five

NanoDam Profiling of EGL-43 in the Anchor Cell

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE232946
下载链接
链接失效反馈
官方服务:
资源简介:
Depending on the cellular context, TF expression can vary dramatically both spatially and temporally. These differences in expression patterns can result in tissue-specific differences in TF binding to downstream targets. To identify targets on a tissue-specific basis, Targeted DamID (TaDa) has been recently introduced to generate TF binding profiles in various models including C. elegans. However, TaDa suffers from portability such that a new promoter-TF fusion transgene must be constructed for every new experimental condition of interest. Here, we adapt NanoDam for usage in C. elegans, which relies on the use of endogenous TF-GFP knock-ins, a plethora of which have already been generated by the community. We report that NanoDam single copy transgenes consisting of lowly expressed, tissue-specific GFP nanobody-Dam fusions, when combined with endogenous GFP-tagged alleles of TFs, results in robust, tissue-specific profiling. Using an endogenous GFP-tagged allele of EGL-43/EVI1, we performed NanoDam profiling of two disparate tissue types, the anchor cell (AC) and dopaminergic neurons, and identify targets unique to each and shared by both cell types. We also identify two GATA TFs, ELT-6 and EGL-18, as novel regulators of AC invasion. Taken together, we demonstrate that NanoDam is capable of profiling endogenous GFP-tagged TFs to identify novel downstream targets in specific cell types of C. elegans. A single copy insertion of an Anchor Cell promoter driving expression of a GFP nanobody fused to Dam methylase was crossed together with animals carrying endogenous EGL-43::GFP. Dam methylase permanently methylated DNA in close proximity to regions of TF binding. DNA from L3 worms was extracted, digested with DpnI, amplified, and sequenced using the MinION Nanopore platform
创建时间:
2023-06-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作