Individual identification in acoustic recordings.

Recent advances in bioacoustics combined with acoustic individual identification (AIID) could open frontiers for ecological and evolutionary research because traditional methods of identifying individuals are invasive, expensive, labor-intensive, and potentially biased. Despite overwhelming evidence that most taxa have individual acoustic signatures, the application of AIID remains challenging and uncommon. Furthermore, the methods most commonly used for AIID are not compatible with many potential AIID applications. Deep learning in adjacent disciplines suggests opportunities to advance AIID, but such progress is limited by training data. We suggest that broadscale implementation of AIID is achievable, but researchers should prioritize methods that maximize the potential applications of AIID, and develop case studies with easy taxa at smaller spatiotemporal scales before progressing to more difficult scenarios.

Accurate identification of individuals with subjective cognitive decline using 3D regional fractal dimensions on structural magnetic resonance imaging.

BACKGROUND AND OBJECTIVE: Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. METHODS: This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions. RESULTS: The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations. CONCLUSION: Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.

Deep learning for automatic facial detection and recognition in Japanese macaques: illuminating social networks.

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research has offered new methodological perspectives through the automatisation of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identification done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques' face detector (Faster-RCNN model), reaching an accuracy of 82.2% and (ii) the creation of an individual recogniser for the Kojima Island macaque population (YOLOv8n model), reaching an accuracy of 83%. We also created a Kojima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques.

Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability.

The functional connectivity (FC) graph of the brain has been widely recognized as a ``fingerprint'' that can be used to identify individuals from a group of subjects. Research has indicated that individual identification accuracy can be improved by eliminating the impact of shared information among individuals. However, current research extracts not only shared information of inter-subject but also individual-specific information from FC graphs, resulting in incomplete separation of shared information and fingerprint information among individuals, leading to lower individual identification accuracy across all functional magnetic resonance imaging (fMRI) states session pairs and poor cognitive behavior prediction performance. In this paper, we propose a method to enhance inter-subject variability combining conditional variational autoencoder (CVAE) network and sparse dictionary learning (SDL) module. By embedding fMRI state information in the encoding and decoding processes, the CVAE network can better capture and represent the common features among individuals and enhance inter-subject variability by residual. Our experimental results on Human Connectome Project (HCP) data show that the refined connectomes obtained by using CVAE with SDL can accurately distinguish an individual from the remaining participants. The success accuracies reached 99.7 % and 99.6 % in the session pair rest1-rest2 and reverse rest2-rest1, respectively. In the identification experiment involving task-task combinations carried out on the same day, the identification accuracies ranged from 94.2 % to 98.8 %. Furthermore, we showed the Frontoparietal and Default networks make the most significant contributions to individual identification and the edges that significantly contribute to individual identification are found within and between the Frontoparietal and Default networks. Additionally, high-level cognitive behaviors can also be better predicted with the obtained refined connectomes, suggesting that higher fingerprinting can be useful for resulting in higher behavioral associations. In summary, our proposed framework provides a promising approach to use functional connectivity networks for studying cognition and behavior, promoting a deeper understanding of brain functions.

Elusive mustelids-18 months in the search of near-threatened stoat (Mustela erminea) and weasel (M. nivalis) reveals low captures.

Stoat (Mustela erminea) and weasel (M. nivalis) are hard to monitor as they are elusive of nature and leave few identifying marks in their surroundings. Stoat and weasel are both fully protected in Denmark and are thought to be widely distributed throughout the country. Despite this stoat and weasel were listed on the Danish Red List as Near Threatened in 2019, as their densities and population trends are unknown. Using a modified novel camera trapping device, the Double-Mostela, a wooden box comprising a tracking tunnel and two camera traps, we attempted to obtain density estimates based on identification of individual stoats and weasels. We deployed camera traps both inside Double-Mostela traps and externally in three different study areas in northern Zealand, Denmark, and tested commercial, American scent-based lures to attract stoat and weasel. We obtained very low seasonal trapping rates of weasel in two study areas, but in one study area, we obtained a seasonal trapping rate of stoat larger compared to another study using the Mostela. In one study area, both species were absent. We observed no effect of scent-based lures in attracting small mustelids compared to non-bait traps. Potential reasons behind low capture rates of weasel and stoat are suboptimal habitat placement and timing of deployment of the Double-Mostelas, land-use changes over the last 200 years, predation from larger predators, as well as unintended secondary poisoning with rodenticides. Due to the scarcity of weasel and stoat captures, we were unable to make density estimates based on identification of individuals; however, we identified potential features that could be used for identification and density estimates with more captures.

Development and validation of a novel 30-plex STR assay for canine individual identification and parentage testing.

Domestic dogs are helpers in outdoor human work and companions for families; thus, individual canine identification and parentage testing are crucial in certain fields, including forensics and breeding programs. In this study, a six-dye fluorescent labeling multiplex amplification system containing 29 canine short tandem repeats (STRs) and the sex-determining marker DAmel was developed. The system was called the Tronfo Canine 30-plex STR Kit and was further validated according to the Scientific Working Group on DNA Analysis Methods and the Organization of Scientific Area Committees for Wildlife Forensics guidelines, including tests for PCR conditions, precision, species specificity, sensitivity, stability, repeatability and reproducibility, a population study, and a study of 16 paternity test cases. The results indicated that the novel canine STR assay was accurate, specific, reproducible, stable, and robust. Complete profiles were obtained with 31.25 pg of canine DNA. Additionally, 500 unrelated canine individuals were investigated using this novel system, and the combined power of discrimination and exclusion values were 0.999999999999999999 and 0.999996451039850, respectively. These results suggest that the Tronfo Canine 30-plex STR Kit is highly polymorphic, informative, and suitable for individual canine identification and parentage testing.

Optimizing Bangkaew dog breed identification using DNA technology.

BACKGROUND: The Bangkaew dog is an indigenous dog breed in the Phitsanulok province of Thailand. This breed is recognized by the Fédération Cynologique Internationale (FCI), a global canine organization. The unique traits of the Bangkaew breed lead to purebred selection for breeding, while only their traits and pedigree from parental history are recorded. Determination of the risk of inbreeding depression and the origin of unknown DNA profiles is essential due to the challenges in predicting puppy characteristics, which are crucial for breed management and conservation. OBJECTIVE: This study aimed to emphasize that current allelic frequency data for the Bangkaew dog breed must be considered for precise individual identification. METHODS: Approximately 82 Bangkaew dogs from various Thai localities were studied using 15 microsatellite markers for genotypic monitoring and individual identification. Maternal genetic inheritance was assessed via mtDNA D-loop analysis. RESULTS: The results revealed high genetic diversity in the Bangkaew breed, indicating low potential for inbreeding. We also found that using a 15 loci microsatellite panel was effective for the identification of Bangkaew dogs. The optimized 10 loci microsatellite genotyping panel developed in this study presents improved identification testing efficiency, promoting both time- and cost-effectiveness. CONCLUSION: Analysis of microsatellite DNA markers in Bangkaew dogs using an optimized panel of 10 loci selected from 15 loci effectively facilitated individual identification. This approach not only enhances time and cost efficiency, but also provides accurate allelic frequency estimates, which are crucial for the realistic evaluation of DNA evidence.

Systematical explorations of forensic feature and population genetic diversity of the Chinese Mongolian group from northwest China via a self-constructed Multi-InDel panel.

This study aimed to investigate the genetic polymorphisms and population characteristics of Chinese Mongolian group from northwest China (NCM) through a self-developed panel including 43 autosomal insertion/deletion (A-InDel) polymorphism genetic markers. Herein, 288 unrelated healthy individuals from the NCM group were employed to obtain the genetic data of 43 A-InDels through multiplex PCR amplification and InDel genotyping using capillary electrophoresis platform. In addition, multiplex population genetic analyses were performed between the NCM group and 27 reference populations. There were no deviations at 43 loci from Hardy-Weinberg equilibrium in the NCM group. The observed heterozygosity (Ho) values ranged from 0.312 8 to 0.559 2, and the combined power of discrimination (CPD) and cumulative probability of exclusion (CPE) values in the NCM group were 0.999 999 999 999 999 998 77 and 0.999 814, respectively. The forensic parameter values indicated that this panel was polymorphic and informative in the NCM group and could be used as an effective tool for forensic personal identification. Furthermore, the results of pairwise genetic distances, principal component analysis, multidimensional scaling analysis, phylogenetic tree construction, and admixture analysis among the NCM group and 27 reference populations revealed that there were closer genetic relationships between the NCM group and East Asian populations, especially Chinese Hui group (CHH) from the northwest China, which is consistent with the geographical location. These present findings contributed to the ongoing genetic explorations and insights into the genetic architecture of the NCM group.

Establishment and Application of a 42-plex Microhaplotype Assay in Forensic Genetics.

OBJECTIVES: To establish and forensically verify a 42 microhaplotypes (mircohaps, MHs) multiplex assay system based on next-generation sequencing (NGS), and to explore the application value of this system in the practice of forensic genetics. METHODS: A total of 42 highly polymorphic MHs were selected from previous studies, and sequenced by the MiSeq FGxTM platform to verify the repeata-bility, sensitivity, specificity, stability, and mixture analysis ability of the detection system. Through population genetic investigation of 102 unrelated Chinese Han individuals in Liyang City, Jiangsu Province, China, the application value of this system in forensic genetics was evaluated. RESULTS: The sequencing repeatability of the 42-plex MHs assay was 100% and the sensitivity was as low as 0.062 5 ng. The system had the ability to withstand the interference of indigo (≤2 500 ng/µL), humic acid (≤9 ng/µL), hemoglobin(≤20 µmol), and urea (≤200 ng/µL) and to detect mixtures of 2 people (1∶19), 3 people (1∶1∶9) and 4 people (1∶1∶1∶9). Based on 102 individual data, the combined power of discrimination and the combined power of exclusion were 1-3.45×10-30 and 1-3.77×10-11, respectively, and the average effect value of alleles was 2.899. CONCLUSIONS: The 42-plex MHs assay was successfully established in this study and this system has high repeatability and sensitivity, good anti-jamming ability and mixture analysis ability. The 42 MHs are highly polymorphism and have good application value in individual identification and paternity testing.

Research Progress on Biological Evidence Identification in Fire Scenes.

Biological evidence is relatively common evidence in criminal cases, and it has strong probative power because it carries DNA information for individual identification. At the scene of fire-related cases, the complex thermal environment, the escape of trapped people, the firefighting and rescue operations, and the deliberate destruction of criminal suspects will all affect the biological evidence in the fire scene. Scholars at home and abroad have explored and studied the effectiveness of biological evidence identification in fire scenes, and found that the blood stains, semen stains, bones, etc. are the main biological evidence which can be easily recovered with DNA in fire scenes. In order to analyze the research status and development trend of biological evidence in fire scenes, this paper systematically sorts out the relevant research, mainly including the soot removal technology, appearance method of typical biological evidence, and possibility of identifying other biological evidence. This paper also prospects the next step of research direction, in order to provide reference for the identification of biological evidence and improve the value of biological evidence in fire scenes.

The Latest Research Progress on Cell-Free DNA and Prospects of Its Forensic Application.

In recent years, with the continuous progress of DNA extraction and detection technology, cell-free DNA(cfDNA)has been widely used in the life science field, and its potential application value in forensic identification is becoming more and more obvious. This paper reviews the concept, formation mechanism, and classification of cfDNA, etc., and describes the latest research progress of cfDNA in personal identification of crime scene touch DNA samples and non-invasive prenatal paternity testing (NIPPT). Meanwhile, this paper summarizes the potential application of cfDNA in injury inference, and discusses the advantages and disadvantages of common cfDNA analysis methods and techniques, and its application prospects, to provide a new idea for the wide application of cfDNA in the field of forensic science.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification.

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

Population genetic analyses of Eastern Chinese Han nationality using ForenSeq™ DNA Signature Prep Kit.

Currently, the most commonly used method for human identification and kinship analysis in forensic genetics is the detection of length polymorphism in short tandem repeats (STRs) using polymerase chain reaction (PCR) and capillary electrophoresis (CE). However, numerous studies have shown that considerable sequence variations exist in the repeat and flanking regions of the STR loci, which cannot be identified by CE detection. Comparatively, massively parallel sequencing (MPS) technology can capture these sequence differences, thereby enhancing the identification capability of certain STRs. In this study, we used the ForenSeq™ DNA Signature Prep Kit to sequence 58 STRs and 94 individual identification SNPs (iiSNPs) in a sample of 220 unrelated individuals from the Eastern Chinese Han population. Our aim is to obtain MPS-based STR and SNP data, providing further evidence for the study of population genetics and forensic applications. The results showed that the MPS method, utilizing sequence information, identified a total of 486 alleles on autosomal STRs (A-STRs), 97 alleles on X-chromosome STRs (X-STRs), and 218 alleles on Y-chromosome STRs (Y-STRs). Compared with length polymorphism, we observed an increase of 260 alleles (157, 31, and 72 alleles on A-STRs, X-STRs, and Y-STRs, respectively) across 36 STRs. The most substantial increments were observed in DYF387S1 and DYS389II, with increases of 287.5% and 250%, respectively. The most increment in the number of alleles was found at DYF387S1 and DYS389II (287.5% and 250%, respectively). The length-based (LB) and sequence-based (SB) combined random match probability (RMP) of 27 A-STRs were 6.05E-31 and 1.53E-34, respectively. Furthermore, other forensic parameters such as total discrimination power (TDP), cumulative probability of exclusion of trios (CPEtrio), and duos (CPEduo) were significantly improved when using the SB data, and informative data were obtained for the 94 iiSNPs. Collectively, these findings highlight the advantages of MPS technology in forensic genetics, and the Eastern Chinese Han genetic data generated in this study could be used as a valuable reference for future research in this field.

Genetic polymorphism analysis and forensic application evaluation of 57 insertion/deletion polymorphisms from Yi ethnic group in Yunnan.

BACKGROUND: As a new kind of diallelic genetic marker, insertion/deletion (InDel) polymorphisms have recently been used in forensic science. However, there are relatively few studies on the forensic evaluation of InDel genetic polymorphisms from different populations. AIM: The aim of the present work is to assess the genetic polymorphism and forensic applicability of 57 InDels from the Yi ethnic group and explore the genetic background of this group. SUBJECTS AND METHODS: A total sample of 122 unrelated individuals of Yi group from the Yunnan province were genotyped by the AGCU indel 60 Kit. Multiplex population genetic analyses on the same 57 InDels were carried out among the Yunnan Yi group and 29 reference populations. RESULTS: The average allele frequency of these loci in the Yi ethnic group was 0.485. Heterozygosity, polymorphism information content, and the power of discrimination were 0.477, 0.362, and 0.612, respectively. The combined power of discrimination and the combined power of exclusion reached to 0.99999999999999999669 and 0.999962965, respectively. The results showed that 57 InDels polymorphisms have high genetic polymorphisms in the Yi ethnic group. CONCLUSIONS: The 57 InDels could be used for forensic individual identification, paternity testing, and intercontinental population discrimination, with the potential for use in biogeographic ancestry inference.

Individual genotypes from environmental DNA: Fingerprinting snow tracks of three large carnivore species.

Continued advancements in environmental DNA (eDNA) research have made it possible to access intraspecific variation from eDNA samples, opening new opportunities to expand non-invasive genetic studies of wildlife populations. However, the use of eDNA samples for individual genotyping, as typically performed in non-invasive genetics, still remains elusive. We present successful individual genotyping of eDNA obtained from snow tracks of three large carnivores: brown bear (Ursus arctos), European lynx (Lynx lynx) and wolf (Canis lupus). DNA was extracted using a protocol for isolating water eDNA and genotyped using amplicon sequencing of short tandem repeats (STR), and for brown bear a sex marker, on a high-throughput sequencing platform. Individual genotypes were obtained for all species, but genotyping performance differed among samples and species. The proportion of samples genotyped to individuals was higher for brown bear (5/7) and wolf (7/10) than for lynx (4/9), and locus genotyping success was greater for brown bear (0.88). The sex marker was typed in six out of seven brown bear samples. Results for three species show that reliable individual genotyping, including sex identification, is now possible from eDNA in snow tracks, underlining its vast potential to complement the non-invasive genetic methods used for wildlife. To fully leverage the application of snow track eDNA, improved understanding of the ideal species- and site-specific sampling conditions, as well as laboratory methods promoting genotyping success, is needed. This will also inform efforts to retrieve and type nuclear DNA from other eDNA samples, thereby advancing eDNA-based individual and population-level studies.

Discovering individual fingerprints in resting-state functional connectivity using deep neural networks.

Non-negligible idiosyncrasy due to interindividual differences is an ongoing issue in resting-state functional MRI (rfMRI) analysis. We show that a deep neural network (DNN) can be employed for individual identification by learning important features from the time-varying functional connectivity (FC) of rfMRI in the Human Connectome Project. We employed the trained DNN to identify individuals from an independent dataset acquired at our institution. The results revealed that the DNN could successfully identify 300 individuals with an error rate of 2.9% using 15 s time-window and 870 individuals with an error rate of 6.7%. A trained DNN with nonlinear hidden layers led to the proposal of the "fingerprint of FC" (fpFC) as representative edges of individual FC. The fpFCs for individuals exhibited commonly important and individual-specific edges across time-window lengths (from 5 min to 15 s). Furthermore, the utility of our model for another group of subjects was validated, supporting the feasibility of our technique in the context of transfer learning. In conclusion, our study offers an insight into the discovery of the intrinsic mode of the human brain using whole-brain resting-state FC and DNNs.

Process of Forensic Medicine in DNA Identification of Aged Human Remains.

Skeleton and teeth are important biological samples. Due to their special structure and strong ability to resist degradation, they are ideal biological materials to retain DNA under natural condition. In many cases, such as historical figure identification, aged skeleton and teeth are usually the only biological samples. However, their DNA is in a state of trace, damage and degradation to different degrees, which requires special experimental treatment to achieve identification. This paper reviews the sample selection, DNA extraction, DNA enrichment and analysis approaches based on relevant research reports in recent years, aiming to promote the further development and improvement of the aged skeleton and teeth identification system.

Developmental validation of a novel multiple genotyping assay with 24 Canine STR loci.

Canine individual identification and parentage testing are essential in various fields, including forensics and breeding programs. This study aimed to develop and validate the Canine 25 A kit, a multiplex polymerase chain reaction (PCR) system designed to address these critical requirements. This novel system enables the simultaneous amplification of 24 canine autosomal short tandem repeat (STR) loci and one sex-determining marker. Validation of the Canine 25 A kit was conducted following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, demonstrating significant sensitivity, high inhibitor tolerance, canine specificity within a mixture, species specificity, and precision in genotype determination. The Canine 25 A kit was crucial in resolving several forensic cases, such as casework samples from a dog attack incident and parentage determination. Its effectiveness in genotyping these samples highlights its significance in forensic applications. Population genetic parameter analysis revealed a high discriminatory power, as indicated by the calculated combined discrimination power (CDP) values for each breed exceeding 0.999 999 999 999, while the combined power of exclusion (CPE) surpassed 0.9999. Overall, the Canine 25 A kit offers a precise and dependable tool for canine individual identification and parentage determination.

3D-3D dentition superimposition for individual identification: A study of an Eastern Chinese population.

Recently, 3D dental intraoral scanning technology has been developed rapidly and applied widely in everyday dental practice. Since 3D dental scanning could provide valuable personal information, it enabled researchers to develop novel procedures for individual identification through 3D-3D dentition superimposition. This study aimed to test the applicability of this method in an Eastern Chinese population and propose a threshold for personal identification. For this purpose, 40 volunteers were recruited, and the initial 80 (upper and lower) 3D intraoral scans (IOS) were collected. After one year, 80 IOS of these volunteers were repeatedly collected. In addition, the other 120 IOS of 60 patients were extracted from the database. The 3D models were trimmed, aligned, and superimposed via Geomagic Control X software, and then the root mean square (RMS) value of point-to-point distance between the two models was calculated. The superimposition of two IOS belonging to the same individual was considered as a match, and superimposition of two IOS belonging to different individuals was considered as a mismatch. Totally, superimpositions of 80 matches and 3120 mismatches were obtained. Intra- and inter-observer errors were assessed through the calculation of relative technical error of measurement (rTEM). Mann-Whitney U test verified possible statistically significant differences between matches and mismatches (P < 0.05). The rTEM of intra- and inter-observer repeatability analyses was lower than 4.7 %. The range of RMS value was 0.05-0.18 mm in matches and 0.72-2.28 mm in mismatches without overlapping. The percentage of accurate identification reached 100 % in blind test through an arbitrary RMS threshold of 0.45 mm. The results indicated that individual identification through the 3D-3D dentition superimposition was effective in Eastern Chinese population. Successful identification could be achieved with high probability when the RMS value of the point-to-point distance of two dentitions is <0.45 mm.

A human identification system for hair shaft using RNA polymorphism.

Hair is one of the common pieces of evidence at crime scenes, with abundant mitochondrial DNA but limited nuclear DNA in its shaft. It also helps to narrow the investigation scope to maternal lineage but fails to provide unique individual information. We assumed that RNA in hair shafts would be an alternative resource used to perform human identification based on the facts that (1) RNA retains the polymorphic information; (2) the multi-copy of RNA in a cell resists degradation as compared to the one-copy of nuclear DNA. In this study, we explored the potential of RNA polymorphism in hair shafts for forensic individual identification. A SNaPshot typing system was constructed using 18 SNPs located on 11 genes (ABCA13, AHNAK, EXPH5, KMT2D, KRT35, PPP1R15A, RBM33, S100A5, TBC1D4, TMC5, TRPV2). The RNA typing system was evaluated for sensitivity, species specificity, and feasibility for aged hair samples. Hair samples from a Shanxi population in China were used for the population study of the system. The detection limit of the assay was 2 ng RNA. The CDP of these 11 genes was 0.999969 in the Shanxi population. We also identified the concordance of the RNA and DNA typing results. In summary, we developed an RNA typing method to perform human identification from hair shafts, which performed as accurately as nuclear DNA typing. Our method provides a potential basis for solving the human identification problem from hair shafts, as well as other biological materials that lack nuclear DNA.