MétaCan
Menu
Back to cohort
Record W3131575142 · doi:10.3389/fgene.2020.613636

Impacts of Epigenetic Processes on the Health and Productivity of Livestock

2021· review· en· W3131575142 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Genetics · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité LavalAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsEpigenomeEpigeneticsBiologyLivestockProductivityDNA methylationBiotechnologyGeneticsEcologyGene

Abstract

fetched live from OpenAlex

The dynamic changes in the epigenome resulting from the intricate interactions of genetic and environmental factors play crucial roles in individual growth and development. Numerous studies in plants, rodents, and humans have provided evidence of the regulatory roles of epigenetic processes in health and disease. There is increasing pressure to increase livestock production in light of increasing food needs of an expanding human population and environment challenges, but there is limited related epigenetic data on livestock to complement genomic information and support advances in improvement breeding and health management. This review examines the recent discoveries on epigenetic processes due to DNA methylation, histone modification, and chromatin remodeling and their impacts on health and production traits in farm animals, including bovine, swine, sheep, goat, and poultry species. Most of the reports focused on epigenome profiling at the genome-wide or specific genic regions in response to developmental processes, environmental stressors, nutrition, and disease pathogens. The bulk of available data mainly characterized the epigenetic markers in tissues/organs or in relation to traits and detection of epigenetic regulatory mechanisms underlying livestock phenotype diversity. However, available data is inadequate to support gainful exploitation of epigenetic processes for improved animal health and productivity management. Increased research effort, which is vital to elucidate how epigenetic mechanisms affect the health and productivity of livestock, is currently limited due to several factors including lack of adequate analytical tools. In this review, we (1) summarize available evidence of the impacts of epigenetic processes on livestock production and health traits, (2) discuss the application of epigenetics data in livestock production, and (3) present gaps in livestock epigenetics research. Knowledge of the epigenetic factors influencing livestock health and productivity is vital for the management and improvement of livestock productivity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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