Data from: DNA metabarcoding improves the taxonomic resolution of visually determined diet composition of beaked redfish (Sebastes sp.)
Data files
Dec 05, 2022 version files 121.31 KB
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Brown-Vuillemin_DNA_metabarcoding_SCA_Redfish.xlsx
118.80 KB
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README.md
2.51 KB
Jun 04, 2024 version files 191.90 KB
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Brown-Vuillemin_DNA_metabarcoding_SCA_Redfish.xlsx
188.97 KB
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README.md
2.93 KB
Jun 04, 2024 version files 191.90 KB
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Brown-Vuillemin_DNA_metabarcoding_SCA_Redfish.xlsx
188.97 KB
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README.md
2.93 KB
Abstract
Beaked redfishes (Sebastes fasciatus and Sebastes mentella) of the northwest Atlantic have recently reached record abundance levels in the estuary and the northern Gulf of St. Lawrence, dominated by Sebastes mentella. Knowledge of their diet composition is essential to understand the trophic role that these groundfish play in the ecosystem. The objective of the present study was to compare the performance of visual examination and DNA metabarcoding of stomach contents of the same individual redfish caught in the lower Estuary and northern Gulf of St. Lawrence. Using a universal metazoan mitochondrial cytochrome c oxidase subunit I (COI) marker, we identified a total of 24 taxonomic groups, composed of 22 species and two genera in the content of 185 stomachs with DNA metabarcoding. We compared these results to the 25 prey types, eight identified at the genus and nine at the species level, obtained with visual stomach content analysis (SCA). While both techniques revealed a similar diet composition, our results showed that the SCA and DNA metabarcoding perform differently for particular prey categories, both in terms of detectability and taxonomic resolution, as well as in the estimated relative importance of weight and occurrence in the diet. The use of DNA metabarcoding along with SCA validates and improves the taxonomic resolution of visually determined prey, which supports the concept that both techniques provide useful complementary information on the diet of these redfish species.
Description of the Data
Redfish diet composition data were analysed within three defined size classes: small (< 20 cm, n=95), medium (20–30 cm, n=53), and large redfish (≥ 30 cm, n=37), for both the visual and molecular methods.
Excel tab 1 (Sequence Dropout)
Sequencing result information: Total reads produced by the MiSeq sequencer and total reads after each step of Barque. Two negative controls (Control_blank_1 and Control_blank_2) were treated and extracted as regular samples and sequenced to check for DNA contamination. The first blank control corresponds to samples whose boxes are in gray and the second white control corresponds to samples whose boxes are not highlighted.
Excel tab 2 (SequenceRead_before_processing)
Raw metabarcoding results. We used Barque (https://github.com/enormandeau/barque to examine the biodiversity of stomach contents at the species level. All the animal bins (barcode index number) were downloaded from the BOLD database on 2023-09-12 and all the COI fragments corresponding to the used primers were incorporated into the database used by Barque v1.8.5 (https://boldsystems.org/index.php/Public_BarcodeIndexNumber_Home. We annotated each unique read of each sample to the most similar species of the database if the sequences had at least 98% similarity. In cases of ties, referred to as multiple hits, when more than one species from the database had the same distance from the queried sequence, all the tied annotations were reported. Barque then produced a table of prey taxa counts (including the multiple hits) for each sample. Sample Read counts from negative controls have been subtracted from the results of prey taxa for each species. The first blank control corresponds to samples whose boxes are in gray and the second white control corresponds to samples whose boxes are not highlighted.
Excel tab 3 (SequenceRead_after_processing)
Reads that had equal similarity scores for more than one species were assigned to a higher taxonomic level since it was impossible to discriminate species with certainty (e.g., Ammodytes sp. for the multiple hits referencing Ammodytes americanus and Ammodytes dubius). Read counts from negative controls have been subtracted from the results of prey taxa for each species.
Excel tab 4 (SCA_MassPrey_Redfish)
Mass of prey is in grams. Redfish stomachs were thawed for visual analysis at the Maurice-Lamontagne Institute (Mont-Joli, Canada) and each prey taxon found in the stomach contents was weighed to the nearest grams and identified to the lowest taxonomic level possible under a dissecting microscope using keys and identification guides.
Redfish stomachs were thawed for visual analysis at the Maurice-Lamontagne Institute (Mont-Joli, Canada) and each prey taxon found in the stomach contents was weighed and identified to the lowest taxonomic level possible under a dissecting microscope using keys and identification guides. For metabarcoding, we annotated each unique read of each sample to the most similar species of the database if the sequences had at least 98% similarity. In cases of ties, referred to as multiple hits, when more than one species from the database had the same distance from the queried sequence, all the tied annotations were reported. Barque then produced a table of prey taxa counts (including the multiple hits) for each sample.