International Journal of Legal Medicine

, Volume 132, Issue 4, pp 997–1006 | Cite as

SNP typing using the HID-Ion AmpliSeq™ Identity Panel in a southern Chinese population

  • Ran Li
  • Chuchu Zhang
  • Haiyan Li
  • Riga Wu
  • Haixia Li
  • Zhenya Tang
  • Chenhao Zhen
  • Jianye Ge
  • Dan Peng
  • Ying Wang
  • Hongying Chen
  • Hongyu Sun
Original Article


In the present study, 90 autosomal single nucleotide polymorphisms (SNPs) and 34 Y chromosomal SNPs were sequenced simultaneously using HID-Ion AmpliSeq™ Identity Panel on the Ion PGM™ platform for 125 samples in a southern Chinese population. Raw data were analyzed and forensic parameters were calculated. Haplogrouping concordance was also assessed using alternative methods based on Y-SNP haplotypes and Y-STR haplotypes. The results showed that allelic imbalance occurred more frequently with low coverage while several SNPs with high coverage were also observed with poor allelic balance, including rs214955, rs430046, rs7520386, rs876724, rs9171188, rs16981290, and rs2032631. Totally, 21,261 miscalled reads (0.28%) were observed. The rate of allele-specific miscalled reads (ASMRs) was higher than that of allele nonspecific miscalled reads (ANMRs) and associated with genetic diversity of the SNP. The ASMRs of major allele were lower than that of minor allele while there was no difference for ANMRs. The combined discrimination power (CDP) was 1–4.81 × 10−34 and the combined power of exclusion (CPE) was 0.99989 and 0.99999992 for duo and trio paternity testing, respectively. No significant genetic difference was detected between southern and northern Chinese populations. For haplogroup study, O2 was the predominant haplogroup and 97.01% of samples were assigned consistent haplogoups with Y-SNP and Y-STR haplotypes. In conclusion, the AmpliSeq™ Identity Panel was powerful for individual identification and trio paternity testing. ASMRs were associated with the genetic diversity and allele frequency while neither was related for ANMRs. High concordance of haplogrouping assignment can be obtained with Y-STR and Y-SNP haplotypes.


Single nucleotide polymorphism (SNP) Next generation sequencing (NGS) Ion torrent PGM™ Population genetics Miscalled reads 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

414_2017_1706_MOESM1_ESM.xls (99 kb)
ESM 1 (XLS 99 kb)
414_2017_1706_MOESM2_ESM.pdf (406 kb)
ESM 2 (PDF 406 kb)
414_2017_1706_MOESM3_ESM.pdf (120 kb)
ESM 3 (PDF 120 kb)


  1. 1.
    Kidd KK, Pakstis AJ, Speed WC, Grigorenko EL, Kajuna SLB, Karoma NJ, Kungulilo S, Kim J, Lu R, Odunsi A, Okonofua F, Parnas J, Schulz LO, Zhukova OV, Kidd JR (2006) Developing a SNP panel for forensic identification of individuals. Forensic Sci Int 164:20–32CrossRefPubMedGoogle Scholar
  2. 2.
    Amorim A, Pereira L (2005) Pros and cons in the use of SNPs in forensic kinship investigation: a comparative analysis with STRs. Forensic Sci Int 150:17–21CrossRefPubMedGoogle Scholar
  3. 3.
    Mo S, Liu Y, Wang S, Bo X, Li Z, Chen Y, Ni M (2016) Exploring the efficacy of paternity and kinship testing based on single nucleotide polymorphisms. Forensic Sci Int Genet 22:161–168CrossRefPubMedGoogle Scholar
  4. 4.
    Sanchez JJ, Phillips C, Borsting C, Balogh K, Bogus M, Fondevila M, Harrison CD, Musgrave-Brown E, Salas A, Syndercombe-Court D, Schneider PM, Carracedo A, Morling N (2006) A multiplex assay with 52 single nucleotide polymorphisms for human identification. Electrophoresis 27:1713–1724CrossRefPubMedGoogle Scholar
  5. 5.
    Pakstis AJ, Speed WC, Fang R, Hyland FCL, Furtado MR, Kidd JR, Kidd KK (2010) SNPs for a universal individual identification panel. Hum Genet 127:315–324CrossRefPubMedGoogle Scholar
  6. 6.
    Sobrino B, Brión M, Carracedo A (2005) SNPs in forensic genetics: a review on SNP typing methodologies. Forensic Sci Int 154:181–194CrossRefPubMedGoogle Scholar
  7. 7.
    Seo SB, King JL, Warshauer DH, Davis CP, Ge J, Budowle B (2013) Single nucleotide polymorphism typing with massively parallel sequencing for human identification. Int J Legal Med 127:1079–1086CrossRefPubMedGoogle Scholar
  8. 8.
    Guo F, Zhou Y, Song H, Zhao J, Shen H, Zhao B, Liu F, Jiang X (2016) Next generation sequencing of SNPs using the HID-Ion AmpliSeq™ Identity Panel on the Ion Torrent PGM™ platform. Forensic Sci Int Genet 25:73–84CrossRefPubMedGoogle Scholar
  9. 9.
    Børsting C, Fordyce SL, Olofsson J, Mogensen HS, Morling N (2014) Evaluation of the Ion Torrent™ HID SNP 169-plex: a SNP typing assay developed for human identification by second generation sequencing. Forensic Sci Int Genet 12:144–154CrossRefPubMedGoogle Scholar
  10. 10.
    Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, Pallen MJ (2012) Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol 30:434–439CrossRefPubMedGoogle Scholar
  11. 11.
    Eduardoff M, Santos C, de la Puente M, Gross TE, Fondevila M, Strobl C, Sobrino B, Ballard D, Schneider PM, Carracedo Á, Lareu MV, Parson W, Phillips C (2015) Inter-laboratory evaluation of SNP-based forensic identification by massively parallel sequencing using the Ion PGM™. Forensic Sci Int Genet 17:110–121CrossRefPubMedGoogle Scholar
  12. 12.
    Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, Leamon JH, Johnson K, Milgrew MJ, Edwards M, Hoon J, Simons JF, Marran D, Myers JW, Davidson JF, Branting A, Nobile JR, Puc BP, Light D, Clark TA, Huber M, Branciforte JT, Stoner IB, Cawley SE, Lyons M, Fu Y, Homer N, Sedova M, Miao X, Reed B, Sabina J, Feierstein E, Schorn M, Alanjary M, Dimalanta E, Dressman D, Kasinskas R, Sokolsky T, Fidanza JA, Namsaraev E, McKernan KJ, Williams A, Roth GT, Bustillo J (2011) An integrated semiconductor device enabling non-optical genome sequencing. Nature 475:348–352CrossRefPubMedGoogle Scholar
  13. 13.
    Elena S, Alessandro A, Ignazio C, Sharon W, Luigi R, Andrea B (2016) Revealing the challenges of low template DNA analysis with the prototype Ion AmpliSeq™ Identity panel v2.3 on the PGM™ Sequencer. Forensic Sci Int Genet 22:25–36CrossRefPubMedGoogle Scholar
  14. 14.
    Karafet TM, Mendez FL, Meilerman MB, Underhill PA, Zegura SL, Hammer MF (2008) New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree. Genome Res 18:830–838CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Zhang S, Bian Y, Zhang Z, Zheng H, Wang Z, Zha L, Cai J, Gao Y, Ji C, Hou Y, Li C (2015) Parallel analysis of 124 universal SNPs for human identification by targeted semiconductor sequencing. Sci Rep-UK 5:18683CrossRefGoogle Scholar
  16. 16.
    Athey TW (2006) Haplogroup prediction from Y-STR values using a Bayesian-allele-frequency approach. J Genet Geneal 2:34–39Google Scholar
  17. 17.
    Athey TW (2005) Haplogroup prediction from Y-STR values using an allele-frequency approach. J Genet Geneal 1:1–7Google Scholar
  18. 18.
    Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1106CrossRefPubMedGoogle Scholar
  19. 19.
    Excoffier L, Lischer HE (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564–567CrossRefPubMedGoogle Scholar
  20. 20.
    Amigo J, Salas A, Phillips C, Carracedo A (2008) SPSmart: adapting population based SNP genotype databases for fast and comprehensive web access. BMC Bioinformatics 9:428CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    International Society of Genetic Genealogy (ISOGG): Y-DNA Haplogroup Tree 2017, Version: 12.128. In, 2017. Available at:
  22. 22.
    Wright S (1978) Evolution and the genetics of populations. Vol. 4. Variability within and among natural populations. University of Chicago Press, ChicagoGoogle Scholar
  23. 23.
    Phillips C, García-Magariños M, Salas A, Carracedo Á, Lareu MV (2012) SNPs as supplements in simple kinship analysis or as core markers in distant pairwise relationship tests: when do SNPs add value or replace well-established and powerful STR tests? Transfus Med Hemoth 39:202–210CrossRefGoogle Scholar
  24. 24.
    Wang Y, Liu C, Zhang CC, Li R, Li Y, XL O, Sun HY (2015) Analysis of 17 Y-STR loci haplotype and Y-chromosome haplogroup distribution in five Chinese ethnic groups. Electrophoresis 36:2546–2552CrossRefPubMedGoogle Scholar
  25. 25.
    Muzzio M, Ramallo V, Motti JMB, Santos MR, López Camelo JS, Bailliet G (2011) Software for Y-haplogroup predictions: a word of caution. Int J Legal Med 125:143–147CrossRefPubMedGoogle Scholar
  26. 26.
    Petrejcikova E, Carnogurska J, Hronska D, Bernasovska J, Boronova I, Gabrikova D, Bozikova A, Macekova S (2014) Y-SNP analysis versus Y-haplogroup predictor in the Slovak population. Anthropol Anz 71:275–285CrossRefPubMedGoogle Scholar
  27. 27.
    Dogan S, Babic N, Gurkan C, Goksu A, Marjanovic D, Hadziavdic V (2016) Y-chromosomal haplogroup distribution in the Tuzla Canton of Bosnia and Herzegovina: a concordance study using four different in silico assignment algorithms based on Y-STR data. Homo 67:471–483CrossRefPubMedGoogle Scholar
  28. 28.
    Nunez C, Geppert M, Baeta M, Roewer L, Martinez-Jarreta B (2012) Y chromosome haplogroup diversity in a Mestizo population of Nicaragua. Forensic Sci Int Genet 6:e192–e195CrossRefPubMedGoogle Scholar
  29. 29.
    Athey W (2011) Comments on the article, “Software for Y haplogroup predictions, a word of caution”. Int J Legal Med 125(901–903):905–906Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Ran Li
    • 1
  • Chuchu Zhang
    • 1
  • Haiyan Li
    • 2
  • Riga Wu
    • 1
  • Haixia Li
    • 1
  • Zhenya Tang
    • 2
  • Chenhao Zhen
    • 3
  • Jianye Ge
    • 4
  • Dan Peng
    • 1
  • Ying Wang
    • 1
  • Hongying Chen
    • 2
  • Hongyu Sun
    • 1
    • 5
  1. 1.Faculty of Forensic Medicine, Zhongshan School of MedicineSun Yat-sen UniversityGuangzhouPeople’s Republic of China
  2. 2.The Center of Criminal Technology of Guangdong ProvinceGuangzhouPeople’s Republic of China
  3. 3.The Second Clinical Medical School (Zhujiang Hospital)Southern Medical UniversityGuangzhouPeople’s Republic of China
  4. 4.Thermo Fisher Scientific IncSouth San FranciscoUSA
  5. 5.Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of MedicineSun Yat-sen UniversityGuangzhouPeople’s Republic of China

Personalised recommendations