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Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs
Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421339/ https://www.ncbi.nlm.nih.gov/pubmed/30915106 http://dx.doi.org/10.3389/fgene.2019.00183 |
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author | Liang, Zuoxiang Bu, Lina Qin, Yidi Peng, Yebo Yang, Ruifei Zhao, Yiqiang |
author_facet | Liang, Zuoxiang Bu, Lina Qin, Yidi Peng, Yebo Yang, Ruifei Zhao, Yiqiang |
author_sort | Liang, Zuoxiang |
collection | PubMed |
description | Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner. |
format | Online Article Text |
id | pubmed-6421339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64213392019-03-26 Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs Liang, Zuoxiang Bu, Lina Qin, Yidi Peng, Yebo Yang, Ruifei Zhao, Yiqiang Front Genet Genetics Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner. Frontiers Media S.A. 2019-03-11 /pmc/articles/PMC6421339/ /pubmed/30915106 http://dx.doi.org/10.3389/fgene.2019.00183 Text en Copyright © 2019 Liang, Bu, Qin, Peng, Yang and Zhao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liang, Zuoxiang Bu, Lina Qin, Yidi Peng, Yebo Yang, Ruifei Zhao, Yiqiang Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title | Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title_full | Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title_fullStr | Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title_full_unstemmed | Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title_short | Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs |
title_sort | selection of optimal ancestry informative markers for classification and ancestry proportion estimation in pigs |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421339/ https://www.ncbi.nlm.nih.gov/pubmed/30915106 http://dx.doi.org/10.3389/fgene.2019.00183 |
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