Show simple item record

dc.contributor.authorRamirez, Kelly S.
dc.contributor.authorKnight, Christopher G.
dc.contributor.authorde Hollander, Mattias
dc.contributor.authorBrearley, Francis Q.
dc.contributor.authorConstantinides, Bede
dc.contributor.authorCotton, Anne
dc.contributor.authorCreer, Si
dc.contributor.authorCrowther, Thomas W.
dc.contributor.authorDavison, John
dc.contributor.authorDelgado-Baquerizo, Manuel
dc.contributor.authorDorrepaal, Ellen
dc.contributor.authorElliott, David R.
dc.contributor.authorFox, Graeme
dc.contributor.authorGriffiths, Robert I.
dc.contributor.authorHale, Chris
dc.contributor.authorHartman, Kyle
dc.contributor.authorHoulden, Ashley
dc.contributor.authorJones, David L.
dc.contributor.authorKrab, Eveline J.
dc.contributor.authorMaestre, Fernando T.
dc.contributor.authorMcGuire, Krista L.
dc.contributor.authorMonteux, Sylvain
dc.contributor.authorOrr, Caroline H.
dc.contributor.authorvan der Putten, Wim H.
dc.contributor.authorRoberts, Ian S.
dc.contributor.authorRobinson, David A.
dc.contributor.authorRocca, Jennifer D.
dc.contributor.authorRowntree, Jennifer
dc.contributor.authorSchlaeppi, Klaus
dc.contributor.authorShepherd, Matthew
dc.contributor.authorSingh, Brajesh K.
dc.contributor.authorStraathof, Angela L.
dc.contributor.authorBhatnagar, Jennifer M.
dc.contributor.authorThion, Cécile
dc.contributor.authorvan der Heijden, Marcel G. A.
dc.contributor.authorde Vries, Franciska T.
dc.date.accessioned2018-01-25T15:16:08Z
dc.date.available2018-01-25T15:16:08Z
dc.date.issued2017-11-20
dc.identifier.citationRamirez, K. S. et al (2018) 'Detecting macroecological patterns in bacterial communities across independent studies of global soils,' Nature Microbiology, vol 3. pp. 189-196, DOI: 10.1038/s41564-017-0062-xen
dc.identifier.issn20585276
dc.identifier.doi10.1038/s41564-017-0062-x
dc.identifier.urihttp://hdl.handle.net/10545/622077
dc.description.abstractThe 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.
dc.description.sponsorshipBritish Ecological Society’s special interest group Plants-Soils-Ecosystems; ERC Advanced Grant;26055290; BBSRC David Phillips Fellowship (BB/L02456X/1); ERC Grant Agreements 242658 (BIOCOM) and 647038 (BIODESERT); the European Regional Development Fund (Centre of Excellence EcolChange) Yorkshire Agricultural Society, Nafferton Ecological Farming Group, and the Northumbria University Research Development Fund; BBSRC Training Grant (BB/K501943/1); Wallenberg Academy Fellowship (KAW 2012.0152), Formas (214-2011-788) and Vetenskapsrådet (612-2011-5444); the Glastir Monitoring & Evaluation Programme (contract reference: C147/2010/11) and the full support of the GMEP team on the Glastir project (D.L.J., S.C., and D.A.R.); Yorkshire Agricultural Society, Nafferton Ecological Farming Group, and the Northumbria University Research Development Fund; BBSRC Training Grant (BB/K501943/1); Wallenberg Academy Fellowship (KAW 2012.0152), Formas (214-2011-788) and Vetenskapsrådet (612-2011-5444); the Glastir Monitoring & Evaluation Programme (contract reference: C147/2010/11) and the full support of the GMEP team on the Glastir project .en
dc.language.isoenen
dc.publisherNatureen
dc.relation.urlhttp://www.nature.com/articles/s41564-017-0062-xen
dc.rightsArchived with thanks to Nature Microbiologyen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMicrobial ecologyen
dc.subjectSoilen
dc.subjectDiversityen
dc.subjectCommunity structureen
dc.subjectIllumina sequencingen
dc.subject16S rRNA geneen
dc.subjectBiogeographyen
dc.subjectMicrobiologyen
dc.subjectMeta-analysisen
dc.titleDetecting macroecological patterns in bacterial communities across independent studies of global soils.en
dc.typeArticleen
dc.contributor.departmentNetherlands Institute of Ecologyen
dc.contributor.departmentUniversity of Manchesteren
dc.contributor.departmentManchester Metropolitan Universityen
dc.contributor.departmentUniversity of Sheffielden
dc.contributor.departmentBangor Universityen
dc.contributor.departmentUniversity of Tartuen
dc.contributor.departmentUniversity of Coloradoen
dc.contributor.departmentUmeå Universityen
dc.contributor.departmentUniversity of Derbyen
dc.contributor.departmentCentre of Ecology and Hydrologyen
dc.contributor.departmentUniversity of Warwicken
dc.contributor.departmentAgroscopeen
dc.contributor.departmentUniversidad Rey Juan Carlosen
dc.contributor.departmentUniversity of Oregonen
dc.contributor.departmentTeeside Universityen
dc.contributor.departmentWageningen Universityen
dc.contributor.departmentDuke Universityen
dc.contributor.departmentNatural Englanden
dc.contributor.departmentWestern Sydney Universityen
dc.contributor.departmentBoston Universityen
dc.contributor.departmentUniversity of Aberdeenen
dc.identifier.journalNature Microbiologyen
dcterms.dateAccepted2017-10-13
refterms.dateFOA2018-05-20T00:00:00Z
html.description.abstractThe 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.


Files in this item

Thumbnail
Name:
2017-10-13 @paper Ramirez mega ...
Size:
1.819Mb
Format:
PDF
Description:
author accepted version of paper

This item appears in the following Collection(s)

Show simple item record

Archived with thanks to Nature Microbiology
Except where otherwise noted, this item's license is described as Archived with thanks to Nature Microbiology