Ecuadorian Holstein-Friesian cattle paternal lineages: Demographic structure, inbreeding evolution, and genetic diversity
Bibliographic record
Abstract
Holstein-Friesian cattle are the most important dairy breed worldwide. The main objective was to carry out a detailed pedigree evaluation of the Ecuadorian Holstein-Friesian cattle to investigate the demographic structure, inbreeding evolution, and genetic diversity of the official paternal lineages to determine the potential GD loss after the inclusion of modern Assisted Reproductive Technologies (ARTs). Official pedigree information from 28,893 Holstein-Friesian sires born between 1950 and 2021 and enrolled with the Ecuadorian Holstein-Friesian Association (AHFE, Ecuador) were recorded and evaluated from USA and Canada genetic official databases. After multiple-trait across-country genetic analyses the total population was divided into four subpopulations; i) 1950-1969: natural mating (NM) period; ii) 1970-1989: NM + artificial insemination (AI) period; iii) 1990-2009: AI + embryo transfer (ET) period; and iv) 2010-2021: AI + ET + genomic selection (GS) period. Demographic parameters [number of males, pedigree integrity (PI), and generation interval (GI)] were analysed. PI was analysed using known ancestors up to 4 generations considering the number of complete (GCom), maximum (GMax) and equivalent (GEqu) generations. Moreover, Inbreeding parameters [inbreeding coefficient (F), average relatedness (AR), coancestry (C), effective size (Ne), genetic conservation index (GCI)] and parameters related to the gene origin probability (number of founders (f), effective number of founders (fe), genetic conservation index (GCI), among others] were also analysed, together with the fe/f ratio, fge/fe ratio, genetic contributions, and genetic diversity loss (GD-loss) derived parameters. The results indicated that nearly all imported sires used in Ecuador born in the beginning of 1990s could be traced to just three countries, who together account for > 90% of paternal lineages. This fact indicates that GD has undergone a dramatic decrease during the past 30 years. The PCI for the three last periods were > 55%, and the trend was enhanced in the fourth chronological period till > 92%. The estimated proportion of random genetic drift in GD loss increased over time as well as the Ne that decreased by the time. In conclusion, the occurrence of AI + ET + GS period led to the major GD loss. Therefore, due to the extremely limited number of paternal lineages the strategy for recovering the minimal GD on the current and future Ecuadorian Holstein-Friesian cattle should reduce the inbreeding values by increasing the Ne using alternately the foreign genetic material and the national breeding stock.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".