Optimization of the second internal transcribed spacer (ITS2) for characterizing land plants from soil

Molecular-based taxonomy, specifically DNA barcoding, has streamlined organism identification. For land plants, the recommended 2-locus barcode of rbcL and matK is not suitable for all groups, thus the second subunit of the nuclear internal transcribed spacer (ITS2) has received attention as a possible alternative. To date, evaluations of ITS2 have mostly been limited in scope to specific plant orders/families and single source material. Prior to using ITS2 to routinely characterize land plants present in environmental samples (i.e., DNA metabarcoding), a wet lab protocol optimized for bulk sample types is needed. To address this gap, in this study we determined the broad recoverability across land plants when using published ITS2 primer pairs, and subsequently optimized the PCR reaction constituents and cycling conditions for the best two performing primer pairs (ITS2F/ITSp4 and ITSp3/ITSu4). Using these conditions, both primer pairs were used to characterize land plants present in 17 diverse soils collected from across the US. The resulting PCR amplicons were prepared into libraries and pooled for sequencing on an Illumina (R) MiniSeq. Our existing bioinformatics workflow was used to process raw sequencing data and taxonomically assign unique ITS2 plant sequences by comparison to GenBank. Given strict quality criteria were imposed on sequences for inclusion in data analysis, only 43.6% and 7.5% of sequences from ITS2F/ITSp4 and ITSp3/ITSu4 respectively remained for taxonomic comparisons; similar to 7-11% of sequences originated from fungal co-amplification. The number of orders and families recovered did differ between primer pairs, with ITS2F/ITSp4 consistently outperforming ITSp3/ITSu4 by > 15%. Primer pair bias was observed in the recovery of certain taxonomic groups; ITS2F/ITSp4 preferentially recovered flowering plants and grasses, whereas ITSp3/ITSu4 recovered more moss taxa. To maximize data recovery and reduce potential bias, we advocate that studies using ITS2 to characterize land plants from environmental samples such as soil use a multiple primer pair approach.