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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2020
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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. |
format | Online Article Text |
id | pubmed-7734503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
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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