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20 p, 3.9 MB

Opportunities and limits of combining microbiome and genome data for complex trait prediction / Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica) ; Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ; Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries) ; de los Campos, Gustavo (Michigan State University. Department of Epidemiology & Biostatistics)
Analysis and prediction of complex traits using microbiome data combined with host genomic information is a topic of utmost interest. However, numerous questions remain to be answered: how useful can the microbiome be for complex trait prediction? Are estimates of microbiability reliable? Can the underlying biological links between the host's genome, microbiome, and phenome be recovered? Here, we address these issues by (i) developing a novel simulation strategy that uses real microbiome and genotype data as inputs, and (ii) using variance-component approaches (Bayesian Reproducing Kernel Hilbert Space (RKHS) and Bayesian variable selection methods (Bayes C)) to quantify the proportion of phenotypic variance explained by the genome and the microbiome. [...]
2021 - DOI (Digital Object Identifier)

10.1186/s12711-021-00658-7
Genetics, selection, evolution, Vol. 53 (August 2021) , art. 65

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