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Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys

The data presented here are related to the research article “Multi-marker metabarcoding of coral skeletons reveals a rich microbiome and diverse evolutionary origins of endolithic algae” (Marcelino and Verbruggen, 2016) [1]. Here we provide reference datasets of the elongation factor Tu (tufA) and t...

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Detalles Bibliográficos
Autores principales: Rossetto Marcelino, Vanessa, Verbruggen, Heroen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320050/
https://www.ncbi.nlm.nih.gov/pubmed/28243624
http://dx.doi.org/10.1016/j.dib.2017.02.013
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author Rossetto Marcelino, Vanessa
Verbruggen, Heroen
author_facet Rossetto Marcelino, Vanessa
Verbruggen, Heroen
author_sort Rossetto Marcelino, Vanessa
collection PubMed
description The data presented here are related to the research article “Multi-marker metabarcoding of coral skeletons reveals a rich microbiome and diverse evolutionary origins of endolithic algae” (Marcelino and Verbruggen, 2016) [1]. Here we provide reference datasets of the elongation factor Tu (tufA) and the Universal Plastid Amplicon (UPA) markers in a format that is ready-to-use in the QIIME pipeline (Caporaso et al., 2010) [2]. In addition to sequences previously available in GenBank, we included newly discovered endolithic algae lineages using both amplicon sequencing (Marcelino and Verbruggen, 2016) [1] and chloroplast genome data (Marcelino et al., 2016; Verbruggen et al., in press) [3], [4]. We also provide a script to convert GenBank flatfiles into reference datasets that can be used with other markers. The tufA and UPA reference datasets are made publicly available here to facilitate biodiversity assessments of microalgal communities.
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spelling pubmed-53200502017-02-27 Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys Rossetto Marcelino, Vanessa Verbruggen, Heroen Data Brief Data Article The data presented here are related to the research article “Multi-marker metabarcoding of coral skeletons reveals a rich microbiome and diverse evolutionary origins of endolithic algae” (Marcelino and Verbruggen, 2016) [1]. Here we provide reference datasets of the elongation factor Tu (tufA) and the Universal Plastid Amplicon (UPA) markers in a format that is ready-to-use in the QIIME pipeline (Caporaso et al., 2010) [2]. In addition to sequences previously available in GenBank, we included newly discovered endolithic algae lineages using both amplicon sequencing (Marcelino and Verbruggen, 2016) [1] and chloroplast genome data (Marcelino et al., 2016; Verbruggen et al., in press) [3], [4]. We also provide a script to convert GenBank flatfiles into reference datasets that can be used with other markers. The tufA and UPA reference datasets are made publicly available here to facilitate biodiversity assessments of microalgal communities. Elsevier 2017-02-13 /pmc/articles/PMC5320050/ /pubmed/28243624 http://dx.doi.org/10.1016/j.dib.2017.02.013 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Rossetto Marcelino, Vanessa
Verbruggen, Heroen
Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title_full Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title_fullStr Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title_full_unstemmed Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title_short Reference datasets of tufA and UPA markers to identify algae in metabarcoding surveys
title_sort reference datasets of tufa and upa markers to identify algae in metabarcoding surveys
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320050/
https://www.ncbi.nlm.nih.gov/pubmed/28243624
http://dx.doi.org/10.1016/j.dib.2017.02.013
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