DNA-DIFFUSION: LEVERAGING GENERATIVE MODELS FOR CONTROLLING CHROMATIN ACCESSIBILITY AND GENE EXPRESSION VIA SYNTHETIC REGULATORY ELEMENTS
Keywords: Diffusion, Generative AI, Genomics, Synthetic Biology, Gene Expression
TL;DR: A conditional diffusion model to generate synthetic DNA-sequence to control in a cell-type specific fashion gene expression and chromatin accessibility.
Abstract: The challenge of systematically modifying and optimizing regulatory elements
for precise gene expression control is central to modern genomics and synthetic
biology. Advancements in generative AI have paved the way for designing synthetic
sequences with the aim of safely and accurately modulating gene expression.
We leverage diffusion models to design context-specific DNA regulatory
sequences, which hold significant potential toward enabling novel therapeutic applications
requiring precise modulation of gene expression. Our framework uses
a cell type-specific diffusion model to generate synthetic 200 bp DNA regulatory
elements based on chromatin accessibility across different cell types. We evaluate
the generated sequences based on key metrics to ensure they retain properties of
endogenous sequences: transcription factor binding site composition, potential for
cell type-specific chromatin accessibility, and capacity for sequences generated by
DNA diffusion to activate gene expression in different cell contexts using state-ofthe-
art prediction models. Our results demonstrate the ability to robustly generate
DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves
the way for revolutionizing a regulatory modulation approach to mammalian synthetic
biology and precision gene therapy.
Submission Number: 35
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