Comparative genomic organization and tissue-specific transcription of the duplicated<i>fabp7</i>and<i>fabp10</i>genes in teleost fishes
Bibliographic record
Abstract
A whole-genome duplication (WGD) early in the teleost fish lineage makes fish ideal organisms to study the fate of duplicated genes and underlying evolutionary trajectories that have led to the retention of ohnologous gene duplicates in fish genomes. Here, we compare the genomic organization and tissue-specific transcription of the ohnologous fabp7 and fabp10 genes in medaka, three-spined stickleback, and spotted green pufferfish to the well-studied duplicated fabp7 and fabp10 genes of zebrafish. Teleost fabp7 and fabp10 genes contain four exons interrupted by three introns. Polypeptide sequences of Fabp7 and Fabp10 show the highest sequence identity and similarity with their orthologs from vertebrates. Orthology was evident as the ohnologous Fabp7 and Fabp10 polypeptides of teleost fishes each formed distinct clades and clustered together with their orthologs from other vertebrates in a phylogenetic tree. Furthermore, ohnologous teleost fabp7 and fabp10 genes exhibit conserved gene synteny with human FABP7 and chicken FABP10, respectively, which provides compelling evidence that the duplicated fabp7 and fabp10 genes of teleost fishes most likely arose from the well-documented WGD. The tissue-specific distribution of fabp7a, fabp7b, fabp10a, and fabp10b transcripts provides evidence of diverged spatial transcriptional regulation between ohnologous gene duplicates of fabp7 and fabp10 in teleost fishes.
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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".