Opportunities for diversified usage of metabarcoding data for fungal biogeography through increased metadata quality

The widely adopted use of metabarcoding techniques and the ability to sequence microbial communities directly from environmental samples have advanced the field of fungal ecology. The growth of publicly available big data offers opportunities for collating data from different sources to explore biogeographical and macroecological patterns of fungal groups over large spatial scales. This requires reliable and high-quality metadata associated with the raw sequencing data. We assessed the accuracy of submitted metadata linked to terrestrial plant-associated fungal genetic marker sequences, extracted from NCBI's BioProject web-portal. The amount of correctly captured, missing, and incorrectly supplied metadata was determined. The quality of submitter-defined metadata was of a variable quality, with some adhering to metadata standards, and others not capturing metadata for certain attributes or, when metadata was captured, duplicating metadata across samples, or only partially meeting metadata requirements. This ultimately limits the ability to find, and subsequently re-use, sequence data. The rapid accumulation of metabarcoding data and the ability to directly compare samples taken from different studies holds opportunities for gaining a deeper understanding of fungal biogeographical patterns and their drivers. Standardised vocabularies for metadata attributes during submission to public repositories like NCBI's Sequence Read Archive, coupled with adequate incentives for the data providers, would facilitate the Findability, Accessibility, Interoperability, and Reusability (FAIR) data principles and ultimately enable metabarcoding sequence data to be readily utilized to perform large scale global biogeographical studies on the kingdom Fungi.