Polymorphism, Allelic and Genotypic Frequencies of κ-Casein and β-LG genes in Egyptian Buffaloes
Bibliographic record
Abstract
With a view to detecting the genotypes of both κ-CN and β-LG genes in native populations of Egyptian buffalo using PCR-RFLP technique, 80 randomly, individuals were selected from five geographical locations of some Egyptian provinces. Also, to estimate the population genetic parameters such as, allelic and genotypic frequencies, heterozygosity, and inbreeding coefficient (FIS) of these studied genes. For genotyping, 453 bp PCR product of κ-CN was digested with AcuI and HpyCH4IV (Isoschizomer for MaeII) restriction enzymes while the 247 bp PCR product of β-LG was digested with HaeIII restriction enzyme. PCR-RFLP results discovered polymorphism at the level of κ-CN gene in all studied Egyptian buffaloes with two distinct alleles “A” and “B”. PCR-RFLP analysis for κ-CN gene using both restriction enzymes successfully detected that polymorphic status of the studied populations. We recommended using AcuI enzyme which was more capable for differentiating between homozygous (17%) and heterozygous (83%) individuals than HpyCH4IV enzyme which defined only 4% of homozygous individuals and the remaining was heterozygous (96%) individuals. Existence of heterozygosity excess in all studied populations referred to higher degree of genetic variability between individuals within these populations. On contrary, results of PCR-RFLP at the level of β-LG gene revealed a monomorphic pattern of Egyptian buffaloes and genotyped as “AA” animals which signified that PCR-RFLP assay with HaeIII enzyme for β-LG gene failed to discover any evidence of polymorphism in Egyptian buffalo under the circumstances of this study or all studied animals possess only one allele.
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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 | 0.000 |
| 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".