Genetic Testing for TMEM154 Mutations Associated with Lentivirus Susceptibility in Sheep
Bibliographic record
Abstract
In sheep, small ruminant lentiviruses cause an incurable, progressive, lymphoproliferative disease that affects millions of animals worldwide. Known as ovine progressive pneumonia virus (OPPV) in the U.S., and Visna/Maedi virus (VMV) elsewhere, these viruses reduce an animal's health, productivity, and lifespan. Genetic variation in the ovine transmembrane protein 154 gene (TMEM154) has been previously associated with OPPV infection in U.S. sheep. Sheep with the ancestral TMEM154 haplotype encoding glutamate (E) at position 35, and either form of an N70I variant, were highly-susceptible compared to sheep homozygous for the K35 missense mutation. Our current overall aim was to characterize TMEM154 in sheep from around the world to develop an efficient genetic test for reduced susceptibility. The average frequency of TMEM154 E35 among 74 breeds was 0.51 and indicated that highly-susceptible alleles were present in most breeds around the world. Analysis of whole genome sequences from an international panel of 75 sheep revealed more than 1,300 previously unreported polymorphisms in a 62 kb region containing TMEM154 and confirmed that the most susceptible haplotypes were distributed worldwide. Novel missense mutations were discovered in the signal peptide (A13V) and the extracellular domains (E31Q, I74F, and I102T) of TMEM154. A matrix-assisted laser desorption/ionization-time-of flight mass spectrometry (MALDI-TOF MS) assay was developed to detect these and six previously reported missense and two deletion mutations in TMEM154. In blinded trials, the call rate for the eight most common coding polymorphisms was 99.4% for 499 sheep tested and 96.0% of the animals were assigned paired TMEM154 haplotypes (i.e., diplotypes). The widespread distribution of highly-susceptible TMEM154 alleles suggests that genetic testing and selection may improve the health and productivity of infected flocks.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".