High-throughput sequencing of the kelp <i>Alaria</i> (Phaeophyceae) reveals epi-endobiotic associations, including a likely phaeophycean parasite
Bibliographic record
Abstract
Whole genome sequencing datasets present the opportunity to not only study evolution in the target organism, but also the associated holobiont. The capacity to study epi-endobiotic kelp associations is improving substantially with the increased availability of high-throughput sequencing datasets. The goal of this study was to determine if shotgun sequencing libraries could be used to document epi- and endophyte/faunal species colonizing Alaria kelp sporophytes from Kamchatka (Russia), the Bay of Fundy (Atlantic Canada) and Nuuk (Greenland). Mitochondrial coxI and plastid rbcL reads were extracted and assembled from six Alaria whole genome sequencing datasets. In total, contigs representing 11 epi-endobiotic species were assembled, of which Chordariacean diversity dominated. Given the presence of a newly discovered phaeophycean coxI sequence lacking an rbcL counterpart, we secondarily tested our hypothesis that the coxI sequence belonged to a phaeophycean parasite. The entire read dataset was assembled for the Alaria specimen hosting the putative parasite, the mitochondrial genome was retrieved, and plastid scaffolds were annotated and screened for phylogenetic placement matching the coxI sequence. The mitochondrial genome of the candidate parasite displayed numerous atypical features, including duplicated genes and rearrangements, and clear signs of relaxed selection, in line with the notion this organism may have a deviant lifestyle. The plastid genome was recovered as several fragments and lacked genes for photosystem and cytochrome complexes and chlorophyll biosynthesis, confirming our hypothesis that the unknown phaeophycean represented a parasitic species. Furthermore, classification to order remained unclear for the phaeophycean parasite, suggesting this species could represent a newly discovered higher-level lineage. Our study showcases the utility of whole-genome sequencing datasets in revealing surprising aspects of the eukaryotic diversity inhabiting kelp holobionts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".