DAPE-PD adapts genomic foundation model via diffusion for tailored cis-regulatory DNA generation

[bioRxiv] A bioRxiv preprint by Echavarria Galindo et al. introduces DAPE-PD (Diffusion Adaptation of Pretrained Evo for Promoter Design), which adapts the autoregressive Evo model into a bidirectional masked diffusion model without foundation-scale retraining. The method combines pretrained genomic representations with iterative unmasking to generate regulatory DNA sequences. After genus-specific fine-tuning on genome-derived intergenic sequences, DAPE-PD generated sequences that retained genus-associated compositional features despite low similarity to the fine-tuning datasets, according to the authors. Experimental validation identified functional de novo promoters, and in silico prioritization recovered active designs from small experimental candidate sets across three non-model gut commensals. The authors said the framework connects genomic pretraining with diffusion-based generation, extending genomic foundation models from sequence understanding toward functional cis-regulatory DNA engineering in living cells.