Relative abundance data can misrepresent heritability of the microbiome

Open Access
Authors
  • K.M. Meyer
  • C..E. Metcalf
Publication date 09-10-2023
Journal Microbiome
Article number 222
Volume | Issue number 11
Number of pages 14
Organisations
  • Faculty of Science (FNWI) - Institute for Biodiversity and Ecosystem Dynamics (IBED)
Abstract

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 (h2) 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. [MediaObject not available: see fulltext.].

Document type Article
Note With supplementary file.
Language English
Published at https://doi.org/10.1186/s40168-023-01669-w
Other links https://www.scopus.com/pages/publications/85173636664
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