Greengenes2 enables a shared data universe for microbiome studies

Daniel T. McDonald; Yueyu Jiang; Metin Balaban; Kalen Cantrell; Qiyun Zhu; Antonio González; James T. Morton; Giorgia Nicolaou; Donovan H. Parks; Søren Michael Karst; Mads Albertsen; Philip Hugenholtz; Todd Z. DeSantis; Se Jin Song; Andrew P. Bartko; Aki Samuli Havulinna; Pekka Jousilahti; Susan C. Cheng; Mike Inouye; Teemu Niiranen; Mohit Jain; Veikko V Salomaa; Leo Lahti; Siavash Mirarab; Rob D. Knight

doi:10.1101/2022.12.19.520774

BioinformaticsbioRxivDec 19, 2022

Preprint

Greengenes2 enables a shared data universe for microbiome studies

Daniel T. McDonald iD, Yueyu Jiang iD, Metin Balaban iD, Kalen Cantrell iD, Qiyun Zhu iD, Antonio González iD, James T. Morton iD, Giorgia Nicolaou iD, Donovan H. Parks iD, Søren Michael Karst iD, Mads Albertsen iD, Philip Hugenholtz iD, Todd Z. DeSantis iD, Se Jin Song iD, Andrew P. Bartko iD, Aki Samuli Havulinna iD, Pekka Jousilahti iD, Susan C. Cheng iD, Mike Inouye, Teemu Niiranen iD, Mohit Jain iD, Veikko V Salomaa iD, Leo Lahti iD, Siavash Mirarab iD, Rob D. Knight iD

Abstract

16S rRNA and shotgun metagenomics studies typically yield different results, usually attributed to biases in PCR amplification of 16S rRNA genes. Here, we introduce Greengenes2 and show that differences in reference phylogeny are more important. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy, and in phenotype effect size when analyzed with the same tree.

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