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Record W2744011328 · doi:10.2527/asasann.2017.129

129 Maternal plane of nutrition during mid-gestation affects the skeletal muscle transcriptome in beef cattle progeny

2017· article· en· W2744011328 on OpenAlexaff
Joshua C McCann, Thomas B Wilson, Lindsey Guan, Daniel W Shike, Juan J. Loor

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTranscriptomeBiologyGestationIce calvingAnimal scienceBeef cattleLongissimus muscleGeneRNA-SeqBiotechnologyGeneticsPregnancyGene expressionLactation

Abstract

fetched live from OpenAlex

The objective was to determine the effect of maternal nutrition management during mid-gestation on the skeletal muscle transcriptome in progeny using 3 dietary treatments. Spring-calving, multiparous cows (n = 25) were limit-fed a common diet at three levels of intake to achieve 70% NRC requirement (70%REQ; 5.2 kg DMI), 100% NRC energy and protein requirements (REQ; 7.4 kg DMI), and 130% NRC requirements (130%REQ; 9.7 kg DMI). Diet composition included soy hulls, corn silage, and alfalfa haylage. Treatment diets were fed during mid-gestation (d 88 to 171 of gestation), and a common diet formulated to meet 100% NRC requirements was fed during the remainder of gestation. After calving, all cows and calves were managed similarly as a single contemporary group. Longissimus muscle biopsies were taken on 99 and 392 d of age. Extracted RNA was used in paired-end RNA sequencing on the Illumina HiSeq 2500 platform to analyze the transcriptome at d 99 and 392. Transcriptomic data were mapped to the UMD3.1.1 bovine reference genome and analyzed using a mixed model approach within the R-package limma. Over 7,000 expressed genes were included in weighted gene co-expression network analysis (WGCNA), which clustered genes into 11 modules including 4 that correlated to phenotypic measures. The largest module included over 2,000 co-expressed genes and was downregulated (P < 0.01) in progeny born to 130%REQ-fed compared with REQ-fed dams. The Dynamic Impact Approach annotated genes within this module to KEGG pathways. The pathways most impacted by maternal plane of nutrition were mainly lipid-associated including steroid and steroid hormone biosynthesis, sulfur metabolism, retinol metabolism, ketone synthesis and degradation, fat digestion and absorption, and PPAR signaling pathways. Module 7 (342 genes) was correlated positively with Warner-Bratzler shear force and negatively with marbling score. Major pathways in module 7 centered on glycolysis/gluconeogenesis, energy metabolism, and calcium signaling. These genes and associated pathways support increased glycolytic muscle fibers (type 2x) in progeny born to 130%REQ-fed compared with 70%REQ-fed dams. Results indicate the skeletal muscle transcriptome and associated metabolic functions prior to slaughter are affected by mid-gestation maternal plane of nutrition and may be regulated by epigenetic factors.

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 score0.003
Threshold uncertainty score0.006

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 head0.012
GPT teacher head0.290
Teacher spread0.278 · 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".

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Citations1
Published2017
Admission routes1
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