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Record W4408977426 · doi:10.1093/biolre/ioaf056

From sperm to offspring: epigenetic markers for dairy herd fertility

2025· article· en· W4408977426 on OpenAlexaff
Ying Zhang, Marc Andre A Sirard

Bibliographic record

VenueBiology of Reproduction · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversité LavalMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
Fundersnot available
KeywordsBiologyEpigeneticsFertilityOffspringGeneticsDNA methylationQuantitative trait locusSpermSingle-nucleotide polymorphismPregnancyPopulationGenotypeGeneDemography

Abstract

fetched live from OpenAlex

In recent years, the study of bovine sperm epigenetics has garnered increasing attention alongside research on biomarkers associated with dairy cattle fertility. Male gametes not only transmit the paternal haploid genome to the offspring through fertilization, but also convey epigenetic components, such as DNA methylation, small non-coding RNA, histone variants, and histone modifications to offspring. This epigenetic information may transmit an acquired phenotype leading to intergenerational inheritance. The ongoing worldwide decline in dairy herd fertility affecting both males and females causes significant economic losses for dairy farmers. Previous scientific efforts to address this issue primarily targeted genetic aspects, identifying numerous fertility-related QTLs (Quantitative trait locus) and SNPs (Single nucleotide polymorphisms). However, since fertility is influenced by genetic, epigenetic, and environmental factors, this review highlights the importance of identifying sperm epigenetic markers as additional tools for evaluating and predicting cattle fertility.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.451

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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