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Han J, Zhuang B, Zou L, Wang D, Jiang L, Wei YL, Zhao L, Zhao L, Li C. A developmental validation of the Quick TargSeq 1.0 integrated system for automated DNA genotyping in forensic science for reference samples. Electrophoresis 2024; 45:814-828. [PMID: 38459798 DOI: 10.1002/elps.202300187] [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: 08/22/2023] [Revised: 02/07/2024] [Accepted: 02/21/2024] [Indexed: 03/10/2024]
Abstract
Analysis of short tandem repeats (STRs) is a global standard method for human identification. Insertion/Deletion polymorphisms (DIPs) can be used for biogeographical ancestry inference. Current DNA typing involves a trained forensic worker operating several specialized instruments in a controlled laboratory environment, which takes 6-8 h. We developed the Quick TargSeq 1.0 integrated system (hereinafter abbreviated to Quick TargSeq) for automated generation of STR and DIP profiles from buccal swab samples and blood stains. The system fully integrates the processes of DNA extraction, polymerase chain reaction (PCR) amplification, and electrophoresis separation using microfluidic biochip technology. Internal validation studies were performed using RTyper 21 or DIP 38 chip cartridges with single-source reference samples according to the Scientific Working Group for DNA Analysis Methods guidelines. These results indicated that the Quick TargSeq system can process reference samples and generate STR or DIP profiles in approximately 2 h, and the profiles were concordant with those determined using traditional STR or DIP analysis methods. Thus, reproducible and concordant DNA profiles were obtained from reference samples. Throughout the study, no lane-to-lane or run-to-run contamination was observed. The Quick TargSeq system produced full profiles from buccal swabs with at least eight swipes, dried blood spot cards with two 2-mm disks, or 10 ng of purified DNA. Potential PCR inhibitors (i.e., coffee, smoking tobacco, and chewing tobacco) did not appear to affect the amplification reactions of the instrument. The overall success rate and concordance rate of 153 samples were 94.12% and 93.44%, respectively, which is comparable to other commercially available rapid DNA instruments. A blind test initiated by a DNA expert group showed that the system can correctly produce DNA profiles with 97.29% genotype concordance with standard bench-processing methods, and the profiles can be uploaded into the national DNA database. These results demonstrated that the Quick TargSeq system can rapidly generate reliable DNA profiles in an automated manner and has the potential for use in the field and forensic laboratories.
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Affiliation(s)
- Junping Han
- Technology Department of Chaoyang Sub-bureau, Beijing Public Security Bureau, Beijing, P. R. China
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, P. R. China
| | - Bin Zhuang
- Beijing CapitalBio Technology Ltd. Co., Beijing, P. R. China
| | - Lixin Zou
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, Jiangsu International Joint Center of Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, Jiangsu, P. R. China
| | - Daoyu Wang
- People's Public Security University of China, Beijing, P. R. China
| | - Li Jiang
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, P. R. China
| | - Yi-Liang Wei
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, Jiangsu International Joint Center of Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, Jiangsu, P. R. China
| | - Lijian Zhao
- Beijing CapitalBio Technology Ltd. Co., Beijing, P. R. China
| | - Lei Zhao
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, P. R. China
| | - Caixia Li
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, P. R. China
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Pilli E, Morelli S, Poggiali B, Alladio E. Biogeographical ancestry, variable selection, and PLS-DA method: a new panel to assess ancestry in forensic samples via MPS technology. Forensic Sci Int Genet 2023; 62:102806. [PMID: 36399972 DOI: 10.1016/j.fsigen.2022.102806] [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: 07/18/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 11/14/2022]
Abstract
As evidenced by the large number of articles recently published in the literature, forensic scientists are making great efforts to infer externally visible features and biogeographical ancestry (BGA) from DNA analysis. Just as phenotypic, ancestry information obtained from DNA can provide investigative leads to identify the victims (missing/unidentified persons, crime/armed conflict/mass disaster victims) or trace their perpetrators when no matches were found with the reference profile or in the database. Recently, the advent of Massively Parallel Sequencing technologies associated with the possibility of harnessing high-throughput genetic data allowed us to investigate the associations between phenotypic and genomic variations in worldwide human populations and develop new BGA forensic tools capable of simultaneously analyzing up to millions of markers if for example the ancient DNA approach of hybridization capture was adopted to target SNPs of interest. In the present study, a selection of more than 3000 SNPs was performed to create a new BGA panel and the accuracy of the new panel to infer ancestry from unknown samples was evaluated by the PLS-DA method. Subsequently, the panel created was assessed using three variable selection techniques (Backward variable elimination, Genetic Algorithm and Regularized elimination procedure), and the best SNPs in terms of inferring bio-geographical ancestry at inter- and intra-continental level were selected to obtain panels to predict BGA with a reduced number of selected markers to be applied in routine forensic cases where PCR amplification is the best choice to target SNPs.
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Affiliation(s)
- Elena Pilli
- Department of Biology, Forensic Molecular Anthropology Laboratory, University of Florence, Florence, Italy
| | - Stefania Morelli
- Department of Biology, Forensic Molecular Anthropology Laboratory, University of Florence, Florence, Italy
| | - Brando Poggiali
- Department of Biology, Forensic Molecular Anthropology Laboratory, University of Florence, Florence, Italy
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3
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Huang S, Sheng M, Li Z, Li K, Chen J, Wu J, Wang K, Shi C, Ding H, Zhou H, Ma L, Yang J, Pu Y, Yu Y, Chen F, Chen P. Inferring bio-geographical ancestry with 35 microhaplotypes. Forensic Sci Int 2022; 341:111509. [DOI: 10.1016/j.forsciint.2022.111509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 10/04/2022] [Accepted: 10/30/2022] [Indexed: 11/24/2022]
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Diepenbroek M, Bayer B, Anslinger K. Pushing the Boundaries: Forensic DNA Phenotyping Challenged by Single-Cell Sequencing. Genes (Basel) 2021; 12:genes12091362. [PMID: 34573344 PMCID: PMC8466929 DOI: 10.3390/genes12091362] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/24/2021] [Accepted: 08/27/2021] [Indexed: 12/26/2022] Open
Abstract
Single-cell sequencing is a fast developing and very promising field; however, it is not commonly used in forensics. The main motivation behind introducing this technology into forensics is to improve mixture deconvolution, especially when a trace consists of the same cell type. Successful studies demonstrate the ability to analyze a mixture by separating single cells and obtaining CE-based STR profiles. This indicates a potential use of the method in other forensic investigations, like forensic DNA phenotyping, in which using mixed traces is not fully recommended. For this study, we collected single-source autopsy blood from which the white cells were first stained and later separated with the DEPArray™ N×T System. Groups of 20, 10, and 5 cells, as well as 20 single cells, were collected and submitted for DNA extraction. Libraries were prepared using the Ion AmpliSeq™ PhenoTrivium Panel, which includes both phenotype (HIrisPlex-S: eye, hair, and skin color) and ancestry-associated SNP-markers. Prior to sequencing, half of the single-cell-based libraries were additionally amplified and purified in order to improve the library concentrations. Ancestry and phenotype analysis resulted in nearly full consensus profiles resulting in correct predictions not only for the cells groups but also for the ten re-amplified single-cell libraries. Our results suggest that sequencing of single cells can be a promising tool used to deconvolute mixed traces submitted for forensic DNA phenotyping.
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Ghaiyed AP, Chaseling J, Lea RA, Bernie A, Haupt LM, Griffiths LR, Wright KM. Development of an accurate genomic ancestry prediction strategy to enable the accounting of Australian and Japanese historical military remains. AUST J FORENSIC SCI 2020. [DOI: 10.1080/00450618.2020.1853233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- A. P. Ghaiyed
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Kelvin Grove, Australia
| | - J. Chaseling
- School of Environment and Science, Griffith University, Nathan, Australia
| | - R. A. Lea
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Kelvin Grove, Australia
| | - A. Bernie
- Unrecovered War Casualties-Army, Australian Defence Force, Russell Offices, Canberra, Australia
| | - L. M. Haupt
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Kelvin Grove, Australia
| | - L. R. Griffiths
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Kelvin Grove, Australia
| | - K. M. Wright
- Unrecovered War Casualties-Army, Australian Defence Force, Russell Offices, Canberra, Australia
- Royal Australian Air Force (RAAF) No 2 Expeditionary Health Squadron, Williamtown, Australia
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Evaluation of the Ion AmpliSeq™ PhenoTrivium Panel: MPS-Based Assay for Ancestry and Phenotype Predictions Challenged by Casework Samples. Genes (Basel) 2020; 11:genes11121398. [PMID: 33255693 PMCID: PMC7760956 DOI: 10.3390/genes11121398] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 11/19/2020] [Accepted: 11/22/2020] [Indexed: 12/21/2022] Open
Abstract
As the field of forensic DNA analysis has started to transition from genetics to genomics, new methods to aid in crime scene investigations have arisen. The development of informative single nucleotide polymorphism (SNP) markers has led the forensic community to question if DNA can be a reliable "eye-witness" and whether the data it provides can shed light on unknown perpetrators. We have developed an assay called the Ion AmpliSeq™ PhenoTrivium Panel, which combines three groups of markers: 41 phenotype- and 163 ancestry-informative autosomal SNPs together with 120 lineage-specific Y-SNPs. Here, we report the results of testing the assay's sensitivity and the predictions obtained for known reference samples. Moreover, we present the outcome of a blind study performed on real casework samples in order to understand the value and reliability of the information that would be provided to police investigators. Furthermore, we evaluated the accuracy of admixture prediction in Converge™ Software. The results show the panel to be a robust and sensitive assay which can be used to analyze casework samples. We conclude that the combination of the obtained predictions of phenotype, biogeographical ancestry, and male lineage can serve as a potential lead in challenging police investigations such as cold cases or cases with no suspect.
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Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers. Sci Rep 2020; 10:7745. [PMID: 32385290 PMCID: PMC7210943 DOI: 10.1038/s41598-020-64245-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 04/03/2020] [Indexed: 11/09/2022] Open
Abstract
Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.
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Pfaffelhuber P, Grundner-Culemann F, Lipphardt V, Baumdicker F. How to choose sets of ancestry informative markers: A supervised feature selection approach. Forensic Sci Int Genet 2020; 46:102259. [PMID: 32105949 DOI: 10.1016/j.fsigen.2020.102259] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 12/23/2019] [Accepted: 02/01/2020] [Indexed: 01/06/2023]
Abstract
Inference of the Biogeographical Ancestry (BGA) of a person or trace relies on three ingredients: (1) a reference database of DNA samples including BGA information; (2) a statistical clustering method; (3) a set of loci which segregate dependent on geographical location, i.e. a set of so-called Ancestry Informative Markers (AIMs). We used the theory of feature selection from statistical learning in order to obtain AIMsets for BGA inference. Using simulations, we show that this learning procedure works in various cases, and outperforms ad hoc methods, based on statistics like FST or informativeness for the choice of AIMs. Applying our method to data from the 1000 genomes project (excluding Admixed Americans) we identified an AIMset of 12 SNPs, which gives a vanishing misclassification error on a continental scale, as do other published AIMsets. In fact, cross validation shows that there exists a multitude of sets with comparable performance to the optimal AIMset. On a sub-continental scale, we find a set of 55 SNPs for distinguishing the five European populations. The misclassification error is reduced by a factor of two relative to published AIMsets, but is still 30% and therefore too large in order to be useful in forensic applications.
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Affiliation(s)
- Peter Pfaffelhuber
- University of Freiburg, Department of Mathematical Stochastics, Ernst-Zermelo-Straße 1, D-79104 Freiburg, Germany.
| | | | - Veronika Lipphardt
- University College Freiburg, Bertoldstraße 17, D-79098 Freiburg, Germany
| | - Franz Baumdicker
- University of Freiburg, Department of Mathematical Stochastics, Ernst-Zermelo-Straße 1, D-79104 Freiburg, Germany
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Jin X, Cui W, Chen C, Guo Y, Tao Y, Lan Q, Kong T, Zhu B. Biogeographic origin prediction of three continental populations through 42 ancestry informative SNPs. Electrophoresis 2019; 41:235-245. [DOI: 10.1002/elps.201900241] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 11/04/2019] [Accepted: 11/13/2019] [Indexed: 12/17/2022]
Affiliation(s)
- Xiao‐Ye Jin
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- College of Forensic MedicineXi'an Jiaotong University Health Science Center Xi'an P. R. China
| | - Wei Cui
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- College of Forensic MedicineXi'an Jiaotong University Health Science Center Xi'an P. R. China
| | - Chong Chen
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- College of Forensic MedicineXi'an Jiaotong University Health Science Center Xi'an P. R. China
| | - Yu‐Xin Guo
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- College of Forensic MedicineXi'an Jiaotong University Health Science Center Xi'an P. R. China
| | - Yong‐Wei Tao
- Cranio‐Maxillofacial Trauma Plastic SurgeryStomatology Hospital of Xi'an Jiaotong University College of Medicine Xi'an P. R. China
| | - Qiong Lan
- Department of Forensic GeneticsSchool of Forensic MedicineSouthern Medical University Guangzhou P. R. China
| | - Ting‐Ting Kong
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
| | - Bo‐Feng Zhu
- Key laboratory of Shaanxi Province for Craniofacial Precision Medicine ResearchCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Clinical Research Center of Shaanxi Province for Dental and Maxillofacial DiseasesCollege of StomatologyXi'an Jiaotong University Xi'an P. R. China
- Department of Forensic GeneticsSchool of Forensic MedicineSouthern Medical University Guangzhou P. R. China
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Qu S, Zhu J, Wang Y, Yin L, Lv M, Wang L, Jian H, Tan Y, Zhang R, Liu Y, Li F, Huang S, Liang W, Zhang L. Establishing a second-tier panel of 18 ancestry informative markers to improve ancestry distinctions among Asian populations. Forensic Sci Int Genet 2019; 41:159-167. [DOI: 10.1016/j.fsigen.2019.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 05/08/2019] [Accepted: 05/09/2019] [Indexed: 11/16/2022]
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Bradbury C, Köttgen A, Staubach F. Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource. Forensic Sci Int Genet 2018; 38:93-104. [PMID: 30391626 DOI: 10.1016/j.fsigen.2018.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 08/27/2018] [Accepted: 10/13/2018] [Indexed: 01/04/2023]
Abstract
With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application. In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.
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Affiliation(s)
- Cedric Bradbury
- University College Freiburg, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Dept. of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Fabian Staubach
- Institute of Biology I, Dept. of Evolutionary Biology and Ecology, Albert-Ludwigs-University Freiburg, Freiburg, Germany.
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Yang CH, Yin CY, Shen CM, Guo YX, Dong Q, Yan JW, Wang HD, Zhang YD, Meng HT, Jin R, Chen F, Zhu BF. Genetic variation and forensic efficiency of autosomal insertion/deletion polymorphisms in Chinese Bai ethnic group: phylogenetic analysis to other populations. Oncotarget 2018; 8:39582-39591. [PMID: 28465476 PMCID: PMC5503634 DOI: 10.18632/oncotarget.17137] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Accepted: 02/17/2017] [Indexed: 01/01/2023] Open
Abstract
Thirty insertion/deletion loci were utilized to study the genetic diversities of 125 bloodstain samples collected from Bai group in Yunnan Dali region, China. The observed heterozygosity and expected heterozygosity of the 30 loci ranged from 0.1520 to 0.5680, and 0.1927 to 0.4997, respectively. No deviations from Hardy-Weinberg equilibrium tests after Bonferroni correction were found at all 30 loci in Bai group. The cumulative probability of exclusion and combined discrimination power were 0.9859 and 0.9999999999887, respectively, which indicated the 30 loci could be used as complementary genetic markers for paternity testing and were qualified for personal identification in forensic cases. We found the studied Bai group had close relationships with Tibetan, Yi and Han groups from China by the population structure, principal component analysis, population differentiations, and phylogenetic reconstruction studies. Even so, for a better understanding of Bai ethnicity's genetic milieu, DNA genotyping at various genetic markers is necessary in future studies.
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Affiliation(s)
- Chun-Hua Yang
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong, P. R. China
| | - Cai-Yong Yin
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, P. R. China
| | - Chun-Mei Shen
- Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong, P. R. China.,Institute of Brain and Behavioral Sciences, College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, P. R. China
| | - Yu-Xin Guo
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Qian Dong
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Jiang-Wei Yan
- Key Laboratory of Genome Sciences, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, P. R. China
| | - Hong-Dan Wang
- Medical Genetic Institute of Henan Province, People's Hospital of Henan Province, Zhengzhou, Henan, P. R. China
| | - Yu-Dang Zhang
- Institue of Forensic Sciences of Anhui Public Security Department, Hefei, Anhui, P. R. China
| | - Hao-Tian Meng
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Rui Jin
- Department of Radiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Feng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, P. R. China
| | - Bo-Feng Zhu
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China.,Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong, P. R. China
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Ramani A, Wong Y, Tan SZ, Shue BH, Syn C. Ancestry prediction in Singapore population samples using the Illumina ForenSeq kit. Forensic Sci Int Genet 2017; 31:171-179. [DOI: 10.1016/j.fsigen.2017.08.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Revised: 07/18/2017] [Accepted: 08/11/2017] [Indexed: 11/24/2022]
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14
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Sun Q, Jiang L, Zhang G, Liu J, Zhao L, Zhao W, Li C. Twenty-seven continental ancestry-informative SNP analysis of bone remains to resolve a forensic case. Forensic Sci Res 2017; 4:364-366. [PMID: 32002497 PMCID: PMC6968571 DOI: 10.1080/20961790.2017.1306431] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Accepted: 02/22/2017] [Indexed: 12/30/2022] Open
Abstract
We employed our previously developed 27-plex ancestry-informative single nucleotide polymorphism (SNP) panel to infer the ancestral components of bone remains of a possible foreign pilot found in south-western China. For ancestry assignment of this unknown individual, we first obtained the 27-SNP genotype of the individual. Then, based on a reference database of 3081 individuals from 33 populations, we calculated the match probability and likelihood ratio using the self-developed software program Forensic Intelligence. Inferred ancestral components of this individual were calculated by structure at K = 3. A complete profile was obtained for the individual using our multiplexed SNP assay. The European population was within one order of magnitude of the highest likelihood. The major ancestral component of this individual was 97.6% European.
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Affiliation(s)
- Qifan Sun
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Li Jiang
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Guangfeng Zhang
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Jing Liu
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Lei Zhao
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Wenting Zhao
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
| | - Caixia Li
- Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing, China
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15
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Castillo-Peinado LS, Luque de Castro MD. An overview on forensic analysis devoted to analytical chemists. Talanta 2017; 167:181-192. [PMID: 28340709 DOI: 10.1016/j.talanta.2017.01.087] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 01/28/2017] [Accepted: 01/29/2017] [Indexed: 12/01/2022]
Abstract
The present article has as main aim to show analytical chemists interested in forensic analysis the world they will face if decision in favor of being a forensic analytical chemist is adopted. With this purpose, the most outstanding aspects of forensic analysis in dealing with sampling (involving both bodily and no bodily samples), sample preparation, and analytical equipment used in detection, identification and quantitation of key sample components are critically discussed. The role of the great omics in forensic analysis, and the growing role of the youngest of the great omics -metabolomics- are also discussed. The foreseeable role of integrative omics is also outlined.
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Affiliation(s)
- L S Castillo-Peinado
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain; University of Córdoba, Agrifood Excellence Campus, ceiA3, Spain; Maimónides Institute of Biomedical Research (IMIBIC), Reina Sofía University Hospital, University of Córdoba, E-14071 Córdoba, Spain
| | - M D Luque de Castro
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain; University of Córdoba, Agrifood Excellence Campus, ceiA3, Spain; Maimónides Institute of Biomedical Research (IMIBIC), Reina Sofía University Hospital, University of Córdoba, E-14071 Córdoba, Spain.
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16
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Sun K, Ye Y, Luo T, Hou Y. Multi-InDel Analysis for Ancestry Inference of Sub-Populations in China. Sci Rep 2016; 6:39797. [PMID: 28004788 PMCID: PMC5177877 DOI: 10.1038/srep39797] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 11/29/2016] [Indexed: 01/03/2023] Open
Abstract
Ancestry inference is of great interest in diverse areas of scientific researches, including the forensic biology, medical genetics and anthropology. Various methods have been published for distinguishing populations. However, few reports refer to sub-populations (like ethnic groups) within Asian populations for the limitation of markers. Several InDel loci located very tightly in physical positions were treated as one marker by us, which is multi-InDel. The multi-InDel shows potential as Ancestry Inference Marker (AIM). In this study, we performed a genome-wide scan for multi-InDels as AIM. After examining the FST distributions in the 1000 Genomes Database, 12 candidates were selected and validated for eastern Asian populations. A multiplexed assay was developed as a panel to genotype 12 multi-InDel markers simultaneously. Ancestry component analysis with STRUCTURE and principal component analysis (PCA) were employed to estimate its capability for ancestry inference. Furthermore, ancestry assignments of trial individuals were conducted. It proved to be very effective when 210 samples from Han and Tibetan individuals in China were tested. The panel consisting of multi-InDel markers exhibited considerable potency in ancestry inference, and was suggested to be applied in forensic practices and genetic population studies.
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Affiliation(s)
- Kuan Sun
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, P.R. China
| | - Yi Ye
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, P.R. China
| | - Tao Luo
- Laboratory of Infection and Immunity, School of Basic Medical Sciences, West China Center of Medical Science, Sichuan University, Chengdu P.R. China
| | - Yiping Hou
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, P.R. China
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17
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Parker GJ, Leppert T, Anex DS, Hilmer JK, Matsunami N, Baird L, Stevens J, Parsawar K, Durbin-Johnson BP, Rocke DM, Nelson C, Fairbanks DJ, Wilson AS, Rice RH, Woodward SR, Bothner B, Hart BR, Leppert M. Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome. PLoS One 2016; 11:e0160653. [PMID: 27603779 PMCID: PMC5014411 DOI: 10.1371/journal.pone.0160653] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Accepted: 07/21/2016] [Indexed: 12/28/2022] Open
Abstract
Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects' DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European-American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.
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Affiliation(s)
- Glendon J. Parker
- Department of Biology, Utah Valley University, Orem, Utah, United States of America
- Protein-Based Identification Technologies L.L.C., Orem, Utah, United States of America
- * E-mail: parker64@llnl;
| | - Tami Leppert
- Protein-Based Identification Technologies L.L.C., Orem, Utah, United States of America
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Deon S. Anex
- Forensic Science Center, Lawrence Livermore National Laboratory, Livermore, California, United States of America
| | - Jonathan K. Hilmer
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, United States of America
| | - Nori Matsunami
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Lisa Baird
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Jeffery Stevens
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Krishna Parsawar
- Mass Spectrometry and Proteomics Core Facility, University of Utah, Salt Lake City, Utah, United States of America
| | - Blythe P. Durbin-Johnson
- Department of Public Health Sciences, University of California, Davis, California, United States of America
| | - David M. Rocke
- Department of Public Health Sciences, University of California, Davis, California, United States of America
| | - Chad Nelson
- Mass Spectrometry and Proteomics Core Facility, University of Utah, Salt Lake City, Utah, United States of America
| | - Daniel J. Fairbanks
- Department of Biology, Utah Valley University, Orem, Utah, United States of America
| | - Andrew S. Wilson
- School of Archaeological Sciences, University of Bradford, Bradford, United Kingdom
| | - Robert H. Rice
- Department of Environmental Toxicology, University of California, Davis, California, United States of America
| | - Scott R. Woodward
- Sorenson Molecular Genealogical Foundation, Salt Lake City, Utah, United States of America
| | - Brian Bothner
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, United States of America
| | - Bradley R. Hart
- Forensic Science Center, Lawrence Livermore National Laboratory, Livermore, California, United States of America
| | - Mark Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
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18
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A panel of 74 AISNPs: Improved ancestry inference within Eastern Asia. Forensic Sci Int Genet 2016; 23:101-110. [DOI: 10.1016/j.fsigen.2016.04.002] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Revised: 02/17/2016] [Accepted: 04/01/2016] [Indexed: 02/04/2023]
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19
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Soundararajan U, Yun L, Shi M, Kidd KK. Minimal SNP overlap among multiple panels of ancestry informative markers argues for more international collaboration. Forensic Sci Int Genet 2016; 23:25-32. [DOI: 10.1016/j.fsigen.2016.01.013] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 12/24/2015] [Accepted: 01/20/2016] [Indexed: 12/16/2022]
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20
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Wei YL, Sun QF, Li Q, Yi JL, Zhao L, Ou Y, Jiang L, Zhang T, Liu HB, Chen JG, Zhu BF, Ye J, Hu L, Li CX. Genetic structure and differentiation analysis of a Eurasian Uyghur population by use of 27 continental ancestry-informative SNPs. Int J Legal Med 2016; 130:897-903. [DOI: 10.1007/s00414-016-1335-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Accepted: 02/10/2016] [Indexed: 01/12/2023]
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21
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Zeng X, Chakraborty R, King JL, LaRue B, Moura-Neto RS, Budowle B. Selection of highly informative SNP markers for population affiliation of major US populations. Int J Legal Med 2015; 130:341-52. [DOI: 10.1007/s00414-015-1297-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 11/23/2015] [Indexed: 01/17/2023]
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22
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Casarini L, Santi D, Marino M. Impact of gene polymorphisms of gonadotropins and their receptors on human reproductive success. Reproduction 2015; 150:R175-84. [PMID: 26370242 DOI: 10.1530/rep-15-0251] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/08/2015] [Indexed: 12/17/2022]
Abstract
Gonadotropins and their receptors' genes carry several single-nucleotide polymorphisms resulting in endocrine genotypes modulating reproductive parameters, diseases, and lifespan leading to important implications for reproductive success and potential relevance during human evolution. Here we illustrate common genotypes of the gonadotropins and gonadotropin receptors' genes and their clinical implications in phenotypes relevant for reproduction such as ovarian cycle length, age of menopause, testosterone levels, polycystic ovary syndrome, and cancer. We then discuss their possible role in human reproduction and adaptation to the environment. Gonadotropins and their receptors' variants are differently distributed among human populations. Some hints suggest that they may be the result of natural selection that occurred in ancient times, increasing the individual chance of successful mating, pregnancy, and effective post-natal parental cares. The gender-related differences in the regulation of the reproductive endocrine systems imply that many of these genotypes may lead to sex-dependent effects, increasing the chance of mating and reproductive success in one sex at the expenses of the other sex. Also, we suggest that sexual conflicts within the FSH and LH-choriogonadotropin receptor genes contributed to maintain genotypes linked to subfertility among humans. Because the distribution of polymorphic markers results in a defined geographical pattern due to human migrations rather than natural selection, these polymorphisms may have had only a weak impact on reproductive success. On the contrary, such genotypes could acquire relevant consequences in the modern, developed societies in which parenthood attempts often occur at a later age, during a short, suboptimal reproductive window, making clinical fertility treatments necessary.
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Affiliation(s)
- Livio Casarini
- Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy
| | - Daniele Santi
- Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy
| | - Marco Marino
- Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy Unit of EndocrinologyDepartment of Biomedical, Metabolic and Neural SciencesCenter for Genomic ResearchUniversity of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, ItalyAzienda USL of ModenaNOCSAE, Via P. Giardini 1355, 41126 Modena, Italy
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23
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A single-tube 27-plex SNP assay for estimating individual ancestry and admixture from three continents. Int J Legal Med 2015; 130:27-37. [DOI: 10.1007/s00414-015-1183-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2014] [Accepted: 03/18/2015] [Indexed: 01/08/2023]
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24
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Yuasa I, Umetsu K, Adachi N, Matsusue A, Nakayashiki N, Fujihara J, Akane A, Harihara S, Jin F, Ishikawa T. Investigation of Japanese-specific alleles: Most are of Jomon lineage. Leg Med (Tokyo) 2015; 17:52-5. [DOI: 10.1016/j.legalmed.2014.08.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 08/25/2014] [Accepted: 08/28/2014] [Indexed: 11/26/2022]
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25
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Wei YL, Qin CJ, Liu HB, Jia J, Hu L, Li CX. Validation of 58 autosomal individual identification SNPs in three Chinese populations. Croat Med J 2014; 55:10-3. [PMID: 24577821 PMCID: PMC3944413 DOI: 10.3325/cmj.2014.55.10] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Aim To genotype and evaluate a panel of single-nucleotide polymorphisms for individual identification (IISNPs) in three Chinese populations: Chinese Han, Uyghur, and Tibetan. Methods Two previously identified panels of IISNPs, 86 unlinked IISNPs and SNPforID 52-plex markers, were pooled and analyzed. Four SNPs were included in both panels. In total, 132 SNPs were typed on Sequenom MassARRAY® platform in 330 individuals from Han Chinese, Uyghur, and Tibetan populations. Population genetic indices and forensic parameters were determined for all studied markers. Results No significant deviation from Hardy-Weinberg equilibrium was observed for any of the SNPs in 3 populations. Expected heterozygosity (He) ranged from 0.144 to 0.500 in Han Chinese, from 0.197 to 0.500 in Uyghur, and from 0.018 to 0.500 in Tibetan population. Wright's Fst values ranged from 0.0001 to 0.1613. Pairwise linkage disequilibrium (LD) calculations for all 132 SNPs showed no significant LD across the populations (r2<0.147). A subset of 58 unlinked IISNPs (r2<0.094) with He>0.450 and Fst values from 0.0002 to 0.0536 gave match probabilities of 10−25 and a cumulative probability of exclusion of 0.999992. Conclusion The 58 unlinked IISNPs with high heterozygosity have low allele frequency variation among 3 Chinese populations, which makes them excellent candidates for the development of multiplex assays for individual identification and paternity testing.
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Affiliation(s)
| | | | | | | | | | - Cai-Xia Li
- Cai-Xia Li, Institute of Forensic Science, Ministry of Public Security, Muxidi Nanli 17, Xicheng District, Beijing 100038, China,
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