Genome-wide microRNA and messenger RNA profiling in rodent liver development implicates mir302b and mir20a in repressing transforming growth factor-beta signaling
Bibliographic record
Abstract
MicroRNAs (miRNAs) are recently discovered small RNA molecules that regulate developmental processes, such as proliferation, differentiation, and apoptosis; however, the identity of miRNAs and their functions during liver development are largely unknown. Here we investigated the miRNA and gene expression profiles for embryonic day (E)8.5 endoderm, E14.5 Dlk1(+) liver cells (hepatoblasts), and adult liver by employing Illumina sequencing. We found that miRNAs were abundantly expressed at all three stages. Using K-means clustering analysis, 13 miRNA clusters with distinct temporal expression patterns were identified. mir302b, an endoderm-enriched miRNA, was identified as an miRNA whose predicted targets are expressed highly in E14.5 hepatoblasts but low in the endoderm. We validated the expression of mir302b in the endoderm by whole-mount in situ hybridization. Interestingly, mir20a, the most highly expressed miRNA in the endoderm library, was also predicted to regulate some of the same targets as mir302b. We found that through targeting Tgfbr2, mir302b and mir20a are able to regulate transforming growth factor beta (TGFβ) signal transduction. Moreover, mir302b can repress liver markers in an embryonic stem cell differentiation model. Collectively, we uncovered dynamic patterns of individual miRNAs during liver development, as well as miRNA networks that could be essential for the specification and differentiation of liver progenitors. (HEPATOLOGY 2013).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".