Genotype-associated heritable rumen bacteria can be a stable microbiota passed to the offspring
Bibliographic record
Abstract
Abstract Recent studies have reported that some rumen microbes are “heritable” (those have significant narrow sense heritability) and can significantly contribute to host phenotype variations. However, it is unknown if these heritable rumen bacteria can be passed to the next generation. In this study, the rumen bacteria from mother cows (sampled in 2016) and their offspring (sampled in 2019) were assessed to determine if vertical transmission occurred between the two generations. The analysis of relationship between host genotypes and heritable bacterial abundances showed that potential of five host genotypes can affect the relative abundances of two unclassified species level heritable bacteria (Pseudoscardovia and p-251-o5). The G allele of BTB-01532239 and A allele of ARS-BFGL-NGS-8960 were associated with a higher relative abundance of p-251-o5. The A allele of BTB-00740910 and BovineHD1300021786 and G allele of BovineHD1900005868 were associated with a higher relative abundance of Pseudoscardovia. The mother–offspring comparison revealed that the heritable rumen bacteria had higher compositional similarity than nonheritable bacteria between two generations, and the predicted heritable microbial functions had higher stability than those from nonheritable bacteria. These findings suggest that a high stability exists in heritable rumen bacteria, which could be passed to the next generation in dairy cows.
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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 | 0.001 |
| 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) | 0.002 | 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".