Unraveling the phenotypic and genomic background of behavioral plasticity and temperament in North American Angus cattle
Bibliographic record
Abstract
BACKGROUND: Longitudinal records of temperament can be used for assessing behavioral plasticity, such as aptness to learn, memorize, or change behavioral responses based on affective state. In this study, we evaluated the phenotypic and genomic background of North American Angus cow temperament measured throughout their lifetime around the weaning season, including the development of a new indicator trait termed docility-based learning and behavioral plasticity. The analyses included 273,695 and 153,898 records for yearling (YT) and cow at weaning (CT) temperament, respectively, 723,248 animals in the pedigree, and 8784 genotyped animals. Both YT and CT were measured when the animal was loading into/exiting the chute. Moreover, CT was measured around the time in which the cow was separated from her calf. A random regression model fitting a first-order Legendre orthogonal polynomial was used to model the covariance structure of temperament and to assess the learning and behavioral plasticity (i.e., slope of the regression) of individual cows. This study provides, for the first time, a longitudinal perspective of the genetic and genomic mechanisms underlying temperament, learning, and behavioral plasticity in beef cattle. RESULTS: CT measured across years is heritable (0.38-0.53). Positive and strong genetic correlations (0.91-1.00) were observed among all CT age-group pairs and between CT and YT (0.84). Over 90% of the candidate genes identified overlapped among CT age-groups and the estimated effect of genomic markers located within important candidate genes changed over time. A small but significant genetic component was observed for learning and behavioral plasticity (heritability = 0.02 ± 0.002). Various candidate genes were identified, revealing the polygenic nature of the traits evaluated. The pathways and candidate genes identified are associated with steroid and glucocorticoid hormones, development delay, cognitive development, and behavioral changes in cattle and other species. CONCLUSIONS: Cow temperament is highly heritable and repeatable. The changes in temperament can be genetically improved by selecting animals with favorable learning and behavioral plasticity (i.e., habituation). Furthermore, the environment explains a large part of the variation in learning and behavioral plasticity, leading to opportunities to also improve the overall temperament by refining management practices. Moreover, behavioral plasticity offers opportunities to improve the long-term animal and handler welfare through habituation.
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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".