Elucidation of Mechanisms of Fetal Hemoglobin Regulation by CRISPR/Cas9 Mediated Genome Editing
Bibliographic record
Abstract
Despite nearly complete understanding of the genetics of the β-hemoglobinopathies for several decades, definitive treatment options have lagged behind. Fetal hemoglobin (HbF) reinduction represents a “silver bullet” for therapy of the β-globin disorders. Recent development of the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 nuclease system has allowed for facile manipulation of the genome for the study of genes and genetic elements. Here we developed CRISPR/Cas9-based methodology to reliably engender targeted genomic deletions ranging from 1.3 kilobases to over 1 megabase, which suggested an inverse relationship between deletion size and deletion frequency. Targeted deletion methods and Cas9-mediated in situ saturating mutagenesis were applied to the enhancer of the HbF repressor BCL11A, which revealed discrete vulnerabilities. This finding is consistent with emerging evidence in the field that large enhancers are comprised of constituent parts with some harboring the majority of the activity. The identified “Achilles heel” of the enhancer represents a promising therapeutic target. We further enhanced the resolution of the in situ saturating mutagenesis technique by using multiple Cas9 nucleases and variant-aware library design to identify functional sequences within the HBS1L-MYB intergenic region, a locus associated with elevated HbF levels. These data demonstrate the robustness of CRISPR/Cas9 mediated in situ saturating mutagenesis and targeted deletion to interrogate functional sequence within regulatory DNA. Harnessing the power of genome editing may usher in a second generation form of gene therapy for the β-globin disorders.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".