Inferring Distant Relationships From Dense SNP Data Utilizing Two Genealogy Algorithms.

Autor: Lin X; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China.; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, P. R. China., Han S; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China.; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, P. R. China., Zhang N; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China., Ling X; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China.; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, P. R. China., Bai Z; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China., Ou X; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China.; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, P. R. China.
Jazyk: angličtina
Zdroj: Electrophoresis [Electrophoresis] 2024 Dec 18. Date of Electronic Publication: 2024 Dec 18.
DOI: 10.1002/elps.202400208
Abstrakt: A highly esteemed method known as investigative genetic genealogy (IGG) has been developed to identify DNA samples from forensic crime scenes and human remains of disaster victims. With the advent of next-generation sequencing, it is now feasible to access information on millions of SNPs typed in a single sequencing run that fulfill the requirements for kinship inference. However, challenges such as the poor quality of forensic samples, the high cost associated with sequencing technology, and privacy concerns regarding large-scale genetic databases remain unresolved in this field. In the present study, we validated the identification of relationships up to the seventh degree using two genealogy algorithms (IBIS and KING) under various parameter settings. This was accomplished through whole genome sequencing data derived from two southern Chinese Han pedigrees during an initial phase, while also exploring workflows adapted for low-quality samples. To achieve this objective, low-coverage whole genome sequencing data were downsampled from high-coverage original datasets; additionally, mimic SNP array data-containing less information but offering greater accessibility-were prepared as reference samples. Through a series of experimental analyses, we not only validate the applicability of selected processing procedures and inference tools for low-coverage samples but also proposed that a meticulously crafted site filtering strategy can significantly improve the accuracy of kinship identification. This acknowledges the necessity for further systematic evidence in future research endeavors.
(© 2024 Wiley‐VCH GmbH.)
Databáze: MEDLINE
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