Optimized reporters for multiplexed detection of transcription factor activity.

Cell systems Pub Date : 2024-12-18 Epub Date: 2024-12-06 DOI:10.1016/j.cels.2024.11.003
Max Trauernicht, Teodora Filipovska, Chaitanya Rastogi, Bas van Steensel
{"title":"Optimized reporters for multiplexed detection of transcription factor activity.","authors":"Max Trauernicht, Teodora Filipovska, Chaitanya Rastogi, Bas van Steensel","doi":"10.1016/j.cels.2024.11.003","DOIUrl":null,"url":null,"abstract":"<p><p>In any given cell type, dozens of transcription factors (TFs) act in concert to control the activity of the genome by binding to specific DNA sequences in regulatory elements. Despite their considerable importance, we currently lack simple tools to directly measure the activity of many TFs in parallel. Massively parallel reporter assays (MPRAs) allow the detection of TF activities in a multiplexed fashion; however, we lack basic understanding to rationally design sensitive reporters for many TFs. Here, we use an MPRA to systematically optimize transcriptional reporters for 86 TFs and evaluate the specificity of all reporters across a wide array of TF perturbation conditions. We thus identified critical TF reporter design features and obtained highly sensitive and specific reporters for 62 TFs, many of which outperform available reporters. The resulting collection of \"prime\" TF reporters can be used to uncover TF regulatory networks and to illuminate signaling pathways. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"1107-1122.e7"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11667439/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2024.11.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/6 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In any given cell type, dozens of transcription factors (TFs) act in concert to control the activity of the genome by binding to specific DNA sequences in regulatory elements. Despite their considerable importance, we currently lack simple tools to directly measure the activity of many TFs in parallel. Massively parallel reporter assays (MPRAs) allow the detection of TF activities in a multiplexed fashion; however, we lack basic understanding to rationally design sensitive reporters for many TFs. Here, we use an MPRA to systematically optimize transcriptional reporters for 86 TFs and evaluate the specificity of all reporters across a wide array of TF perturbation conditions. We thus identified critical TF reporter design features and obtained highly sensitive and specific reporters for 62 TFs, many of which outperform available reporters. The resulting collection of "prime" TF reporters can be used to uncover TF regulatory networks and to illuminate signaling pathways. A record of this paper's transparent peer review process is included in the supplemental information.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
优化的转录因子活性多重检测报告。
在任何给定的细胞类型中,数十个转录因子(TFs)通过结合调控元件中的特定DNA序列来协同控制基因组的活性。尽管它们相当重要,但我们目前缺乏简单的工具来直接并行测量许多tf的活性。大规模并行报告分析(MPRAs)允许以多路方式检测TF活动;然而,我们缺乏基本的认识,以合理地设计敏感的报告许多tf。在这里,我们使用MPRA系统地优化了86个TF的转录报告,并评估了各种TF扰动条件下所有报告的特异性。因此,我们确定了关键的TF报告器设计特征,并获得了62个TF的高灵敏度和特异性报告器,其中许多报告器的性能优于现有报告器。由此产生的“主要”TF报告者的集合可用于揭示TF调控网络并阐明信号通路。本文的透明同行评议过程记录包含在补充信息中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Subspecies phylogeny in the human gut revealed by co-evolutionary constraints across the bacterial kingdom. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome. Stochastic modeling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones. Active learning of enhancers and silencers in the developing neural retina. Contrastive learning of T cell receptor representations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1