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The ancestry inference of Chinese populations using 74-plex SNPs system.
Liu, Yang; Sun, Chang Chun; Ma, Mi; Wang, Ling; Zhao, Wen Ting; Ma, Quan; Ji, An Quan; Liu, Jing; Li, Cai Xia.
Affiliation
  • Liu Y; Shanxi Medical University, Taiyuan 036000, China.
  • Sun CC; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
  • Ma M; Shanxi Medical University, Taiyuan 036000, China.
  • Wang L; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
  • Zhao WT; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
  • Ma Q; Production and Construction Corps of Seventh Division Public Security Bureau, Kuitun 833200, China.
  • Ji AQ; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
  • Liu J; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
  • Li CX; Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China.
Yi Chuan ; 42(3): 296-308, 2020 Mar 20.
Article in En | MEDLINE | ID: mdl-32217515
ABSTRACT
A panel of ancestry informative SNPs (AISNPs) can be used to analyze the genetic components of a population and infer the ancestral origin of a DNA sample. Previously, we have selected a 74-AISNPs panel and used it to infer the ancestry of unknown individuals in the following ten geographical regions Sub-Saharan Africa, North Africa, Europe, Pacific, Americas, Southwest Asia, South Asia, North Asia, East Asia and Southeast Asia. We have also established a 74-plex SNPs assay based on SEQUENOM system. In the present study, we genotyped 1371 individuals from 14 populations of China using this multiplex assay, and validated its ability to infer the ancestry in Chinese populations. Firstly, based on the reference database of 3628 individuals from 57 world populations, Structure and Heatmap were employed to evaluate the population differentiation capacity. The training data include 1654 individuals from 14 Chinese populations and 3 populations from 1K Genome, which are not included in the reference database. Then the likelihood ratio and ancestry components were analyzed for individual ancestry assignment using the 74-plex SNPs. The minimum amount of DNA required for a full genotype of the 74 SNPs is 1.5 ng, which is applicable for forensic analysis. The results demonstrate that this system can be used in differentiating the population from ten geographical regions. The ancestry inference accuracy for EUR/SAFR/AME population is 95.4%, 71.0% for East Asia and 66.4% for Southeast Asia respectively. The ancestry inference inclusive rate for EUR/SAFR/AME population is 1.06%, 17.9% for East Asia and 33.3% for Southeast Asia respectively. The results suggest that this method can be used in forensic investigations of criminal cases.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Polymorphism, Single Nucleotide / Asian People / Genetics, Population Limits: Humans Country/Region as subject: Asia Language: En Journal: Yi Chuan Journal subject: GENETICA Year: 2020 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Polymorphism, Single Nucleotide / Asian People / Genetics, Population Limits: Humans Country/Region as subject: Asia Language: En Journal: Yi Chuan Journal subject: GENETICA Year: 2020 Type: Article Affiliation country: China