Informational blueprints reveal condition-dependent gene regulatory architectures
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arXiv
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| Format: | Preprint |
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2026
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| author | Gökmen, Doruk Efe Pan, Rosalind Wenshan Röschinger, Tom Quake, Stephen Garcia, Hernan Phillips, Rob Vitelli, Vincenzo |
| author_facet | Gökmen, Doruk Efe Pan, Rosalind Wenshan Röschinger, Tom Quake, Stephen Garcia, Hernan Phillips, Rob Vitelli, Vincenzo |
| contents | While coding regions in the genome have a direct interpretation in terms of protein products, significant fractions are non-coding and yet control essential biological functions. Unlike the genetic code, there is no "lookup table" that identifies where regulatory proteins, known as transcription factors (TFs), bind. Here, we extract these binding sites by distilling sequences of nucleotide letters into collective coordinates (hyperletters) representing the binding sites that are active under specific environmental conditions. Going beyond local information footprints between individual bases and expression levels, our $\textit{information blueprint}$ algorithm compresses the global information by optimising filters that simultaneously scan an entire promoter sequence. Inspired by renormalisation-group techniques, we identify TF binding sites as coarse-grained variables combining groups of correlated mutations with the highest collective impact on gene expression. We validate our approach on experimental data for $\textit{E. coli}$ and discover novel regulatory elements illustrating its deployment at scale across growth conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_19071 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Informational blueprints reveal condition-dependent gene regulatory architectures Gökmen, Doruk Efe Pan, Rosalind Wenshan Röschinger, Tom Quake, Stephen Garcia, Hernan Phillips, Rob Vitelli, Vincenzo Genomics Statistical Mechanics Molecular Networks Quantitative Methods While coding regions in the genome have a direct interpretation in terms of protein products, significant fractions are non-coding and yet control essential biological functions. Unlike the genetic code, there is no "lookup table" that identifies where regulatory proteins, known as transcription factors (TFs), bind. Here, we extract these binding sites by distilling sequences of nucleotide letters into collective coordinates (hyperletters) representing the binding sites that are active under specific environmental conditions. Going beyond local information footprints between individual bases and expression levels, our $\textit{information blueprint}$ algorithm compresses the global information by optimising filters that simultaneously scan an entire promoter sequence. Inspired by renormalisation-group techniques, we identify TF binding sites as coarse-grained variables combining groups of correlated mutations with the highest collective impact on gene expression. We validate our approach on experimental data for $\textit{E. coli}$ and discover novel regulatory elements illustrating its deployment at scale across growth conditions. |
| title | Informational blueprints reveal condition-dependent gene regulatory architectures |
| topic | Genomics Statistical Mechanics Molecular Networks Quantitative Methods |
| url | https://arxiv.org/abs/2605.19071 |