J Integr Plant Biol. ›› 2022, Vol. 64 ›› Issue (11): 2033-2038.DOI: 10.1111/jipb.13354

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A cost-effective tsCUT&Tag method for profiling transcription factor binding landscape

Leiming Wu1,2†, Zi Luo1†, Yanni Shi1, Yizhe Jiang1, Ruonan Li1, Xinxin Miao1, Fang Yang1, Qing Li1, Han Zhao3, Jiquan Xue4, Shutu Xu4, Tifu Zhang3* and Lin Li1,5*   

  1. 1 National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
    2 The National Engineering Laboratory of Crop Resistance Breeding, School of Life Sciences, Anhui Agricultural University, Hefei 230036, China
    3 Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
    4 The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling 712100, China
    5 Hubei Hongshan Laboratory, Wuhan 430070, China

    These authors contributed equally to this article.
    *Correspondences: Lin Li (hzaulilin@mail.hzau.edu.cn, Dr. Li is responsible for the distribution of the materials associated with this article); Tifu Zhang (zhangtifu@jaas.ac.cn)
  • Received:2022-05-11 Accepted:2022-08-25 Online:2022-09-01 Published:2022-11-01


Knowledge of the transcription factor binding landscape (TFBL) is necessary to analyze gene regulatory networks for important agronomic traits. However, a low-cost and high-throughput in vivo chromatin profiling method is still lacking in plants. Here, we developed a transient and simplified cleavage under targets and tagmentation (tsCUT&Tag) that combines transient expression of transcription factor proteins in protoplasts with a simplified CUT&Tag without nucleus extraction. Our tsCUT&Tag method provided higher data quality and signal resolution with lower sequencing depth compared with traditional ChIP-seq. Furthermore, we developed a strategy combining tsCUT&Tag with machine learning, which has great potential for profiling the TFBL across plant development.

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