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Relative abundance data can misrepresent heritability of the microbiome
BACKGROUND: Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h(2)) of the microbiome—the proportion of variance in the abundance in each taxon that is at...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10561453/ https://www.ncbi.nlm.nih.gov/pubmed/37814275 http://dx.doi.org/10.1186/s40168-023-01669-w |
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author | Bruijning, Marjolein Ayroles, Julien F. Henry, Lucas P. Koskella, Britt Meyer, Kyle M. Metcalf, C. Jessica E. |
author_facet | Bruijning, Marjolein Ayroles, Julien F. Henry, Lucas P. Koskella, Britt Meyer, Kyle M. Metcalf, C. Jessica E. |
author_sort | Bruijning, Marjolein |
collection | PubMed |
description | BACKGROUND: Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h(2)) of the microbiome—the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample. RESULTS: We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates. CONCLUSIONS: We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01669-w. |
format | Online Article Text |
id | pubmed-10561453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105614532023-10-10 Relative abundance data can misrepresent heritability of the microbiome Bruijning, Marjolein Ayroles, Julien F. Henry, Lucas P. Koskella, Britt Meyer, Kyle M. Metcalf, C. Jessica E. Microbiome Research BACKGROUND: Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h(2)) of the microbiome—the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample. RESULTS: We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates. CONCLUSIONS: We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01669-w. BioMed Central 2023-10-09 /pmc/articles/PMC10561453/ /pubmed/37814275 http://dx.doi.org/10.1186/s40168-023-01669-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Bruijning, Marjolein Ayroles, Julien F. Henry, Lucas P. Koskella, Britt Meyer, Kyle M. Metcalf, C. Jessica E. Relative abundance data can misrepresent heritability of the microbiome |
title | Relative abundance data can misrepresent heritability of the microbiome |
title_full | Relative abundance data can misrepresent heritability of the microbiome |
title_fullStr | Relative abundance data can misrepresent heritability of the microbiome |
title_full_unstemmed | Relative abundance data can misrepresent heritability of the microbiome |
title_short | Relative abundance data can misrepresent heritability of the microbiome |
title_sort | relative abundance data can misrepresent heritability of the microbiome |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10561453/ https://www.ncbi.nlm.nih.gov/pubmed/37814275 http://dx.doi.org/10.1186/s40168-023-01669-w |
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