Sexing Frogs by Real-Time PCR: Using Aromatase <b><i>(cyp19) </i></b>as an Early Ovarian Differentiation Marker
Bibliographic record
Abstract
Most anurans have no identified sex-markers; therefore, alternative methods for identification of early changes in sex ratios are required. In this study, Lithobates sylvaticus and Silurana tropicalis tadpoles were sampled at different developmental stages covering the entire process of sex differentiation. Three candidate genes known to be involved in sex differentiation in other vertebrate species were selected to develop a method to identify phenotypic sex in frogs: cytochrome p450 aromatase (cyp19), forkhead box L2 (foxl2) and the cytochrome 17-alpha-hydroxylase/17,20 lyase (cyp17). Cloning of these genes revealed nucleotide identity values ranging between 75-97% when compared to other amphibian species. Gene expression of cyp17,cyp19 and foxl2 in L. sylvaticus adult gonads and gonad-mesonephros complex (GMC) of tadpoles was analyzed by real-time RT-PCR. Results showed clear sexually dimorphic patterns in the expression of the 3 genes. Our analysis reveals that GMC gene expression levels of cyp19 alone can be used as a robust predictor of phenotypic sex in L. sylvaticus tadpoles. In addition, we validated this method measuring cyp19 mRNA levels in S. tropicalis GMCs. We propose measuring cyp19 as a tool to study the effects of chemical contaminants (including endocrine disrupting compounds) on amphibian gonadal development and sex ratios in the future.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".