Sequences, Annotation and Single Nucleotide Polymorphism of the Major Histocompatibility Complex in the Domestic Cat
Bibliographic record
Abstract
Two sequences of major histocompatibility complex (MHC) regions in the domestic cat, 2.976 and 0.362 Mbps, which were separated by an ancient chromosome break (55-80 MYA) and followed by a chromosomal inversion were annotated in detail. Gene annotation of this MHC was completed and identified 183 possible coding regions, 147 human homologues, possible functional genes and 36 pseudo/unidentified genes) by GENSCAN and BLASTN, BLASTP RepeatMasker programs. The first region spans 2.976 Mbp sequence, which encodes six classical class II antigens (three DRA and three DRB antigens) lacking the functional DP, DQ regions, nine antigen processing molecules (DOA/DOB, DMA/DMB, TAPASIN, and LMP2/LMP7,TAP1/TAP2), 52 class III genes, nineteen class I genes/gene fragments (FLAI-A to FLAI-S). Three class I genes (FLAI-H, I-K, I-E) may encode functional classical class I antigens based on deduced amino acid sequence and promoter structure. The second region spans 0.362 Mbp sequence encoding no class I genes and 18 cross-species conserved genes, excluding class I, II and their functionally related/associated genes, namely framework genes, including three olfactory receptor genes. One previously identified feline endogenous retrovirus, a baboon retrovirus derived sequence (ECE1) and two new endogenous retrovirus sequences, similar to brown bat endogenous retrovirus (FERVmlu1, FERVmlu2) were found within a 140 Kbp interval in the middle of class I region. MHC SNPs were examined based on comparisons of this BAC sequence and MHC homozygous 1.9x WGS sequences and found that 11,654 SNPs in 2.84 Mbp (0.00411 SNP per bp), which is 2.4 times higher rate than average heterozygous region in the WGS (0.0017 SNP per bp genome), and slightly higher than the SNP rate observed in human MHC (0.00337 SNP per bp).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".