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Inferring bio-geographical ancestry with 35 microhaplotypes
Shuainan Huang1, Mingchen Sheng1, Zheng Li2
1Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, PR China.
Forensic Science International
|November 7, 2022
Summary
This study introduces 35 novel bio-geographical informative microhaplotypes (BIMs) for ancestry inference. These BIMs effectively differentiate human populations, offering a powerful new tool for forensic genetics and population studies.
Area of Science:
- Genetics
- Forensic Science
- Population Genetics
Background:
- Large-scale human genetic studies reveal links between genetic variations and bio-geographical information.
- Advancements in massively parallel sequencing enable novel forensic markers like microhaplotypes (BIMs).
Purpose of the Study:
- To select and characterize 35 novel bio-geographical informative BIMs.
- To evaluate the utility of these BIMs for inferring bio-geographical ancestry.
Main Methods:
- Selection of 35 BIMs based on the 1000 Genomes Project (1KG) data.
- Characterization of BIM loci for length, effective allele number (Ae), and informativeness (In).
- Application of BIMs to differentiate individuals from 1KG and Simons Genome Diversity Project (SGDP) datasets.
Main Results:
- The 35 selected BIMs are short (<100 bp) with high Ae (avg. 2.798) and In (avg. 0.748), indicating strong discriminating power.
- Individuals from the 1KG dataset were successfully classified into five supergroups (AFR, AMR, EAS, EUR, SAS).
- Accurate ancestry prediction was achieved for most individuals, with minor exceptions for populations outside the 1KG dataset.
Conclusions:
- The developed 35 BIMs are a valuable tool for bio-geographical ancestry inference.
- These BIMs demonstrate high accuracy in differentiating major human populations.
- The findings support the application of BIMs in forensic genetics and population studies.
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