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Ji Z, Xing Y, Li J, Feng X, Yang F, Zhu B, Yan J. Male-specific age prediction based on Y-chromosome DNA methylation with blood using pyrosequencing. Forensic Sci Int Genet 2024; 71:103050. [PMID: 38703560 DOI: 10.1016/j.fsigen.2024.103050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/14/2024] [Accepted: 04/19/2024] [Indexed: 05/06/2024]
Abstract
Age prediction is an important aspect of forensic science that offers valuable insight into identification. In recent years, extensive studies have been conducted on age prediction based on DNA methylation, and numerous studies have demonstrated that DNA methylation is a reliable biomarker for age prediction. However, almost all studies on age prediction based on DNA methylation have focused on age-related CpG sites in autosomes, which are concentrated on single-source DNA samples. Mixed samples, especially male-female mixed samples, are common in forensic casework. The application of Y-STRs and Y-SNPs can provide clues for the genetic typing of male individuals in male-female mixtures, but they cannot provide the age information of male individuals. Studies on Y-chromosome DNA methylation can address this issue. In this study, we identified five age-related CpG sites on the Y chromosome (Y-CpGs) and developed a male-specific age prediction model using pyrosequencing combined with a support vector machine algorithm. The mean absolute deviation of the model was 5.50 years in the training set and 6.74 years in the testing set. When we used a male blood sample to predict age, the deviation between the predicted and chronological age was 1.18 years. Then, we mixed the genomic DNA of the male and a female at ratios of 1:1, 1:5, 1:10, and 1:50, the range of deviation between the predicted and chronological age of the male in the mixture was 1.16-1.74 years. In addition, there was no significant difference between the methylation values of bloodstains and blood in the same sample, which indicates that our model is also suitable for bloodstain samples. Overall, our results show that age prediction using DNA methylation of the Y chromosome has potential applications in forensic science and can be of great help in predicting the age of males in male-female mixtures. Furthermore, this work lays the foundation for future research on age-related applications of Y-CpGs.
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Affiliation(s)
- Zhimin Ji
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China
| | - Yangfeng Xing
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China
| | - Junli Li
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China
| | - Xiaoxiao Feng
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China
| | - Fenglong Yang
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China.
| | - Bofeng Zhu
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China; Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, PR China.
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030009, PR China.
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2
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Yuen ZWS, Shanmuganandam S, Stanley M, Jiang S, Hein N, Daniel R, McNevin D, Jack C, Eyras E. Profiling age and body fluid DNA methylation markers using nanopore adaptive sampling. Forensic Sci Int Genet 2024; 71:103048. [PMID: 38640705 DOI: 10.1016/j.fsigen.2024.103048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/07/2024] [Accepted: 04/11/2024] [Indexed: 04/21/2024]
Abstract
DNA methylation plays essential roles in regulating physiological processes, from tissue and organ development to gene expression and aging processes and has emerged as a widely used biomarker for the identification of body fluids and age prediction. Currently, methylation markers are targeted independently at specific CpG sites as part of a multiplexed assay rather than through a unified assay. Methylation detection is also dependent on divergent methodologies, ranging from enzyme digestion and affinity enrichment to bisulfite treatment, alongside various technologies for high-throughput profiling, including microarray and sequencing. In this pilot study, we test the simultaneous identification of age-associated and body fluid-specific methylation markers using a single technology, nanopore adaptive sampling. This innovative approach enables the profiling of multiple CpG marker sites across entire gene regions from a single sample without the need for specialized DNA preparation or additional biochemical treatments. Our study demonstrates that adaptive sampling achieves sufficient coverage in regions of interest to accurately determine the methylation status, shows a robust consistency with whole-genome bisulfite sequencing data, and corroborates known CpG markers of age and body fluids. Our work also resulted in the identification of new sites strongly correlated with age, suggesting new possible age methylation markers. This study lays the groundwork for the systematic development of nanopore-based methodologies in both age prediction and body fluid identification, highlighting the feasibility and potential of nanopore adaptive sampling while acknowledging the need for further validation and expansion in future research.
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Affiliation(s)
- Zaka Wing-Sze Yuen
- EMBL Australia Partner Laboratory Network, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; The Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, The Australian National University, Canberra, Australia
| | - Somasundhari Shanmuganandam
- Department of Immunity, Inflammation and Infection, The John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia; Centre for Personalised Immunology, NHMRC Centre for Research Excellence, Australian National University, Canberra, ACT 2601, Australia
| | - Maurice Stanley
- Department of Immunity, Inflammation and Infection, The John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia; Centre for Personalised Immunology, NHMRC Centre for Research Excellence, Australian National University, Canberra, ACT 2601, Australia
| | - Simon Jiang
- Department of Immunity, Inflammation and Infection, The John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia; Centre for Personalised Immunology, NHMRC Centre for Research Excellence, Australian National University, Canberra, ACT 2601, Australia; Department of Renal Medicine, The Canberra Hospital, Canberra, ACT 2605, Australia
| | - Nadine Hein
- ACRF Department of Cancer Biology and Therapeutics and Division of Genome Sciences and Cancer, John Curtin School of Medical Research, Australian National University, Acton, Canberra, Australia
| | - Runa Daniel
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, Queensland, Australia
| | - Dennis McNevin
- Centre for Forensic Science, School of Mathematical & Physical Sciences, Faculty of Science, University of Technology Sydney, Sydney, Australia
| | - Cameron Jack
- ANU Bioinformatics Consultancy, John Curtin School of Medical Research, The Australian National University, Canberra, Australia
| | - Eduardo Eyras
- EMBL Australia Partner Laboratory Network, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, The Australian National University, Canberra, Australia; The Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, The Australian National University, Canberra, Australia.
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Castagnola MJ, Medina-Paz F, Zapico SC. Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation. Int J Mol Sci 2024; 25:4917. [PMID: 38732129 PMCID: PMC11084977 DOI: 10.3390/ijms25094917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/13/2024] Open
Abstract
Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.
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Affiliation(s)
- María Josefina Castagnola
- Department of Chemistry and Environmental Sciences, New Jersey Institute of Technology, Tiernan Hall 365, Newark, NJ 07102, USA; (M.J.C.); (F.M.-P.)
| | - Francisco Medina-Paz
- Department of Chemistry and Environmental Sciences, New Jersey Institute of Technology, Tiernan Hall 365, Newark, NJ 07102, USA; (M.J.C.); (F.M.-P.)
| | - Sara C. Zapico
- Department of Chemistry and Environmental Sciences, New Jersey Institute of Technology, Tiernan Hall 365, Newark, NJ 07102, USA; (M.J.C.); (F.M.-P.)
- Department of Anthropology and Laboratories of Analytical Biology, National Museum of Natural History, MRC 112, Smithsonian Institution, Washington, DC 20560, USA
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Kotková L, Drábek J. Age-related changes in sperm DNA methylation and their forensic and clinical implications. Epigenomics 2023; 15:1157-1173. [PMID: 38031735 DOI: 10.2217/epi-2023-0307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
As a link between a stable genome and a dynamic environment, epigenetics is a promising tool for mapping age-related changes in human DNA. Methylated cytosine changes at specific loci are generally less studied in sperm DNA than in somatic cell DNA. Age-related methylation changes can be connected to various reproductive health problems and multiple disorders in offspring. In addition, they can be helpful in forensic fields, where testing of specific loci in semen samples found at sexual assault crime scenes can predict a perpetrator's age and narrow down the police investigation. This review focuses on age-related methylation changes in sperm. It covers the biological role of methylation, methylation testing techniques and the implications of methylation changes in forensics and clinical practice.
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Affiliation(s)
- Lucie Kotková
- Institute of Molecular & Translational Medicine, Faculty of Medicine & Dentistry, Palacky University Olomouc and University Hospital Olomouc, 77900, Czech Republic
| | - Jiří Drábek
- Institute of Molecular & Translational Medicine, Faculty of Medicine & Dentistry, Palacky University Olomouc and University Hospital Olomouc, 77900, Czech Republic
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Xiao C, Li Y, Chen M, Yi S, Huang D. Improved age estimation from semen using sperm-specific age-related CpG markers. Forensic Sci Int Genet 2023; 67:102941. [PMID: 37820545 DOI: 10.1016/j.fsigen.2023.102941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/25/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023]
Abstract
Accurate age estimation from semen has the potential to greatly narrow the pool of unidentified suspects in sexual assault investigations. However, previous efforts utilizing semen age-related CpG (AR-CpG) markers have shown lower accuracy compared to blood AR-CpG-based methods. This discrepancy may be attributed to DNA methylation (DNAm) interferences from "round cells" such as leukocytes and immature sperm cells in semen. This study aimed to develop age calculators based on sperm-specific AR-CpG markers and to achieve performance-improved age estimates from sperm DNA. Through an analysis of publicly available MethylationEPIC microarray data from 90 sperm samples of healthy males aged 22-51 years, we identified 31 sperm-specific AR-CpG markers with absolute Pearson's R values > 0.5 and Benjamini-Hochberg adjusted p values < 0.013. The top 19 AR-CpG markers with the largest absolute R values and beta ranges > 0.10, along with 3 reported semen AR-CpG markers (cg06304190, cg06979108, and cg12837463), were integrated into two methylation SNaPshot panels (Ⅰ and Ⅱ), each containing 11 markers. The 21 qualified AR-CpG markers showed absolute R values ≥ 0.427 in an independent validation cohort of 253 sperm DNA samples (22-67 years), with cg21843517 exhibiting the strongest age correlation (R = 0.853). The optimal models, constructed using sperm DNAm data of the training set (n = 214, 22-67 years) and markers from panel Ⅰ (n = 11), panel Ⅱ (n = 10), or both panels, achieved mean absolute errors (MAEs) of 2.526-4.746, 3.890-5.715, and > 9.800 years on the test sets of sperm (n = 39, 23-64 years), semen (same donors as the sperm test set), and whole blood (n = 40, 22-65 years), respectively. The simplified models incorporating 3, 5, 9, or 14 AR-CpG markers (MAE = 2.918-4.139 years for sperm) still outperformed the Lee et al. original model (MAE = 6.444 years for semen) and the reconstructed panel Lee model (MAE = 6.011 years for sperm). The final models, utilizing all sperm DNAm data (n = 253) and markers from panel Ⅰ, panel Ⅱ, or both panels, yielded mean MAEs of 2.587, 2.766, and 2.200 years, respectively, on the 50 test sets generated by 5 repeats of 10-fold cross-validations. Additionally, multiple markers in both panels demonstrated the ability to discern sperm or semen from blood with 100% accuracy. In summary, our study substantiates the potential of sperm-specific AR-CpG markers for precise age estimation from sperm DNA, providing an improved toolset for forensic investigations.
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Affiliation(s)
- Chao Xiao
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China; Hubei Key Laboratory of the Forensic Science, Hubei University of Police, Wuhan, Hubei 430035, PR China.
| | - Ya Li
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Maomin Chen
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Shaohua Yi
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Daixin Huang
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China.
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Naue J. Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications. Genes Genomics 2023; 45:1239-1261. [PMID: 37253906 PMCID: PMC10504122 DOI: 10.1007/s13258-023-01392-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/15/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals. OBJECTIVE This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application. METHODS The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics. CONCLUSION The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.
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Affiliation(s)
- Jana Naue
- Institute of Forensic Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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Refn MR, Kampmann ML, Morling N, Tfelt-Hansen J, Børsting C, Pereira V. Prediction of chronological age and its applications in forensic casework: methods, current practices, and future perspectives. Forensic Sci Res 2023; 8:85-97. [PMID: 37621446 PMCID: PMC10445583 DOI: 10.1093/fsr/owad021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 04/28/2023] [Indexed: 08/26/2023] Open
Abstract
Estimating an individual's age can be relevant in several areas primarily related to the clinical and forensic fields. In the latter, estimation of an individual's chronological age from biological material left by the perpetrator at a crime scene may provide helpful information for police investigation. Estimation of age is also beneficial in immigration cases, where age can affect the person's protection status under the law, or in disaster victim identification to narrow the list of potential missing persons. In the last decade, research has focused on establishing new approaches for age prediction in the forensic field. From the first forensic age estimations based on morphological inspections of macroscopic changes in bone and teeth, the focus has shifted to molecular methods for age estimation. These methods allow the use of samples from human biological material that does not contain morphological age features and can, in theory, be investigated in traces containing only small amounts of biological material. Molecular methods involving DNA analyses are the primary choice and estimation of DNA methylation levels at specific sites in the genome is the most promising tool. This review aims to provide an overview of the status of forensic age prediction using molecular methods, with particular focus in DNA methylation. The frequent challenges that impact forensic age prediction model development will be addressed, together with the importance of validation efforts within the forensic community.
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Affiliation(s)
- Mie Rath Refn
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marie-Louise Kampmann
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jacob Tfelt-Hansen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen , Denmark
| | - Claus Børsting
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vania Pereira
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Kayser M, Branicki W, Parson W, Phillips C. Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age. Forensic Sci Int Genet 2023; 65:102870. [PMID: 37084623 DOI: 10.1016/j.fsigen.2023.102870] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023]
Abstract
Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.
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Affiliation(s)
- Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland,; Institute of Forensic Research, Kraków, Poland
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
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Fokias K, Dierckx L, Van de Voorde W, Bekaert B. Age determination through DNA methylation patterns in fingernails and toenails. Forensic Sci Int Genet 2023; 64:102846. [PMID: 36867979 DOI: 10.1016/j.fsigen.2023.102846] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/05/2022] [Accepted: 02/09/2023] [Indexed: 02/18/2023]
Abstract
Over the past decade, age prediction based on DNA methylation has become a vastly investigated topic; many age prediction models have been developed based on different DNAm markers and using various tissues. However, the potential of using nails to this end has not yet been explored. Their inherent resistance to decay and ease of sampling would offer an advantage in cases where post-mortem degradation poses challenges concerning sample collection and DNA-extraction. In the current study, clippings from both fingernails and toenails were collected from 108 living test subjects (age range: 0-96 years). The methylation status of 15 CpGs located in 4 previously established age-related markers (ASPA, EDARADD, PDE4C, ELOVL2) was investigated through pyrosequencing of bisulphite converted DNA. Significant dissimilarities in methylation levels were observed between all four limbs, hence both limb-specific age prediction models and prediction models combining multiple sampling locations were developed. When applied to their respective test sets, these models yielded a mean absolute deviation between predicted and chronological age ranging from 5.48 to 9.36 years when using ordinary least squares regression. In addition, the assay was tested on methylation data derived from 5 nail samples collected from deceased individuals, demonstrating its feasibility for application in post-mortem cases. In conclusion, this study provides the first proof that chronological age can be assessed through DNA methylation patterns in nails.
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Affiliation(s)
- Kristina Fokias
- KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium
| | - Lotte Dierckx
- KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium
| | - Wim Van de Voorde
- KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium; UZ Leuven, Laboratory of Forensic Genetics, Leuven, Belgium
| | - Bram Bekaert
- KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium; UZ Leuven, Laboratory of Forensic Genetics, Leuven, Belgium.
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Ghemrawi M, Tejero NF, Duncan G, McCord B. Pyrosequencing: Current forensic methodology and future applications-a review. Electrophoresis 2023; 44:298-312. [PMID: 36168852 DOI: 10.1002/elps.202200177] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 02/01/2023]
Abstract
The recent development of small, single-amplicon-based benchtop systems for pyrosequencing has opened up a host of novel procedures for applications in forensic science. Pyrosequencing is a sequencing by synthesis technique, based on chemiluminescent inorganic pyrophosphate detection. This review explains the pyrosequencing workflow and illustrates the step-by-step chemistry, followed by a description of the assay design and factors to keep in mind for an exemplary assay. Existing and potential forensic applications are highlighted using this technology. Current applications include identifying species, identifying bodily fluids, and determining smoking status. We also review progress in potential applications for the future, including research on distinguishing monozygotic twins, detecting alcohol and drug abuse, and other phenotypic characteristics such as diet and body mass index. Overall, the versatility of the pyrosequencing technologies renders it a useful tool in forensic genomics.
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Affiliation(s)
- Mirna Ghemrawi
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
| | - Nicole Fernandez Tejero
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
| | - George Duncan
- Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Dania Beach, Florida, USA
| | - Bruce McCord
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
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Carratto TMT, Moraes VMS, Recalde TSF, Oliveira MLGD, Teixeira Mendes-Junior C. Applications of massively parallel sequencing in forensic genetics. Genet Mol Biol 2022; 45:e20220077. [PMID: 36121926 PMCID: PMC9514793 DOI: 10.1590/1678-4685-gmb-2022-0077] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 07/15/2022] [Indexed: 11/22/2022] Open
Abstract
Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.
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Affiliation(s)
- Thássia Mayra Telles Carratto
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | - Vitor Matheus Soares Moraes
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | | | | | - Celso Teixeira Mendes-Junior
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
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12
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A collaborative exercise on DNA methylation-based age prediction and body fluid typing. Forensic Sci Int Genet 2021; 57:102656. [PMID: 34973557 DOI: 10.1016/j.fsigen.2021.102656] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/09/2021] [Accepted: 12/14/2021] [Indexed: 11/20/2022]
Abstract
DNA methylation has become one of the most useful biomarkers for age prediction and body fluid identification in the forensic field. Therefore, several assays have been developed to detect age-associated and body fluid-specific DNA methylation changes. Among the many methods developed, SNaPshot-based assays should be particularly useful in forensic laboratories, as they permit multiplex analysis and use the same capillary electrophoresis instrumentation as STR analysis. However, technical validation of any developed assays is crucial for their proper integration into routine forensic workflow. In the present collaborative exercise, two SNaPshot multiplex assays for age prediction and a SNaPshot multiplex for body fluid identification were tested in twelve laboratories. The experimental set-up of the exercise was designed to reflect the entire workflow of SNaPshot-based methylation analysis and involved four increasingly complex tasks designed to detect potential factors influencing methylation measurements. The results of body fluid identification from each laboratory provided sufficient information to determine appropriate age prediction methods in subsequent analysis. In age prediction, systematic measurement differences resulting from the type of genetic analyzer used were identified as the biggest cause of DNA methylation variation between laboratories. Also, the use of a buffer that ensures a high ratio of specific to non-specific primer binding resulted in changes in DNA methylation measurement, especially when using degenerate primers in the PCR reaction. In addition, high input volumes of bisulfite-converted DNA often caused PCR failure, presumably due to carry-over of PCR inhibitors from the bisulfite conversion reaction. The proficiency of the analysts and experimental conditions for efficient SNaPshot reactions were also important for consistent DNA methylation measurement. Several bisulfite conversion kits were used for this study, but differences resulting from the use of any specific kit were not clearly discerned. Even when different experimental settings were used in each laboratory, a positive outcome of the study was a mean absolute age prediction error amongst participant's data of only 2.7 years for semen, 5.0 years for blood and 3.8 years for saliva.
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Heidegger A, Pisarek A, de la Puente M, Niederstätter H, Pośpiech E, Woźniak A, Schury N, Unterländer M, Sidstedt M, Junker K, Ventayol Garcia M, Laurent FX, Ulus A, Vannier J, Bastisch I, Hedman J, Sijen T, Branicki W, Xavier C, Parson W. Development and inter-laboratory validation of the VISAGE enhanced tool for age estimation from semen using quantitative DNA methylation analysis. Forensic Sci Int Genet 2021; 56:102596. [PMID: 34763164 DOI: 10.1016/j.fsigen.2021.102596] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 09/07/2021] [Accepted: 09/08/2021] [Indexed: 12/27/2022]
Abstract
The analysis of DNA methylation has become an established method for chronological age estimation. This has triggered interest in the forensic community to develop new methods for age estimation from biological crime scene material. Various assays are available for age estimation from somatic tissues, the majority from blood. Age prediction from semen requires different DNA methylation markers and the only assays currently developed for forensic analysis are based on SNaPshot or pyrosequencing. Here, we describe a new assay using massively parallel sequencing to analyse 13 candidate CpG sites targeted in two multiplex PCRs. The assay has been validated by five consortium laboratories of the VISible Attributes through GEnomics (VISAGE) project within a collaborative exercise and was tested for reproducible quantification of DNA methylation levels and sensitivity with DNA methylation controls. Furthermore, DNA extracts and stains on Whatman FTA cards from two semen samples were used to evaluate concordance and mimic casework samples. Overall, the assay yielded high read depths (> 1000 reads) at all 13 marker positions. The methylation values obtained indicated robust quantification with an average standard deviation of 2.8% at the expected methylation level of 50% across the 13 markers and a good performance with 50 ng DNA input into bisulfite conversion. The absolute difference of quantifications from one participating laboratory to the mean quantifications of concordance and semen stains of remaining laboratories was approximately 1%. These results demonstrated the assay to be robust and suitable for age estimation from semen in forensic investigations. In addition to the 13-marker assay, a more streamlined protocol combining only five age markers in one multiplex PCR was developed. Preliminary results showed no substantial differences in DNA methylation quantification between the two assays, indicating its applicability with the VISAGE age model for semen developed with data from the complete 13-marker tool.
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Affiliation(s)
- A Heidegger
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - A Pisarek
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
| | - M de la Puente
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
| | - H Niederstätter
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - E Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
| | - A Woźniak
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - N Schury
- Federal Criminal Police Office, Wiesbaden, Germany
| | | | - M Sidstedt
- National Forensic Centre (NFC), Swedish Police Authority, Linköping, Sweden
| | - K Junker
- National Forensic Centre (NFC), Swedish Police Authority, Linköping, Sweden
| | - M Ventayol Garcia
- Biological Traces, Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB The Hague, The Netherlands
| | - F X Laurent
- Institut National de Police Scientifique, Laboratoire de Police Scientifique de Lyon, Ecully Cedex, France
| | - A Ulus
- Institut National de Police Scientifique, Laboratoire de Police Scientifique de Lyon, Ecully Cedex, France
| | - J Vannier
- Institut National de Police Scientifique, Laboratoire de Police Scientifique de Lyon, Ecully Cedex, France
| | - I Bastisch
- Federal Criminal Police Office, Wiesbaden, Germany
| | - J Hedman
- National Forensic Centre (NFC), Swedish Police Authority, Linköping, Sweden; Applied Microbiology, Department of Chemistry, Lund University, Lund, Sweden
| | - T Sijen
- Biological Traces, Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB The Hague, The Netherlands; University of Amsterdam, Swammerdam Institute of Life Sciences, Science Park 904, 1098XH Amsterdam, The Netherlands
| | - W Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland; Central Forensic Laboratory of the Police, Warsaw, Poland
| | - C Xavier
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria.
| | - W Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, State College, PA, USA.
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Epigenetic age prediction in semen - marker selection and model development. Aging (Albany NY) 2021; 13:19145-19164. [PMID: 34375949 PMCID: PMC8386575 DOI: 10.18632/aging.203399] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 07/17/2021] [Indexed: 12/12/2022]
Abstract
DNA methylation analysis is becoming increasingly useful in biomedical research and forensic practice. The discovery of differentially methylated sites (DMSs) that continuously change over an individual's lifetime has led to breakthroughs in molecular age estimation. Although semen samples are often used in forensic DNA analysis, previous epigenetic age prediction studies mainly focused on somatic cell types. Here, Infinium MethylationEPIC BeadChip arrays were applied to semen-derived DNA samples, which identified numerous novel DMSs moderately correlated with age. Validation of the ten most age-correlated novel DMSs and three previously known sites in an independent set of semen-derived DNA samples using targeted bisulfite massively parallel sequencing, confirmed age-correlation for nine new and three previously known markers. Prediction modelling revealed the best model for semen, based on 6 CpGs from newly identified genes SH2B2, EXOC3, IFITM2, and GALR2 as well as the previously known FOLH1B gene, which predict age with a mean absolute error of 5.1 years in an independent test set. Further increases in the accuracy of age prediction from semen DNA will require technological progress to allow sensitive, simultaneous analysis of a much larger number of age correlated DMSs from the compromised DNA typical of forensic semen stains.
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