Single‐Cell <scp>RNA</scp>‐Sequencing Reveals the Breadth of Osteoblast Heterogeneity
Bibliographic record
Abstract
ABSTRACT The current paradigm of osteoblast fate is that the majority undergo apoptosis, while some further differentiate into osteocytes and others flatten and cover bone surfaces as bone lining cells. Osteoblasts have been described to exhibit heterogeneous expression of a variety of osteoblast markers at both transcriptional and protein levels. To explore further this heterogeneity and its biological significance, Venus‐positive (Venus+) cells expressing the fluorescent protein Venus under the control of the 2.3‐kb Col1a1 promoter were isolated from newborn mouse calvariae and subjected to single‐cell RNA sequencing. Functional annotation of the genes expressed in 272 Venus+ single cells indicated that Venus+ cells are osteoblasts that can be categorized into four clusters. Of these, three clusters (clusters 1 to 3) exhibited similarities in their expression of osteoblast markers, while one (cluster 4) was distinctly different. We identified a total of 1920 cluster‐specific genes and pseudotime ordering analyses based on established concepts and known markers showed that clusters 1 to 3 captured osteoblasts at different maturational stages. Analysis of gene co‐expression networks showed that genes involved in protein synthesis and protein trafficking between endoplasmic reticulum (ER) and Golgi are active in these clusters. However, the cells in these clusters were also defined by extensive heterogeneity of gene expression, independently of maturational stage. Cells of cluster 4 expressed Cd34 and Cxcl12 with relatively lower levels of osteoblast markers, suggesting that this cell type differs from actively bone‐forming osteoblasts and retain or reacquire progenitor properties. Based on expression and machine learning analyses of the transcriptomes of individual osteoblasts, we also identified genes that may be useful as new markers of osteoblast maturational stages. Taken together, our data show much more extensive heterogeneity of osteoblasts than previously documented, with gene profiles supporting diversity of osteoblast functional activities and developmental fates. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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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 | 0.000 | 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 | 0.001 |
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".