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Record W4396652150 · doi:10.1093/jas/skae102.063

131 DNA methylation profile in bovine fetal liver is affected by maternal vitamin and mineral supplementation during early gestation

2024· article· en· W4396652150 on OpenAlexaff
Muhammad Anas, Alison K Ward, Kacie L McCarthy, Pawel P. Borowicz, Lawrence P P Reynold, Joel S Caton, Carl R Dahlen, Wellison J j S Diniz

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGestationDNA methylationFetusMethylationVitaminBiologyPhysiologyPregnancyObstetricsAndrologyMedicineEndocrinologyDNABiochemistryGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

Abstract Early gestation is the critical period for successful pregnancy establishment. During this period, maternal nutrition affects fetal development with potentially long-lasting consequences on offspring performance. Despite the known effects of vitamins and minerals on embryonic development, supplementation is still not a widely adopted practice. Here we focused on the effects of maternal vitamin and mineral supplementation from pre-breeding to d 83 of gestation. We hypothesized that the DNA methylation pattern of genes involved with fetal hepatic metabolism and function would be altered in response to vitamin and mineral supplementation during early gestation. Sixteen Angus crossbred heifers (~16 mo of age) were randomly assigned to either a treatment (vitamin and mineral supplementation, VTM, n = 8) or control (corn-based carrier without supplementation, NoVTM, n = 8) group. Supplemented heifers received 0.45 kg •heifer-1•d-1 of to provide 113 g of vitamin-mineral premix (Purina Wind & Rain Storm All-Season 7.5 Complete, Land O’Lakes, Inc., Arden Hills, MN) from d 71 to 148 before breeding to d 83 of gestation. All heifers received 100% of NRC recommended nutritional requirements targeting 0.28 kg •heifer-1•d-1 of gain. The heifers were bred through artificial insemination following a 7-d Co-Synch + CIDR estrus synchronization protocol. All pregnant heifers were surgically ovariohysterectomized on d 83, and liver samples were collected from the fetuses. DNA methylation profiles from 16 fetuses (8 per treatment) were determined using Reduced Representation Bisulfite Sequencing (RRBS). The analysis was conducted using methylKit pipeline where data was normalized using principal components. We identified 794 differentially methylated cytosines (DMCs) for the control (NoVTM) vs VTM comparison. Most of the DMCs were found in introns followed by intergenic, promoter, and exonic regions. Among these DMCs, 60% (479) were hypermethylated and 40% (315) were hypomethylated, potentially regulating 739 nearby genes (FDR < 0.1). Biological processes over-represented by these genes included transport of ions through voltage gated channels (KCNK13, KCNT1, CACNA1B, KCNK9, LRRC55, KCNAB2, CACNA1S, KCNJ2, CACNG5, CLIC5, TPCN2, KCNQ1), which may be associated to pregnancy establishment by inducing pregnancy-associated relaxation and uterine artery dilatation. Some genes associated with structural development were also regulated by VTM supplementation (i.e., TIAM1, COL18A1, DYSF, BMP10, RXRA, EHMT1, COL4A2, PLEC, ZFAT, MTMR2, NAV1, ANHX, ACACB, and LIMK2). Collectively, these results suggest that periconceptual maternal vitamin and mineral supplementation affects the methylation pattern and potentially regulates the expression of genes involved in fetal liver development and ion transport.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.304
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2024
Admission routes1
Has abstractyes

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