A compact, in vivo screen of all 6-mers reveals drivers of tissue-specific expression and guides synthetic regulatory element design
Bibliographic record
Abstract
BACKGROUND: Large-scale annotation efforts have improved our ability to coarsely predict regulatory elements throughout vertebrate genomes. However, it is unclear how complex spatiotemporal patterns of gene expression driven by these elements emerge from the activity of short, transcription factor binding sequences. RESULTS: We describe a comprehensive promoter extension assay in which the regulatory potential of all 6 base-pair (bp) sequences was tested in the context of a minimal promoter. To enable this large-scale screen, we developed algorithms that use a reverse-complement aware decomposition of the de Bruijn graph to design a library of DNA oligomers incorporating every 6-bp sequence exactly once. Our library multiplexes all 4,096 unique 6-mers into 184 double-stranded 15-bp oligomers, which is sufficiently compact for in vivo testing. We injected each multiplexed construct into zebrafish embryos and scored GFP expression in 15 tissues at two developmental time points. Twenty-seven constructs produced consistent expression patterns, with the majority doing so in only one tissue. Functional sequences are enriched near biologically relevant genes, match motifs for developmental transcription factors, and are required for enhancer activity. By concatenating tissue-specific functional sequences, we generated completely synthetic enhancers for the notochord, epidermis, spinal cord, forebrain and otic lateral line, and show that short regulatory sequences do not always function modularly. CONCLUSIONS: This work introduces a unique in vivo catalog of short, functional regulatory sequences and demonstrates several important principles of regulatory element organization. Furthermore, we provide resources for designing compact, reverse-complement aware k-mer libraries.
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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) | 0.000 | 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 | 0.000 |
| 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".