Phylogenomics of 10,575 genomes reveals evolutionary proximity between domains Bacteria and Archaea

Qiyun Zhu; Uyen Mai; Wayne Pfeiffer; Stefan Janssen; Francesco Asnicar; Jon G Sanders; Pedro Belda-Ferre; Gabriel A Al-Ghalith; Evguenia Kopylova; Daniel McDonald; Tomasz Kosciolek; John B Yin; Shi Huang; Nimaichand Salam; Jian-Yu Jiao; Zijun Wu; Zhenjiang Z Xu; Kalen Cantrell; Yimeng Yang; Erfan Sayyari; Maryam Rabiee; James T Morton; Sheila Podell; Dan Knights; Wen-Jun Li; Curtis Huttenhower; Nicola Segata; Larry Smarr; Siavash Mirarab; Rob Knight

doi:10.1038/s41467-019-13443-4

Phylogenomics of 10,575 genomes reveals evolutionary proximity between domains Bacteria and Archaea

Nat Commun. 2019 Dec 2;10(1):5477. doi: 10.1038/s41467-019-13443-4.

Authors

Qiyun Zhu¹, Uyen Mai², Wayne Pfeiffer³, Stefan Janssen^{1

4}, Francesco Asnicar⁵, Jon G Sanders¹, Pedro Belda-Ferre¹, Gabriel A Al-Ghalith⁶, Evguenia Kopylova¹, Daniel McDonald¹, Tomasz Kosciolek^{1

7}, John B Yin^{8

9}, Shi Huang^{1

10}, Nimaichand Salam¹¹, Jian-Yu Jiao¹¹, Zijun Wu^{1

12}, Zhenjiang Z Xu¹, Kalen Cantrell⁶, Yimeng Yang⁶, Erfan Sayyari⁸, Maryam Rabiee², James T Morton^{1

2}, Sheila Podell¹³, Dan Knights⁶, Wen-Jun Li¹¹, Curtis Huttenhower^{14

15}, Nicola Segata⁵, Larry Smarr^{2

16

17}, Siavash Mirarab⁷, Rob Knight^{18

19

20

21}

Affiliations

¹ Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
² Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
³ San Diego Supercomputer Center, University of California San Diego, La Jolla, CA, USA.
⁴ Algorithmic Bioinformatics, Department of Biology and Chemistry, Justus Liebig University Gießen, Giessen, Germany.
⁵ Department CIBIO, University of Trento, Trento, Italy.
⁶ Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.
⁷ Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
⁸ Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
⁹ Department of Mathematics, University of California San Diego, La Jolla, CA, USA.
¹⁰ Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
¹¹ State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
¹² Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA.
¹³ Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
¹⁴ Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹⁵ The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁶ Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.
¹⁷ California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, CA, USA.
¹⁸ Department of Pediatrics, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.
¹⁹ Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.
²⁰ Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.
²¹ Department of Bioengineering, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.

Abstract

Rapid growth of genome data provides opportunities for updating microbial evolutionary relationships, but this is challenged by the discordant evolution of individual genes. Here we build a reference phylogeny of 10,575 evenly-sampled bacterial and archaeal genomes, based on a comprehensive set of 381 markers, using multiple strategies. Our trees indicate remarkably closer evolutionary proximity between Archaea and Bacteria than previous estimates that were limited to fewer "core" genes, such as the ribosomal proteins. The robustness of the results was tested with respect to several variables, including taxon and site sampling, amino acid substitution heterogeneity and saturation, non-vertical evolution, and the impact of exclusion of candidate phyla radiation (CPR) taxa. Our results provide an updated view of domain-level relationships.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Archaea / classification*
Archaea / genetics
Bacteria / classification*
Bacteria / genetics
Evolution, Molecular*
Genome, Archaeal*
Genome, Bacterial*
Phylogeny*

Grants and funding

P30 MH062512/MH/NIMH NIH HHS/United States