Genome-wide analysis of the Siboney de Cuba cattle breed: genetic characterization and framing with cattle breeds worldwide
Bibliographic record
Abstract
Crossbreeding has been employed to address environmental challenges. One successful example is the Siboney de Cuba, developed in response to economic challenges in the 1960s. The aim of this study was to perform the first genomic characterization of the Siboney de Cuba breed, a successful hybrid breed resulting from the crossbreeding of Cuban Zebu and Holstein, using SNP array chip. For this purpose, 48 Siboney de Cuba cattle samples were collected and genotyped with the GGP Bovine 100k BeadChip, resulting in 83,314 SNPs after quality control. The genetic diversity was investigated using observed and expected heterozygosity, inbreeding coefficient, and minor allele frequency. Runs of homozygosity (ROH) analysis provided insights into molecular inbreeding. Additionally, the study investigated copy number variants (CNV), identifying CNV regions and their distribution. The genetic relationship and population structure of Siboney de Cuba were analyzed in comparison with worldwide cattle populations using ADMIXTURE, multidimensional scaling, and phylogenetic analysis. Six ROH islands containing a total of 50 genes were discovered, some of which were uncharacterized loci. Furthermore, 792 CNV with higher occurrence of genetic material loss were observed. The overall genome coverage for CNV regions was 2.16%. The Siboney de Cuba exhibited a good level of genetic variability with high heterozygosity and low inbreeding when compared with other cattle breeds worldwide. Also, the breed shared genetic similarity to hybrids from America and Bos indicus from Africa and highlighted a moderate level of genetic isolation with some overlaps with Bos taurus from America. The breed showed a complex genetic composition, influenced by historical factors. Overall, findings of the present study contribute to the understanding of genomic structure of Siboney de Cuba cattle breed.
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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".