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APEX-seq Maps Transcriptome-wide Subcellular RNA Localization in Living Cells

GSE299592 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2026/01/09 Platform GPL34284Platform GPL20301
Summary
Although we know a great deal about the subcellular location of most proteins, our knowledge of where most RNAs localize within cells remains limited. As RNA subcellular localization determines the fate, function, and regulation of both coding and non-coding RNAs , there has been substantial interest in developing new scalable approaches to study the location of RNAs in their native context. Furthermore, many locations, such as membrane-bound and membrane-less organelles, have traditionally been challenging to study due to lack of suitable tools to interrogate their constituents. Here, we describe a detailed protocol for APEX-seq that yields transcriptome-wide information of the subcellular address of RNAs that can, in principle, be applied to any subcellular location, membrane, or condensate. APEX-seq utilizes a genetically-encoded engineered ascorbate peroxidase (APEX2) tagged to a specific protein that localizes it to a region of interest. In the presence of biotin-phenol (BP) and hydrogen peroxide, APEX2 catalyzes the biotinylation of RNAs in its vicinity, which can be purified using streptavidin beads and sequenced to reveal the RNA repertoire at that subcellular location. APEX-seq experiments can be carried out by laboratory personnel trained in molecular biology. The analysis of APEX-seq data requires familiarity with standard RNA-seq workflows. With APEX2-expressing cell lines in hand, the entire procedure from labeling reaction to analysis can be completed in one week. We expect this proximity labeling approach to facilitate the unbiased discovery of RNAs localizing to different organelles and to generate hypotheses for the mechanisms and pathways involved in regulating these processes.
Published in
APEX-seq maps transcriptome-wide subcellular RNA localization in living cells
Sharma S, Rasband ME, Wang X et al. · Nature protocols 2026 · PMID 41927971 · doi:10.1038/s41596-026-01342-0
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Also filed as BioProject PRJNA1275032 and SRA study SRP591425. Searching any of these in the dataset finder brings you back here.

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