The highly repetitive genome of Myxobolus sp., a myxozoan parasite of fathead minnows
Bibliographic record
Abstract
Background: The Myxozoa is a group of at least 2,400 endoparasites within the phylum Cnidaria. All myxozoans have greatly reduced in size and morphology compared to free-living members of the phylum. They are best known for causing disease in economically important fish across the world; for example, Myxobolus cerebralis causes Whirling Disease, which can kill 90% of infected juvenile salmonid fish. In 2017, a potentially new myxozoan species was identified in Alberta. Myxobolus sp. causes distinct lesions in fathead minnows, which are ultimately fatal. Here, we sequenced, assembled and analyzed the genome of Myxobolus sp. to understand how the parasite interacts with its fish host and identify potential strategies to counter this emerging threat. Results: At 185 Mb, the Myxobolus sp. genome is the largest myxozoan genome sequenced so far. This large genome size is, in part, due to the high repetitive content; 68% of the genome was interspersed repeats, with the MULE-MuDR transposon covering 18% of the Myxobolus sp. genome. Similar to myxozoan genomes, the Myxobolus sp. genome has lost many genes well conserved in other eukaryotes. However, we also identified multiple expansions in gene families (serine proteases, hexokinases, and FLYWCH-domain containing proteins) which suggests their functional importance in the parasite. The mitochondrial genome of Myxobolus sp. encodes only five of the thirteen protein-coding genes typically found in animals. We found that the mitochondrial gene atp6 was transferred to the nucleus and acquired a mitochondria-targeting signal in Myxobolus sp. Conclusions: Our study provides valuable insights into myxozoan biology and identify promising avenues for future research. We also propose that M. rasmusseni is promising myxozoan model to explore host-parasite interactions in these parasites.
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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 | 0.000 | 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".