Development and field application of metabarcoding-adapted mt-ND4 markers shows substantial gene flow and varying local pressures on Haemonchus contortus and Teladorsagia circumcincta populations in the UK
Bibliographic record
Abstract
Gastrointestinal nematodes impose a significant burden on livestock production and public health by reducing animal productivity and increasing the environmental impact of farming. Modern sequencing techniques enable the efficient exploration of genetic diversity, necessary to inform effective parasite control. In this study, we developed and validated new mitochondrial ND4-based markers adapted for high-throughput sequencing. This enabled detailed analysis of genetic diversity in two important nematode species, Haemonchus contortus and Teladorsagia circumcincta. Laboratory validations confirmed that the assay reliably detected as little as 1% of larvae in mixed samples and accurately identified strain variants. Field application on 30 sheep farms across England and Scotland revealed 60 unique genetic variants in H. contortus and 35 in T. circumcincta. A single variant dominated the sequence reads in both species, particularly T. circumcincta. Regional comparisons showed that H. contortus exhibited fewer yet persistent variants in Scotland than in England; while phylogenetic analyses indicated a common origin and significant gene flow between regions. In contrast, T. circumcincta, despite being more prevalent across all farms, displayed lower overall diversity with a shared dominant variant; evidence of dual origins and marked regional differences in evolutionary pressures. Comparisons with publicly available global sequence data revealed distinct clustering of H. contortus isolates, separating Asian sequences from those in the United Kingdom and Australia. T. circumcincta isolates showed no apparent geographic clustering. These findings demonstrate the potential of high-throughput mitochondrial marker analysis to unravel complex parasite population dynamics, and to inform sustainable management strategies in the face of challenges such as drug resistance and climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".