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MycoPins: a metabarcoding-based method to monitor fungal colonization of fine woody debris.
Shumskaya, Maria; Lorusso, Nicholas; Patel, Urvi; Leigh, Madison; Somervuo, Panu; Schigel, Dmitry.
Afiliación
  • Shumskaya M; Department of Biology, Kean University, Union, USA Kean University Union United States of America.
  • Lorusso N; Department of Biology, Kean University, Union, USA Kean University Union United States of America.
  • Patel U; University of North Texas at Dallas, Dallas, USA University of North Texas at Dallas Dallas United States of America.
  • Leigh M; Department of Biology, Kean University, Union, USA Kean University Union United States of America.
  • Somervuo P; Department of Biology, Kean University, Union, USA Kean University Union United States of America.
  • Schigel D; Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland University of Helsinki Helsinki Finland.
MycoKeys ; 96: 77-95, 2023.
Article en En | MEDLINE | ID: mdl-37214177
ABSTRACT
The MycoPins method described here is a rapid and affordable protocol to monitor early colonization events in communities of wood-inhabiting fungi in fine woody debris. It includes easy to implement field sampling techniques and sample processing, followed by data processing, and analysis of the development of early dead wood fungal communities. The method is based on fieldwork from a time series experiment on standard sterilized colonization targets followed by the metabarcoding analysis and automated molecular identification of species. This new monitoring method through its simplicity, moderate costs, and scalability paves a way for a broader and scalable project pipeline. MycoPins establishes a standard routine for research stations or regularly visited field sites for monitoring of fungal colonization of woody substrates. The routine uses widely available consumables and therefore presents a unifying method for monitoring of fungi of this type.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: MycoKeys Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: MycoKeys Año: 2023 Tipo del documento: Article