From Natural Discovery to AI-Guided Design: A Curated Collection of Compact Enhancers for Crop Engineering

从自然发现到人工智能引导设计:精选作物工程紧凑型增强剂系列

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Abstract

Precise transgene-free gene upregulation remains a challenge in crop biotechnology, as conventional enhancers often exceed CRISPR-mediated knock-in size constraints and face regulatory hurdles. Here we establish a foundational cross-species resource of compact transcriptional enhancers developed via STEM-seq, a high-throughput screening platform that systematically evaluated 81 475 genomic elements across maize, wheat, tomato, and soybean. This screen identified 6904 natural short transcriptional enhancers (STEs; 60-80 bp) exhibiting a broad range of activation efficiencies, with the most potent elements derived from wheat (up to 46.3-fold activation). Augmenting this resource, we developed BaseSearch, an AI-driven design framework, which computationally generated 5000 synthetic STE candidates and achieved a 9.1% success rate (11.4× higher than genome-wide screening). This set included ten ultra-potent enhancers outperforming natural counterparts by 2.27-fold (64.5-fold vs. 28.4-fold activation). Notably, the compact size of these STEs aligns with regulatory frameworks that favor endogenous sequence lengths, offering potential pathways for policy-compatible precision breeding. This integrated platform provides a substantial collection of functionally validated enhancers for crops, supplying the research community with immediately applicable elements for engineering agronomic traits while advancing the fundamental understanding of plant cis-regulation.

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