PSI-B-14 Late-Breaking: Evaluation of mRNA isoforms expression profile using two approaches to measure meat tenderness from Longissimus thoracis muscle in beef cattle
Bibliographic record
Abstract
Abstract The Warner-Bratzler shear force (WBSF) and myofibrillar fragmentation index (MFI) are complementary methodologies commonly used to measure beef tenderness. To identify mRNA isoforms differentially expressed became an important tool to provide new insights to better understand the transcripts involved in the regulation of the meat tenderness, using MFI and WBSF measures in Nellore beef cattle. Longissimus thoracis muscle samples from the 20 most extreme bulls (out of 80 bulls set) for WBSF [tender (n = 9) and tough (n = 10) groups] and MFI [high (n = 10) and low (n = 10) groups] traits were collected to perform transcriptomic analysis using RNA-Sequencing. The CLC Genomics Workbench v.12.0 was used to align the fragments of each sample to the bovine reference genome ARS.UCD1.2. An average of 37 million transcripts were expressed in the Nellore muscle transcriptome. A total of 41 and 31 mRNA isoforms were differentially expressed (q≤0.05 and Fold Change greater than 2) between the two groups of divergent bulls for WBSF and MFI traits, respectively. The RPL14-202 mRNA isoform was the only isoform differentially expressed in common between both traits and is one of two known transcripts of the RPL14 gene. The RPL14 gene contains a trinucleotide repeat tract whose length is highly polymorphic and has several biochemical functions. Bulls with tender meat have one base insertion inside this region and possibly has splice site disruption effects. The RPL14-202 mRNA isoform could be used as potential biological marker for beef tenderness. The identified differentially expressed mRNA isoforms (ACTA1-202, ACTN3-201, MYL6-202, MYL6-201, MYBPC2-202) were involved with skeletal muscle cell differentiation, negative regulation of sarcomere organization and regulation of skeletal muscle contraction. mRNA isoforms directly associated with muscle development were identified using different approaches to measure beef tenderness suggesting potential key regulator genes and biomarkers associated with an important consumer valued trait for the beef industry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".