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Towards the biogeography of prokaryotic genes.
Coelho, Luis Pedro; Alves, Renato; Del Río, Álvaro Rodríguez; Myers, Pernille Neve; Cantalapiedra, Carlos P; Giner-Lamia, Joaquín; Schmidt, Thomas Sebastian; Mende, Daniel R; Orakov, Askarbek; Letunic, Ivica; Hildebrand, Falk; Van Rossum, Thea; Forslund, Sofia K; Khedkar, Supriya; Maistrenko, Oleksandr M; Pan, Shaojun; Jia, Longhao; Ferretti, Pamela; Sunagawa, Shinichi; Zhao, Xing-Ming; Nielsen, Henrik Bjørn; Huerta-Cepas, Jaime; Bork, Peer.
Affiliation
  • Coelho LP; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. coelho@fudan.edu.cn.
  • Alves R; MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Shanghai, China. coelho@fudan.edu.cn.
  • Del Río ÁR; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. coelho@fudan.edu.cn.
  • Myers PN; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Cantalapiedra CP; Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain.
  • Giner-Lamia J; Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark.
  • Schmidt TS; Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain.
  • Mende DR; Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain.
  • Orakov A; Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid (UPM), Madrid, Spain.
  • Letunic I; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Hildebrand F; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Van Rossum T; Daniel K. Inouye Center for Microbial Oceanography: Research and Education, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Forslund SK; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Khedkar S; biobyte solutions GmbH, Heidelberg, Germany.
  • Maistrenko OM; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Pan S; Earlham Institute, Norwich Research Park, Norwich, UK.
  • Jia L; Gut Health and Microbes Programme, Quadram Institute, Norwich Research Park, Norwich, UK.
  • Ferretti P; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Sunagawa S; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Zhao XM; Experimental and Clinical Research Center (ECRC), a joint venture of the Max Delbrück Centre (MDC) and Charité University Hospital, Berlin, Germany.
  • Nielsen HB; Berlin Initiative of Health, Berlin, Germany.
  • Huerta-Cepas J; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
  • Bork P; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Nature ; 601(7892): 252-256, 2022 01.
Article in En | MEDLINE | ID: mdl-34912116
ABSTRACT
Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Metagenome / Metagenomics Limits: Humans Language: En Journal: Nature Year: 2022 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Metagenome / Metagenomics Limits: Humans Language: En Journal: Nature Year: 2022 Type: Article Affiliation country: China