一种具有成本效益的 tsCUT&Tag 方法，用于分析转录因子结合景观。

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

机构信息

National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.

The National Engineering Laboratory of Crop Resistance Breeding, School of Life Sciences, Anhui Agricultural University, Hefei, 230036, China.

出版信息

J Integr Plant Biol. 2022 Nov;64(11):2033-2038. doi: 10.1111/jipb.13354. Epub 2022 Oct 4.

DOI:10.1111/jipb.13354

PMID:36047457

Abstract

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.

摘要

了解转录因子结合景观（TFBL）对于分析重要农艺性状的基因调控网络是必要的。然而，在植物中仍然缺乏一种低成本、高通量的体内染色质分析方法。在这里，我们开发了一种瞬时和简化的靶向切割和标签化（tsCUT&Tag）方法，该方法将转录因子蛋白在原生质体中的瞬时表达与简化的 CUT&Tag 结合在一起，而无需细胞核提取。与传统的 ChIP-seq 相比，我们的 tsCUT&Tag 方法在较低的测序深度下提供了更高的数据质量和信号分辨率。此外，我们开发了一种将 tsCUT&Tag 与机器学习相结合的策略，该策略在植物发育过程中的 TFBL 分析方面具有很大的潜力。