Genetic analysis and forensic evaluation of 47 autosomal InDel markers in four different Chinese populations

  • Xiyong Pan
  • Changhui Liu
  • Weian Du
  • Ling Chen
  • Xiaolong Han
  • Xingyi Yang
  • Chao LiuEmail author
Population Data


This study aims to investigate the population-wide genetic data and forensic efficiency of 47 autosomal InDels in the four Chinese populations of Chinese Han, Tibetan, Uighur, and Chinese Hui. The allele frequencies and forensic parameters of the 47 InDels were investigated in 638 unrelated individuals from these four populations. The results can serve as a reference database that includes InDels in the populations, and they can contribute to population diversity studies.


Forensic efficiency Insertion/deletion polymorphism Chinese populations Population genetics 



The authors are very grateful to all sample donors for their contributions to this work and all those who helped with sample collection. This study was supported by the Science and Technology Program of Guangzhou, China (grant numbers 201605131210203 and 201707010486).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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Figure S1

Linkage disequilibrium analysis for 47 autosomal InDels in the four populations. A: Chinese Han population. B: Tibetan population. C: Uighur population. D: Chinese Hui population. (PNG 121 kb)

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Figure S2

The allele frequencies of the 47 autosomal InDels in the four populations. A: Chinese Han population. B: Tibetan population. C: Uighur population. D: Chinese Hui population. (PNG 149 kb)

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Figure S3

The forensic statistical parameters of the 47 autosomal InDel markers in the four Chinese populations. A: Expected heterozygosity. B: Observed heterozygosity. C: Polymorphism information content. D: Typical paternity index of the four population. (PNG 288 kb)

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Supplementary Table 1 (DOCX 29 kb)
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Supplementary Table 2 (DOCX 35 kb)
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Supplementary Table 3 (DOCX 28 kb)


  1. 1.
    Weber JL, David D, Heil J, Fan Y, Zhao C, Marth G (2002) Human diallelic insertion/deletion polymorphisms. Am J Hum Genet 71:854–862. CrossRefGoogle Scholar
  2. 2.
    Pereira R, Phillips C, Alves C, Amorim A, Carracedo A, Gusmão L (2009) A new multiplex for human identification using insertion/deletion polymorphisms. Electrophoresis 30:3682–3690. CrossRefGoogle Scholar
  3. 3.
    Torres SR, Uehara CJ, Sutter-Latorre AF et al (2014) Population genetic data and forensic parameters of 30 autosomal InDel markers in Santa Catarina State population, Southern Brazil. Mol Biol Rep 41:5429–5433. CrossRefGoogle Scholar
  4. 4.
    Pimenta JR, Pena SD (2010) Efficient human paternity testing with a panel of 40 short insertion-deletion polymorphisms. Genet Mol Res 9:601–607. CrossRefGoogle Scholar
  5. 5.
    Li C, Zhang S, Li L, Chen J, Liu Y, zhao S (2012) Selection of 29 highly informative InDel markers for human identification and paternity analysis in Chinese Han population by the SNPlex genotyping system. Mol Biol Rep 39:3143–3152. CrossRefGoogle Scholar
  6. 6.
    Chen L, Du W, Wu W et al (2019) Developmental validation of a novel six-dye typing system with 47 A-InDels and 2 Y-InDels. Forensic Sci Int Genet 40:64–73. CrossRefGoogle Scholar
  7. 7.
    Walsh PS, Metzger DA, Higuchi R (1991) Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. Biotechniques 10:506–513Google Scholar
  8. 8.
    Yoo J, Lee Y, Kim Y, Rha SY, Kim Y (2008) SNPAnalyzer 2.0: a web-based integrated workbench for linkage disequilibrium analysis and association analysis. BMC Bioinf 9:290. CrossRefGoogle Scholar
  9. 9.
    Excoffier L, Laval G, Schneider S (2007) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinformatics Online 1:47–50Google Scholar
  10. 10.
    Mills RE, Pittard WS, Mullaney JM, Farooq U, Creasy TH, Mahurkar AA, Kemeza DM, Strassler DS, Ponting CP, Webber C, Devine SE (2011) Natural genetic variation caused by small insertions and deletions in the human genome. Genome Res 21(6):830–839. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiyong Pan
    • 1
    • 2
  • Changhui Liu
    • 3
  • Weian Du
    • 4
  • Ling Chen
    • 5
  • Xiaolong Han
    • 3
  • Xingyi Yang
    • 3
  • Chao Liu
    • 3
    Email author
  1. 1.Faculty of Forensic Medicine, Zhongshan School of MedicineSun Yat-Sen UniversityGuangzhouChina
  2. 2.Forensic Science Center of Yuexiu District BranchGuangzhou Public Security Bureau in GuangDong ProvinceGuangzhouChina
  3. 3.Guangzhou Forensic Science InstituteGuangzhouChina
  4. 4.AGCU ScienTech IncorporationWuxiChina
  5. 5.School of Forensic MedicineSouthern Medical UniversityGuangzhouChina

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