Variation in yolk precursor receptor mRNA expression is a key determinant of reproductive phenotype in the zebra finch (<i>Taeniopygia guttata</i>)
Bibliographic record
Abstract
The vitellogenin/very low density lipoprotein receptor (VTG/VLDL-R), a 95 kDa protein that belongs to the low density lipoprotein receptor gene family, mediates the uptake of yolk precursors by developing follicles during oocyte growth. However, the extent to which variation in VTG/VLDL-R expression plays a role in determining inter-individual variation in reproductive phenotype (e.g. follicle or egg size) is not known. Here we show that the mRNA sequence of the zebra finch (Taeniopygia guttata) VTG/VLDL-R shows a high degree of sequence identity (92%) with chicken VTG/VLDL-R mRNA. Using quantitative real-time PCR we measured transcriptional expression of VTG/VLDL-R mRNA in various tissues, and for different stages of oocyte growth, in individual female zebra finches. VTG/VLDL-R mRNA was expressed at high levels in vitellogenic oocytes and in skeletal muscle, and was also detectable in liver, but these tissues expressed different splice variants: the short-form LR8-in oocytes and liver, and the LR8+ form in skeletal muscle. There was significant temporal variation in VTG/VLDL-R expression during follicle growth, with highest levels in ovary and a gradual decrease from pre-F3 to F1 vitellogenic follicles. Variation in ovary mRNA expression was correlated with inter-individual variation in clutch size and laying interval. Furthermore, variation in F3 follicle VTG/VLDL-R mRNA expression was correlated with inter-individual variation in egg mass and F1 follicle mass, suggesting that VTG/VLDL receptor mRNA expression is a key determinant of inter-individual variation in reproductive phenotype.
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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 | 0.000 |
| 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".