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

Publisher: WILEY-VCH Country of Publication: Germany NLM ID: 101664569 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2198-3844 (Electronic) Linking ISSN: 21983844 NLM ISO Abbreviation: Adv Sci (Weinh) Subsets: MEDLINE

Original Publication: Weinheim : WILEY-VCH, [2014]-

Crops, Agricultural*/genetics ; Enhancer Elements, Genetic*/genetics ; Genetic Engineering*/methods; Plants, Genetically Modified/genetics ; Zea mays/genetics ; Gene Expression Regulation, Plant/genetics ; Triticum/genetics ; Solanum lycopersicum/genetics

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.
(© 2026 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

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K2025001 Shanghai Agricultural Science and Technology Innovation Program; 2021YFD1201300 National Key R&D Program of China; GZB20250924 Postdoctoral Fellowship Program of CPSF; 32501966 National Natural Science Foundation of China; 25ZR1402271 Natural Science Foundation of Shanghai

Keywords: AI‐driven design; cis‐regulatory elements; crop improvement; genome‐wide screening

Date Created: 20260105 Date Completed: 20260307 Latest Revision: 20260307

20260307

PMC12955884

10.1002/advs.202516600

41486594