Piptocephalis phylogeny and metagenomics experiment

The Piptocephalidaceae (Zoopagales, Zoopagomycota) contains three genera of mycoparasitic, haustoria-forming fungi: Kuzuhaea, Piptocephalis, and Syncephalis. Although the fungi in this group are diverse and ubiquitous in soil and dung, they are among the least studied fungi on the planet. Co-cultures of Piptocephalis and their hosts are relatively easy to isolate from soil and dung samples across the globe, making them a good model taxon for the order Zoopagales. This study focuses on the systematics of the genus Piptocephalis. Despite the fact that there are approximately 40 described Piptocephalis species, there are no modern taxonomic or molecular phylogenetic treatments of this group. Minimal sequence data are available for Piptocephalis species and relatively little is known about the true diversity or biogeography of the genus. Likewise, representation of the genus in environmental sequencing surveys is limited, possibly due to methodological difficulties in sequencing the internal transcribed spacer region (ITS) of rDNA. Our study addresses two aspects: Piptocephalis systematics and representation of Piptocephalidaceae taxa in metagenomics surveys. First, we generated a large subunit (28S) nuc rDNA phylogeny and evaluated several morphological characters by testing their correlation with the phylogeny using Bayesian Tip-association Significance testing (BaTS). We found monophyly of Piptocephalis species identified based on morphological traits but morphological character states were not conserved across clades, suggesting that there have been multiple gains and losses of morphological features. We also found that Kuzhuaea is nested within Piptocephalis. Secondly, we tested the effect of ITS region length on amplification and detection from metagenomic samples sequenced on an Illumina high-throughput platform. We found evidence to support our hypothesis of bias against long ITS sequences and preferential sequencing of short ITS sequences. We suggest that an optimized environmental sequencing protocol should be developed to detect long and divergent Zoopagomycotina sequences from metagenomic samples.