Forensic inference of biogeographical ancestry from genotype: The Genetic Ancestry Lab

被引:5
|
作者
McNevin, Dennis [1 ,2 ]
机构
[1] Univ Technol Sydney, Fac Sci, Ctr Forens Sci, Sch Math & Phys Sci, Ultimo, NSW 2007, Australia
[2] Univ Canberra, Fac Sci & Technol, Bruce, ACT, Australia
来源
关键词
admixture; biogeographical ancestry; Genetic Ancestry Lab; massively parallel sequencing; GENOME DIVERSITY PROJECT; POPULATION-STRUCTURE; SNAPSHOT ASSAY; Y-CHROMOSOME; SNP PANEL; MARKER; SYSTEM; DIFFERENTIATION; PREDICTION; ADMIXTURE;
D O I
10.1002/wfs2.1356
中图分类号
DF [法律]; D9 [法律];
学科分类号
0301 ;
摘要
Short tandem repeat (STR) profiling of DNA has become ubiquitous in forensic practice and is used to associate people, objects, and places with each other and with crimes. STRs can include or exclude a suspect or victim as the donor of biological evidence. In the absence of a matching profile, however, STRs have limited value. It is possible, then, to extract other information from the DNA that might lead forensic investigators to an offender. Examples include biogeographical ancestry (BGA) and externally visible characteristics (EVCs). These require alternative genetic markers including single nucleotide polymorphisms and microhaplotypes which can be genotyped on many different platforms including capillary electrophoresis, microarrays, and massively parallel sequencing (MPS). The Genetic Ancestry Lab (GAL) in Australia provides estimates of BGA and EVCs derived from DNA that is extracted from biological evidence and then subjected to targeted amplicon enrichment and subsequent MPS. This review will describe the process of BGA prediction employed by the GAL as well as describing alternative practices. Limitations are addressed and future directions highlighted, including resolution of genetic admixture. It is highly likely that inference of BGA will become standard forensic practice, performed simultaneously with or in addition to STR profiling, and it is hoped that this review might provide a road map. This article is categorized under: Forensic Anthropology > Ancestry Determination Forensic Science in Action/Crime Scene Investigation > From Traces to Intelligence and Evidence Forensic Biology > Ancestry Determination using DNA Methods Forensic Biology > Forensic DNA Technologies
引用
收藏
页数:26
相关论文
共 50 条
  • [1] Forensic biogeographical ancestry inference: recent insights and current trends
    Wen, Yufeng
    Liu, Jing
    Su, Yonglin
    Chen, Xiacan
    Hou, Yiping
    Liao, Linchuan
    Wang, Zheng
    [J]. GENES & GENOMICS, 2023, 45 (10) : 1229 - 1238
  • [2] Forensic biogeographical ancestry inference: recent insights and current trends
    Yufeng Wen
    Jing Liu
    Yonglin Su
    Xiacan Chen
    Yiping Hou
    Linchuan Liao
    Zheng Wang
    [J]. Genes & Genomics, 2023, 45 : 1229 - 1238
  • [3] Prediction of biogeographical ancestry from genotype: a comparison of classifiers
    Elaine Y Y Cheung
    Michelle Elizabeth Gahan
    Dennis McNevin
    [J]. International Journal of Legal Medicine, 2017, 131 : 901 - 912
  • [4] Prediction of biogeographical ancestry from genotype: a comparison of classifiers
    Cheung, Elaine Y. Y.
    Gahan, Michelle Elizabeth
    McNevin, Dennis
    [J]. INTERNATIONAL JOURNAL OF LEGAL MEDICINE, 2017, 131 (04) : 901 - 912
  • [5] Deep Learning Approach to Biogeographical Ancestry Inference
    Qu, Yue
    Tran, Dat
    Ma, Wanli
    [J]. KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019), 2019, 159 : 552 - 561
  • [6] Genetic estimation of biogeographical ancestry.
    Pfaff, CL
    Parra, EJ
    Shriver, MD
    [J]. AMERICAN JOURNAL OF HUMAN GENETICS, 2000, 67 (04) : 221 - 221
  • [7] Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field
    Eugenio Alladio
    Brando Poggiali
    Giulia Cosenza
    Elena Pilli
    [J]. Scientific Reports, 12
  • [8] Partial forensic validation of a 16plex SNP assay for the inference of biogeographical ancestry
    Daniel, Runa
    Sanchez, Juan J.
    Nassif, Najah T.
    Hernandez, Alexis
    Walsh, Simon J.
    [J]. FORENSIC SCIENCE INTERNATIONAL GENETICS SUPPLEMENT SERIES, 2009, 2 (01) : 477 - 478
  • [9] Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field
    Alladio, Eugenio
    Poggiali, Brando
    Cosenza, Giulia
    Pilli, Elena
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [10] Biogeographical Ancestry Inference from Genotype: A Comparison of Ancestral Informative SNPs and Genome-wide SNPs
    Qu, Yue
    Tran, Dat
    Martinez-Marroquin, Elisa
    [J]. 2020 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2020, : 64 - 70