Greengenes2 unifies microbial data in a single reference tree

Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome p...

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Published in:	Nature biotechnology Vol. 42; no. 5; pp. 715 - 718
Main Authors:	McDonald, Daniel, Jiang, Yueyu, Balaban, Metin, Cantrell, Kalen, Zhu, Qiyun, Gonzalez, Antonio, Morton, James T., Nicolaou, Giorgia, Parks, Donovan H., Karst, Søren M., Albertsen, Mads, Hugenholtz, Philip, DeSantis, Todd, Song, Se Jin, Bartko, Andrew, Havulinna, Aki S., Jousilahti, Pekka, Cheng, Susan, Inouye, Michael, Niiranen, Teemu, Jain, Mohit, Salomaa, Veikko, Lahti, Leo, Mirarab, Siavash, Knight, Rob
Format:	Journal Article
Language:	English
Published:	New York Nature Publishing Group US 01.05.2024 Nature Publishing Group
Subjects:	631/114/129 631/158/855 Agriculture Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Brief Communication Communication Computer engineering Genomes Genomics Life Sciences Metagenomics Microorganisms Phenotypes Phylogenetics Phylogeny rRNA 16S Taxonomy
ISSN:	1087-0156, 1546-1696, 1546-1696
Online Access:	Get full text
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Abstract	Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree. A comprehensive microbial resource reconciles genomic and 16S rRNA data in a single tree.
AbstractList	Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree.A comprehensive microbial resource reconciles genomic and 16S rRNA data in a single tree. Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree.Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree. Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree. Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. 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 phenotype effect size when analyzed with the same tree. A comprehensive microbial resource reconciles genomic and 16S rRNA data in a single tree.
Author	Balaban, Metin Jain, Mohit Zhu, Qiyun Cheng, Susan Jousilahti, Pekka Nicolaou, Giorgia McDonald, Daniel Knight, Rob Niiranen, Teemu Jiang, Yueyu Inouye, Michael Havulinna, Aki S. Bartko, Andrew Morton, James T. Salomaa, Veikko Mirarab, Siavash Albertsen, Mads Karst, Søren M. Parks, Donovan H. Lahti, Leo Gonzalez, Antonio Cantrell, Kalen DeSantis, Todd Hugenholtz, Philip Song, Se Jin
Author_xml	– sequence: 1 givenname: Daniel surname: McDonald fullname: McDonald, Daniel organization: Department of Pediatrics, University of California San Diego School of Medicine – sequence: 2 givenname: Yueyu surname: Jiang fullname: Jiang, Yueyu organization: Department of Electrical and Computer Engineering, University of California San Diego – sequence: 3 givenname: Metin surname: Balaban fullname: Balaban, Metin organization: Bioinformatics and Systems Biology Program, University of California San Diego – sequence: 4 givenname: Kalen surname: Cantrell fullname: Cantrell, Kalen organization: Department of Computer Science and Engineering, University of California San Diego – sequence: 5 givenname: Qiyun orcidid: 0000-0002-3568-6271 surname: Zhu fullname: Zhu, Qiyun organization: School of Life Sciences, Arizona State University, Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University – sequence: 6 givenname: Antonio surname: Gonzalez fullname: Gonzalez, Antonio organization: Department of Pediatrics, University of California San Diego School of Medicine – sequence: 7 givenname: James T. surname: Morton fullname: Morton, James T. organization: Biostatistics & Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health – sequence: 8 givenname: Giorgia surname: Nicolaou fullname: Nicolaou, Giorgia organization: Halicioglu Data Science Institute, University of California San Diego – sequence: 9 givenname: Donovan H. orcidid: 0000-0001-6662-9010 surname: Parks fullname: Parks, Donovan H. organization: Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland – sequence: 10 givenname: Søren M. surname: Karst fullname: Karst, Søren M. organization: Department of Obstetrics and Gynecology, Columbia University – sequence: 11 givenname: Mads orcidid: 0000-0002-6151-190X surname: Albertsen fullname: Albertsen, Mads organization: Department of Chemistry and Bioscience, Aalborg University – sequence: 12 givenname: Philip orcidid: 0000-0001-5386-7925 surname: Hugenholtz fullname: Hugenholtz, Philip organization: Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland – sequence: 13 givenname: Todd surname: DeSantis fullname: DeSantis, Todd organization: Department of Informatics, Second Genome – sequence: 14 givenname: Se Jin surname: Song fullname: Song, Se Jin organization: Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego – sequence: 15 givenname: Andrew orcidid: 0000-0002-1237-2747 surname: Bartko fullname: Bartko, Andrew organization: Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego – sequence: 16 givenname: Aki S. orcidid: 0000-0002-4787-8959 surname: Havulinna fullname: Havulinna, Aki S. organization: Finnish Institute for Health and Welfare, Institute for Molecular Medicine Finland, FIMM-HiLIFE – sequence: 17 givenname: Pekka surname: Jousilahti fullname: Jousilahti, Pekka organization: Finnish Institute for Health and Welfare – sequence: 18 givenname: Susan surname: Cheng fullname: Cheng, Susan organization: Division of Cardiology, Brigham and Women’s Hospital, Cedars-Sinai Medical Center – sequence: 19 givenname: Michael surname: Inouye fullname: Inouye, Michael organization: Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge – sequence: 20 givenname: Teemu surname: Niiranen fullname: Niiranen, Teemu organization: Finnish Institute for Health and Welfare, Division of Medicine, Turku University Hospital and University of Turku – sequence: 21 givenname: Mohit surname: Jain fullname: Jain, Mohit organization: Sapient Bioanalytics, LLC – sequence: 22 givenname: Veikko orcidid: 0000-0001-7563-5324 surname: Salomaa fullname: Salomaa, Veikko organization: Finnish Institute for Health and Welfare – sequence: 23 givenname: Leo surname: Lahti fullname: Lahti, Leo organization: Department of Computing, University of Turku – sequence: 24 givenname: Siavash orcidid: 0000-0001-5410-1518 surname: Mirarab fullname: Mirarab, Siavash organization: Department of Electrical and Computer Engineering, University of California San Diego – sequence: 25 givenname: Rob orcidid: 0000-0002-0975-9019 surname: Knight fullname: Knight, Rob email: robknight@eng.ucsd.edu organization: Department of Pediatrics, University of California San Diego School of Medicine, Department of Computer Science and Engineering, University of California San Diego, Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, Department of Bioengineering, University of California San Diego
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DOI	10.1038/s41587-023-01845-1
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Snippet	Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a...
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SubjectTerms	631/114/129 631/158/855 Agriculture Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Brief Communication Communication Computer engineering Genomes Genomics Life Sciences Metagenomics Microorganisms Phenotypes Phylogenetics Phylogeny rRNA 16S Taxonomy
Title	Greengenes2 unifies microbial data in a single reference tree
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