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Phylogenetic analyses of 41 Y-STRs and machine learning-based haplogroup prediction in the Qingdao Han population from Shandong province, Eastern China

Authors :
Guang-Yao Fan
De-Zhi Jiang
Yao-Heng Jiang
Wei Song
Ying-Yun He
Nixon Austin Wuo
Source :
Annals of Human Biology, Vol 50, Iss 1, Pp 35-41 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

Background Known for its rich history and culture, Qingdao is a typical symbol of Chinese maritime culture. Its unique genetic landscape has aroused interest among geneticists and forensic scientists. However, the genetic landscape of Qingdao has never been uncovered. Aim This investigation intends to provide light on Qingdao’s paternal genetic diversity and its evolutionary connections to other Han subgroups. Subjects and methods The genetic polymorphisms of 41 Y-chromosomal short tandem repeat (STR) loci in the Qingdao Han were investigated using SureID® PathFinder Plus Kit. Phylogenetic studies were performed using genotype data from 52 East Asian groups at 23 common Y-STR loci. A multidimensional scaling plot and cladogram were constructed. Linear Discriminant Analysis (LDA) was carried out for predicting categories among the Han people. The k-nearest neighbour (kNN) algorithm was utilised to designate Y-SNP haplogroups for each haplotype. Results The Qingdao Han were genetically far from the Tibeto-Burman populations and close with the Han people from northern China. LDA indicated a deep integration among the present-day Han people. By the kNN model, the predicted O2a2 and O2a1 were shown to be the predominant Y-SNP haplogroups. Conclusions This study would be helpful for reconstructing the patrilineal history in China and establishing a more comprehensive Y-STR database.

Details

Language :
English
ISSN :
03014460 and 14645033
Volume :
50
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Annals of Human Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.ba83c0e26334c6aa8ed136e1186dc71
Document Type :
article
Full Text :
https://doi.org/10.1080/03014460.2023.2168057