Detecting macroecological patterns in bacterial communities across independent studies of global soils

Ramirez, Kelly S. and Knight, Christopher G. and de Hollander, Mattias and Brearley, Francis Q. and Constantinides, Bede and Cotton, Anne and Creer, Si and Crowther, Thomas W. and Davison, John and Delgado-Baquerizo, Manuel and Dorrepaal, Ellen and Elliott, David R. and Fox, Graeme and Griffiths, Robert I. and Hale, Chris and Hartman, Kyle and Houlden, Ashley and Jones, David L. and Krab, Eveline J. and Maestre, Fernando T. and McGuire, Krista L. and Monteux, Sylvain and Orr, Caroline H. and van der Putten, Wim H. and Roberts, Ian S. and Robinson, David A. and Rocca, Jennifer D. and Rowntree, Jennifer and Schlaeppi, Klaus and Shepherd, Matthew and Singh, Brajesh K. and Straathof, Angela L. and Bhatnagar, Jennifer M. and Thion, Cécile and van der Heijden, Marcel G. A. and de Vries, Franciska T.. (2018) Detecting macroecological patterns in bacterial communities across independent studies of global soils. Nature Microbiology, 3 (2). pp. 189-196.

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Official URL: https://edoc.unibas.ch/79071/

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The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.
Faculties and Departments:05 Faculty of Science > Departement Umweltwissenschaften > Integrative Biologie > Plant-Microbe Interaction (Schläppi)
UniBasel Contributors:Schläppi, Klaus Bernhard
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Nature Publishing Group
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:05 Nov 2020 11:13
Deposited On:05 Nov 2020 11:13

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