DOI: 10.5061/dryad.xgxd254j2
title: Data from: Metabarcoding of soil environmental DNA replicates plant community variation but not specificity

description: While metabarcoding of plant DNA from their environment is an exciting
 method that can supplement inventorying of live plant species, the
 accuracy and specificity has yet to be fully assessed over complex
 continuous landscapes. In this work, we evaluate plant community profiles
 produced via metabarcoding of soil by comparing them to a morphological
 survey. We assessed plant communities by metabarcoding of soil DNA in 130
 sites along ecological gradients (nutrients, succession, moisture) in
 Denmark using chloroplast trnL region (10-143 bp) primer set and
 compared the resulting communities to communities produced with a longer
 nuclear ITS2 region (~216 bp) and a morphological survey. We found that
 the community variation observed within the morphological survey was well
 represented by molecular surveys, with significant correlation with both
 community composition and richness using both primer sets. While the
 majority of the ITS2 sequences could be assigned to species (over 80%), we
 had less success with the trnL sequences (70%), which was only
 possible after restricting the reference database to local species. We
 conclude that the community profiles produced by metabarcoding can be
 highly effective in performing large-scale macroecological studies.
 However, the discovery rates and taxonomic assignments produced via
 metabarcoding remained inferior to morphological surveys, but manual
 curation of databases improves the specificity of
 assignments made by the trnL primers, and improves
 the accuracy of the assignments made with the ITS2
 primers. Finally, we suggest that a greater percentage of named diversity
 would be recovered by increasing soil sampling with the use of additional
 universal primer sets.
description: Sampling was performed across 130 sites (40 m x 40 m) in Denmark.
 For this study we generated new sequence data for trnL from existing DNA
 extracts, and used already published sequence data for ITS2 (from the same
 DNA extracts) and combined with published survey data for plants from the
 same study sites. Detailed materials and methods can be read in detail in
 the associated publication and in Frøslev et al (2017) and Brunbjerg et al
 (2019). This repository holds the following
 material: TRNL SEQUENCE DATA:<br> A)
 trnl_fastq.tar.gz – Sequence data. Raw tRNL sequencing data from MiSeq. 6
 sequencing libraries (R1 + R2), with multiplexed primers, approximately
 67-71 samples (PCR products) per library.<br> B) trnl_taglists.zip –
 PCR tagging. One file per library with tag pairs used. Each tag is a 6 bp
 oligo preceding the primer.<br> C) trnl_replicate_Info.csv – PCR
 replicates. One file with PCR numbers (S001 and up) and corresponding
 sample numbers (like SN081). Each of the 130 samples were amplified in
 three PCR replicates ITS2 SEQUENCE DATA:<br> D)
 Raw its2 sequence data can be downloaded here:
 https://doi.org/10.5061/dryad.n9077<br> E) trnl_taglists.zip – PCR
 tagging. One file per library with tag pairs used. Each tag is a 6 bp
 oligo preceding the primer.<br> F) Its2_replicate_Info.csv - PCR
 replicates. One file with PCR numbers (S001 and up) and corresponding
 sample numbers (like SN081). Each of the 130 samples were amplified in
 three PCR replicates Processed data:<br> G)
 community_tables.zip - Taxonomically annotated tables with used for the
 analyses. 7 tables in rds format. (read in r with function readRDS). For
 tRNL and ITS2 there are tables annotated with local, regional and global
 reference databases, respectively. Each table contains: read counts for
 each OTU in each of the 130 sites; OTU_ID = a sha1 hash of the sequence;
 sequence = DNA sequence of the OTU; seq_len = length of the sequence;
 pident = match with reference sequence; and taxonomic affiliation at 6
 levels, and a field indicating if the annotation is taxonomically
 redundant. And a table with the inventory (survey) data.
 References: Frøslev, T.G., R. Kjøller, H.H.
 Bruun, R. Ejrnæs, A.K. Brunbjerg, C. Pietroni and A.J. Hansen. 2017.
 Algorithm for post-clustering curation of DNA amplicon data yields
 reliable biodiversity estimates. Nature communications 8(1):
 1–11. Brunbjerg, A. K., H.H. Bruun, K. Brøndum, A.T.
 Classen, L. Dalby, K. Fog, T.G. Frøslev, I. Goldberg, et al. 2019. A
 systematic survey of regional multi-taxon biodiversity: evaluating
 strategies and coverage. BMC ecology, 19(1): 1–15.