Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification

Detalhes bibliográficos
Autor(a) principal: Gonçalves, Adriano Marques [UNESP]
Data de Publicação: 2022
Outros Autores: Girolli, Douglas Aparecido, Futenma de Lima, Mariana, Gorni, Guilherme Rossi
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s11756-022-01042-6
http://hdl.handle.net/11449/230399
Resumo: Aquatic Oligochaeta are one of most dominant taxa in freshwater sediments. Additionally, they have low dispersal capacity, and are highly sensitive to environmental changes. These characteristics make them important bioindicators to assess aquatic environment quality. Although many groups require experienced taxonomists for identification, the cytochrome C oxidase subunit I gene (COI) has been successfully used to identify Oligochaeta groups. Therefore, molecular barcoding strategy and evaluation, along with already deposited sequences, may be used to simplify Oligochaeta identification and environmental quality monitoring. A total of 1267 COI sequences, with 615–660 length, of fifteen genera of Oligochaeta and three genera of Polychaeta, as outgroups, were retrieved from NCBI GenBank. The sequences were aligned with MAFFT, curated with BMGE and Maximum Likelihood (ML) tree was inferred with GTR as evolutionary model, empirical equilibrium frequencies, SPR tree topology search and approximate Bayes branch support as statistical test. All analyses were performed with NGPhylogeny.fr server and ML tree editing was performed with MEGA X software. The inferred ML tree was able to robustly group different orders, and to satisfactorily differentiate the studied genera. Herein a method using free and intuitive bioinformatics tools is presented to assist non-specialists with a method to identify Oligochaeta genus, using molecular data. To improve the reliability of the method, including other genera, more efforts should be taken to increase the number of available COI sequences along with high quality morphological identification, especially for Neotropical environments.
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spelling Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identificationBarcodingBioinformaticsCOIDatabaseOligochaetesWormsAquatic Oligochaeta are one of most dominant taxa in freshwater sediments. Additionally, they have low dispersal capacity, and are highly sensitive to environmental changes. These characteristics make them important bioindicators to assess aquatic environment quality. Although many groups require experienced taxonomists for identification, the cytochrome C oxidase subunit I gene (COI) has been successfully used to identify Oligochaeta groups. Therefore, molecular barcoding strategy and evaluation, along with already deposited sequences, may be used to simplify Oligochaeta identification and environmental quality monitoring. A total of 1267 COI sequences, with 615–660 length, of fifteen genera of Oligochaeta and three genera of Polychaeta, as outgroups, were retrieved from NCBI GenBank. The sequences were aligned with MAFFT, curated with BMGE and Maximum Likelihood (ML) tree was inferred with GTR as evolutionary model, empirical equilibrium frequencies, SPR tree topology search and approximate Bayes branch support as statistical test. All analyses were performed with NGPhylogeny.fr server and ML tree editing was performed with MEGA X software. The inferred ML tree was able to robustly group different orders, and to satisfactorily differentiate the studied genera. Herein a method using free and intuitive bioinformatics tools is presented to assist non-specialists with a method to identify Oligochaeta genus, using molecular data. To improve the reliability of the method, including other genera, more efforts should be taken to increase the number of available COI sequences along with high quality morphological identification, especially for Neotropical environments.Departmento de Ciências Biológicas e da Saúde Universidade de Araraquara (UNIARA), SPDepartamento de Bioquímica e Química Orgânica Instituto de Química Universidade Estadual Paulista (UNESP), SPPrograma de Pós-graduação em Desenvolvimento Territorial e Meio Ambiente Universidade de Araraquara (UNIARA), SPDepartamento de Bioquímica e Química Orgânica Instituto de Química Universidade Estadual Paulista (UNESP), SPUniversidade de Araraquara (UNIARA)Universidade Estadual Paulista (UNESP)Gonçalves, Adriano Marques [UNESP]Girolli, Douglas AparecidoFutenma de Lima, MarianaGorni, Guilherme Rossi2022-04-29T08:39:37Z2022-04-29T08:39:37Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s11756-022-01042-6Biologia.1336-95630006-3088http://hdl.handle.net/11449/23039910.1007/s11756-022-01042-62-s2.0-85124730507Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBiologiainfo:eu-repo/semantics/openAccess2022-04-29T08:39:37Zoai:repositorio.unesp.br:11449/230399Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:53:44.709659Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
title Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
spellingShingle Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
Gonçalves, Adriano Marques [UNESP]
Barcoding
Bioinformatics
COI
Database
Oligochaetes
Worms
title_short Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
title_full Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
title_fullStr Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
title_full_unstemmed Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
title_sort Simple molecular based method for selected Oligochaeta (Annelida: Clitellata) genera identification
author Gonçalves, Adriano Marques [UNESP]
author_facet Gonçalves, Adriano Marques [UNESP]
Girolli, Douglas Aparecido
Futenma de Lima, Mariana
Gorni, Guilherme Rossi
author_role author
author2 Girolli, Douglas Aparecido
Futenma de Lima, Mariana
Gorni, Guilherme Rossi
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de Araraquara (UNIARA)
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Gonçalves, Adriano Marques [UNESP]
Girolli, Douglas Aparecido
Futenma de Lima, Mariana
Gorni, Guilherme Rossi
dc.subject.por.fl_str_mv Barcoding
Bioinformatics
COI
Database
Oligochaetes
Worms
topic Barcoding
Bioinformatics
COI
Database
Oligochaetes
Worms
description Aquatic Oligochaeta are one of most dominant taxa in freshwater sediments. Additionally, they have low dispersal capacity, and are highly sensitive to environmental changes. These characteristics make them important bioindicators to assess aquatic environment quality. Although many groups require experienced taxonomists for identification, the cytochrome C oxidase subunit I gene (COI) has been successfully used to identify Oligochaeta groups. Therefore, molecular barcoding strategy and evaluation, along with already deposited sequences, may be used to simplify Oligochaeta identification and environmental quality monitoring. A total of 1267 COI sequences, with 615–660 length, of fifteen genera of Oligochaeta and three genera of Polychaeta, as outgroups, were retrieved from NCBI GenBank. The sequences were aligned with MAFFT, curated with BMGE and Maximum Likelihood (ML) tree was inferred with GTR as evolutionary model, empirical equilibrium frequencies, SPR tree topology search and approximate Bayes branch support as statistical test. All analyses were performed with NGPhylogeny.fr server and ML tree editing was performed with MEGA X software. The inferred ML tree was able to robustly group different orders, and to satisfactorily differentiate the studied genera. Herein a method using free and intuitive bioinformatics tools is presented to assist non-specialists with a method to identify Oligochaeta genus, using molecular data. To improve the reliability of the method, including other genera, more efforts should be taken to increase the number of available COI sequences along with high quality morphological identification, especially for Neotropical environments.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-29T08:39:37Z
2022-04-29T08:39:37Z
2022-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s11756-022-01042-6
Biologia.
1336-9563
0006-3088
http://hdl.handle.net/11449/230399
10.1007/s11756-022-01042-6
2-s2.0-85124730507
url http://dx.doi.org/10.1007/s11756-022-01042-6
http://hdl.handle.net/11449/230399
identifier_str_mv Biologia.
1336-9563
0006-3088
10.1007/s11756-022-01042-6
2-s2.0-85124730507
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Biologia
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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