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Related Experiment Video

Updated: Dec 15, 2025

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Simple and efficient profiling of transcription initiation and transcript levels with STRIPE-seq.

Robert A Policastro¹, R Taylor Raborn¹, Volker P Brendel^1,2

¹Department of Biology.

Genome Research

|July 15, 2020

Summary

This summary is machine-generated.

We developed STRIPE-seq, a fast and affordable method for mapping transcription start sites (TSSs) using capped RNA sequencing. This technique simplifies TSS profiling and gene expression analysis in various cell types.

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Published on: March 12, 2017

Area of Science:

Molecular Biology
Genomics
Transcriptomics

Background:

Accurate mapping of transcription start sites (TSSs) is crucial for understanding gene regulation.
Existing genome-wide TSS profiling methods are often time-consuming and costly.

Purpose of the Study:

To introduce STRIPE-seq, a novel, simple, rapid, and cost-effective protocol for high-throughput sequencing of capped RNA 5' ends.
To enable efficient TSS profiling from minimal RNA input.

Main Methods:

STRIPE-seq (Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing) protocol development.
Depletion of uncapped RNA and library construction within approximately 5 hours.
Application in yeast and human cell lines.

Main Results:

STRIPE-seq successfully profiles genome-wide TSSs.
The protocol requires as little as 50 ng of total RNA.
STRIPE-seq also enables transcript quantification and differential gene expression analysis.

Conclusions:

STRIPE-seq offers a straightforward and efficient method for probing transcriptional initiation landscapes.
The protocol is cost-effective and rapid, making TSS profiling more accessible.
Integrated computational workflows facilitate data analysis.