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Sun W, Wang Z, Wen S, Huang A, Li H, Jiang L, Feng Q, Fan D, Tian Q, Han D, Liu X. Technical strategy for monozygotic twin discrimination by single-nucleotide variants. Int J Legal Med 2024; 138:767-779. [PMID: 38197923 DOI: 10.1007/s00414-023-03150-7] [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: 03/08/2023] [Accepted: 12/11/2023] [Indexed: 01/11/2024]
Abstract
Monozygotic (MZ) twins are theoretically genetically identical. Although they are revealed to accumulate mutations after the zygote splits, discriminating between twin genomes remains a formidable challenge in the field of forensic genetics. Single-nucleotide variants (SNVs) are responsible for a substantial portion of genetic variation, thus potentially serving as promising biomarkers for the identification of MZ twins. In this study, we sequenced the whole genome of a pair of female MZ twins when they were 27 and 33 years old to approximately 30 × coverage using peripheral blood on an Illumina NovaSeq 6000 Sequencing System. Potentially discordant SNVs supported by whole-genome sequencing were validated extensively by amplicon-based targeted deep sequencing and Sanger sequencing. In total, we found nine bona fide post-twinning SNVs, all of which were identified in the younger genomes and found in the older genomes. None of the SNVs occurred within coding exons, three of which were observed in introns, supported by whole-exome sequencing results. A double-blind test was employed, and the reliability of MZ twin discrimination by discordant SNVs was endorsed. All SNVs were successfully detected when input DNA amounts decreased to 0.25 ng, and reliable detection was limited to seven SNVs below 0.075 ng input. This comprehensive analysis confirms that SNVs could serve as cost-effective biomarkers for MZ twin discrimination.
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Affiliation(s)
- Weifen Sun
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ziwei Wang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
- Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, China
| | - Shubo Wen
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
- Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, China
| | - Ao Huang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
- Department of Forensic Science, Medical School of Soochow University, Suzhou, 215123, China
| | - Hui Li
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
| | - Lei Jiang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China
| | - Qi Feng
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center of Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Danlin Fan
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center of Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Qilin Tian
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center of Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Dingding Han
- Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
| | - Xiling Liu
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China.
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Hwa HL, Lin CY, Yu YJ, Linacre A, Lee JCI. DNA identification of monozygotic twins. Forensic Sci Int Genet 2024; 69:102998. [PMID: 38100853 DOI: 10.1016/j.fsigen.2023.102998] [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: 08/23/2023] [Revised: 11/14/2023] [Accepted: 12/10/2023] [Indexed: 12/17/2023]
Abstract
This study details the differentiation of identical twins based on single mutational base differences. There were three pairs of male monozygotic (MZ) twins in this study. DNA samples from blood, a buccal swab or saliva from each individual were all initially genotyped using 22 autosomal STR and 27 Y-STR loci. Preliminary screening confirmed there were no differences in the STR data between each pair of MZ twins. Whole Genome Sequence (WGS) data were generated from DNA extracted from the three body fluids from each individual. Kinship coefficients with 0.4254, 0.4557 and 0.4543 from 3 twins were generated based on WGS data to further confirm that their relationship was that of MZ twins. The fastq data generated by the Illumina Hiseq 2000 between MZ twins were then treated as "normal" as opposed to "tumor" using commercially available software tools to identify mutational single base changes. Sanger DNA sequencing confirmed there were 1, 5 and 9 single base changes found in WGS data from each of the three MZ twin sets. There was individual variation in the mutational base changes when comparing data from the three body fluids. The methods used in this study to differentiate MZ twins based on WGS data can readily be performed in many operational forensic DNA laboratories using user friendly software.
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Affiliation(s)
- Hsiao-Lin Hwa
- Department of Forensic Medicine, College of Medicine, National Taiwan University, No.1 Jen-Ai Road Section 1, Taipei 10051, Taiwan
| | - Chun-Yen Lin
- Institute of Forensic Medicine, Ministry of Justice, New Taipei City 23016, Taiwan
| | - Yu-Jen Yu
- Department of Forensic Medicine, College of Medicine, National Taiwan University, No.1 Jen-Ai Road Section 1, Taipei 10051, Taiwan
| | - Adrian Linacre
- College of Science & Engineering, Flinders University, Adelaide 5001, Australia
| | - James Chun-I Lee
- Department of Forensic Medicine, College of Medicine, National Taiwan University, No.1 Jen-Ai Road Section 1, Taipei 10051, Taiwan.
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Frontanilla TS, Valle-Silva G, Ayala J, Mendes-Junior CT. Open-Access Worldwide Population STR Database Constructed Using High-Coverage Massively Parallel Sequencing Data Obtained from the 1000 Genomes Project. Genes (Basel) 2022; 13:genes13122205. [PMID: 36553472 PMCID: PMC9778533 DOI: 10.3390/genes13122205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/13/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022] Open
Abstract
Achieving accurate STR genotyping by using next-generation sequencing data has been challenging. To provide the forensic genetics community with a reliable open-access STR database, we conducted a comprehensive genotyping analysis of a set of STRs of broad forensic interest obtained from 1000 Genome populations. We analyzed 22 STR markers using files of the high-coverage dataset of Phase 3 of the 1000 Genomes Project. We used HipSTR to call genotypes from 2504 samples obtained from 26 populations. We were not able to detect the D21S11 marker. The Hardy-Weinberg equilibrium analysis coupled with a comprehensive analysis of allele frequencies revealed that HipSTR was not able to identify longer alleles, which resulted in heterozygote deficiency. Nevertheless, AMOVA, a clustering analysis that uses STRUCTURE, and a Principal Coordinates Analysis showed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium. Except for larger Penta D and Penta E alleles, and two very small Penta D alleles (2.2 and 3.2) usually observed in African populations, our analyses revealed that allele frequencies and genotypes offered as an open-access database are consistent and reliable.
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Affiliation(s)
- Tamara Soledad Frontanilla
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14049-900, SP, Brazil
| | - Guilherme Valle-Silva
- Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-901, SP, Brazil
| | - Jesus Ayala
- Facultad de Ingeniería Informática, Universidad de la Integración de las Americas, Asunción 00120-6, Paraguay
| | - Celso Teixeira Mendes-Junior
- Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-901, SP, Brazil
- Correspondence:
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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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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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