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A Practical Guide to Estimating the Heritability of Pathogen Traits

Pathogen traits, such as the virulence of an infection, can vary significantly between patients. A major challenge is to measure the extent to which genetic differences between infecting strains explain the observed variation of the trait. This is quantified by the trait’s broad-sense heritability,...

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Autores principales: Mitov, Venelin, Stadler, Tanja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850476/
https://www.ncbi.nlm.nih.gov/pubmed/29329426
http://dx.doi.org/10.1093/molbev/msx328
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author Mitov, Venelin
Stadler, Tanja
author_facet Mitov, Venelin
Stadler, Tanja
author_sort Mitov, Venelin
collection PubMed
description Pathogen traits, such as the virulence of an infection, can vary significantly between patients. A major challenge is to measure the extent to which genetic differences between infecting strains explain the observed variation of the trait. This is quantified by the trait’s broad-sense heritability, H(2). A recent discrepancy between estimates of the heritability of HIV-virulence has opened a debate on the estimators’ accuracy. Here, we show that the discrepancy originates from model limitations and important lifecycle differences between sexually reproducing organisms and transmittable pathogens. In particular, current quantitative genetics methods, such as donor–recipient regression of surveyed serodiscordant couples and the phylogenetic mixed model (PMM), are prone to underestimate H(2), because they neglect or do not fit to the loss of resemblance between transmission partners caused by within-host evolution. In a phylogenetic analysis of 8,483 HIV patients from the United Kingdom, we show that the phenotypic correlation between transmission partners decays with the amount of within-host evolution of the virus. We reproduce this pattern in toy-model simulations and show that a phylogenetic Ornstein–Uhlenbeck model (POUMM) outperforms the PMM in capturing this correlation pattern and in quantifying H(2). In particular, we show that POUMM outperforms PMM even in simulations without selection—as it captures the mentioned correlation pattern—which has not been appreciated until now. By cross-validating the POUMM estimates with ANOVA on closest phylogenetic pairs, we obtain H(2) ≈ 0.2, meaning ∼20% of the variation in HIV-virulence is explained by the virus genome both for European and African data.
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spelling pubmed-58504762018-03-23 A Practical Guide to Estimating the Heritability of Pathogen Traits Mitov, Venelin Stadler, Tanja Mol Biol Evol Methods Pathogen traits, such as the virulence of an infection, can vary significantly between patients. A major challenge is to measure the extent to which genetic differences between infecting strains explain the observed variation of the trait. This is quantified by the trait’s broad-sense heritability, H(2). A recent discrepancy between estimates of the heritability of HIV-virulence has opened a debate on the estimators’ accuracy. Here, we show that the discrepancy originates from model limitations and important lifecycle differences between sexually reproducing organisms and transmittable pathogens. In particular, current quantitative genetics methods, such as donor–recipient regression of surveyed serodiscordant couples and the phylogenetic mixed model (PMM), are prone to underestimate H(2), because they neglect or do not fit to the loss of resemblance between transmission partners caused by within-host evolution. In a phylogenetic analysis of 8,483 HIV patients from the United Kingdom, we show that the phenotypic correlation between transmission partners decays with the amount of within-host evolution of the virus. We reproduce this pattern in toy-model simulations and show that a phylogenetic Ornstein–Uhlenbeck model (POUMM) outperforms the PMM in capturing this correlation pattern and in quantifying H(2). In particular, we show that POUMM outperforms PMM even in simulations without selection—as it captures the mentioned correlation pattern—which has not been appreciated until now. By cross-validating the POUMM estimates with ANOVA on closest phylogenetic pairs, we obtain H(2) ≈ 0.2, meaning ∼20% of the variation in HIV-virulence is explained by the virus genome both for European and African data. Oxford University Press 2018-03 2018-01-09 /pmc/articles/PMC5850476/ /pubmed/29329426 http://dx.doi.org/10.1093/molbev/msx328 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Methods
Mitov, Venelin
Stadler, Tanja
A Practical Guide to Estimating the Heritability of Pathogen Traits
title A Practical Guide to Estimating the Heritability of Pathogen Traits
title_full A Practical Guide to Estimating the Heritability of Pathogen Traits
title_fullStr A Practical Guide to Estimating the Heritability of Pathogen Traits
title_full_unstemmed A Practical Guide to Estimating the Heritability of Pathogen Traits
title_short A Practical Guide to Estimating the Heritability of Pathogen Traits
title_sort practical guide to estimating the heritability of pathogen traits
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850476/
https://www.ncbi.nlm.nih.gov/pubmed/29329426
http://dx.doi.org/10.1093/molbev/msx328
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