five

Efficient and sensitive profiling of RNA-protein interactions using TLC-CLIP [dataset 2]

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE225357
下载链接
链接失效反馈
官方服务:
资源简介:
RNA-binding proteins are instrumental for post-transcriptional gene regulation, yet transcriptome-wide methods to profile RNA-protein interactions remain technically challenging. We present an improved library preparation strategy for cross-linking and immunoprecipitation (CLIP) that involves tailing and ligation of cDNA molecules (TLC) for increased sensitivity and efficiency. TLC-CLIP eliminates time-consuming purifications, reduces sample loss, and minimises experimental steps, allowing precise profiling of RNA-protein interactions from limited starting material at nucleotide resolution. We have generated benchmarking libraries for 4 well-studied RNA-binding proteins from 50.000 293T cells in duplicates, including additional control samples comparing different RNase concentrations, additional adapter removal, omitting PAGE purification and profiling of co-purifying fragments from non-crosslinked samples. We further demonstrate the high sensitivity of our protocol by profiling hnRNPc and RBFOX2 from only 10,000 and 1,000 cells. To integrate our CLIP data with functionally relevant sites we have performed RNA-Seq in 293T knockout cells for RBFOX2 to identify alternatively spliced exons.

RNA结合蛋白(RNA-binding proteins)在转录后基因调控中具有核心作用,但用于解析RNA-蛋白质相互作用的全转录组方法仍存在技术难题。本研究提出一种针对交联免疫沉淀(cross-linking and immunoprecipitation,CLIP)的优化文库制备策略,该策略通过cDNA分子加尾与连接(tailing and ligation of cDNA molecules,TLC)技术提升了检测灵敏度与实验效率。TLC-CLIP省去了耗时的纯化步骤,减少了样品损失,同时简化了实验流程,可从微量起始材料中以核苷酸分辨率精准解析RNA-蛋白质相互作用。我们针对4种研究较为深入的RNA结合蛋白构建了基准文库,起始材料为50000个293T细胞,设置了生物学重复,同时包含多组对照样本:对比不同核糖核酸酶浓度的样本、额外增设接头移除步骤的样本、省略聚丙烯酰胺凝胶电泳(PAGE)纯化的样本,以及对非交联样品的共纯化片段进行解析的样本。此外,我们仅使用10000个和1000个293T细胞分别解析hnRNPc与RBFOX2,验证了本实验方案的高灵敏度。为将CLIP数据与功能相关位点进行整合,我们对RBFOX2敲除的293T细胞开展了RNA测序(RNA-Seq),以鉴定可变剪接外显子。
创建时间:
2023-09-12
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