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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

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.

Keywords:

Ancestry inference Bio-geographic ancestry Forensic marker Microhaplotype Population structure

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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.