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Inference of biogeographical ancestry across central regions of Eurasia

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Abstract

The inference of biogeographical ancestry (BGA) can provide useful information for forensic investigators when there are no suspects to be compared with DNA collected at the crime scene or when no DNA database matches exist. Although public databases are increasing in size and population scope, there is a lack of information regarding genetic variation in Eurasian populations, especially in central regions such as the Middle East. Inhabitants of these regions show a high degree of genetic admixture, characterized by an allele frequency cline running from NW Europe to East Asia. Although a proper differentiation has been established between the cline extremes of western Europe and South Asia, populations geographically located in between, i.e, Middle East and Mediterranean populations, require more detailed study in order to characterize their genetic background as well as to further understand their demographic histories. To initiate these studies, three ancestry informative SNP (AI-SNP) multiplex panels: the SNPforID 34-plex, Eurasiaplex and a novel 33-plex assay were used to describe the ancestry patterns of a total of 24 populations ranging across the longitudinal axis from NW Europe to East Asia. Different ancestry inference approaches, including STRUCTURE, PCA, DAPC and Snipper Bayes analysis, were applied to determine relationships among populations. The structure results show differentiation between continental groups and a NW to SE allele frequency cline running across Eurasian populations. This study adds useful population data that could be used as reference genotypes for future ancestry investigations in forensic cases. The 33-plex assay also includes pigmentation predictive SNPs, but this study primarily focused on Eurasian population differentiation using 33-plex and its combination with the other two AI-SNP sets.

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Acknowledgments

This research was supported by Istanbul University Scientific Research Projects Unit (BAP) under project number 19042. OB was supported by the German Academic Exchange Service (DAAD) under Research Grants for Doctoral Candidates and Young Academics and Scientists Programme and by The Scientific And Technological Research Council Of Turkey (TÜBİTAK) under 2211-Grant Programme. We sincerely thank all the sample contributors. The authors would like to thank Suad Alfadhli from the Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, Kuwait University, for collecting the Kuwait samples, Department of Criminalistic Investigations DNA Laboratory, Ministry of Internal Affairs of Azerbaijan Republic and Katharina Läer from the Department of Forensic Medicine, Hannover Medical School, Germany for technical assistance.

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Authors and Affiliations

  1. Institute of Forensic Sciences, Istanbul University, Istanbul, Turkey

    O. Bulbul, G. Filoglu, T. Zorlu & H. Altuncul

  2. Institute of Legal Medicine, Faculty of Medicine, University of Cologne, Cologne, Germany

    O. Bulbul & P. M. Schneider

  3. Forensic Genetics Unit, Institute of Forensic Science “Luís Concheiro”, University of Santiago de Compostela, Santiago de Compostela, Spain

    A. Freire-Aradas, J. Söchtig, Y. Ruiz, C. Phillips, M. V. Lareu & Á. Carracedo

  4. Department of Forensic Medicine, Hannover Medical School, Hannover, Germany

    J. Söchtig & M. Klintschar

  5. Bioinformatics Research Group, Centre of Biotechnology of Sfax, Sfax, Tunisia

    S. Triki-Fendri & A. Rebai

  6. Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia

    Á. Carracedo

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  1. O. Bulbul
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  2. G. Filoglu
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  3. T. Zorlu
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  4. H. Altuncul
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  5. A. Freire-Aradas
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  7. Y. Ruiz
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  8. M. Klintschar
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Corresponding author

Correspondence to O. Bulbul.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Fig. S1

Allele frequency comparisons for Africa, Europe and East Asia for the selected 22 AI-SNPs using SPSmart ENGINES SNP browser (http://spsmart.cesga.es/search.php). One missing AI-SNP data (rs1343879) is not available in SPSmart and it added manually from 1000 Genome Phase3 data below the figure. (GIF 376 kb)

High resolution (TIFF 22822 kb)

Supplementary Fig. S2

33-plex SNP profile for standard forensic control DNA 9947A (GIF 1645 kb)

High resolution (TIFF 487 kb)

Supplementary Fig. S3

Arlequin population divergence analyses of pairwise FST (blue squares), pairwise between-population differences (green) and pairwise within-population differences (orange) for 87 SNPs. Populations represented: Africa (LWK and YRI), Europe/Mediterranean (CEU, FIN, GBR, Germany, northwest Spain, Italy, Greece, Turkey, Russia-Adygei and Azerbaijan), Middle East (Algeria, Israel, Egypt, Kuwait, Libya, Yemen and Morocco), Central South Asia (BEB, GIH, ITU, PJL, STU, India, Pakistan and Uygur) and East Asia (Vietnam, Japan and China). Data was collected from 1000 Genomes, HGDP-CEPH and study populations as described in section 2.1. (GIF 2021 kb)

High resolution (TIFF 7402 kb)

Supplementary Fig. S4

Principal component analysis of the 34-plex alone, 34-plex plus Eurasiaplex and 34-plex, Eurasiaplex plus 33-plex. (PDF 3419 kb)

Supplementary Fig. S5

Bayesian ancestry assignments for European vs. Middle Eastern populations using Snipper. Grey colours represent individuals from 16 populations clustered into three ancestries and ordered by likelihoods ratios. Three ancestry groups represented are: European (CEU; FIN; GBR; Germany and northwest Spain), Mediterranean (Italy: Bergamo, Sardinia and Tuscan; Azerbaijan; Greece, Adygei and Turkey) and Middle Eastern (Algeria; Israel: Druze, Palestinian and Bedouin; Egypt, Kuwait, Libya; Morocco and Yemen). (GIF 1418 kb)

High resolution (TIFF 13955 kb)

Supplementary Table S1

Details of the 33-plex component SNPs. (XLSX 17 kb)

Supplementary Table S2

Bins and panels for the developed 33-plex using POP4. (XLSX 15 kb)

Supplementary Table S3

a. Cumulative informativeness values of each multiplex between five groups (Africa = AFR, Europe = EUR, Middle East = ME, Central-South Asia = CSA and East Asia = EAS) and values from combined sets. IN OVERALL is the divergence value for the comparison of all five population groups. b. Cumulative informativeness values of each multiplex between three groups and values from combined sets. (XLSX 12 kb)

Supplementary Table S4

Pairwise genetic distance matrix based on the FST values. (XLSX 23 kb)

Supplementary Table S5

Five-group training set for Snipper Bayesian analysis portal. Note this worksheet can be used ‘as is’, because rows 2-5 are not read by Snipper. (XLSX 372 kb)

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Bulbul, O., Filoglu, G., Zorlu, T. et al. Inference of biogeographical ancestry across central regions of Eurasia. Int J Legal Med 130, 73–79 (2016). https://doi.org/10.1007/s00414-015-1246-7

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