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The Effect of Population Structure on Murine Genome-Wide Association Studies
The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analys...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475632/ https://www.ncbi.nlm.nih.gov/pubmed/34589118 http://dx.doi.org/10.3389/fgene.2021.745361 |
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author | Wang, Meiyue Fang, Zhuoqing Yoo, Boyoung Bejerano, Gill Peltz, Gary |
author_facet | Wang, Meiyue Fang, Zhuoqing Yoo, Boyoung Bejerano, Gill Peltz, Gary |
author_sort | Wang, Meiyue |
collection | PubMed |
description | The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 – 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated. |
format | Online Article Text |
id | pubmed-8475632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84756322021-09-28 The Effect of Population Structure on Murine Genome-Wide Association Studies Wang, Meiyue Fang, Zhuoqing Yoo, Boyoung Bejerano, Gill Peltz, Gary Front Genet Genetics The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 – 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated. Frontiers Media S.A. 2021-09-13 /pmc/articles/PMC8475632/ /pubmed/34589118 http://dx.doi.org/10.3389/fgene.2021.745361 Text en Copyright © 2021 Wang, Fang, Yoo, Bejerano and Peltz. https://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 Wang, Meiyue Fang, Zhuoqing Yoo, Boyoung Bejerano, Gill Peltz, Gary The Effect of Population Structure on Murine Genome-Wide Association Studies |
title | The Effect of Population Structure on Murine Genome-Wide Association Studies |
title_full | The Effect of Population Structure on Murine Genome-Wide Association Studies |
title_fullStr | The Effect of Population Structure on Murine Genome-Wide Association Studies |
title_full_unstemmed | The Effect of Population Structure on Murine Genome-Wide Association Studies |
title_short | The Effect of Population Structure on Murine Genome-Wide Association Studies |
title_sort | effect of population structure on murine genome-wide association studies |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475632/ https://www.ncbi.nlm.nih.gov/pubmed/34589118 http://dx.doi.org/10.3389/fgene.2021.745361 |
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