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Record W4410358135 · doi:10.1093/genetics/iyaf092

Genetic analysis of stress hormone levels in hair of healthy nursery pigs and their relationships with backtest responses

2025· article· en· W4410358135 on OpenAlexafffund
Fazhir Kayondo, hayder al-shanoon, Yolande M. Seddon, Dylan Carette, Carmen Cole, David M. Janz, Frédéric Fortin, John C. S. Harding, Michael K. Dyck, Graham Plastow, Pig Gen Canada, Jack C. M. Dekkers

Bibliographic record

VenueGenetics · 2025
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsCentre de Développement du Porc du QuébecUniversity of GuelphUniversity of AlbertaUniversity of Saskatchewan
FundersNational Institute of Food and AgricultureCollege of Engineering, Michigan State UniversityU.S. Department of AgricultureGenome AlbertaGenome CanadaGenome PrairieMichigan State University
KeywordsBiologyHeritabilitySingle-nucleotide polymorphismEndocrinologyInternal medicineGlucocorticoid receptorQuantitative trait locusGeneticsCortisoneGlucocorticoidSNPPhysiologyGeneGenotypeMedicine

Abstract

fetched live from OpenAlex

This study explored the genetics of the levels of stress hormones (cortisol, cortisone, DHEA, and DHEA-S) in hair of 863 clinically healthy Yorkshire × Landrace male pigs at ∼40 days of age and evaluated their potential as biomarkers of innate stress response by estimating genetic correlations with responses to a 30 s backtest performed at ∼27 days of age. Backtest responses included the number and intensity of vocalizations (VN and VI) and struggles (SN and SI). With pigs genotyped using a 50 K single nucleotide polymorphism (SNP) panel that was imputed to 650 K SNPs, heritability estimates for the levels of cortisol, cortisone, DHEA, and DHEA-S were 0.33, 0.04, 0, and 0.31, respectively, while those for backtest responses ranged from 0.26 to 0.57. Litter effects accounted for 9 to 16% of the phenotypic variance for stress hormone levels and none for backtest responses. Genetic correlation estimates among stress hormone levels were strongest between cortisol and cortisone (0.99 ± 0.12), while those among backtest responses ranged from 0.60 to 0.99. Cortisol was estimated to have moderate genetic correlations with VN (0.24 ± 0.19) and VI (0.50 ± 0.24) but not with SN and SI. Genome-wide association studies identified a major quantitative trait locus (QTL) for hair cortisol levels near the glucocorticoid receptor gene (NR3C1) that explained 45.3% of the genetic variance and that may be different than a causative mutation that was previously identified in this gene for cortisol levels in porcine blood. An extra copy of the minor allele (frequency = 9%) at the lead SNP for this QTL, rs341258564 originated from both parental breeds and reduced levels of cortisol by 30 ± 6% and of cortisone by 17 ± 4%, and increased VN by 5 ± 2%. Additional QTL with smaller effects (1.0 to 11.1% of genetic variance) were identified for DHEA-S, cortisol/DHEA-S, cortisone/DHEA-S, VI, and VN. Ranked gene set enrichment analyses of 0.25 Mb windows based on genetic variance explained showed that windows associated with glucocorticoid levels were enriched for biological terms related to energy production and suppression of inflammation. In contrast, those associated with DHEA-S were enriched for biological processes related to immunity activation and gene transcriptional and post-transcriptional regulation. These findings establish the genetic basis of stress response in young and clinically healthy pigs, identify the genomic location of a major QTL for hair cortisol levels, and show that cortisol levels in hair of young and healthy pigs are potential genetic biomarkers for the innate coping response style of pigs to noninfectious stressors. These results open avenues that can facilitate selection of pigs that cope better with noninfectious stressors.

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 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 score0.006
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.088
GPT teacher head0.344
Teacher spread0.256 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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