Whole Genome Shotgun Sequencing Detects Greater Lichen Fungal Diversity Than Amplicon-Based Methods in Environmental Samples

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Abstract

In this study we demonstrate the utility of whole genome shotgun (WGS) metagenomics in study organisms with small genomes to improve upon amplicon-based estimates of biodiversity and microbial diversity in environmental samples for the purpose of understanding ecological and evolutionary processes. We generated a database of full-length and near-full-length ribosomal DNA sequence complexes from 273 lichenized fungal species and used this database to facilitate fungal species identification in the southern Appalachian Mountains using low coverage WGS at higher resolution and without the biases of amplicon-based approaches. Using this new database and methods herein developed, we detected between 2.8 and 11 times as many species from lichen fungal propagules by aligning reads from WGS-sequenced environmental samples compared to a traditional amplicon-based approach. We then conducted complete taxonomic diversity inventories of the lichens in each one-hectare plot to assess overlap between standing taxonomic diversity and diversity detected based on propagules present in environmental samples (i.e., the “potential” of diversity). From the environmental samples, we detected 94 species not observed in organism-level sampling in these ecosystems with high confidence using both WGS and amplicon-based methods. This study highlights the utility of WGS sequence-based approaches in detecting hidden species diversity and demonstrates that amplicon-based methods likely miss important components of fungal diversity. We suggest that the adoption of this method will not only improve understanding of biotic constraints on the distributions of biodiversity but will also help to inform important environmental policy.

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Keepers, K. G., Pogoda, C. S., White, K. H., Anderson Stewart, C. R., Hoffman, J. R., Ruiz, A. M., … Tripp, E. A. (2019). Whole Genome Shotgun Sequencing Detects Greater Lichen Fungal Diversity Than Amplicon-Based Methods in Environmental Samples. Frontiers in Ecology and Evolution, 7. https://doi.org/10.3389/fevo.2019.00484

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