Plants and other eukaryotes detected in herbivore faeces (collected 2018) from Iberá National Park, Argentina; inferred from ITS2 DNA metabarcoding data

  • Julia Carolina Mata (Creator)
  • Charles Davison (Creator)
  • Robert Buitenwerf (Creator)
  • Jens-Christian Svenning (Creator)
  • Ida Broman Nielsen (Creator)
  • Tobias Guldberg Frøslev (Creator)
  • Isabel Calabuig (Contributor)
  • Tobias Guldberg Frøslev (Contributor)

Dataset

Description

DNA metabarcoding was used to identify plant diet contents of the faeces in a diverse herbivore community in Argentina's Iberá National Park. The sequence data was generated by sequencing amplicons of the nuclear ribosomal internal transcribed spacer region 2 (ITS2) amplified with the primers S2F and ITS4. The results indicate that despite concerns, there is minimal resource competition between native, reintroduced, and non-native herbivores. Analysis of their diets through DNA metabarcoding of fecal samples revealed varied feeding strategies and significant dietary differentiation among species, indicating that these herbivores are partitioning resources effectively. This suggests that the coexistence of different herbivores might contribute positively to ecosystem restoration without significant competition for resources. PCR reactions contained 0,04 U/μl AmpliTaq Gold (Life Technologies), 0.6 μM of each primer, 0.8 mg/ml bovine serum albumin (BSA), 1X Gold Buffer, 2.5 mM of MgCl, 0.2 mM of each dNTPs and 1 μl DNA extract in a 25 μl total reaction volume. For the plant extracts 2 µl template was used. Thermocycling conditions for plant ITS were: 95°C 5 min; (95°C 30s; 55°C 30s; 72°C 1 min) x 35 cycles; 72°C 7 min, 4°C forever. Both forward and reverse primers were designed with 80 or 96 unique tags (MID/barcodes) of 6 bp at the 5’ end using a restrictive dual-indexing approach. No primer tag (forward or reverse) was used more than once in any sequencing library and no combination of forward and reverse primer was reused in the study. For each multiplex sequencing library, PCR products were pooled (5 µl of each product), for a total of 8 to 9 pools/libraries per marker with up to 80 PCR products per pool. Each pool contained extraction blanks and PCR negatives. Prior to pooling a random selection of 25-50 PCR products were checked for amplification success and measured with Qubit dsDNA HS (High Sensitivity) Assay Kit (Invitrogen). PCR pools were purified with MinElute PCR purification kit (QIAGEN GmbH) and the length of PCR amplicons was verified on Bioanalyzer High-Sensitivity Chip (Agilent Technologies, Inc., Santa Clara, California, USA). Each pool was built into a sequencing library. Libraries were built using the TruSeq DNA PCR-Free Library Preparation Kit (Illumina), replacing all the manufacturer suggested clean-up step with MinElute purification. A final library purification was carried out to remove adapter dimers with HighPrep™ PCR Clean-up System (Magbio). Sequencing was carried out on MiSeq (Illumina Inc., San Diego, CA, USA), at the Danish National High-throughput DNA Sequencing Centre, using two 300 bp paired-end run. The ITS2 was allocated one full run, and trnL and CO1 were pooled in equimolar concentrations on another run. The data mediated in this dataset includes all detections passing the bioinformatic quality filtering. The data used for the associated scientific publication was filtered to exclude the following types of detections: non-plant, low specificity (less than 97% query coverage and/or less than 98% sequence identity with best match in ncbi), low read-abundance detections (fewer than 25 reads or less than 0.5% relative read-abundance in a sample), more than 1000 km outside of their known range. Samples only containing on plant species were also removed. Thus the data here is more complete, contains unidentified sequences and potential errors and contaminants. [This dataset was processed using the GBIF eDNA converter tool.]
Date made available2024
PublisherEcoinformatics & Biodiversity, Department of Biology, Aarhus University
Geographical coverageArgentina
Geospatial polygon-28.689, -57.243, -28.583, -57.469

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