A long-read amplicon approach to scaling up the metabarcoding of lichen herbarium specimens

AbstractReference sequence databases are critical to the accurate detection and identification of fungi in the environment. As repositories of large numbers of well-curated specimens, herbaria and fungal culture collections have the material resources to generate sequence data for large number of taxa, and could therefore allow filling taxonomic gaps often present in reference sequence databases. Financial resources to do that are however often lacking, so that recent efforts have focused on decreasing sequencing cost by increasing the number of multiplexed samples per sequencing run while maintaining high sequence quality. Following a previous study that aimed at decreasing sequencing cost for lichen specimens by generating fungal ITS barcodes for 96 specimens using PacBio amplicon sequencing, we present a method that further decreases lichen specimen metabarcoding costs. A total of 384 mixed DNA extracts obtained from lichen herbarium specimens, mostly from the four genera Buellia, Catillaria, Endocarpon and Parmotrema, were used to generate new fungal ITS sequences using a Sequel I sequencing platform and the PacBio M13 barcoded primers. The average success rate across all taxa was high (86.5%), with particularly high rates for the crustose saxicolous taxa (Buellia, Catillaria and others; 93.3%) and the terricolous squamulose taxa (Endocarpon and others; 96.5%). On the other hand, the success rate for the foliose genus Parmotrema was lower (60.4%). With this taxon sampling, greater specimen age did not appear to impact sequencing success. In fact, the 1966–1980 collection date category showed the highest success rate (97.3%). Compared to the previous study, the abundance-based sequence denoising method showed some limitations, but the cost of generating ITS barcodes was further decreased thanks to the higher multiplexing level. In addition to contributing new ITS barcodes for specimens of four interesting lichen genera, this study further highlights the potential and challenges of using new sequencing technologies on collection specimens to generate DNA sequences for reference databases.