Locus control region activity by 5′HS3 requires a functional interaction with β-globin gene regulatory elements: expression of novel β/γ-globin hybrid transgenes
Bibliographic record
Abstract
The human beta-globin locus control region (LCR) contains chromatin opening and transcriptional enhancement activities that are important to include in beta-globin gene therapy vectors. We previously used single-copy transgenic mice to map chromatin opening activity to the 5'HS3 LCR element. Here, we test novel hybrid globin genes to identify beta-globin gene sequences that functionally interact with 5'HS3. First, we show that an 850-base pair (bp) 5'HS3 element activates high-level beta-globin gene expression in fetal livers of 17 of 17 transgenic mice, including 3 single-copy animals, but fails to reproducibly activate Agamma-globin transgenes. To identify the beta-globin gene sequences required for LCR activity by 5'HS3, we linked the 815-bp beta-globin promoter to Agamma-globin coding sequences (BGT34), together with either the beta-globin intron 2 (BGT35), the beta-globin 3' enhancer (BGT54), or both intron 2 and the 3' enhancer (BGT50). Of these transgenes, only BGT50 reproducibly expresses Agamma-globin RNA (including 7 of 7 single-copy animals, averaging 71% per copy). Modifications to BGT50 show that LCR activity is detected after replacing the beta-globin promoter with the 700-bp Agamma-globin promoter, but is abrogated when an AT-rich region is deleted from beta-globin intron 2. We conclude that LCR activity by 5'HS3 on globin promoters requires the simultaneous presence of beta-globin intron 2 sequences and the 260-bp 3' beta-globin enhancer. The BGT50 construct extends the utility of the 5'HS3 element to include erythroid expression of nonadult beta-globin coding sequences in transgenic animals and its ability to express antisickling gamma-globin coding sequences at single copy are ideal characteristics for a gene therapy cassette.
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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) | 0.001 | 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".