Association analysis of candidate SNPs in <i>TRPM1</i> with leopard complex spotting (<i>LP</i> ) and congenital stationary night blindness (CSNB) in horses
Bibliographic record
Abstract
Leopard complex spotting occurs in several breeds of horses and is caused by a single incompletely dominant autosomal locus, LP.1 In the Appaloosa breed, homozygosity for LP has been associated with congenital stationary night blindness (CSNB).2 Decreased expression of TRPM1 has been implicated as the cause for both LP and CSNB.3LP and CSNB were fine-mapped to a 173 -kb haplotype on ECA1 and Illumina sequencing identified six SNPs for further investigation (Table 1).4 In this study, we investigate these six SNPs for association with CSNB in the Appaloosa and for association with LP in several breeds of horses. DNA was isolated from blood or hair of unrelated horses from breeds segregating for LP: Appaloosa (N = 205), Knabstrupper (N = 66), Noriker (N = 112), American Miniature (N = 63), Pony of the America (N = 20), British Spotted Pony (N = 25), and Australian Spotted Pony (N = 10). DNA was also isolated from the Thoroughbred (N = 37) and American Quarter Horse (N = 3), which are breeds not segregating for LP. LP genotype and CSNB status were determined as previously described.3 Initially, all six SNPs were investigated by PCR amplification and sequencing DNA from 10 individuals (Table 1). Three of these SNPs did not show complete association with LP genotype in this panel and were excluded as the causative mutation and thus not investigated further. The other three SNPs showed complete association and were either genotyped by direct sequencing or by custom TaqMan genotyping assays in 531 additional individuals (Assay IDs AHS0Q19, AHRRSV1, and AHT9O8H, Applied Biosystems) (Table 1). All TaqMan assays were performed in 5 -μL reactions on a Mastercyler® ep realplex thermocycler (Eppendorf). ECA1 g.108281765T>C, ECA1 g.108288853C>T, and ECA1 g.108337089T>G genotypes were analysed for association with LP genotype and CSNB status by chi-squared analysis. All three SNPs were completely associated with LP (N = 513, X2 = 1026, P ≪ 0.0005) and CSNB (N = 28, X2 = 28, P ≪ 0.0005). It is possible that one of these SNPs is the causative mutation for LP and CSNB. However, none of these are located in exonic regions that have previously been characterized, and thus further investigation is warranted.4 It is also likely that these SNPs may simply be associated and are not causative. Nevertheless, any of these SNPs could be used as a DNA test for LP and CSNB until the causative mutation has been identified or confirmed. The authors thank all of the horse owners who provided samples. We thank Karla Brown, Scott Lawson, Elizabeth Kowalski and Janelle Nelson for their assistance in DNA extraction and Dominic Trillizio for his technical assistance. We acknowledge Eppendorf for use of equipment. This study was supported by the Heather Ryan and L. David Dube′ Veterinary Health and Research Fund and a Dana Faculty Development Grant from the University of Tampa. The authors have declared no potential conflicts.
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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 | 0.001 |
| 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) | 0.000 | 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".