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Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)

Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assi...

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Autores principales: Martorelli, Irene, Helwerda, Leon S., Kerkvliet, Jesse, Gomes, Sofia I. F., Nuytinck, Jorinde, van der Werff, Chivany R. A., Ramackers, Guus J., Gultyaev, Alexander P., Merckx, Vincent S. F. T., Verbeek, Fons J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734503/
https://www.ncbi.nlm.nih.gov/pubmed/32463383
http://dx.doi.org/10.1515/jib-2019-0046
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author Martorelli, Irene
Helwerda, Leon S.
Kerkvliet, Jesse
Gomes, Sofia I. F.
Nuytinck, Jorinde
van der Werff, Chivany R. A.
Ramackers, Guus J.
Gultyaev, Alexander P.
Merckx, Vincent S. F. T.
Verbeek, Fons J.
author_facet Martorelli, Irene
Helwerda, Leon S.
Kerkvliet, Jesse
Gomes, Sofia I. F.
Nuytinck, Jorinde
van der Werff, Chivany R. A.
Ramackers, Guus J.
Gultyaev, Alexander P.
Merckx, Vincent S. F. T.
Verbeek, Fons J.
author_sort Martorelli, Irene
collection PubMed
description Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi.
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spelling pubmed-77345032020-12-22 Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB) Martorelli, Irene Helwerda, Leon S. Kerkvliet, Jesse Gomes, Sofia I. F. Nuytinck, Jorinde van der Werff, Chivany R. A. Ramackers, Guus J. Gultyaev, Alexander P. Merckx, Vincent S. F. T. Verbeek, Fons J. J Integr Bioinform Research-Article Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi. De Gruyter 2020-05-28 /pmc/articles/PMC7734503/ /pubmed/32463383 http://dx.doi.org/10.1515/jib-2019-0046 Text en © 2020 Irene Martorelli et al., published by De Gruyter, Berlin/Boston http://creativecommons.org/licenses/by/4.0 This work is licensed under the Creative Commons Attribution 4.0 Public License.
spellingShingle Research-Article
Martorelli, Irene
Helwerda, Leon S.
Kerkvliet, Jesse
Gomes, Sofia I. F.
Nuytinck, Jorinde
van der Werff, Chivany R. A.
Ramackers, Guus J.
Gultyaev, Alexander P.
Merckx, Vincent S. F. T.
Verbeek, Fons J.
Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title_full Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title_fullStr Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title_full_unstemmed Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title_short Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)
title_sort fungal metabarcoding data integration framework for the mycodiversity database (mddb)
topic Research-Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734503/
https://www.ncbi.nlm.nih.gov/pubmed/32463383
http://dx.doi.org/10.1515/jib-2019-0046
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