Study of The SNP Investigative Genetic Genealogy Based on Whole Genome Sequencing
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1)School of Investigation, People’s Public Security University of China, Beijing 100038, China;2)Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China;3)Public Security Bureau of Dachuan District of Dazhou City, Dazhou 635000, China

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This work was supported by grants from The National Natural Science Foundation of China (82171870) and the Ministry of Public Security Technology Research Program (2021JSZ15).

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    Abstract:

    Objective The high density SNP genotype data were obtained by whole genome sequencing (WGS), the accuracy of genotype was evaluated, and this study is intended to establish the method of using whole genome sequencing data for SNP kinship relationship prediction.Methods The samples were sequenced at a depth of 30× through the MGISEQ-200RS sequencing platform, and 645 199 autosomal SNP in the Wegene GSA DNA microarray were extracted from the sequencing data. After quality control and filtering, the prediction relationship was calculated and predicted by IBS/IBD algorithm, and the ancestry of the samples was analyzed.Results The coincidence rate between SNP genotype extracted from sequencing data and Wegene GSA genotype is more than 99.62%.The SNP genotype obtained by sequencing can predict kinship from level 1 to level 4 by using IBS algorithm, and confidence interval accuracy of level 4 kinship prediction is 100%. Using IBD algorithm, the confidence interval accuracy of level 1 to 7 kinship prediction is 100%. The pedigree inference ability of SNP obtained from high-depth whole genome sequence data is not significantly different from that of DNA microarray prediction.At the same time, the use of whole genome sequencing data for ancestry inference is consistent with the survey results.Conclusion The whole genome resequencing technique can be applied to SNP genealogy inference to provide clues for case detection.

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XIE Quan, GUI Xu, ZHAO Wen-Ting, FANG Zhi-Xiao, XU Jing-Yi, LIU Jing, LI Cai-Xia. Study of The SNP Investigative Genetic Genealogy Based on Whole Genome Sequencing[J]. Progress in Biochemistry and Biophysics,2023,50(11):2753-2765

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History
  • Received:October 26,2022
  • Revised:March 01,2023
  • Accepted:March 01,2023
  • Online: November 22,2023
  • Published: November 20,2023