Creator 1.0: Phylogeny-Guided Stagewise Pretraining for Plant Genome Foundation Models across 1,000 Species
Lin YangiD, Sirong JiangiD, Yubo LiiD, Meiling ZouiD, Yu XiaiD, Lu Wang, Yingdong Wu, Hao Wang, Wei Xie, Zhiqiang XiaiD
Abstract
Genomic language models have advanced DNA sequence analysis, but their applicability to plant-specific tasks and representation changes during pretraining remain poorly characterized. Here, we present Creator 1.0, a 2-billion-parameter parameter plant genome foundation model pretrained on 1,000 plant genomes using phylogeny-guided stagewise pretraining (PGSP). Training comprised 83 consecutive stages and produced 52 cumulative checkpoints associated with distinct plant orders. On GENEB, the stage 83 checkpoint ranked first among 46 models across 10 plant-related tasks, with a mean Matthews correlation coefficient (MCC) of 0.565, and fourth across all 100 tasks. Evaluation of 52 checkpoints on six plant lncRNA tasks identified different optimal stages under full-data, 10-shot and 1-shot settings, corresponding to stages 71, 72 and 29, respectively. Checkpoint performance varied across tasks, without consistent advantages for corresponding plant orders. These findings demonstrate the competitive performance of Creator 1.0 and highlight the potential of PGSP to provide task-adaptable checkpoints for plant genomic applications.
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