DOI: 10.5061/dryad.bg79cnpcf
title: Accumulation of airborne, eukaryotic environmental DNA contamination: Raw sequencing data and demultiplexing info

description: Environmental DNA (eDNA) metabarcoding is increasingly being implemented
 as a non-invasive and efficient approach for biodiversity research and
 monitoring across ecosystems. However, accurate detection of species with
 eDNA requires robust experimental designs, as eDNA analysis carries a risk
 of contamination at every step of the fieldwork and laboratory process.
 Several studies focus on rigorous laboratory procedures and processing of
 sequencing data, but surprisingly little research investigates the process
 of background input of DNA in the field. For example, airborne DNA from
 localities outside the study area could potentially contaminate eDNA
 samples. Here, we use an experimental setup and eDNA metabarcoding to
 study the diversity and accumulation of airborne eukaryotic eDNA on
 exposed surfaces in the field. At two different natural locations, a
 coastal marine site, and a terrestrial grassland site, we placed open
 containers each filled with 0.5 litres of water, which was then sampled at
 eight successive time points after exposure to the surroundings. We found
 an accumulation of detected species richness in the samples, which reached
 its maximum at the end of the experiment, 24 hours after exposure. This
 result was consistent across both sites and across two markers (COI for
 eukaryotes and 12S for vertebrates). While many of the detected species
 were contaminants commonly found in eDNA studies, we also detected several
 other eukaryotic taxa. Most notable were metazoan species such as birds,
 fish and insects, likely originating from airborne transport of eDNA. We
 also found that increasing the number of PCR cycles tended to have a
 positive impact on richness for the unfiltered reads but a negative impact
 on the richness after bioinformatic filtering. Our results add to the
 sparse evidence that metazoan eDNA can be transported by air, which has
 wide implications for eDNA research and calls for increased implementation
 of field control samples.
description: This dataset represents environmental DNA sequencing data from
 Mols Bjerge National Park (Denmark) and Aarhus (Denmark) collected on the
 23rd-24th of August 2019 and the 23rd-24th of September 2019 respectively.
 Samples were collected at eight different timepoints over a 24-hour
 period, starting from 11 AM (see connected publication for additional
 details). DNA has been amplified with two different
 primer sets, namely the Tele02 (for 12S fish data) and the
 Leeray XT (for CO1 eukaryote data) primers. Tele02 primers consist of the
 forward primer Tele02_F
 (5’-AAACTCGTGCCAGCCACC-3’) and the reverse primer Tele02_R
 (5’-GGGTATCTAATCCCAGTTTG-3’), targeting a 163-185 bp fragment
 of 12S. Eukaryote amplification was done with forward primer mlCOIintF-XT (5’-GGWACWRGWTGRACWNTNTAYCCYCC-3´)
 and reverse primer jgHCO2198
 (5’-TAIACYTCIGGRTGICCRAARAAYCA-3’), targeting ca. 350 bp of
 CO1. The libraries have been sequenced using paired end NovaSeq 6000
 sequencing (150 BP PE for 12S and 250 BP PE for CO1).
 Libraries are named M1-M4 and M11-M14 for the CO1 data and M5-M10
 for the vertebrate data.
description: We suggest you put the files in 14 separate folders in order to
 demultiplex. The files should be placed accordingly:
 <strong>Folder 1: Aarhus CO1 PCR replicate
 one</strong> M1_MD5.txt (to check
 sums)
 M1_FKDL202559049-1a_HJ77HDRXX_L1_1.fq.gz
 M1_FKDL202559049-1a_HJ77HDRXX_L1_2.fq.gz
 M1_tags.list 
 <strong>Folder 2: Aarhus CO1 PCR replicate
 two</strong> M2_MD5.txt (to check
 sums)
 M2_FKDL202559050-1a_HJ77HDRXX_L1_1.fq.gz
 M2_FKDL202559050-1a_HJ77HDRXX_L1_2.fq.gz
 M2_tags.list 
 <strong>Folder 3: Aarhus Co1 PCR replicate
 three</strong> M3_MD5.txt (to check
 sums)
 M3_FKDL202559051-1a_HJ77HDRXX_L1_1.fq.gz
 M3_FKDL202559051-1a_HJ77HDRXX_L1_2.fq.gz
 M3_tags.list 
 <strong>Folder 4: Aarhus CO1 PCR replicate
 four</strong> M4_MD5.txt (to check
 sums)
 M4_FKDL202559052-1a_HJ77HDRXX_L1_1.fq.gz
 M4_FKDL202559052-1a_HJ77HDRXX_L1_2.fq.gz
 M4_tags.list 
 <strong>Folder 5: Vertebrate 40 cycles PCR replicate
 one</strong> M5_MD5.txt (to check
 sums)
 M5_FKDL202564481-1a_H35WWDSXY_L1_1.fq.gz
 M5_FKDL202564481-1a_H35WWDSXY_L1_2.fq.gz
 M5_tags.list 
 <strong>Folder 6: Vertebrate 40 cycles PCR
 replicate two</strong> M6_MD5.txt (to
 check sums)
 M6_FKDL202564442-1a_H35WWDSXY_L1_1.fq.gz
 M6_FKDL202564442-1a_H35WWDSXY_L1_2.fq.gz
 M6_tags.list 
 <strong>Folder 7: Vertebrate 45 cycles PCR replicate
 one</strong> M7_MD5.txt (to check
 sums)
 M7_FKDL202564482-1a_H35LKDSXY_L4_1.fq.gz
 M7_FKDL202564482-1a_H35LKDSXY_L4_2.fq.gz
 M7_tags.list 
 <strong>Folder 8: Vertebrate 45 cycles PCR replicate
 two</strong> M8_MD5.txt (to check
 sums)
 M8_FKDL202564444-1a_H35WWDSXY_L1_1.fq.gz
 M8_FKDL202564444-1a_H35WWDSXY_L1_2.fq.gz
 M8_tags.list 
 <strong>Folder 9: Vertebrate 50 cycles PCR replicate
 one</strong> M9_MD5.txt (to check
 sums)
 M9_FKDL202564445-1a_H35WWDSXY_L1_1.fq.gz
 M9_FKDL202564445-1a_H35WWDSXY_L1_2.fq.gz
 M9_tags.list 
 <strong>Folder 10: Vertebrate 50 cycles PCR replicate
 two</strong> M10_MD5.txt (to check
 sums)
 M10_FKDL202564483-1a_H35WWDSXY_L1_1.fq.gz
 M10_FKDL202564483-1a_H35WWDSXY_L1_2.fq.gz
 M10_tags.list 
 <strong>Folder 11: Mols CO1 PCR replicate
 one</strong> M11_MD5.txt (to check
 sums)
 M11_FKDL202564451-1a_HJVKFDRXX_L1_1.fq.gz
 M11_FKDL202564451-1a_HJVKFDRXX_L1_2.fq.gz
 M11_tags.list 
 <strong>Folder 12: Mols CO1 PCR replicate
 two</strong> M12_MD5.txt (to check
 sums)
 M12_FKDL202564452-1a_HJVKYDRXX_L1_1.fq.gz
 M12_FKDL202564452-1a_HJVKYDRXX_L1_2.fq.gz
 M12_tags.list 
 <strong>Folder 13: Mols CO1 PCR replicate
 three</strong> M13_MD5.txt (to check
 sums)
 M13_FKDL202564453-1a_HJVKYDRXX_L1_1.fq.gz
 M13_FKDL202564453-1a_HJVKYDRXX_L1_2.fq.gz
 M13_tags.list 
 <strong>Folder 14: Mols CO1 PCR replicate
 four</strong> M14_MD5.txt (to check
 sums)
 M14_FKDL202564454-1a_HJVKYDRXX_L1_1.fq.gz
 M14_FKDL202564454-1a_HJVKYDRXX_L1_2.fq.gz
 M14_tags.list Following this
 folder structure, each folder will now contain two sequence data files
 (paired end sequencing), a barcode/tag file and an MD5 file for checking
 sums. If you would like to demultiplex this data, all
 tag information needed is available in the ”list” files. Each tag file
 contains a number of samples, which are explained below:
 P2.X.Y_Z: Pooled samples (see associated article). P2 refers to
 the project number. X denotes the field replicate number, Y denotes the
 time the sample was taken (Y=C are control samples taken in the lab) and Z
 refers to the sequencing library number. P2.POS(X):
 Field possitive taken at the Mols site (See associated publication for
 explanation) Pos_X: Positive PCR control using
 whaleshark DNA. One positive control was run with every PCR
 setup. CNE: Extraction blanks (one was included for
 each round of extraction). NTC: PCR blanks. Four PCR
 blanks were run in each PCR setup.  
 The ”list” files include the sample name followed by the PCR
 replicate number. The two following columns represent the tags used for
 each sample (both forward and reverse primer were tagged). Tags are
 consistent across PCR replicates. After demultiplexing,
 you should be able to do as you please with the data.
 If you want to follow the exact filtering and data analysis done
 in our study, we refer to the manuscript for further details after the
 demultiplex step. If you have any questions, feel free to send an email to
 Martin Johannesen Klepke with any questions you may have.