Whole-genome sequencing of Schistosoma mansoni reveals extensive diversity with limited selection despite mass drug administration
Bibliographic record
Abstract
Control and elimination of the parasitic disease schistosomiasis relies on mass administration of praziquantel. Whilst these programmes reduce infection prevalence and intensity, their impact on parasite transmission and evolution is poorly understood. Here we examine the genomic impact of repeated mass drug administration on Schistosoma mansoni populations with documented reduced praziquantel efficacy. We sequenced whole-genomes of 198 S. mansoni larvae from 34 Ugandan children from regions with contrasting praziquantel exposure. Parasites infecting children from Lake Victoria, a transmission hotspot, form a diverse panmictic population. A single round of treatment did not reduce this diversity with no apparent population contraction caused by long-term praziquantel use. We find evidence of positive selection acting on members of gene families previously implicated in praziquantel action, but detect no high frequency functionally impactful variants. As efforts to eliminate schistosomiasis intensify, our study provides a foundation for genomic surveillance of this major human parasite.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".