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Record W4317435630 · doi:10.1186/s12711-023-00777-3

Unraveling the phenotypic and genomic background of behavioral plasticity and temperament in North American Angus cattle

2023· article· en· W4317435630 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenetics Selection Evolution · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTemperamentBiologyHeritabilityTraitPhenotypic plasticityCandidate geneEvolutionary biologyGeneticsGenePersonalityPsychology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.254
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it