From metabarcoding to metaphylogeography: separating the wheat from the chaff

Metabarcoding is by now a well‐established method for biodiversity assessment in terrestrial, freshwater and marine environments. Metabarcoding data sets are usually used for α‐ and β‐diversity estimates, that is, interspecies (or inter‐MOTU) patterns. However, the use of hypervariable metabarcoding...

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Detalhes bibliográficos
Autores: Turon, Xavier, Antich, Adrià, Palacín, Cruz, Præbel, Kim, Wangensteen, Owen S.
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/194485
Acesso em linha:http://hdl.handle.net/10261/194485
Access Level:acceso abierto
Palavra-chave:Metabarcoding
COI
Phylogeography
Eukaryotes
Sequencing errors
Illumina
Haplotype networks
AMOVA
Connectivity
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spelling From metabarcoding to metaphylogeography: separating the wheat from the chaffTuron, XavierAntich, AdriàPalacín, CruzPræbel, KimWangensteen, Owen S.MetabarcodingCOIPhylogeographyEukaryotesSequencing errorsIlluminaHaplotype networksAMOVAConnectivityMetabarcoding is by now a well‐established method for biodiversity assessment in terrestrial, freshwater and marine environments. Metabarcoding data sets are usually used for α‐ and β‐diversity estimates, that is, interspecies (or inter‐MOTU) patterns. However, the use of hypervariable metabarcoding markers may provide an enormous amount of intraspecies (intra‐MOTU) information ‐ mostly untapped so far. The use of cytochrome oxidase (COI) amplicons is gaining momentum in metabarcoding studies targeting eukaryote richness. COI has been for a long time the marker of choice in population genetics and phylogeographic studies. Therefore, COI metabarcoding data sets may be used to study intraspecies patterns and phylogeographic features for hundreds of species simultaneously, opening a new field which we suggest to name metaphylogeography. The main challenge for the implementation of this approach is the separation of erroneous sequences from true intra‐MOTU variation. Here, we develop a cleaning protocol based on changes in entropy of the different codon positions of the COI sequence, together with co‐occurrence patterns of sequences. Using a data set of community DNA from several benthic littoral communities in the Mediterranean and Atlantic seas, we first tested by simulation on a subset of sequences a two‐step cleaning approach consisting of a denoising step followed by a minimal abundance filtering. The procedure was then applied to the whole data set. We obtained a total of 563 MOTUs that were usable for phylogeographic inference. We used semiquantitative rank data instead of read abundances to perform AMOVAs and haplotype networks. Genetic variability was mainly concentrated within samples, but with an important between‐seas component as well. There were inter‐group differences in the amount of variability between and within communities in each sea. For two species the results could be compared with traditional Sanger sequence data available for the same zones, giving similar patterns. Our study shows that metabarcoding data can be used to infer intra‐ and interpopulation genetic variability of many species at a time, providing a new method with great potential for basic biogeography, connectivity and dispersal studies, and for the more applied fields of conservation genetics, invasion genetics, and design of protected areas.Peer reviewedJohn Wiley & SonsConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]201920192019info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/194485reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1002/eap.2036Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1944852026-05-22T06:33:51Z
dc.title.none.fl_str_mv From metabarcoding to metaphylogeography: separating the wheat from the chaff
title From metabarcoding to metaphylogeography: separating the wheat from the chaff
spellingShingle From metabarcoding to metaphylogeography: separating the wheat from the chaff
Turon, Xavier
Metabarcoding
COI
Phylogeography
Eukaryotes
Sequencing errors
Illumina
Haplotype networks
AMOVA
Connectivity
title_short From metabarcoding to metaphylogeography: separating the wheat from the chaff
title_full From metabarcoding to metaphylogeography: separating the wheat from the chaff
title_fullStr From metabarcoding to metaphylogeography: separating the wheat from the chaff
title_full_unstemmed From metabarcoding to metaphylogeography: separating the wheat from the chaff
title_sort From metabarcoding to metaphylogeography: separating the wheat from the chaff
dc.creator.none.fl_str_mv Turon, Xavier
Antich, Adrià
Palacín, Cruz
Præbel, Kim
Wangensteen, Owen S.
author Turon, Xavier
author_facet Turon, Xavier
Antich, Adrià
Palacín, Cruz
Præbel, Kim
Wangensteen, Owen S.
author_role author
author2 Antich, Adrià
Palacín, Cruz
Præbel, Kim
Wangensteen, Owen S.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Metabarcoding
COI
Phylogeography
Eukaryotes
Sequencing errors
Illumina
Haplotype networks
AMOVA
Connectivity
topic Metabarcoding
COI
Phylogeography
Eukaryotes
Sequencing errors
Illumina
Haplotype networks
AMOVA
Connectivity
description Metabarcoding is by now a well‐established method for biodiversity assessment in terrestrial, freshwater and marine environments. Metabarcoding data sets are usually used for α‐ and β‐diversity estimates, that is, interspecies (or inter‐MOTU) patterns. However, the use of hypervariable metabarcoding markers may provide an enormous amount of intraspecies (intra‐MOTU) information ‐ mostly untapped so far. The use of cytochrome oxidase (COI) amplicons is gaining momentum in metabarcoding studies targeting eukaryote richness. COI has been for a long time the marker of choice in population genetics and phylogeographic studies. Therefore, COI metabarcoding data sets may be used to study intraspecies patterns and phylogeographic features for hundreds of species simultaneously, opening a new field which we suggest to name metaphylogeography. The main challenge for the implementation of this approach is the separation of erroneous sequences from true intra‐MOTU variation. Here, we develop a cleaning protocol based on changes in entropy of the different codon positions of the COI sequence, together with co‐occurrence patterns of sequences. Using a data set of community DNA from several benthic littoral communities in the Mediterranean and Atlantic seas, we first tested by simulation on a subset of sequences a two‐step cleaning approach consisting of a denoising step followed by a minimal abundance filtering. The procedure was then applied to the whole data set. We obtained a total of 563 MOTUs that were usable for phylogeographic inference. We used semiquantitative rank data instead of read abundances to perform AMOVAs and haplotype networks. Genetic variability was mainly concentrated within samples, but with an important between‐seas component as well. There were inter‐group differences in the amount of variability between and within communities in each sea. For two species the results could be compared with traditional Sanger sequence data available for the same zones, giving similar patterns. Our study shows that metabarcoding data can be used to infer intra‐ and interpopulation genetic variability of many species at a time, providing a new method with great potential for basic biogeography, connectivity and dispersal studies, and for the more applied fields of conservation genetics, invasion genetics, and design of protected areas.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/194485
url http://hdl.handle.net/10261/194485
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1002/eap.2036
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv John Wiley & Sons
publisher.none.fl_str_mv John Wiley & Sons
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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