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.
Authors
- Qi Ming Deng
- Yufeng Liu (ORCID: https://orcid.org/0009-0003-6285-7819)
- Dating Zhong
- Dequan Wang (ORCID: https://orcid.org/0000-0003-3931-5133)
- Lingling Gao (ORCID: https://orcid.org/0000-0002-9965-6952)
- Qi Yao (ORCID: https://orcid.org/0000-0002-9813-4650)
- Lu Ye
- Qianlan Yin
- Peijin Han
- Xiaofeng Yang
- Keling Wang
- Yuming Lu
- Hong Pan
- Xiaoyu Tu
- Jin Gao
Institutions
- South China Agricultural University (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai Innovative Research Center of Traditional Chinese Medicine (CN)
- Kai Biotech (South Korea) (KR)
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
Funders
- Natural Science Foundation of Shanghai
- National Natural Science Foundation of China
- Agricultural Science and Technology Innovation Program