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

Area of Science:

• Ecology
• Mycology
• Bioinformatics

Background:

• Fungi play vital ecological roles but their global distribution and diversity are poorly understood.
• Environmental DNA (eDNA) metabarcoding significantly aids fungal diversity detection.
• Publicly available fungal eDNA data is vast but suffers from heterogeneous annotation and lacks uniform processing pipelines.

Purpose of the Study:

• To establish a comprehensive framework for analyzing fungal metabarcoding data.
• To create the MycoDiversity DataBase for studying fungal biodiversity patterns.
• To facilitate large-scale, spatio-temporal analyses and ecological research on Fungi.

Main Methods:

• Development of a standardized processing framework for fungal metabarcoding data.
• Integration of public fungal metabarcoding sequences and associated environmental descriptors.
• Creation of the MycoDiversity DataBase to host curated data.

Main Results:

• The MycoDiversity DataBase provides a centralized resource for fungal biodiversity research.
• The proposed framework enables consistent analysis of diverse fungal eDNA datasets.
• The database supports the investigation of fungal distribution and diversity patterns.

Conclusions:

• The MycoDiversity DataBase and framework offer a valuable resource for advancing fungal ecological and evolutionary studies.
• Standardized analysis of public fungal eDNA data is crucial for understanding global fungal diversity.
• This initiative will enhance large-scale biodiversity assessments in space and time.