Supplementary material 1 from: Zafeiropoulos H, Gargan L, Hintikka S, Pavloudi C, Carlsson J (2021) The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data. Metabarcoding and Metagenomics 5: e69657. https://doi.org/10.3897/mbmg.5.69657 Article Swipe
Haris Zafeiropoulos
,
Laura Gargan
,
Sanni Hintikka
,
Christina Pavloudi
,
Jens Carlsson
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3897/mbmg.5.69657.suppl1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3897/mbmg.5.69657.suppl1
The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.
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Supplementary material 1 from: Zafeiropoulos H, Gargan L, Hintikka S, Pavloudi C, Carlsson J (2021) The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data. Metabarcoding and Metagenomics 5: e69657. https://doi.org/10.3897/mbmg.5.69657Work title
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2021Year of publication
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2021-11-11Full publication date if available
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Haris Zafeiropoulos, Laura Gargan, Sanni Hintikka, Christina Pavloudi, Jens CarlssonList of authors in order
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| abstract_inverted_index.variants | 36 |
| abstract_inverted_index.amplified | 218 |
| abstract_inverted_index.analysed. | 200 |
| abstract_inverted_index.assessing | 20 |
| abstract_inverted_index.available | 252 |
| abstract_inverted_index.bacterial | 125 |
| abstract_inverted_index.consensus | 80, 93 |
| abstract_inverted_index.database, | 110 |
| abstract_inverted_index.databases | 234 |
| abstract_inverted_index.developed | 60 |
| abstract_inverted_index.different | 192 |
| abstract_inverted_index.graphical | 176 |
| abstract_inverted_index.reference | 50, 72, 108, 119, 142, 233 |
| abstract_inverted_index.retrieved | 38, 104, 146 |
| abstract_inverted_index.sequence. | 51 |
| abstract_inverted_index.sequences | 81, 94, 103, 122, 143, 165, 227 |
| abstract_inverted_index.taxonomic | 30, 46 |
| abstract_inverted_index.Similarly, | 121 |
| abstract_inverted_index.assignment | 47, 239 |
| abstract_inverted_index.cytochrome | 2 |
| abstract_inverted_index.databases. | 153 |
| abstract_inverted_index.diversity. | 22 |
| abstract_inverted_index.especially | 18 |
| abstract_inverted_index.non-target | 208 |
| abstract_inverted_index.organisms, | 210 |
| abstract_inverted_index.proportion | 206 |
| abstract_inverted_index.sequences, | 57 |
| abstract_inverted_index.sequences. | 120 |
| abstract_inverted_index.constructed | 100 |
| abstract_inverted_index.demonstrate | 202 |
| abstract_inverted_index.eukaryotes, | 92 |
| abstract_inverted_index.investigate | 55, 162 |
| abstract_inverted_index.operational | 29 |
| abstract_inverted_index.prokaryotic | 209, 225 |
| abstract_inverted_index.represented | 112 |
| abstract_inverted_index.COI-oriented | 73 |
| abstract_inverted_index.assignments. | 181 |
| abstract_inverted_index.environments | 194 |
| abstract_inverted_index.iNvestigator | 64 |
| abstract_inverted_index.phylogenetic | 74, 159, 180 |
| abstract_inverted_index.environmental | 13, 186 |
| abstract_inverted_index.metabarcoding | 16, 189 |
| abstract_inverted_index.mitochondrial | 1 |
| abstract_inverted_index.pre-processed | 164 |
| abstract_inverted_index.respectively) | 144 |
| abstract_inverted_index.https://github.com/hariszaf/darn | 256 |
| abstract_inverted_index.https://hub.docker.com/r/hariszaf/darn. | 263 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.8100000023841858 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile |