仿形(计算机编程)
计算生物学
生物
多路复用
细胞生物学
政治学
计算机科学
电信
操作系统
作者
Simón Álamos,Lucas Waldburger,Amanda Dee,Lauren A. Owens,Rameshwar Singh Rattan,S.-E. Ong,Patrick M. Shih
标识
DOI:10.1101/2025.05.12.653590
摘要
Abstract Transcriptional regulators play key roles in plant growth, development, and environmental responses; however, understanding how their regulatory activity is encoded at the protein level has been hindered by a lack of multiplexed large–scale methods to characterize protein libraries in planta . Here, we present ENTRAP-seq (Enrichment of Nuclear Trans -elements Reporter Assay in Plants), a high-throughput method that introduces protein-coding libraries into plant cells to drive a nuclear magnetic sorting-based reporter, enabling multiplexed measurement of regulatory activity from thousands of protein variants. Using ENTRAP-seq and machine learning, we screened 1,495 plant viruses and identified hundreds of novel putative transcriptional regulatory domains found in structural proteins and enzymes not associated with gene regulation. In addition, we combined ENTRAP-seq with machine-guided design to engineer the activity of a plant transcription factor in a semi-rational fashion. Our findings demonstrate how scalable protein function assays deployed in planta will enable the characterization of natural and synthetic coding diversity in plants.
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