Rapid Transcriptional Pulsing Dynamics of High Expressing Retroviral Transgenes in Embryonic Stem Cells
Bibliographic record
Abstract
Single cell imaging studies suggest that transcription is not continuous and occurs as discrete pulses of gene activity. To study mechanisms by which retroviral transgenes can transcribe to high levels, we used the MS2 system to visualize transcriptional dynamics of high expressing proviral integration sites in embryonic stem (ES) cells. We established two ES cell lines each bearing a single copy, self-inactivating retroviral vector with a strong ubiquitous human EF1α gene promoter directing expression of mRFP fused to an MS2-stem-loop array. Transfection of MS2-EGFP generated EGFP focal dots bound to the mRFP-MS2 stem loop mRNA. These transcription foci colocalized with the transgene integration site detected by immunoFISH. Live tracking of single cells for 20 minutes detected EGFP focal dots that displayed frequent and rapid fluctuations in transcription over periods as short as 25 seconds. Similarly rapid fluctuations were detected from focal doublet signals that colocalized with replicated proviral integration sites by immunoFISH, consistent with transcriptional pulses from sister chromatids. We concluded that retroviral transgenes experience rapid transcriptional pulses in clonal ES cell lines that exhibit high level expression. These events are directed by a constitutive housekeeping gene promoter and may provide precedence for rapid transcriptional pulsing at endogenous genes in mammalian stem cells.
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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 | 0.001 |
| 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 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".