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DOI 10.3390/genes17091062

Медицинская библиотека · Genes · 2026

Cross-Model Uncertainty-Aware Minimal Editing of Cis-Regulatory Elements for Cell-Type-Selective Design.

Xia Angran, Wang Changwei, Xia Yemao

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Аннотация

Background/

Objectives

Cis-regulatory elements (CREs) help mediate cell-type-selective gene expression, yet sequence-to-activity models are rarely converted into compact, experimentally tractable variant panels that retain natural regulatory scaffolds. We developed SafeEdit-CRE to select minimal edits that preserve cross-model specificity while reducing predictive uncertainty, yielding an auditable CRE variant library for reporter-screening prioritization.

Methods

SafeEdit-CRE combines the published Malinois sequence-activity predictor with an architecture-distinct reviewer ensemble, validation-calibrated uncertainty, sequence-domain controls, and constrained beam search. Natural 200 nt CREs were edited under fixed substitution budgets of 1, 5, 10, or 20 nucleotides and evaluated by a separately trained multi-kernel ensemble kept entirely separate from candidate generation.

Results

Across 600 held-out CRE parents in K562, HepG2, and SK-N-SH cells, SafeEdit-CRE achieved a mean cross-model specificity-margin gain of 0.877 versus 0.822 for greedy editing (paired difference 0.055; 95% CI 0.040-0.071). Relative to a compute-matched primary-model beam, SafeEdit-CRE yielded a similar cross-model specificity-margin gain (difference -0.004; 95% CI -0.011-0.004) with lower ensemble uncertainty (0.314 vs. 0.335). In a locked 90-parent benchmark, 60.6% of designs passed all nine prespecified sequence and model-agreement checks, compared with 38.8% for greedy and 13.1% for random substitution (paired difference 21.8 percentage points; 95% CI 18.3-25.3).

Conclusions

SafeEdit-CRE reduced 3240 designs to 74 Tier A computational candidates prioritized for reporter screening across three cell types and four edit budgets. By separating search from cross-model audit and enforcing explicit edit budgets and sequence-domain safeguards, the framework provides a reproducible and auditable approach to computational CRE prioritization, regulatory-grammar studies, and synthetic regulatory-element design.

Для цитирования: Xia Angran, Wang Changwei, Xia Yemao. Cross-Model Uncertainty-Aware Minimal Editing of Cis-Regulatory Elements for Cell-Type-Selective Design.. Genes. 2026. DOI: 10.3390/genes17091062.

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