Quantification of mRNA Turnover in Living Cells: A Pipeline for TREAT Data Analysis
mRNA turnover plays an important role in the regulation of post-transcriptional gene expression. While many protein factors involved in mRNA degradation have been identified, we still lack a basic understanding of the principles that regulate the spatiotemporal dynamics of mRNA turnover within single cells. To overcome this limitation, we have developed the TREAT biosensor, which allows for discrimination of intact reporter transcripts and stabilized decay intermediates using single RNA imaging. Here, we present an image analysis pipeline that performs semiautomated detection and tracking of individual mRNA particles. It colocalizes tracks and applies the colocalization information to quantify the number of intact transcripts and degradation intermediates. Based on the analysis of control data, the workflow further determines detection efficiencies and uses them to correct RNA particle numbers.
Key wordsmRNA turnover TREAT MS2/PP7 stem-loops Fluorescence microscopy Live cell imaging Single-molecule
The authors would like to thank all members of the Chao lab for their joint efforts in developing the TREAT assay. In particular, we thank Ivana Horvathova for generation of the reporter transcripts. We further thank the Facility for Advanced Imaging and Microscopy at FMI for data acquisition and analysis support. Research in the Chao lab is funded by the Novartis Research Foundation (J.A.C.), a Swiss National Science Foundation (SNF) grant 31003A_182314 (J.A.C.), the SNF-NCCR RNA & Disease (J.A.C.), and an SNF Marie Heim-Vögtlin fellowship (F.V.).
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