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A set of novel SNP loci for differentiating continental populations and three Chinese populations

In recent years, forensic geneticists have begun to develop some ancestry informative marker (AIM) panels for ancestry analysis of regional populations. In this study, we chose 48 single nucleotide polymorphisms (SNPs) from SPSmart database to infer ancestry origins of continental populations and Ch...

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Autores principales: Jin, Xiao-Ye, Wei, Yuan-Yuan, Lan, Qiong, Cui, Wei, Chen, Chong, Guo, Yu-Xin, Fang, Ya-Ting, Zhu, Bo-Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445247/
https://www.ncbi.nlm.nih.gov/pubmed/30956897
http://dx.doi.org/10.7717/peerj.6508
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author Jin, Xiao-Ye
Wei, Yuan-Yuan
Lan, Qiong
Cui, Wei
Chen, Chong
Guo, Yu-Xin
Fang, Ya-Ting
Zhu, Bo-Feng
author_facet Jin, Xiao-Ye
Wei, Yuan-Yuan
Lan, Qiong
Cui, Wei
Chen, Chong
Guo, Yu-Xin
Fang, Ya-Ting
Zhu, Bo-Feng
author_sort Jin, Xiao-Ye
collection PubMed
description In recent years, forensic geneticists have begun to develop some ancestry informative marker (AIM) panels for ancestry analysis of regional populations. In this study, we chose 48 single nucleotide polymorphisms (SNPs) from SPSmart database to infer ancestry origins of continental populations and Chinese subpopulations. Based on the genetic data of four continental populations (African, American, East Asian and European) from the CEPH-HGDP database, the power of these SNPs for differentiating continental populations was assessed. Population genetic structure revealed that distinct ancestry components among these continental populations could be discerned by these SNPs. Another novel population set from 1000 Genomes Phase 3 was treated as testing populations to further validate the efficiency of the selected SNPs. Twenty-two populations from CEPH-HGDP database were classified into three known populations (African, East Asian, and European) based on their biogeographical regions. Principal component analysis and Bayes analysis of testing populations and three known populations indicated these testing populations could be correctly assigned to their corresponding biogeographical origins. For three Chinese populations (Han, Mongolian, and Uygur), multinomial logistic regression analyses indicated that these 48 SNPs could be used to estimate ancestry origins of these populations. Therefore, these SNPs possessed the promising potency in ancestry analysis among continental populations and some Chinese populations, and they could be used in population genetics and forensic research.
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spelling pubmed-64452472019-04-05 A set of novel SNP loci for differentiating continental populations and three Chinese populations Jin, Xiao-Ye Wei, Yuan-Yuan Lan, Qiong Cui, Wei Chen, Chong Guo, Yu-Xin Fang, Ya-Ting Zhu, Bo-Feng PeerJ Bioinformatics In recent years, forensic geneticists have begun to develop some ancestry informative marker (AIM) panels for ancestry analysis of regional populations. In this study, we chose 48 single nucleotide polymorphisms (SNPs) from SPSmart database to infer ancestry origins of continental populations and Chinese subpopulations. Based on the genetic data of four continental populations (African, American, East Asian and European) from the CEPH-HGDP database, the power of these SNPs for differentiating continental populations was assessed. Population genetic structure revealed that distinct ancestry components among these continental populations could be discerned by these SNPs. Another novel population set from 1000 Genomes Phase 3 was treated as testing populations to further validate the efficiency of the selected SNPs. Twenty-two populations from CEPH-HGDP database were classified into three known populations (African, East Asian, and European) based on their biogeographical regions. Principal component analysis and Bayes analysis of testing populations and three known populations indicated these testing populations could be correctly assigned to their corresponding biogeographical origins. For three Chinese populations (Han, Mongolian, and Uygur), multinomial logistic regression analyses indicated that these 48 SNPs could be used to estimate ancestry origins of these populations. Therefore, these SNPs possessed the promising potency in ancestry analysis among continental populations and some Chinese populations, and they could be used in population genetics and forensic research. PeerJ Inc. 2019-03-29 /pmc/articles/PMC6445247/ /pubmed/30956897 http://dx.doi.org/10.7717/peerj.6508 Text en ©2019 Jin et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Jin, Xiao-Ye
Wei, Yuan-Yuan
Lan, Qiong
Cui, Wei
Chen, Chong
Guo, Yu-Xin
Fang, Ya-Ting
Zhu, Bo-Feng
A set of novel SNP loci for differentiating continental populations and three Chinese populations
title A set of novel SNP loci for differentiating continental populations and three Chinese populations
title_full A set of novel SNP loci for differentiating continental populations and three Chinese populations
title_fullStr A set of novel SNP loci for differentiating continental populations and three Chinese populations
title_full_unstemmed A set of novel SNP loci for differentiating continental populations and three Chinese populations
title_short A set of novel SNP loci for differentiating continental populations and three Chinese populations
title_sort set of novel snp loci for differentiating continental populations and three chinese populations
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445247/
https://www.ncbi.nlm.nih.gov/pubmed/30956897
http://dx.doi.org/10.7717/peerj.6508
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