bioRxivGenomicsPreprint
Agro-STARR-seq enables in planta genome-wide enhancer discovery and AI-empowerd enhancer design
Yongzhou Bao, Xiwen Zhang, Yanwei Song, Huiming LiiD, Junyan Qi, Hongqiu Cui, Na LiiD, Yun CheniD, Weigang ZhengiD, Lingna Xu, Yuanyuan ZhangiD, Choulin Chen, Fangjie ZhuiD, Shaoqun ZhouiD, Zhaohong LiiD, Yuwen Liu
Abstract
Comprehensive enhancer screening is essential for dissecting gene regulatory networks. However, methods for such screening remain limited in plants. We present Agro-STARR-seq, an in planta enhancer screening platform using Agrobacterium-mediated delivery of STARR-seq libraries into Nicotiana benthamiana leaves. In the Arabidopsis genome, we identified 14,715 sequences with enhancer activity, of which 91.59% were located outside of open chromatin regions. This largest in planta enhancer dataset to date enabled AI-assisted design of highly active synthetic enhancers. For the large N. benthamiana genome, we pre-processed the genomic DNA with an Assay for Transposase Accessible Chromatin (ATAC) procedure before the Agro-STARR-seq protocol,and found that only one-third of open chromatin exhibited enhancer activity, 76.00% of which showed no canonical H3K27ac histone marks. Footprinting analysis further enables systematic linkage of transcription factor (TF) binding to enhancer function. Overall, Agro-STARR-seq provides a novel platform for dissecting and engineering plant enhancers.
- organism: Arabidopsis
- assay: DNA methylation
- assay: ATAC-seq
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 0
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