Comparative analysis of oocyte transcript profiles reveals a high degree of conservation among species
Bibliographic record
Abstract
Cross-species comparison of gene expression is a powerful approach for discovering genes that have been conserved throughout evolution. Conserved genes are presumably very important in the mechanisms related to the unique molecular functions in oocytes. The objective of this study was to identify genes expressed in the oocyte and conserved across three diverse vertebrate species. We report the global gene expression profiles of Bos taurus and Xenopus laevis oocytes on an NIA mouse development microarray that consists of 60-mer oligonucleotide probes representing more than 20,000 mouse transcripts derived from stem cell, oocyte, and early embryo cDNA libraries. Analysis based on intensity values revealed that 9853 and 10,046 genes are expressed in bovine and Xenopus oocytes respectively. Furthermore, previously published microarray data on preimplantation development in the mouse were used for a comparative analysis of global oocyte gene expression profiles. Interestingly, a substantial proportion of the genes expressed in mouse oocytes is conserved between the three species (74%, 7275 genes). Moreover, functional annotation of these conserved oocyte-expressed genes confirmed that certain functions are conserved among the three species. RNA metabolism and cell cycle were among the over-represented Gene Ontology terms in the biological process category. Finally, a pattern-matching analysis identified 208 conserved maternally expressed genes. Results from these cross-species hybridizations allowed numerous genes expressed in oocytes and conserved between Mus musculus, B. taurus, and X. laevis to be identified. This comparative analysis of oocyte transcript profiles revealed a high degree of conservation among species.
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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".