals. Although 6 different methods were identified, Mann et al.'s revised method was the most used. The selection of appropriate methods for AE depends on what skeletal elements are present and the general age of the specimens. Although evaluation of the obliteration of the palatal sutures has been found to be simple and promising for AE in individuals over 60years of age, this method has been reported to have less precision than other more complex methods, which makes the use of a combination of methods necessary to increase the level of confidence and the percentage of success. Further research could resolve this weakness, and methodological refinement (perhaps the digitization and automation of processes, or the application of Bayesian methodology) could provide the necessary solidity to comply with international standards in the forensic scenario.

Toxicological Analysis of Drugs in Human Mummified Bodies and Proposed Guidelines.

From palaeopathology to forensic taphonomy, mummified human bodies constitute biological archives of paramount importance. Toxicology analysis of endobiotics and xenobiotics has already shown value to archaeological mummies research with detecting heavy metals, sedative-hypnotic drugs, and stimulants. Thanks to the large window of drug detection in hair and nails, the information from such studies has increased the scientific community's knowledge regarding past populations' lifestyles. Still, few bibliographic references exist regarding toxicology reports in mummified bodies from forensic settings. Here, the authors aim to draw attention to the valuable contribution of toxicology analysis, taking into account previously conducted studies and their findings. Given that sample collection on mummified bodies from forensic scenarios may not always happen in laboratories or autopsy rooms, the authors also suggest guidelines for in situ sampling of forensic mummies. It is expected that the present technical note will encourage experts to perform toxicology analysis in mummified bodies and publish their case reports more often.

Identification parade in immersive virtual reality - A technical setup

Virtual Reality (VR) has sparked interest within the forensic community, where it is currently used for training purposes and in variety of forensic scenarios. In combination with efficient and user friendly full body 3-Dimensional (3D) documentation methods, VR visualisations present a viable tool for suspect witness identification. The well-known procedure of placing several persons in a room with a one-way-mirror, along with a witness on the other side of the mirror has practical disadvantages. The primary concern implicates the witness(s) and person(s) of interest coming face-to-face prior to the line-up, combined with finding sufficient persons to include within the line-up. Although image identification using printed paper partially resolved this problem, features such as body stature also marks an issue for the recognition and identification process.To test whether VR provides the technical capabilities to perform an identification parade, a total of 15 subjects were 3D documented using the multi-camera device “Photobox”. From this group, one of the documented persons then interrupted a lecture, where consequently, the students were asked afterwards to identify the same person in VR and paper identification sets. It was found that the participating students were able to identify the “suspect” in both datasets. The results imply that VR technology allow users to identify persons. However, as this is a preliminary study the similarity problem was not analysed in this paper and requires further investigation to demonstrate the robustness of this approach.

Physical visualization and squalene-based scanning electrochemical microscopy imaging of latent fingerprints on PVDF membrane.

Fingerprints have long been the gold standard for personal identification in forensic science. However, realizing the high-resolution enhancement of eccrine LFPs is difficult using the traditional methods and the label-free detection of fingerprint residue information is also challenging. Herein, we propose two enhancement strategies for LFPs on PVDF membrane (LFPs/PVDF) using blue-black ink staining and scanning electrochemical microscopy (SECM). The blue-black ink staining method was used for the first time to develop three types (sebaceous, natural and eccrine) of LFPs/PVDF based on the difference in wettability between the fingerprint residues and PVDF membrane. The enhanced fingerprints clearly displayed levels 1-3 features with high contrast and low background interference. Furthermore, we achieved chemical imaging of the LFP/PVDF samples, where their possible visualization mechanisms were ascribed to the electrochemical reactivity of squalene and difference in wettability between the LFP and PVDF membrane, which was first proposed and investigated by SECM imaging and water contact angle (WCA) measurements, respectively. Significantly, SECM imaging not only provided fingerprint patterns without any labelling but also revealed the spatial distribution information of squalene in LFPs simultaneously. In addition, it was also demonstrated that LFPs deposited on various surfaces were first successfully transferred to the PVDF membrane, and then further developed with both methods, making them general for personal identity-related applications. Taken together, the blue-black ink staining method can easily and quickly obtain level 3 features of LFPs/PVDF and the SECM approach can non-invasively image the topography and chemical information of LFPs/PVDF, and thus they can be potentially selected according to various requirements in forensic scenarios.

Large-scale digital forensic investigation for Windows registry on Apache Spark.

In this study, we investigate large-scale digital forensic investigation on Apache Spark using a Windows registry. Because the Windows registry depends on the system on which it operates, the existing forensic methods on the Windows registry have been targeted on the Windows registry in a single system. However, it is a critical issue to analyze large-scale registry data collected from several Windows systems because it allows us to detect suspiciously changed data by comparing the Windows registry in multiple systems. To this end, we devise distributed algorithms to analyze large-scale registry data collected from multiple Windows systems on the Apache Spark framework. First, we define three main scenarios in which we classify the existing registry forensic studies into them. Second, we propose an algorithm to load the Windows registry into the Hadoop distributed file system (HDFS) for subsequent forensics. Third, we propose a distributed algorithm for each defined forensic scenario using Apache Spark operations. Through extensive experiments using eight nodes in an actual distributed environment, we demonstrate that the proposed method can perform forensics efficiently on large-scale registry data. Specifically, we perform forensics on 1.52 GB of Windows registry data collected from four computers and show that the proposed algorithms can reduce the processing time by up to approximately 3.31 times, as we increase the number of CPUs from 1 to 8 and the number of worker nodes from 2 to 8. Because the distributed algorithms on Apache Spark require the inherent network and MapReduce overheads, this improvement of the processing performance verifies the efficiency and scalability of the proposed algorithms.

Likelihood ratio to evaluate handwriting evidence using similarity index

Abstract Previous methods to evaluate evidence from handwriting examinations were usually associated with a redefinition of how these examinations are to be made. Here we propose the likelihood ratio method for handwriting evidence evaluation which is fully compatible with the current handwriting examination protocols. The method is focused on the similarity between handwriting samples, quantified using Jaccard index from results of a usual forensic handwriting comparison. The numerator of the likelihood ratio is the probability of a given class of similarity, assuming that a given person wrote the questioned sample. The denominator is the probability of the same class of similarity, assuming that a randomly selected person wrote questioned sample. The similarity distribution to quantify the numerator is derived from comparisons across reference handwritings. To calculate the denominator we propose to develop similarity distributions relevant for particular forensic scenarios. In the proof-of-a-concept study, we developed the distribution for the simulation scenario.

Age estimation using London Atlas methodology: A systematic review and meta-analysis

Age estimation is a fundamental competence of Forensic Anthropologists and Odontologists. The London Atlas is a dental development chart by AlQahtani et al. (2010) that gained recent notoriety due to its applicability in forensic scenarios. This study aimed to answer, by a systematic review of literature and meta-analysis, the following question: “on average, what is the deviation between real and estimated ages, when applying the London Atlas method in sub-adults?”. This study was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in the International Prospective Register of Systematic Reviews (PROSPERO). Five electronic databases were screened (PubMed, SciELO, Scopus, Web of Science, and LILACS), and active search was carried out. The quality assessment was performed by means of Joanna Briggs Institute Critical Appraisal Tools for Systematic Reviews. The initial search resulted in 1021 studies, from which 24 filled the inclusion criteria. For the meta-analysis, 17 studies provided sufficient data. Out of these, eleven studies enabled meta-analysis of mean absolute difference values. Standardized mean differences were 0.02 years for MD and 0.78 for MAD. Analysis of subgroups was also accomplished by sex, and did not indicated heterogeneity between males and females. The London Atlas is an accurate age estimation method, presenting acceptable error and bias values worldwide. Despite the high heterogeneity of the studies, majority of studies presented a low risk of bias. Meta-analysis showed a non-significant and slight tendency of overestimating age, in total. Sub-group analysis showed modestly better results for boys than girls.

Molar pregnancy unveiled by DNA profiling: a rare forensic case study

BackgroundForensic DNA analysis is one of the most advanced tools in the criminal investigation. It is used successfully in solving offenses involving rape, paternity disputes, murder or attempt to murder, and dacoity as well as identification of mutilated body remains. DNA profiling is used to determine paternity in sexual offense cases where abortion takes place and the product of conception can be anywhere from 6 to 10 weeks of gestation to 8 months. In the present case, a tissue sample stated as a vesicular mole and blood samples of the mother and suspected father were submitted to the DNA division of our laboratory for paternity analysis.ResultsGenotyping results revealed a single allele at all the tested short tandem repeat (STR) loci. The allele obtained at each locus was common with the suspected father. Such type of genotype was very rare and not observed earlier; therefore, repeated analysis was done and the same genotype was obtained every time. DNA profiling revealed all the alleles in the vesicular mole to be of paternal origin only, devoid of any maternal alleles. After referring to books on gynecology, it was confirmed that the genotype obtained was of hydatidiform mole.ConclusionsIn this POCSO Act case, the product of conception (about 1.5 months old) was termed a vesicular mole, and blood samples of the mother and suspected father were sent for the DNA paternity test. STR profiling of the product of conception sample displayed no maternal tissue contamination and non-inheritance of maternal alleles, showing the case to be of molar pregnancy also called hydatidiform mole, a very rare phenomenon in the forensic scenario. After thorough analysis, the case was reported and it was the first of its kind to be reported in a forensic laboratory in Maharashtra, India.

Beyond PRNU: Learning Robust Device-Specific Fingerprint for Source Camera Identification.

Source-camera identification tools assist image forensics investigators to associate an image with a camera. The Photo Response Non-Uniformity (PRNU) noise pattern caused by sensor imperfections has been proven to be an effective way to identify the source camera. However, the PRNU is susceptible to camera settings, scene details, image processing operations (e.g., simple low-pass filtering or JPEG compression), and counter-forensic attacks. A forensic investigator unaware of malicious counter-forensic attacks or incidental image manipulation is at risk of being misled. The spatial synchronization requirement during the matching of two PRNUs also represents a major limitation of the PRNU. To address the PRNU’s fragility issue, in recent years, deep learning-based data-driven approaches have been developed to identify source-camera models. However, the source information learned by existing deep learning models is not able to distinguish individual cameras of the same model. In light of the vulnerabilities of the PRNU fingerprint and data-driven techniques, in this paper, we bring to light the existence of a new robust data-driven device-specific fingerprint in digital images that is capable of identifying individual cameras of the same model in practical forensic scenarios. We discover that the new device fingerprint is location-independent, stochastic, and globally available, which resolves the spatial synchronization issue. Unlike the PRNU, which resides in the high-frequency band, the new device fingerprint is extracted from the low- and mid-frequency bands, which resolves the fragility issue that the PRNU is unable to contend with. Our experiments on various datasets also demonstrate that the new fingerprint is highly resilient to image manipulations such as rotation, gamma correction, and aggressive JPEG compression.

In depth investigation of the capabilities and limitations of combined proteomic-MALDI MS based approach for the forensic detection of blood

For the past 7 years, Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) based methods have been developed and published for the forensic detection of blood in stains and fingermarks. However, in the view of adoption in an operational context, further investigation into the capabilities and limitations of this approach must be conducted. The refinement and testing of this approach must also be tailored to the requirements of the end users, enabling them to address the specific circumstances most encountered in a forensic scenario. The present study delves deeper into the assessment of the applicability of MALDI MS based strategy for the reliable and robust detection of human blood through: (i) a semi-qualitative assessment of the sensitivity of the method, (ii) a wider investigation of the compatibility of the method with the prior application of commonly used presumptive tests and (iii) assessment of the specificity of the method (when blood is present in mixture with other biofluids) and of its robustness, by assessing blood detection from a range of porous materials. The findings strengthen the evidence supporting the adoption of MALDI MS based approaches as a confirmatory test for the forensic detection of human blood in an operational context.

A Comprehensive Characterization of Small RNA Profiles by Massively Parallel Sequencing in Six Forensic Body Fluids/Tissue.

Body fluids/tissue identification (BFID) is an essential procedure in forensic practice, and RNA profiling has become one of the most important methods. Small non-coding RNAs, being expressed in high copy numbers and resistant to degradation, have great potential in BFID but have not been comprehensively characterized in common forensic stains. In this study, the miRNA, piRNA, snoRNA, and snRNA were sequenced in 30 forensic relevant samples (menstrual blood, saliva, semen, skin, venous blood, and vaginal secretion) using the BGI platform. Based on small RNA profiles, relative specific markers (RSM) and absolute specific markers (ASM) were defined, which can be used to identify a specific body fluid/tissue out of two or six, respectively. A total of 5204 small RNAs were discovered including 1394 miRNAs (including 236 novel miRNA), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs. RSMs for 15 pairwise body fluid/tissue groups were discovered by differential RNA analysis. In addition, 90 ASMs that were specifically expressed in a certain type of body fluid/tissue were screened, among them, snoRNAs were reported first in forensic genetics. In brief, our study deepened the understanding of small RNA profiles in forensic stains and offered potential BFID markers that can be applied in different forensic scenarios.

Sexual Dimorphism of Cranial Morphological Traits in an Italian Sample: A Population-Specific Logistic Regression Model for Predicting Sex.

Simple SummaryDespite the fact that sex estimation methods from crania are very popular in forensic anthropology, few validation studies have verified their accuracy and reliability in different populations. Different from craniometrics, for which validation studies have remarkably increased lately, the methods based on cranial morphology still need to be thoroughly investigated, even if a large consensus exists on the effects of population variability on sexual cranial dimorphism. When dealing with forensic contexts, appropriately-validated methods should be applied for building accurate biological profiles. Since the possible sexual dimorphism variation of cranial morphological traits needs to be evaluated properly in various populations, in this study, we analyzed the accuracy of existing regression models for predicting sex from cranial morphological traits in an Italian contemporary/modern population. In addition, we propose new logistic regression models that are more accurate and specific for our sample. The results also update the reference standards for populations of this geographical area and provide an additional important warning on sexual dimorphism to anthropologists working in forensic contexts.Although not without subjectivity, the cranial trait scoring method is an easy visual method routinely used by forensic anthropologists in sex estimation. The revision presented by Walker in 2008 has introduced predictive models with good accuracies in the original populations. However, such models may lead to unsatisfactory performances when applied to populations that are different from the original. Therefore, this study aimed to test the sex predictive equations reported by Walker on a contemporary Italian population (177 individuals) in order to evaluate the reliability of the method and to identify potential sexual dimorphic differences between American and Italian individuals. In order to provide new reference data to be used by forensic experts dealing with human remains of modern/contemporary individuals from this geographical area, we designed logistic regression models specific to our population, whose accuracy was evaluated on a validation sample from the same population. In particular, we fitted logistic regression models for all possible combinations of the five cranial morphological traits (i.e., nuchal crest, mastoid process, orbital margin, glabella, and mental eminence). This approach provided a comprehensive set of population-specific equations that can be used in forensic contexts where crania might be retrieved with severe taphonomic damages, thus limiting the application of the method only to a few morphological features. The results proved once again that the effects of secular changes and biogeographic ancestry on sexual dimorphism of cranial morphological traits are remarkable, as highlighted by the low accuracy (from 56% to 78%) of the six Walker’s equations when applied to our female sample. Among our fitted models, the one including the glabella and mastoid process was the most accurate since these features are more sexually dimorphic in our population. Finally, our models proved to have high predictive performances in both training and validation samples, with accuracy percentages up to 91.7% for Italian females, which represents a significant success in minimizing the potential misclassifications in real forensic scenarios.

Distinguishing natural and computer generated images using Multi-Colorspace fused EfficientNet

The problem of distinguishing natural images from photo-realistic computer generated ones either addresses natural images versus computer graphics or natural images versus GAN images at a time. But in a real-world image forensic scenario, it is highly essential to consider all categories of image generation since in most cases image generation is unknown. We for the first time to our best knowledge, approach the problem of distinguishing natural images from photo-realistic computer generated images as a three-class classification task classifying natural, computer graphics and GAN images. For the task, we propose a Multi-Colorspace fused EfficientNet model by parallelly fusing three EfficientNet networks that follow transfer learning methodology where each of the three networks operates in a different colorspace, one in RGB, the other in LCH and the last in HSV that are chosen after analyzing the efficacy of various colorspace transformations in this image forensics problem. Our model outperforms the baselines in terms of accuracy, robustness towards post-processing and generalizability towards other datasets. We conduct psychophysics experiments to understand how accurately humans can distinguish natural, computer graphics and GAN images where we could observe that humans find difficulty in classifying these images, particularly the computer generated images, indicating the necessity of computational algorithms for the task. We also analyze the behavior of our model through visual explanations to understand salient regions that contribute to model’s decision making and compare with manual explanations provided by human participants in the form of region markings where we could observe similarities in both the explanations indicating powerful nature of our model to take the decisions meaningfully.

Profiling and imaging of forensic evidence – A pan-European forensic round robin study part 1: Document forgery

The forensic scenario, on which the round robin study was based, simulated a suspected intentional manipulation of a real estate rental agreement consisting of a total of three pages. The aims of this study were to (i) establish the amount and reliability of information extractable from a single type of evidence and to (ii) provide suggestions on the most suitable combination of compatible techniques for a multi-modal imaging approach to forgery detection. To address these aims, seventeen laboratories from sixteen countries were invited to answer the following tasks questions: (i) which printing technique was used? (ii) were the three pages printed with the same printer? (iii) were the three pages made from the same paper? (iv) were the three pages originally stapled? (v) were the headings and signatures written with the same ink? and (vi) were headings and signatures of the same age on all pages? The methods used were classified into the following categories: Optical spectroscopy, including multispectral imaging, smartphone mapping, UV-luminescence and LIBS; Infrared spectroscopy, including Raman and FTIR (micro-)spectroscopy; X-ray spectroscopy, including SEM-EDX, PIXE and XPS; Mass spectrometry, including ICPMS, SIMS, MALDI and LDIMS; Electrostatic imaging, as well as non-imaging methods, such as non-multimodal visual inspection, (micro-)spectroscopy, physical testing and thin layer chromatography. The performance of the techniques was evaluated as the proportion of discriminated sample pairs to all possible sample pairs. For the undiscriminated sample pairs, a distinction was made between undecidability and false positive claims. It was found that none of the methods used were able to solve all tasks completely and/or correctly and that certain methods were a priori judged unsuitable by the laboratories for some tasks. Correct results were generally achieved for the discrimination of printer toners, whereas incorrect results in the discrimination of inks. For the discrimination of paper, solid state analytical methods proved to be superior to mass spectrometric methods. None of the participating laboratories deemed addressing ink age feasible. It was concluded that correct forensic statements can only be achieved by the complementary application of different methods and that the classical approach of round robin studies to send standardised subsamples to the participants is not feasible for a true multimodal approach if the techniques are not available at one location.

Mapping the lie: A smallest space analysis of truthful and deceptive mock-informant accounts

Detecting informant deception is a key concern for law enforcement officers, with implications for resource-management, operational decision-making and protecting officers from risk of harm. However, the situational dilemma of a police informant, otherwise known as a Covert Human Intelligence Source (CHIS), is unique. Informants are tasked to obtain information about the transgressive actions or intentions of their associates, knowing they will later disclose this information to a handler. Thus, techniques for detecting deception in other forensic scenarios may not be transferrable to an informant interview. Utilising truthful and deceptive transcripts from a unique mock-informant role play paradigm, Smallest Space Analysis was used to map the co-occurrence of content themes. Results found that deceptive content frequently co-occurred with emotive and low-potency content themes. This provides support for the future analysis of verbal content when seeking to detect informant deception.

Eye Optics

Eye is the vital organ of the body and has been an area of interest in forensic scenario, eye can also act as a valuable forensic evidence as it can primarily aid in the postmortem interval estimation, therefore assists in identifying time since death. Moreover, the secretion from eye that is tears and eye wears also play major role in crime investigation. This review has aimed to highlight the scope and breadth of research into the field of forensic ophthalmology. We have discussed the current aspects which are existing in this discipline and also the imperative avenues for future perspectives.

Simultaneous detection of residual diazepam, ketamine, nimetazepam, and xylazine by high-performance liquid chromatography: application in drug-spiked beverages for forensic investigation

ABSTRACT Drug facilitated crimes (DFCs) involve the incapacitation of a victim due to the administration of a single drug or a combination of drugs. Traditionally, biological samples are collected from a victim and analysed to provide evidence of drug administration. However, the rapid metabolism of many such drugs together with delays in analysis can compromise the detection of such substances. This study investigated the capacity of a high-performance liquid chromatography (HPLC) method to detect, simultaneously, four sedative-hypnotic drugs, diazepam, ketamine, nimetazepam, and xylazine, recovered from spiked beverages. A HPLC method was developed and validated and was then applied to the detection of the target substances in simulate forensic case scenarios. The four target substances were well-separated (correlation coefficient, 0.99) while the limit of detection was determined to be 39.1 ng/mL (xylazine), 78.1 ng/mL (diazepam and nimetazepam), and 156.3 ng/mL (ketamine), respectively. Precision (%RSD <7.8%) and accuracy (95.3%–106.6% recovery) were also acceptable and good recoveries were achieved from the drug-spiked samples. In conclusion, a simple and direct HPLC method was successfully developed and applied to the recovery of sedative-hypnotic drugs from spiked beverages.

IPAS-Net: A deep-learning model for generating high-fidelity shoeprints from low-quality images with no natural references

Single image super-resolution (SISR) typically reconstructs higher-resolution (HR) images from the corresponding low-resolution (LR) images in the presence of natural HR images. SISR is highly important in generating high-quality images in forensic scenarios since it facilitates close investigation and examination of captured shoeprints. However, it becomes more challenging when there are no available natural HR ground truth images that correspond to the input LR images. In such cases, HR reconstruction becomes even more crucial for providing HR versions that retain the natural characteristics of shoeprints. For this purpose, we propose IPAS-Net, which utilizes U-Net for feature extraction, shares the learned parameters from LR space in HR space, and innovatively upscales, refines, and enhances the HR space via special treatments. The upsampling-and-refinement block comprises a parallel pipeline composed of attention mechanism block (AMB) and one-step-high-iteration (OSHI). All upsampling solutions are infused so that distinct upscaling can compensate each others’ weaknesses. The generated HR shoeprints are evaluated using blind/non-reference evaluation metrics, and the proposed method outperforms the state of the art (SOTA) deep learning modalities on low-quality shoeprints.

Microhaplotype and Y-SNP/STR (MY): A novel MPS-based system for genotype pattern recognition in two-person DNA mixtures

BackgroundsY-chromosomal haplotypes based on Y-short tandem repeats (STRs) and Y-single nucleotide polymorphisms/insertion and deletion polymorphisms (SNPs/InDels) are used to characterize paternal lineages of unknown male trace donors. However, Y-chromosomal genetic markers are not currently sufficient for precise individual identification. Microhaplotype (MH), generally < 200 bp on autosomes and consisting of two or more SNPs, was recently introduced in forensic genetics with the development of massive parallel sequencing technology and may facilitate identification and DNA mixture deconvolution. Therefore, combining the two kinds of genetic markers may be beneficial in many forensic scenarios, especially crime scenes with male suspects, such as sexual assault cases. MethodsIn the present study, we developed a novel MPS-based panel, Microhaplotype and Y-SNP/STR (MY), by multiplex PCR and 150-bp paired-end sequencing, including 114 Y-SNPs (twelve dominant Y-DNA haplogroups), 45 Y-STRs (N-1 stutter < 0.09; estimated mutation rate < 5 × 10−3), and 22 MHs (allele coverage ratio > 0.91; pairwise distance > 10 Mb). Additionally, MY system-based genotype pattern recognition (GPR), a regression-based method to identify the genotype pattern for each MH locus, is proposed for two-person DNA mixture deconvolution. We integrated 26 two-person genotype combinations into nine genotype patterns and validated the application range of GPR based on DNA profiles of ten sets of simulated male-male DNA mixtures (1:10–1:2). ResultsThe effective number of alleles (Ae) ranged from 3.62 to 14.72, with an average of 7.17, in 100 Chinese Guangdong Han individuals. The cumulative discrimination power was 1–5.00 × 10−31, and the cumulative power of exclusion was 1–5.00 × 10−8 and 1–4.85 × 10−12 for duo and trio paternity testing, respectively. Furthermore, the actual mixing ratio-depth of coverage (DoC) ratio (RDoC) regression relationships were established for different genetic markers and genotype patterns. In five overlapping areas, genotype differentiation of the major and minor contributors required likelihood ratio methods. In nonoverlapping areas, the genotype pattern could be recognized by comparing the observed RDoC and RDoC ranges. ConclusionThe GPR can be used to deconvolute two-person DNA mixtures (application range: 1:10–1:2) for individual identification.