Abstract: Over the last two decades, the study of fungal communities in natural environments has been revolutionized by the implementation of DNA-based sequencing methods. Currently, high-throughput sequencing (HTS) has become the de facto tool to characterize the richness and composition of fungal communities. Despite having a number of advantages, there are many choices to consider when using HTS, each potentially influencing ecological inference. In this talk, I will discuss some of my lab's recent efforts to test and optimize the use of HTS to maximize ecological inferences about fungi. Specifically, I will focus on our work on the effects of sample preparation, sequencing technology, and clustering method on HTS data generation and interpretation. I will also discuss the role of ITS copy number variation as an often-cited factor affecting sequence abundances in HTS datasets.
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