Influence of Sire Breed on the Interplay among Rumen Microbial Populations Inhabiting the Rumen Liquid of the Progeny in Beef Cattle
Bibliographic record
Abstract
This study aimed to evaluate whether the host genetic background impact the ruminal microbial communities of the progeny of sires from three different breeds under different diets. Eighty five bacterial and twenty eight methanogen phylotypes from 49 individuals of diverging sire breed (Angus, ANG; Charolais, CHA; and Hybrid, HYB), fed high energy density (HE) and low energy density (LE) diets were determined and correlated with breed, rumen fermentation and phenotypic variables, using multivariate statistical approaches. When bacterial phylotypes were compared between diets, ANG offspring showed the lowest number of diet-associated phylotypes, whereas CHA and HYB progenies had seventeen and twenty-three diet-associated phylotypes, respectively. For the methanogen phylotypes, there were no sire breed-associated phylotypes; however, seven phylotypes were significantly different among breeds on either diet (P<0.05). Sire breed did not influence the metabolic variables measured when high energy diet was fed. A correlation matrix of all pairwise comparisons among frequencies of bacterial and methanogen phylotypes uncovered their relationships with sire breed. A cluster containing methanogen phylotypes M16 (Methanobrevibacter gottschalkii) and M20 (Methanobrevibacter smithii), and bacterial phylotype B62 (Robinsoniella sp.) in Angus offspring fed low energy diet reflected the metabolic interactions among microbial consortia. The clustering of the phylotype frequencies from the three breeds indicated that phylotypes detected in CHA and HYB progenies are more similar among them, compared to ANG animals. Our results revealed that the frequency of particular microbial phylotypes in the progeny of cattle may be influenced by the sire breed when different diets are fed and ultimately further impact host metabolic functions, such as feed efficiency.
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 | 0.000 | 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".