Genetic polymorphism in the POU1F1 gene in Kalahari Red and two Nigerian goat breeds and their relationship with litter size
Bibliographic record
Abstract
POU1F1 gene controls cell differentiation and animal growth by binding to target DNA promoter sequence, thereby auto-regulating its own expression and expression of growth hormone (GH), prolactin (PRL) and thyroid-stimulating hormone beta sub-unit (TSHβ) genes. Therefore, the exploration of caprine POU1F1 gene polymorphisms may be vital in the formulation of conservation and breed improvement strategies. In this study, POU1F1 gene was characterized for sequence polymorphisms in 366 individuals from two Nigerian goat breeds ((West African Dwarf (WAD) and Red Sokoto (RS)) and one South African goat breed (Kalahari (KR)). The effects of polymorphisms on litter size were investigated using linear mixed model. Two intronic mutations (g.306G>A and g.11236C>T) were identified. However, no significant association was found between the Single Nucleotide Polymorphisms (SNPs) and litter size in the three populations. The genetic distance based on POU1F1 investigated region revealed that the two Nigerian breeds and the South African breed were identical (pairwise genetic distance of 0.00). Phylogenetic tree constructed from the pairwise distance clustered the three breeds into a single clade with the two Nigerian goat breeds having a more recent common ancestor. Structural analysis of the POU1F1 protein confirmed that Pit-Oct-Unc transcription factors domain (POU) and Homeodomain (HOX) domains are conserved in mammals, with several overlapping sub-domains across the same region in all the three populations. We found a subdomain Subfamily of SANT domain or myb/SANT-like domain in Adf-1 (MADF) in goat, cattle, buffalo and camel that has not been reported in mammals
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 | 0.000 |
| 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 | 0.000 | 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".