G4SCOPE identifies sequence features and epigenetic contexts of chromatin G-quadruplexes

Abstract

Cancer-associated epigenetic remodeling involves a complex interplay between DNA secondary structures and covalent cytosine modifications, yet predicting endogenously folded, chromatin-constrained G-quadruplex (G4) dynamics remains challenging. Here, we develop G4SCOPE, a multi-task deep learning framework that models chromatin-associated G4 occupancy and reconstructs quantitative high-resolution CUT&Tag profiles directly from primary DNA sequence alone. We initially trained G4SCOPE on genotype-stratified G4 enriched cut&tag landscapes generated across an isogenic series of human breast epithelial cells (WT, TP53-/-, TP53-/-;BRCA1-/-, and TP53-/-;BRCA2-/-). G4SCOPE integrates convolutional motif learning with transformer self-attention to decode long-range sequence contexts. The model robustly distinguishes chromatin-associated G4s from GC-matched loci with intrinsic in vitro folding potential, generalizes across distinct breast lineages, and transfers accurately to an independent K562 cellular context. Strikingly, genotype-resolved mapping reveals a profound divergence in genome maintenance states: BRCA1 deficiency indicated a global inflation of chromatin-embedded G4 density, whereas BRCA2 loss was associated with systemic, chromosome-wide structural depletion. Furthermore, unsupervised clustering of model-derived latent sequence representations identified distinct biological G4 subclasses that occupy unique regulatory class genomic environments associated with distinct local 5-methylcytosine and 5-hydroxymethylcytosine landscapes. Together, our framework decodes the primary sequence grammar governing cell-based G4 occupancy and demonstrates that sequence-defined G4 topologies harbor intrinsic and distinct local epigenetic features.

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BibTeX RIS

BibTeX

@misc{sarvar2026g4scope,
  title = {{G4SCOPE identifies sequence features and epigenetic contexts of chromatin G-quadruplexes}},
  author = {A. Sarvar and I. Esain-Garcia and L. Melidis and D. Yap and C. O'Flanagan and V. Cerda and D. Lai and D. Tannahill and Y. Park and S. Balasubramanian and S. Aparicio},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.28.748631},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.28.748631v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - G4SCOPE identifies sequence features and epigenetic contexts of chromatin G-quadruplexes
AU  - A. Sarvar
AU  - I. Esain-Garcia
AU  - L. Melidis
AU  - D. Yap
AU  - C. O'Flanagan
AU  - V. Cerda
AU  - D. Lai
AU  - D. Tannahill
AU  - Y. Park
AU  - S. Balasubramanian
AU  - S. Aparicio
PY  - 2026
DA  - 2026/09/28
PB  - bioRxiv
DO  - 10.64898/2026.09.28.748631
UR  - https://www.biorxiv.org/content/10.64898/2026.09.28.748631v1
AB  - Cancer-associated epigenetic remodeling involves a complex interplay between DNA secondary structures and covalent cytosine modifications, yet predicting endogenously folded, chromatin-constrained G-quadruplex (G4) dynamics remains challenging. Here, we develop G4SCOPE, a multi-task deep learning framework that models chromatin-associated G4 occupancy and reconstructs quantitative high-resolution CUT&Tag profiles directly from primary DNA sequence alone. We initially trained G4SCOPE on genotype-stratified G4 enriched cut&tag landscapes generated across an isogenic series of human breast epithelial cells (WT, TP53-/-, TP53-/-;BRCA1-/-, and TP53-/-;BRCA2-/-). G4SCOPE integrates convolutional motif learning with transformer self-attention to decode long-range sequence contexts. The model robustly distinguishes chromatin-associated G4s from GC-matched loci with intrinsic in vitro folding potential, generalizes across distinct breast lineages, and transfers accurately to an independent K562 cellular context. Strikingly, genotype-resolved mapping reveals a profound divergence in genome maintenance states: BRCA1 deficiency indicated a global inflation of chromatin-embedded G4 density, whereas BRCA2 loss was associated with systemic, chromosome-wide structural depletion. Furthermore, unsupervised clustering of model-derived latent sequence representations identified distinct biological G4 subclasses that occupy unique regulatory class genomic environments associated with distinct local 5-methylcytosine and 5-hydroxymethylcytosine landscapes. Together, our framework decodes the primary sequence grammar governing cell-based G4 occupancy and demonstrates that sequence-defined G4 topologies harbor intrinsic and distinct local epigenetic features.
ER  -

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