Polygraph: a software framework for the systematic assessment of synthetic regulatory DNA elements

The design of regulatory elements is pivotal in gene and cell therapy, where DNA sequences are engineered to drive elevated and cell-type specific expression. However, the systematic assessment of synthetic DNA sequences without robust metrics and easy-to-use software remains challenging. Here, we introduce Polygraph, a Python framework that evaluates synthetic DNA elements, based on features like diversity, motif and k-mer composition, similarity to endogenous sequences, and screening with predictive and foundational models. Polygraph is the first instrument for assessing synthetic regulatory sequences, enabling faster progress in therapeutic interventions and improving our understanding of gene regulatory mechanisms.

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Publication Details

Journal
Genome biology
Published
2025-05-06
DOI
https://doi.org/10.1186/s13059-025-03584-9
Citations
2
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
1.61
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Polygraph: a software framework for the systematic assessment of synthetic regulatory DNA elements

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2 citations
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CRISPR and Genetic Engineering
1.61
article

Polygraph: a software framework for the systematic assessment of synthetic regulatory DNA elements

Tommaso Biancalani, Laura Gunsalus, Avantika Lal, Gökçen Eraslan, Anay Gupta
article en
2 citations

Abstract

The design of regulatory elements is pivotal in gene and cell therapy, where DNA sequences are engineered to drive elevated and cell-type specific expression. However, the systematic assessment of synthetic DNA sequences without robust metrics and easy-to-use software remains challenging. Here, we introduce Polygraph, a Python framework that evaluates synthetic DNA elements, based on features like diversity, motif and k-mer composition, similarity to endogenous sequences, and screening with predictive and foundational models. Polygraph is the first instrument for assessing synthetic regulatory sequences, enabling faster progress in therapeutic interventions and improving our understanding of gene regulatory mechanisms.

Genome biologyVol. 26(1)
Georgia Institute of Technology (US)
Openalex Percentile: Top 17%
CRISPR and Genetic Engineering
1.61
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