Skip to main content

Advertisement

SpringerLink
Log in

Prediction of people’s origin from degraded DNA—presentation of SNP assays and calculation of probability

  • Short Communication
  • Published:
International Journal of Legal Medicine Aims and scope Submit manuscript

Abstract

The characterization of externally visible traits by DNA analysis is already an important tool when investigating ancient skeletal remains and may gain similar importance in future forensic DNA analysis. This, however, depends on the different legal regulations in the different countries. Besides eye or hair color, the population origin can provide crucial information in criminal prosecution. In this study, we present the analysis of 16 single-nucleotide polymorphisms (SNPs) combined to two robust SNaPshot assays with a detection threshold of 25-pg DNA. This assay was applied to 891 people from seven different populations (West Africa, North Africa, Turkey, Near East, Balkan states, North Europe, and Japan) with a thorough statistical evaluation. The prediction model was validated by an additional 125 individuals predominantly with an ancestry from those same regions. The specificity of these SNPs for the prediction of all population origins is very high (>90 %), but the sensitivity varied greatly (more than 90 % for West Africa, but only 25 % for the Near East). We could identify West Africans with a certainty of 100 %, and people from North Africa, the Balkan states, or North Europe nearly with the same reliability while determination of Turks or people from the Near East was rather difficult. In conclusion, the two SNaPshot assays are a powerful and reliable tool for the identification of people with an ancestry in one of the above listed populations, even from degraded DNA.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Valverde P, Healy E, Jackson I, Rees JL, Thody AJ (1995) Variants of the melanocyte-stimulating hormone receptor gene are associated with red hair and fair skin in humans. Nat Genet 11:328–330

    Article  PubMed  CAS  Google Scholar 

  2. Stokowski RP, Pant PV, Dadd T, Fereday A, Hinds DA, Jarman C, Filsell W, Ginger RS, Green MR, van der Ouderaa FJ, Cox DR (2007) A genomewide association study of skin pigmentation in a South Asian population. Am J Hum Genet 81:1119–1132

    Article  PubMed  CAS  Google Scholar 

  3. Branicki W, Brudnik U, Kupiec T, Wolańska-Nowak P, Szczerbińska A, Wojas-Pelc A (2008) Association of polymorphic sites in the OCA2 gene with eye colour using the tree scanning method. Ann Hum Genet 72:184–192

    Article  PubMed  CAS  Google Scholar 

  4. Branicki W, Brudnik U, Wojas-Pelc A (2009) Interactions between HERC2, OCA2 and MC1R may influence human pigmentation phenotype. Ann Hum Genet 73:160–170

    Article  PubMed  CAS  Google Scholar 

  5. Kayser M, Schneider PM (2009) DNA-based prediction of human externally visible characteristics in forensics: motivation, scientific challenges, and ethical considerations. Forensic Sci Int Genet 3:154–161

    Article  PubMed  CAS  Google Scholar 

  6. Walsh S, Liu F, Ballantyne KN, van Oven M, Lao O, Kayser M (2011) IrisPlex: a sensitive DNA tool for accurate prediction of blue and brown eye colour in the absence of ancestry information. Forensic Sci Int Genet 5:170–180

    Article  PubMed  CAS  Google Scholar 

  7. Walsh S, Lindenbergh A, Zuniga SB, Sijen T, de Knijff P, Kayser M, Ballantyne KN (2011) Developmental validation of the IrisPlex system: determination of blue and brown iris colour for forensic intelligence. Forensic Sci Int Genet 5:464–471

    Article  PubMed  CAS  Google Scholar 

  8. Walsh S, Wallstein A, Liu F, Chakravarthy U, Rahu M, Seland JH, Soubrane F, Tomazzoli L, Topouzis F, Vingerling JR, Vioque J, Fletcher AE, Ballantyne KN, Kayser M (2012) DNA-based eye colour prediction across Europe with the IrisPlex system. Forensic Sci Int Genet 6:330–340

    Article  PubMed  CAS  Google Scholar 

  9. Pośpiech E, Draus-Barini J, Kupiec T, Wojas-Pelc A, Branicki W (2011) Gene-gene interactions contribute to eye colour variation in humans. J Hum Genet 56:447–455

    Article  PubMed  Google Scholar 

  10. Spichenok O, Budimlija ZM, Mitchel AA, Jenny A, Kovacevic L, Marjanovic D, Caragine T, Prinz M, Wurmbach E (2011) Prediction of eye and skin color in diverse populations using seven SNPs. Forensic Sci Int Genet 5:472–478

    Article  PubMed  CAS  Google Scholar 

  11. Pneuman A, Zm B, Caragine T, Prinz M, Wurmbach E (2012) Verification of eye and skin color predictors in various populations. Leg Med 14:78–83

    Article  Google Scholar 

  12. Bouakaze C, Keyser C, Crubezy E, Montagnon D, Ludes B (2009) Pigment phenotype and biogeographical ancestry from ancient skeletal remains: inferences from multiplexed autosomal SNP analysis. Int J Legal Med 123:315–325

    Article  PubMed  Google Scholar 

  13. Rasmussen M, Li Y, Lindgreen S, Pedersen JS, Albrechtsen A, Moltke I, Metspalu M, Metspalu E, Kivisild T, Gupta R, Bertalan M, Nielsen K, Gilbert MT, Wang Y, Raghavan M, Campos PF, Kamp HM, Wilson AS, Gledhill A, Tridico S, Bunce M, Lorenzen ED, Binladen J, Guo X, Zhao J, Zhang X, Zhang H, Li Z, Chen M, Orlando L, Kristiansen K, Bak M, Tommerup N, Bendixen C, Pierre TL, Gronnow B, Meldgaard M, Andreasen C, Fedorova SA, Osipova LP, Higham TF, Ramsey CB, Hansen TV, Nielsen FC, Crawford MH, Brunak S, Sicheritz-Ponten T, Villems R, Nielsen R, Krogh A, Wang J, Willerslev E (2010) Ancient human genome sequence of an extinct Palaeo-Eskimo. Nature 463:757–762

    Article  PubMed  CAS  Google Scholar 

  14. Xing J, Watkins WS, Shlien A, Walker E, Huff CD, Witherspoon DJ, Zhang Y, Simonson TS, Weiss RB, Schiffman JD, Malkin D, Woodward SR, Jorde LB (2010) Toward a more uniform sampling of human genetic diversity: a survey of worldwide populations by high-density genotyping. Genomics 96:199–210

    Article  PubMed  CAS  Google Scholar 

  15. Glover KA, Hansen MM, Lien S, Als TD, Hoyheim B, Skaala O (2010) A comparison of SNP and STR loci for delineating population structure and performing individual genetic assignment. BMC Genet 6(11):2

    Article  Google Scholar 

  16. Huyghe JR, Fransen E, Hannula S, Van Laer L, Van Eyken E, Mäki-Torkko E, Aikio P, Sorri M, Huentelman MJ, Van Camp G (2011) A genome-wide analysis of population structure in the Finnish Saami with implications for genetic association studies. Eur J Hum Genet 19:347–352

    Article  PubMed  Google Scholar 

  17. Sikora M, Laayouni H, Calafell F, Comas D, Bertranpetit J (2011) A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations. Eur J Hum Genet 19:84–88

    Article  PubMed  Google Scholar 

  18. Amigo J, Phillips C, Lareu M, Carracedo A (2008) The SNPforID browser: an online tool for query and display of frequency data from the SNPforID project. Int J Legal Med 122:435–440

    Article  PubMed  Google Scholar 

  19. Kamphausen T, Schadendorf D, von Wurmb-Schwark N, Bajanowski T, Poetsch M (2012) Good shedder or bad shedder—the influence of skin diseases on forensic DNA analysis from epithelial abrasions. Int J Legal Med 126:179–183

    Article  PubMed  Google Scholar 

  20. Austin P, Tu J (2004) Bootstrap methods for developing predictive models. Am Stat 58:131–137

    Article  Google Scholar 

  21. Hosmer DW Jr, Lemeshow S (1989) Applied logistic regression. Wiley, New York

    Google Scholar 

  22. Phillips C, Salas A, Sanchez JJ, Fondevila M, Gomez-Tato A, Ivarez-Dios JA, de Cal Calaza M, Casares M, Ballard D, Lareu MV, Carracedo A, The SNPforID Consortium (2007) Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs. Forensic Sci Int Genet 1:273–280

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We would like to thank all volunteers who participated in this study.

Author information

Authors and Affiliations

  1. Institute of Legal Medicine, University Hospital Essen, Hufelandstr. 55, 45122, Essen, Germany

    Micaela Poetsch & Rowena Blöhm

  2. Institute of Legal Medicine, University of Schleswig-Holstein, Campus Kiel, Kiel, Germany

    Melanie Harder & Nicole von Wurmb-Schwark

  3. Graduate School “Human Development in Landscapes”, Christian-Albrechts-University, Kiel, Germany

    Melanie Harder & Nicole von Wurmb-Schwark

  4. Department of Forensic Medicine and Sciences, Mie University Graduate School of Medicine, Mie, Japan

    Hiromasa Inoue

  5. Institute of Medical Informatics and Statistics, University of Schleswig-Holstein, Campus Kiel, Kiel, Germany

    Sandra Freitag-Wolf

Authors
  1. Micaela Poetsch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rowena Blöhm
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Melanie Harder
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hiromasa Inoue
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nicole von Wurmb-Schwark
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sandra Freitag-Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Micaela Poetsch.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

Characteristics of the chosen SNPs (DOC 34 kb)

ESM 2

Primer sequences for multiplex and SNaPshot PCR (DOC 41 kb)

ESM 3

Results of bootstrap model selection (DOC 26 kb)

ESM 4

Identification of unknown samples in the validation assay. A correct identification (with a probability of more than 50 %) is highlighted in yellow. The two wrong identifications (see text) are indicated in turquoise (XLS 61 kb)

ESM 5

Additional calculation of samples from Table S4 with method 2. A correct identification (with a probability of more than 50%) is highlighted in yellow. The two wrong identifications (see text) are indicated in turquoise (XLS 31 kb)

ESM 6

Results of the analysis of artificial stains derived from two people (XLS 20 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Poetsch, M., Blöhm, R., Harder, M. et al. Prediction of people’s origin from degraded DNA—presentation of SNP assays and calculation of probability. Int J Legal Med 127, 347–357 (2013). https://doi.org/10.1007/s00414-012-0728-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00414-012-0728-0

Keywords

Search

Navigation