Genome-wide association study in thoroughbred horses naturally infected with cyathostomins
Bibliographic record
Abstract
Cyathostomins are considered one of the most important parasites of horses. A group of horses within a herd can be responsible for eliminating the majority of parasite eggs. This phenotype might be explained by genetic factors. This study aimed to identify genomic regions associated with fecal egg count (FEC) and hematological parameters by performing a genomic-wide association study (GWAS) in Thoroughbred horses naturally infected with cyathostomins. Packed cell volume (PCV), differential leukocyte, and FEC were determined from 90 horses. All animals were genotyped using the Illumina Equine 70 K BeadChip panel containing 65,157 SNP markers. The five genomic windows that have explained the highest percentage of the additive genetic variance of a specific trait (top 5) were further explored to identify candidate genes. A total of 33, 21, 30, 21, and 19 genes were identified for FEC, PCV, eosinophils, neutrophils, and lymphocyte count, respectively. The top 5 marker regions explained 2.86, 2.56, 2.73, 2.33, and 2.37% of the additive genetic variation of FEC, PCV, eosinophils, neutrophils, and lymphocytes count, respectively. This is the first study correlating phenotypic horse health traits to GWAS analysis, which may be used for animal breeding activities, reducing losses due to parasite infections.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".