Data from: Finding flies in the mushroom soup: host specificity of fungus-associated communities revisited with a novel molecular method
Koskinen, Janne et al. (2018), Data from: Finding flies in the mushroom soup: host specificity of fungus-associated communities revisited with a novel molecular method, Dryad, Dataset, https://doi.org/10.5061/dryad.tf56fm1
Fruiting bodies of fungi constitute an important resource for thousands of other taxa. The structure of these diverse assemblages has traditionally been studied with labour-intensive methods involving cultivation and morphology-based species identification, to which molecular information might offer convenient complements. To overcome challenges in DNA extraction and PCR associated with the complex chemical properties fruiting bodies, we developed a pipeline applicable for extracting amplifiable total DNA from soft fungal samples of any size. Our protocol purifies DNA in two sequential steps: (1) initial salt-isopropanol extraction of all nucleic acids in the sample is followed by (2) an extra clean-up step using solid-phase reversible immobilization (SPRI) magnetic beads. The protocol proved highly efficient, with practically all of our samples — regardless of biomass or other properties — being successfully PCR amplified using metabarcoding primers and subsequently sequenced. As a proof-of-concept, we apply our methods to address a topical ecological question: is host specificity a major characteristic of fungus-associated communities, i.e., do different fungus species harbour different communities of associated organisms? Based on an analysis of 312 fungal fruiting bodies representing ten species in five genera from three orders, we show that molecular methods are suitable for studying this rich natural microcosm. Comparing to previous knowledge based on rearing and morphology-based identifications, we find a species-rich assemblage characterized by a low degree of host specialization. Our method opens up new horizons for molecular analyses of fungus-associated interaction webs and communities.