AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This study provides a resource for redefining precision-breeding paradigms by harnessing cryptic 3D chromatin targets by decoupling sequence-level from chromatin-level selection and shifting the subgenome expression balance of 39 homoeologs in cultivated cotton.
Flowering plants (angiosperms) exhibit extraordinary species diversity, ∼200-fold variation in genome size, and relatively compact coding regions, presenting both a unique challenge and opportunity for DNA language models. Here, we introduce PlantCAD2, an extended-context, plant-specific DNA language model with single-nucleotide resolution, pre-trained on 65 angiosperm genomes, together with a series of public benchmarks for evaluation. Comprehensive zero-shot testing shows that PlantCAD2 (676 million parameters) efficiently captures evolutionary conservation, surpassing the 7-billion-parameter Evo2 in 10 of 12 tasks. With parameter-efficient fine-tuning, PlantCAD2 outperforms the 1-billion-parameter AgroNT across seven cross-species tasks including chromatin accessible region, gene expression, and protein translation. Its 8,192-bp context window substantially improves accessible chromatin prediction in large genomes such as maize (area under the precision-recall curve [AUPRC] increasing from 0.587 to 0.711), underscoring the importance of long-range context for modeling distal regulation. These results establish PlantCAD2 as a powerful and versatile foundation model for plant genome annotation and interpretation across diverse species.
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