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Distinguishing three distinct biogeographic regions with an in-house developed 39-AIM-InDel panel and further admixture proportion estimation for Uyghurs.

Qiong LanChunmei ShenXiaoye JinYuxin GuoTong XieChong ChenWei CuiYating FangGuang YangBo-Feng Zhu
Published in: Electrophoresis (2019)
In the forensic field, ancestry-informative markers (AIMs) showing remarkable allele frequency discrepancies can be useful in deducing the likely ancestral origin of a person or estimating the ancestry component proportions of an admixed population or individual. Diallelic single nucleotide polymorphisms are genetic markers commonly used for ancestry inference, but the genotyping methods of single nucleotide polymorphisms fail to fulfil the demands of cost-effectiveness and simplicity of experimental manipulation. To overcome the limitations, a 39 ancestry-informative insertion/deletion polymorphism multiplex panel was developed in the present study to perform ancestry assignment of individuals from three distinct biogeographic regions (Africa, Europe, East Asia). And in the panel design, we also attempted to incorporate AIM-insertion/deletion polymorphisms exhibiting allelic frequency differences in Han, Uyghur, and Tibetan populations into the multiplex assay, further expecting to provide valuable information for refining ancestry inference within Chinese populations. Statistical analyses were performed to estimate efficiency of this panel in clustering individuals from three continents mentioned above into their corresponding populations, which indicated the potential of the panel in ancestry inference. Besides, we also estimated the ancestral component proportions of Uyghur group and STRUCTURE analysis revealed that Uyghurs from Urumchi city of northern Xinjiang exhibited a distinctly admixed pattern of East Asian and European ancestry components with a ratio of 49:44, reflecting the relatively higher East Asian ancestry component contribution in the gene pool of the Uyghur group.
Keyphrases
  • genome wide association study
  • single cell
  • high throughput
  • healthcare
  • rna seq
  • genetic diversity
  • risk assessment
  • real time pcr