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Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations

BACKGROUND: Generally, populations differ in terms of environmental and genetic factors, which can create differences in allele substitution effects between populations. Therefore, a single genotype may have different additive genetic values in different populations. The correlation between the two...

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Autores principales: Wientjes, Yvonne C. J., Calus, Mario P. L., Duenk, Pascal, Bijma, Piter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6295113/
https://www.ncbi.nlm.nih.gov/pubmed/30547748
http://dx.doi.org/10.1186/s12711-018-0434-6
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author Wientjes, Yvonne C. J.
Calus, Mario P. L.
Duenk, Pascal
Bijma, Piter
author_facet Wientjes, Yvonne C. J.
Calus, Mario P. L.
Duenk, Pascal
Bijma, Piter
author_sort Wientjes, Yvonne C. J.
collection PubMed
description BACKGROUND: Generally, populations differ in terms of environmental and genetic factors, which can create differences in allele substitution effects between populations. Therefore, a single genotype may have different additive genetic values in different populations. The correlation between the two additive genetic values of a single genotype in two populations is known as the additive genetic correlation between populations and thus, can differ from 1. Our objective was to investigate whether differences in linkage disequilibrium (LD) and allele frequencies of markers and causal loci between populations affect the bias of the estimated genetic correlation. We simulated two populations that were separated by 50 generations and differed in LD pattern between markers and causal loci, as measured by the LD-statistic r. We used a high marker density to represent a high consistency of LD between populations, and lower marker densities to represent situations with a lower consistency of LD between populations. Markers and causal loci were selected to have either similar or different allele frequencies in the two populations. RESULTS: Our results show that genetic correlations were underestimated only slightly when the difference in allele frequencies between the two populations was similar for the markers and the causal loci. A lower marker density, representing a lower consistency of LD between populations, had only a minor effect on the underestimation of the genetic correlation. When the difference in allele frequencies between the two populations was not similar for markers and causal loci, genetic correlations were severely underestimated. This bias occurred because the markers did not predict accurately the relationships at causal loci. CONCLUSIONS: For an unbiased estimation of the genetic correlation between populations, the markers should accurately predict the relationships at the causal loci. To achieve this, it is essential that the difference in allele frequencies between populations is similar for markers and causal loci. Our results show that differences in LD phase between causal loci and markers across populations have little effect on the estimated genetic correlation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0434-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-62951132018-12-18 Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations Wientjes, Yvonne C. J. Calus, Mario P. L. Duenk, Pascal Bijma, Piter Genet Sel Evol Research Article BACKGROUND: Generally, populations differ in terms of environmental and genetic factors, which can create differences in allele substitution effects between populations. Therefore, a single genotype may have different additive genetic values in different populations. The correlation between the two additive genetic values of a single genotype in two populations is known as the additive genetic correlation between populations and thus, can differ from 1. Our objective was to investigate whether differences in linkage disequilibrium (LD) and allele frequencies of markers and causal loci between populations affect the bias of the estimated genetic correlation. We simulated two populations that were separated by 50 generations and differed in LD pattern between markers and causal loci, as measured by the LD-statistic r. We used a high marker density to represent a high consistency of LD between populations, and lower marker densities to represent situations with a lower consistency of LD between populations. Markers and causal loci were selected to have either similar or different allele frequencies in the two populations. RESULTS: Our results show that genetic correlations were underestimated only slightly when the difference in allele frequencies between the two populations was similar for the markers and the causal loci. A lower marker density, representing a lower consistency of LD between populations, had only a minor effect on the underestimation of the genetic correlation. When the difference in allele frequencies between the two populations was not similar for markers and causal loci, genetic correlations were severely underestimated. This bias occurred because the markers did not predict accurately the relationships at causal loci. CONCLUSIONS: For an unbiased estimation of the genetic correlation between populations, the markers should accurately predict the relationships at the causal loci. To achieve this, it is essential that the difference in allele frequencies between populations is similar for markers and causal loci. Our results show that differences in LD phase between causal loci and markers across populations have little effect on the estimated genetic correlation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0434-6) contains supplementary material, which is available to authorized users. BioMed Central 2018-12-14 /pmc/articles/PMC6295113/ /pubmed/30547748 http://dx.doi.org/10.1186/s12711-018-0434-6 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wientjes, Yvonne C. J.
Calus, Mario P. L.
Duenk, Pascal
Bijma, Piter
Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title_full Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title_fullStr Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title_full_unstemmed Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title_short Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
title_sort required properties for markers used to calculate unbiased estimates of the genetic correlation between populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6295113/
https://www.ncbi.nlm.nih.gov/pubmed/30547748
http://dx.doi.org/10.1186/s12711-018-0434-6
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