A system for precise analysis of transcription-regulating elements of immunoglobulin genes
Bibliographic record
Abstract
BACKGROUND: Precise analysis of expression-regulating elements, such as enhancers and insulators, requires that they be tested under reproducible, isogenic conditions. The commonly used methods of transfecting DNA into cell lines and selecting for drug resistance lack the requisite precision, as they yield cell lines in which varying numbers of gene copies have inserted at varying and undefined sites. By contrast, recombination-mediated cassette exchange (RMCE), by which a site-specific recombinase is used to place a single copy of a transgene at a constant chromosomal site of a cell line, offers the necessary precision. Although RMCE is generally applicable, many regulatory elements of interest are tissue-specific in their function and so require cell lines in the appropriate ontogenetic state. RESULTS: As reported here, we have used RMCE in a mouse B hybridoma cell line to establish a system with several additional advantages. To avoid the non-physiological features of prokaryotic DNA, this system uses the immunoglobulin mu heavy chain (IgH) gene from the hybridoma as the reporter. Expression can be measured simply by bulk culture assays (ELISA, Northern blot) and single cell assays (flow cytometry). Expression of the IgH reporter gene varies only 1.5 fold among independent transfectants, and expression is greatly (> 50 fold) increased by inclusion of the IgH intronic enhancer. CONCLUSION: This system is suitable for precise analysis of the regulatory elements of the immunoglobulin loci.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".