Top 50 most wanted fungi

By R. Nilsson, C. Wurzbacher, M. Bahram, V. Coimbra, E. Larsson, Leho Tedersoo, J. Eriksson, C. Ritter, S. Svantesson, M. Sánchez-García and 3 more. 2016

92 citations recorded by the source corpus.

Environmental sequencing regularly recovers fungi that cannot be classified to any meaningful taxonomic level beyond “Fungi”. There are several examples where evidence of such lineages has been sitting in public sequence databases for up to ten years before receiving scientific attention and formal recognition. In order to highlight these unidentified lineages for taxonomic scrutiny, a search function is presented that produces updated lists of approximately genus-level clusters of fungal ITS sequences that remain unidentified at the phylum, class, and order levels, respectively. The search function (https://unite.ut.ee/top50.php) is implemented in the UNITE database for molecular identification of fungi, such that the underlying sequences and fungal lineages are open to third-party annotation. We invite researchers to examine these enigmatic fungal lineages in the hope that their taxonomic resolution will not have to wait another ten years or more.

Subfields: Cell Biology, Ecology, Evolution, Behavior and Systematics, Plant Science

View Paper: https://www.semanticscholar.org/paper/3f29914bac156242d7900a3f59599539f1621f9c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cell Biology

1. P. W. Crous
2. Johannes Z. Groenewald
3. K. D. Hyde

In Ecology, Evolution, Behavior and Systematics

1. U. Eberhardt

In Plant Science

1. P. W. Crous
2. Johannes Z. Groenewald
3. U. Eberhardt
4. K. D. Hyde

Citations in the corpus

• Large-scale generation and analysis of filamentous fungal DNA barcodes boosts coverage for kingdom fungi and reveals thresholds for fungal species and higher taxon delimitation (2018, methodology): “The F-measure proposed by (Paccanaro et al. 2006) was used to evaluate an automatic clustering compared to the curated taxonomic assignments.”
• What we (don’t) know about global plant diversity (2018, unknown): “These include phyndr , an algorithm that maximizes the overlap between phylogenetic and species’ data (i.e., trait and spatial Pennell et al. , 2016), Phylomatic which uses tax-380 onomic data to fill-in missing phylogenetic data, and approaches which use taxonomic information to “gap-fill” our…”