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Evaluation of the MHSeqTyper47 kit for forensically challenging DNA samples. Forensic Sci Int Genet 2022; 61:102763. [PMID: 35939876 DOI: 10.1016/j.fsigen.2022.102763] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 07/05/2022] [Accepted: 08/03/2022] [Indexed: 11/20/2022]
Abstract
Microhaplotypes have been highly regarded for forensic mixture DNA deconvolution because they do not experience interference from stutters in the same way as short tandem repeat markers, and they tend to be more polymorphic than single nucleotide polymorphism markers. However, forensic microhaplotype kits have not been reported. The MHSeqTyper47 kit genotypes 47 microhaplotype loci. In this study, MiSeq FGx sequencing metrics for MHSeqTyper47 were presented, and the genotyping accuracy of this kit was examined. The sensitivity of MHSeqTyper47 reached 62.5 pg, and full genotyping results were obtained from degraded DNA samples with degradation indexes ≤ 3.00. Full genotypes were obtained in the presence of 100 ng/μL tannin, 50 μM heme, 25 ng/μL humic acid, and 1.25 μg/μL indigo dye. In DNA mixture studies, a minimum of 31 loci of the minor contributor were correctly genotyped at 1:99 or 99:1 mixing ratios, with the cumulative random matching probability of these loci reaching 4.54 × 10-25. Mixing ratios could be reliably predicted from two-donor DNA mixtures based on the loci with four called alleles. Taken together, these data showed that the MHSeqTyper47 kit was effective for forensically challenging DNA analysis.
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2
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Urtiaga GO, Domingues WB, Komninou ER, Martins AWS, Blödorn EB, Dellagostin EN, Woloski RDS, Pinto LS, Brum CB, Tovo-Rodrigues L, Campos VF. DNA microarray for forensic intelligence purposes: High-density SNP profiles obtained directly from casework-like samples with and without a DNA purification step. Forensic Sci Int 2022; 332:111181. [PMID: 35042181 DOI: 10.1016/j.forsciint.2022.111181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/16/2021] [Accepted: 01/08/2022] [Indexed: 12/14/2022]
Abstract
SNP analyses from a forensic intelligence perspective have proven to be an important tool to restrict the number of suspected offenders and find missing persons. DNA microarray assays have been demonstrated as a potential feature in forensic analysis, like such as forensic genetic genealogy. The objective of this study was to describe the results from DNA microarray assay from saliva samples deposited on a glass surface collected from by a double swab technique, commonly applied in crime scenes. Eighteen samples from the same person were subjected to Infinium® Global Screening Array-24 v1.0 (~642.824 SNP markers) in two different protocols - with or without the DNA purification procedure. The measured genotype was compared with a Consensus Genotype, obtained from standard control samples, and the parameters such as Call Rate and GenCall Scores were evaluated. Results showed that the Call Rate parameter is enough to estimate the probability of obtaining a correct genotype in the SNP assay. Reliable genotypes with a confidence level of more than 90% (at least 90.15%) were observed in Call Rates above 69.41%, regardless of the experimental condition. Our data demonstrate that DNA Microarray from samples collected under conditions such as those found at crime scenes can generate high-density SNP genetic profiles with a confidence level greater than 90%. Enzymatic adjustments and protocol changes may enable DNA microarray assays for crime analysis and investigation purposes eliminating the purification step in the future. Our data suggest that DNA microarray can support criminal investigation teams from a forensic intelligence perspective.
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Affiliation(s)
- Gabriel O Urtiaga
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil; Núcleo de Identificação, Superintendência da Polícia Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - William B Domingues
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Eliza R Komninou
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Amanda W S Martins
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Eduardo B Blödorn
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Eduardo N Dellagostin
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Rafael Dos S Woloski
- Laboratório de Bioinformática e Proteômica, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Luciano S Pinto
- Laboratório de Bioinformática e Proteômica, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Clarice B Brum
- Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Luciana Tovo-Rodrigues
- Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Vinicius F Campos
- Laboratório de Genômica Estrutural, Programa de Pós-Graduação em Biotecnologia, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS, Brazil.
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3
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Ge J, King J, Mandape S, Budowle B. Enhanced mixture interpretation with macrohaplotypes based on long-read DNA sequencing. Int J Legal Med 2021; 135:2189-2198. [PMID: 34378071 DOI: 10.1007/s00414-021-02679-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/30/2021] [Indexed: 12/18/2022]
Abstract
Deconvoluting mixture samples is one of the most challenging problems confronting DNA forensic laboratories. Efforts have been made to provide solutions regarding mixture interpretation. The probabilistic interpretation of Short Tandem Repeat (STR) profiles has increased the number of complex mixtures that can be analyzed. A portion of complex mixture profiles, particularly for mixtures with a high number of contributors, are still being deemed uninterpretable. Novel forensic markers, such as Single Nucleotide Variants (SNV) and microhaplotypes, also have been proposed to allow for better mixture interpretation. However, these markers have both a lower discrimination power compared with STRs and are not compatible with CODIS or other national DNA databanks worldwide. The short-read sequencing (SRS) technologies can facilitate mixture interpretation by identifying intra-allelic variations within STRs. Unfortunately, the short size of the amplicons containing STR markers and sequence reads limit the alleles that can be attained per STR. The latest long-read sequencing (LRS) technologies can overcome this limitation in some samples in which larger DNA fragments (including both STRs and SNVs) with definitive phasing are available. Based on the LRS technologies, this study developed a novel CODIS compatible forensic marker, called a macrohaplotype, which combines a CODIS STR and flanking variants to offer extremely high number of haplotypes and hence very high discrimination power per marker. The macrohaplotype will substantially improve mixture interpretation capabilities. Based on publicly accessible data, a panel of 20 macrohaplotypes with sizes of ~ 8 k bp and the maximum high discrimination powers were designed. The statistical evaluation demonstrates that these macrohaplotypes substantially outperform CODIS STRs for mixture interpretation, particularly for mixtures with a high number of contributors, as well as other forensic applications. Based on these results, efforts should be undertaken to build a complete workflow, both wet-lab and bioinformatics, to precisely call the variants and generate the macrohaplotypes based on the LRS technologies.
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Affiliation(s)
- Jianye Ge
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, USA.
- Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA.
| | - Jonathan King
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Sammed Mandape
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Bruce Budowle
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, USA
- Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA
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4
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A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures. PLoS One 2021; 16:e0247344. [PMID: 34653182 PMCID: PMC8519470 DOI: 10.1371/journal.pone.0247344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 09/30/2021] [Indexed: 11/24/2022] Open
Abstract
This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MRex) to all the mixing ratios emerging at all other permutations of the mixture (MRobs) using several (1 - χ2) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ2) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ2) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.
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5
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Petrovick MS, Boettcher T, Fremont-Smith P, Peragallo C, Ricke DO, Watkins J, Schwoebel E. Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies. Forensic Sci Int Genet 2020; 46:102234. [PMID: 32018060 DOI: 10.1016/j.fsigen.2020.102234] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 12/05/2019] [Accepted: 01/02/2020] [Indexed: 11/18/2022]
Abstract
DNA mixtures from 3 or more contributors have proven difficult to analyze using the current state-of-the-art method of short-tandem repeat (STR) amplification followed by capillary electrophoresis (CE). Here we analyze samples from both laboratory-defined mixtures and complex multi-contributor touch samples using a single nucleotide polymorphism (SNP) panel comprised of 2311 low-minor-allele-frequency loci, combined with massively parallel sequencing (MPS). This approach demonstrates that as many as 10 people can be identified in touch samples using a threshold of -Log P(RMNE) of 6, and a detection rate of 18-94 % across 10 different materials using a threshold of -Log P(RMNE) of 2. Thirty-two false positives were observed in 100 touch samples.
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Affiliation(s)
- Martha S Petrovick
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States.
| | - Tara Boettcher
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
| | - Philip Fremont-Smith
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
| | - Chelsea Peragallo
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
| | - Darrell O Ricke
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
| | - James Watkins
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
| | - Eric Schwoebel
- Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood St., Lexington, MA 02421, United States
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6
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Carter AB. Considerations for Genomic Data Privacy and Security when Working in the Cloud. J Mol Diagn 2019; 21:542-552. [DOI: 10.1016/j.jmoldx.2018.07.009] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 05/16/2018] [Accepted: 07/02/2018] [Indexed: 01/21/2023] Open
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7
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Yang J, Lin D, Deng C, Li Z, Pu Y, Yu Y, Li K, Li D, Chen P, Chen F. The advances in DNA mixture interpretation. Forensic Sci Int 2019; 301:101-106. [PMID: 31153987 DOI: 10.1016/j.forsciint.2019.05.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 05/09/2019] [Indexed: 12/16/2022]
Abstract
In forensic genetics, the analysis of DNA in biological samples is a valuable tool for personal identification. There is an increasing demand in analyzing of the mixed DNA which may provide insightful investigative instructions. With the continuous effort for the improvement of individual identification, complicated mixed stains represent a growing fraction of the samples processed by forensic laboratories. Recent technological advances have enabled quantitative analysis of DNA mixture and emerging sequencing approaches to decipher the complicated DNA mixture. Here, we describe the use of different genetic markers, typing approaches and analytical methods in mixture analysis, and how useful information can be obtained from complicated DNA mixture.
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Affiliation(s)
- Jiawen Yang
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Donghai Lin
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Chuwei Deng
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Zheng Li
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Yan Pu
- School of Medicine, Southeast University, Nanjing, Jiangsu 210009, PR China
| | - Yanfang Yu
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Kai Li
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Ding Li
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China
| | - Peng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China.
| | - Feng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China; Key Laboratory of Targeted Intervention of Cardiovascular Disease, Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China.
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8
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Chen R, Zhao X, Ma K, Li H, Cao Y, Cao Y, Liu W. Separation of SNP profiles from DNA mixtures with two contributors via massively parallel sequencing technology. AUST J FORENSIC SCI 2019. [DOI: 10.1080/00450618.2019.1586997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Ronghua Chen
- Key Laboratory of Forensic Evidence and Science Technology, Ministry of Public Security, Institute of Forensic Science, Shanghai Public Security Bureau, Shanghai, China
| | - Xueying Zhao
- Shanghai Key Laboratory of Crime Scene Evidence, Shanghai Research Institute of Criminal Science and Technology, Shanghai, China
| | - Ke Ma
- Shanghai Key Laboratory of Crime Scene Evidence, Shanghai Research Institute of Criminal Science and Technology, Shanghai, China
| | - Hui Li
- Shanghai Key Laboratory of Crime Scene Evidence, Shanghai Research Institute of Criminal Science and Technology, Shanghai, China
| | - Yu Cao
- Key Laboratory of Forensic Evidence and Science Technology, Ministry of Public Security, Institute of Forensic Science, Shanghai Public Security Bureau, Shanghai, China
- State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Yandong Cao
- Technical department, Analyses Technology Co. Ltd, Beijing, China
| | - Wenbin Liu
- Shanghai Key Laboratory of Crime Scene Evidence, Shanghai Research Institute of Criminal Science and Technology, Shanghai, China
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9
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Fang C, Zhao J, Li J, Qian J, Liu X, Sun Q, Liu W, Tian Y, Ji A, Wu H, Yan J. Massively parallel sequencing of microRNA in bloodstains and evaluation of environmental influences on miRNA candidates using realtime polymerase chain reaction. Forensic Sci Int Genet 2018; 38:32-38. [PMID: 30321749 DOI: 10.1016/j.fsigen.2018.10.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 06/30/2018] [Accepted: 10/01/2018] [Indexed: 12/21/2022]
Abstract
MicroRNAs (miRNA) are small (22-24 nucleotides) non-coding RNAs with potential application in forensic science because of their anti-degradation property and tissue specificity. Recent studies on the use of miRNA in forensic applications have mainly focused on body fluid identification using realtime polymerase chain reaction or microarray analysis. However, the exploration of miRNA in bloodstains, which are the most valuable source of biological evidence during case investigations, is currently lacking, particularly for aged and environmentally compromised forensic samples. Recent developments in massively parallel sequencing (MPS) technology provide the opportunity to establish a whole-genome miRNA profile with high throughput and efficiency. However, MPS analysis of genome-wide miRNA profiles from bloodstains has not been reported to date. In this study, the whole-genome miRNA profiles of bloodstains were examined using MPS, revealing 633 known miRNAs and 266 novel miRNAs. To further explore the stability of miRNAs in bloodstains under various circumstances, the expression levels of six miRNAs (miR-16-5p, miR-20a-5p, miR-486-5p, miR-148a-3p, miR-151a-3p, and miR-451a) that were abundant in blood/bloodstains were examined. The results showed that freezing/thawing and a high concentration of oxidant solution affects the absolute expression of miRNA significantly, while storage for up to 5 months and a temperature of 37 °C did not have any observed effects. This study not only provides a novel method to explore miRNA profiles in bloodstains using MPS, but also points to the circumstantial influences on miRNA expression, which are an important consideration for practical application. Collectively, our work may shed light on MPS-based approaches with miRNA analysis of bloodstains in forensics.
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Affiliation(s)
- Chen Fang
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Jing Zhao
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100010, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Junbo Li
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Jialin Qian
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Xu Liu
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Qifan Sun
- National Engineering Laboratory for Forensic Science and MPS Key Laboratory of Forensic Genetics, Institute of Forensic Science, Ministry of Public Security, Beijing 100038, PR China
| | - Wenli Liu
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Yanjie Tian
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China
| | - Anquan Ji
- National Engineering Laboratory for Forensic Science and MPS Key Laboratory of Forensic Genetics, Institute of Forensic Science, Ministry of Public Security, Beijing 100038, PR China
| | - Huijuan Wu
- Beijing Center for Physical and Chemical Analysis, Beijing 100094, PR China; Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing 100094, PR China.
| | - Jiangwei Yan
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100010, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, PR China.
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10
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Facilitating complex DNA mixture interpretation by sequencing highly polymorphic haplotypes. Forensic Sci Int Genet 2018; 35:136-140. [DOI: 10.1016/j.fsigen.2018.05.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 03/06/2018] [Accepted: 05/01/2018] [Indexed: 01/01/2023]
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11
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Tao R, Wang S, Zhang J, Zhang J, Yang Z, Sheng X, Hou Y, Zhang S, Li C. Separation/extraction, detection, and interpretation of DNA mixtures in forensic science (review). Int J Legal Med 2018; 132:1247-1261. [PMID: 29802461 DOI: 10.1007/s00414-018-1862-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Accepted: 05/11/2018] [Indexed: 02/08/2023]
Abstract
Interpreting mixed DNA samples containing material from multiple contributors has long been considered a major challenge in forensic casework, especially when encountering low-template DNA (LT-DNA) or high-order mixtures that may involve missing alleles (dropout) and unrelated alleles (drop-in), among others. In the last decades, extraordinary progress has been made in the analysis of mixed DNA samples, which has led to increasing attention to this research field. The advent of new methods for the separation and extraction of DNA from mixtures, novel or jointly applied genetic markers for detection and reliable interpretation approaches for estimating the weight of evidence, as well as the powerful massively parallel sequencing (MPS) technology, has greatly extended the range of mixed samples that can be correctly analyzed. Here, we summarized the investigative approaches and progress in the field of forensic DNA mixture analysis, hoping to provide some assistance to forensic practitioners and to promote further development involving this issue.
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Affiliation(s)
- Ruiyang Tao
- Institute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.,Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China
| | - Shouyu Wang
- Institute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Jiashuo Zhang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.,Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, People's Republic of China
| | - Jingyi Zhang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.,Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, People's Republic of China
| | - Zihao Yang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.,Department of Forensic Medicine, School of Basic Medical Science, Wenzhou Medical University, Wenzhou, 325035, People's Republic of China
| | - Xiang Sheng
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.,Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, People's Republic of China
| | - Yiping Hou
- Institute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Suhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.
| | - Chengtao Li
- Institute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China. .,Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Sciences, Shanghai, 200063, People's Republic of China.
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12
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Chen P, Yin C, Li Z, Pu Y, Yu Y, Zhao P, Chen D, Liang W, Zhang L, Chen F. Evaluation of the Microhaplotypes panel for DNA mixture analyses. Forensic Sci Int Genet 2018; 35:149-155. [PMID: 29778046 DOI: 10.1016/j.fsigen.2018.05.003] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 04/12/2018] [Accepted: 05/11/2018] [Indexed: 11/17/2022]
Abstract
The identification of a suspect in a DNA mixture typed with the standard short tandem repeat polymorphism (STR) kits has faced challenges. Several improved methods or technologies have been introduced to address this issue. However, some complex situations in the process remain elusive. In the present study, we presented a panel of 26 tiny microhaplotypes, each generating a relatively high (>3.0) effective number of alleles (Ae) and possessing low (<50 bp) sequence lengths. The average Ae and heterozygosity values among the 9 populations of 26 microhaps were in ranges from 2.60 to 4.54 and 0.59 to 0.96, respectively. Power of discrimination and power of exclusion values were ranged from 0.49 to 0.87 and 0.29 to 0.94, respectively. Significant positive correlations have been found between Ae values and heterozygosity (r = 0.43, p = 0.02) or power of discrimination values (r = 0.55, p = 0.003), respectively. The cumulative probability of detecting a mixture of two unrelated individuals could reach 0.9999998 when using a panel of 26 microhaps with Ae = 3. We further tested the panel by using massively parallel sequencing, and 14 out of 26 microhaps were successfully genotyped in a single multiplex system. 60 unrelated Chinese Han individuals and 2 artificially prepared samples mixed by two unrelated contributors (in duplicate, ie. 4 mixtures) were sequenced. Approximately 32.14% of the 14 loci presented three or four alleles in the two mixtures. The likelihood ratio values to cognizance the mixtures' contributor were in a range from 1.95 × 106 to 1.10 × 107. The results demonstrated that the present panel could offer a valuable complementary tool in forensic applications.
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Affiliation(s)
- Peng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China.
| | - Caiyong Yin
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Zheng Li
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Yan Pu
- Department of Forensic Biology, West China School of Basic Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, PR China
| | - Youjia Yu
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Peng Zhao
- Institute of Forensic Science, Wuxi Public Security Bureau, Wuxi, 214002, Jiangsu, China
| | - Dexin Chen
- Department of Engineering, Columbia University, New York, 10027, USA
| | - Weibo Liang
- Department of Forensic Biology, West China School of Basic Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, PR China
| | - Lin Zhang
- Department of Forensic Biology, West China School of Basic Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, PR China
| | - Feng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China.
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A 1204-single nucleotide polymorphism and insertion–deletion polymorphism panel for massively parallel sequencing analysis of DNA mixtures. Forensic Sci Int Genet 2018; 32:94-101. [DOI: 10.1016/j.fsigen.2017.11.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 11/03/2017] [Accepted: 11/06/2017] [Indexed: 11/19/2022]
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Abstract
The utility of short tandem repeat genetic (STR) markers for forensic science is beyond question and there are over 50 million STR profiles in current national databases. The magnitude and value of those data, however, are likely to be dwarfed by what is emerging from large-scale SNP and DNA sequence assays. Phenotypic characterization may well accompany future statements about identity. In this very brief review we focus on the use of rare variants to describe relatedness and population structure.
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