Integrated single-cell transcriptome and comparative genome analysis reveals the origin of intermuscular bones in zebrafish
Bibliographic record
Abstract
The evolutionary process of intermuscular bones (IBs) is complex, the molecular regulatory mechanisms of their development are not clear, and even the genes involved in the evolution and development of IBs are poorly understood. In this study, comparative genomic analysis of four fish species with IBs and eleven fish species without IBs identified 106 genes that are more conservatively evolved in fish species with IBs, but highly variable in fish species without IBs. These genes are mainly involved in swimming behavior and BMP signaling pathways . We performed single-cell transcriptome sequencing of IBs origin tissues in zebrafish before and after IBs formation and found that osteoblasts and mesenchymal stem cells (MSCs) increased significantly after IBs formation. RNA velocity analysis showed that osteoblasts in IBs differentiate from MSCs, and the differentiation trajectory of MSCs into osteoblasts was successfully constructed by pseudo-time analysis. Combined with the results of multi-omics analysis, seven candidate genes associated with IBs development were screened and knocked out in zebrafish. It was found that foxn3 mutation resulted in a delay in IB development, whereas bmp6 mutation resulted in a total loss of IB. By comparing the transcriptome of IBs tissues between bmp6 +/+ zebrafish and bmp6 −/− zebrafish, we found that bmp6 deletion may inhibit the differentiation of MSCs into osteoblasts while promoting the formation of osteoclasts and ultimately inhibiting the formation of IBs. This study provides new insights into the molecular regulatory mechanisms and evolutionary processes of IB development.
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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".