Sequence-based modeling of plant epigenomes reveals cell-type-specific cis-regulatory grammar
Yao, J.; Li, J.; Zhang, X.; Li, X.; Marand, A. P.; Pickering, E.; Schmitz, R. J.
Show abstract
How cis-regulatory sequences and their genetic variation govern chromatin accessibility, regulate gene expression, and the establishment of plant cell identities, making them fundamental to development, environmental responses, and phenotypic diversity. Here we present PEAgent, a framework for training, evaluating and interpreting deep-learning models that predict single-cell chromatin accessibility directly from DNA sequence, packaged in an interactive web portal and toolkit. Models were trained on single-cell chromatin-accessibility atlases of soybean, maize and rice, together spanning over 355,000 cells and 320 cell types and [~]150 million years of evolution. We unraveled a lexicon of 243 cell-type-resolved regulatory patterns, half of them composite, with TCP and bHLH showing the greatest influence and strongest conservation across species. Co-occurrence and in silico synergy analyses, explicitly modeling motif orientation and spacing, revealed two distinct cooperative modes acting at short and nucleosome-scale distances. We further showed that model predictions distinguish grass-conserved from rice-specific regulatory sequences far more accurately than sequence conservation scores alone, and validated the models predicted variant effects against cell-type-level chromatin accessible QTLs. PEAgent provides a foundational resource for decoding cell-type-specific plant cis-regulatory logic and interpreting noncoding variation in plants. HighlightsO_LIPEAgent predicts single-cell chromatin accessibility directly from DNA sequence in soybean, rice and maize. C_LIO_LINearly half of cell-type-resolved patterns are composite, with TCP and bHLH motifs most influential and conserved across species. C_LIO_LICo-occurrence and synergy analysis reveals distinct cooperative grammar at short and nucleosome-scale distances. C_LIO_LIPEAgent distinguishes grass-conserved from lineage-specific regulatory sequences better than sequence conservation scores alone. C_LI
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The 3D architecture of the pepper (Capsicum annum) genome and its relationship to function and evolution 98%
- MaizeCODE reveals bi-directionally expressed enhancers that harbor molecular signatures of maize domestication. 98%
- Fine-mapping of nuclear compartments using ultra-deep Hi-C shows that active promoter and enhancer elements localize in the active A compartment even when adjacent sequences do not 97%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms 97%
- scDALI: Modelling allelic heterogeneity of DNA accessibility in single-cells reveals context-specific genetic regulation 97%
- An interpretable bimodal neural network characterizes the sequence and preexisting chromatin predictors of induced TF binding 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.