BOLE: A Knowledge-Enhanced Multi-Agent Framework for Intelligent Genomic Breeding

Abstract

Genomic breeding has become increasingly data-intensive, yet the practical integration of heterogeneous bioinformatics tools into coherent analytical workflows remains a major bottleneck. To address this, we present BOLE, a knowledge-enhanced multi-agent AI framework for autonomous genomic breeding analysis. By integrating a structured script knowledge base with constrained large language model reasoning, BOLE translates high-level analytical intent into validated and executable workflows. Specialized agents collaboratively perform intent interpretation, task decomposition, dependency reasoning, workflow synthesis, and controlled code generation to assemble validated, executable workflows without predefined pipelines. BOLE supports core genomic breeding tasks, including genome-wide association studies, heritability estimation, germplasm evaluation, and genomic selection while preserving artifact-level provenance to ensure reproducibility. Implemented as a web service, BOLE enables end-to-end genomic breeding analysis from raw data to actionable results for non-expert users. This work establishes a generalizable paradigm in which knowledge-driven multi-agent AI bridges the gap between mature analytical methods and their real-world application in genomic breeding.