文献类型： 外文期刊
作者： Wu, Leiming 1 ; Luo, Zi 1 ; Shi, Yanni 1 ; Jiang, Yizhe 1 ; Li, Ruonan 1 ; Miao, Xinxin 1 ; Yang, Fang 1 ; Li, Qing 1 ; Zhao, Han 3 ; Xue, Jiquan 4 ; Xu, Shutu 4 ; Zhang, Tifu 3 ; Li, Lin 1 ;
作者机构： 1.Huazhong Agr Univ, Hubei Hongshan Lab, Natl Key Lab Crop Genet Improvement, Wuhan 430070, Peoples R China
2.Anhui Agr Univ, Sch Life Sci, Natl Engn Lab Crop Resistance Breeding, Hefei 230036, Peoples R China
3.Jiangsu Acad Agr Sci, Inst Germplasm Resources & Biotechnol, Jiangsu Prov Key Lab Agrobiol, Nanjing 210014, Peoples R China
4.Northwest A&F Univ, Minist Agr, Key Lab Biol & Genet Improvement Maize Arid Area, Yangling 712100, Shaanxi, Peoples R China
5.Hubei Hongshan Lab, Wuhan 430070, Peoples R China
关键词： binding sites; ChIP-seq; CUT&Tag; machine learning; transcription factor; transient expression
期刊名称：JOURNAL OF INTEGRATIVE PLANT BIOLOGY （ 影响因子：9.106； 五年影响因子：8.241 ）
ISSN： 1672-9072
年卷期： 2022 年 64 卷 11 期
页码：
收录情况： SCI
摘要： 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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