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

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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Publication Details

Journal
Advanced Science
Published
2026-01-04
DOI
https://doi.org/10.1002/advs.202516600
Citations
1
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
22.24

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article

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

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1 citations
Advanced Science
CRISPR and Genetic Engineering
22.24
article

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

Qi Ming Deng, Yufeng Liu, Dating Zhong, Dequan Wang, Lingling Gao, Qi Yao, Lu Ye, Qianlan Yin, Peijin Han, Xiaofeng Yang, Keling Wang, Yuming Lu, Hong Pan, Xiaoyu Tu, Jin Gao
article en
1 citations

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.

Advanced ScienceVol. 13(13)
South China Agricultural University (CN), Shanghai Jiao Tong University (CN), Shanghai Innovative Research Center of Traditional Chinese Medicine (CN), Kai Biotech (South Korea) (KR)
Natural Science Foundation of Shanghai, National Natural Science Foundation of China, Agricultural Science and Technology Innovation Program
Openalex Percentile: Top 3%
CRISPR and Genetic Engineering
22.24
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