Skeletal muscle lncRNA profile associated with fatty acids in Nellore beef cattle
Bibliographic record
Abstract
This study aimed to identify differentially expressed (DE) long non-coding RNAs (lncRNAs) in muscle tissue of Nellore cattle clustered by their fatty acid profile. Longissimus thoracis muscle samples from 48 young bulls were used to quantify fatty acid (FA) (myristic, palmitic, stearic, oleic, linoleic, conjugated linoleic (CLA), α-linolenic and the groups of saturated fatty acids (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), ω3, ω6, PUFA/SFA ratio and ω6/ω3) and to generate RNA-Sequencing data for transcriptomic analyses. The K-means analysis was used to classify the 48 animals into three clusters based on their FA patterns. The C1 had significantly (p ≤ 0.05) higher PUFA, ω3, ω6, linoleic and α-linolenic content. The proportion of SFA, myristic, palmitic and stearic were significantly (p ≤ 0.05) higher in C3, while C2 presented an intermediate profile. DE analyses were performed on three different comparisons, C1 vs. C2, C1 vs. C3 and C2 vs. C3, and 22, 28 and 22 DE lncRNAs (fold change > | 2 |, p-value < 0.01 and false discovery rate (FDR) < 0.05) were found, respectively. For three comparisons, the novel DE transcripts, lncRNA_15786.3, lncRNA_13894.1 and lincRNA_17393.3 interacted with CCN1, BNIP3, and CNOT2 genes, respectively, and appeared to contribute to a PUFA-enriched fatty acid profile. These genes are responsible for regulating the lipogenic genes, lipid metabolism, immune response and lipid synthesis. Meanwhile, the intergenic DE lncRNAs (lincRNA_18394.1, lincRNA_2526.3 and lincRNA_17681.1) were associated with the genes DDX1, EIF4E and APOL3, and appeared to contribute to a SFA-enriched fatty acid profile. The gene DDX1 was enriched by GO terms related to RNA splicing (GO:0008380), while the other genes (e.g., EIF4E and APOL3) were enriched to GO terms related to lipid transport (GO:0006869), localization (GO:0010876) and to cellular response to lipid (GO:0071396). These findings offer new insights into the biological mechanisms underlying the gene regulation of FA composition in beef and may provide a valuable foundation for further investigations regarding the interactions between lncRNAs and mRNAs, as well as their potential impact on meat quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".