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Record W4414830981 · doi:10.1093/jas/skaf300.473

PSVI-11 Role of differentially expressed and imprinted genes in high and low fertility produced cattle pregnancies.

2025· article· en· W4414830981 on OpenAlexaff
Odile Polanco, Gabriela Dalmaso de Melo, Sofia Ortega, Ramiro V Oliveira, Gessica A Franco, Amanda Bega, R.L.A. Cerri, Ky G Pohler, J Moraes Vasconcelos

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConceptusGenomic imprintingSireGeneTranscriptomeEmbryoCandidate geneEstrous cycle

Abstract

fetched live from OpenAlex

Abstract Pregnancy loss is considered one of the main causes of reproductive inefficiency in beef cattle. Most research focuses on female contribution to pregnancy success leaving the role of the sire in pregnancy loss largely understudied. The objective was to determine the differentially expressed genes (DEGs) and imprinted genes between the conceptus and uterus of pregnancies produced by sires of known fertility. We hypothesized that the paternal genome would have a significant effect on transcript abundance between these tissues. The sires used have been previously reported to have significantly different levels of field fertility; however, they had passed all normal quality control standards for frozen-thawed semen. Bos indicus heifers (n=45) were subjected to estrus synchronization and embryo transfer with IVP embryos from either a High Fertility (HF) or a Low Fertility sire (LF), pregnancies were confirmed at slaughter. Samples were collected from the trophectoderm (TE) and caruncle (CAR) on days 25 and 36 of gestation for transcriptome analysis. Total RNA was isolated from tissue samples using the RNeasy kit (QIAGEN; Hilden, Germany) per manufacturer’s instructions. Sequencing was conducted using an Illumina platform. Sequences were aligned to the reference genome ARS-UCD1.2. DEGs between sires and tissue were determined using edge-R package from R. False discovery rate was 0.1. On day 25, on the TE 29 DEGs and 42 imprinted genes were identified. In the CAR, 16 DEGs and 43 imprinted genes were observed. On day 36 in the TE, 73 DEGs and 46 imprinted were identified. In CAR, there were 40 DEGs and 33 imprinted genes. Gene ontology analysis reported DEGs in the LF compared to the HF were associated with immunology and reproduction. Downregulated DEGs of particular interest: BoLA NC-1 known to be expressed by the trophoblast cells to inhibit the activation of uterine leukocytes and to protect the conceptus from immune-mediated rejection. The APOB gene, known for its involvement in embryonic development, spermatogenesis and flagellated sperm motility, as well as FETUB known for its function of binding sperm to the zona pellucida. Imprinted genes of interest included OOEP known for embryonic pattern specification, establishment of apical/basal cell polarity. MEAK7 involved in TOR signaling; positive regulation of protein localization to lysosome; and response to insulin. Lastly, PHLDA2 known for its role in placental development, regulation of gene expression and embryonic development. These data suggest that field fertility records might be inaccurate for bull selection to improve reproductive performance. The downregulation of these genes appears to be detrimental to pregnancy success and could be responsible for variation seen in conception rates. Results from this study could lead us to identify sub-fertile bulls. It is evident that the paternal genome seems to play a much bigger role in pregnancy establishment than originally thought.

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 score0.001
Threshold uncertainty score0.004

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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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