DOI: 10.5281/zenodo.6400497
title: Using soil eDNA for plant diversity assessments

description: This data sets corresponds to a publication in Methods in Ecology and Evolution titled: <strong>Plant biodiversity assessment through soil eDNA reflects temporal and local diversity</strong> In August 2018, a single soil eDNA sample was collected from the centre of each permanent plot (1m2) in the Solhomfjell Forest Reserve stablished by the Sommerfeltia program. The soil eDNA samples were stored in individual plastic bags for transportation to the lab and stored at -20 °C prior to freeze-drying under vacuum. Each soil eDNA sample was separately homogenized with ceramic beads and one gram was used for eDNA extraction. The latter was done in five rounds of two steps: (1) CTAB/chloroform pre-treatment to increase the separation of the organic phase and (2) aqueous phase and using the E.Z.N.A. soil DNA kit following the manufacturer’s protocol (Omega Bio-tek, Norcross, Georgia, USA). The chloroplast marker trnL (UAA) intron P6 loop was chosen as its short sequence can yield amplification of old DNA material degraded in eDNA samples. This marker was amplified for each sample with the g and h primers by PCR, using three technical replicates (Taberlet et al. 2007; 5'-GGGCAATCCTGAGCCAA-3', 5'-CCATTGAGTCTCTGCACCTATC-3'). Forward and reverse primers were tagged with a unique 12 bp oligonucleotide on the 5’ end (Fadrosh et al. 2014). Unique combinations of tagged primers were set up in panels for each PCR reaction for a total of 309 samples (100 samples with 3 PCR replicates each, 5 extractions blanks and 4 PCR negatives). The PCR negatives had no DNA template and were placed on the 96th well position in each panel. Composition of PCR reactions, final volumes and number of cycles can be found in Supporting Information Data S1. The PCR products were run on a 2% agarose gel, and the amplicon concentrations were measured via band intensity using ImageLab software (Bio-Rad, California, USA). The lowest concentration (μM) available for all PCR products and its relative volume was identified and the relative concentrations of the PCR products were adjusted to this same concentration. Amplicons were pooled in one library using a Biomek 4000 automated liquid handler (Beckman Coulter Life Sciences, Indianapolis, Indiana, USA). The library was cleaned using AMPure XP reagent beads (Beckman Coulter Life Sciences, Indianapolis, Indiana, USA). The length for all amplicons in the library was determined using a Fragment Analyzer (Agilent Technologies, Santa Clara, California, USA). The library was sequenced on an Illumina MiSeq platform with 150 bp paired-end reads (Illumina Inc., San Diego, California, USA). Sequence data was analyzed and curated using OBITools 2 (Boyer et al. 2016) following the wolf tutorial with adaptations for demultiplexing dual indexes from QIIME2 (Caporaso et al. 2010). Sequences were retained with both indexes for dereplication for further analysis. Similar sequences were clustered with obiclean (Boyer et al. 2016) only when the read count of the less abundant sequence was below 5% of the most abundant sequence. To reduce multiple identifications of the same sequence, taxonomic assignment of dereplicated and denoised sequences was done by matching to three reference sequences databases containing: (i) only taxa registered in the local Solholmfjell reference library; (ii) the complete arctic boreal database for vascular plants and bryophytes (Sønstebø et al.2010; Willerslev et al. 2014; Soininen et al. 2015); and (iii) taxa available in the EMBL database (downloaded on 7/02/2020) filtered to sequences with trnL (UUA) intron g-h primers using ecoPCR tool from OBITools (Boyer et al. 2016). Resulting identifications from the three databases were merged by sequence and duplicates were eliminated giving priority to reference databases (i), (ii), and (iii) in that order. To minimize erroneous taxonomic assignments, only taxa with a 100% match to a reference sequence were retained. We observed that below this threshold, sequences remained without a taxonomic rank assigned. Further, assigned taxa names were changed to the lowest taxonomic rank possible with trnL (UUA) intron and thus are identical to those registered in vegetation surveys. When different sequences were identified with identical taxa names, a unique entry was retained and the read counts within plots and replicates were summed. Read counts were averaged across all samples and negative controls (extraction + PCR). All analyses are plot-based, and coded using R v 1.4.17 (R Core Team, 2019) and with packages listed in the code. Separate analyses are made for vascular plants and bryophytes, and/or for spruce and pine data subsets, or combinations thereof, when relevant.