Ribosome-tethered in situ sequencing for single-cell translatome analysis
TL;DR
Ribo-ISS provides a scalable framework for investigating spatially organized translational programs and expands the capability of spatial omics toward understanding gene regulation beyond transcription, as an imaging-based spatial translatomics technology that enables high-throughput mapping of ribosome-associated mRNAs in intact tissues.
Abstract
Translational regulation plays a critical role in shaping cellular states and functions, yet approaches for spatially resolved translatome profiling at single-cell resolution remain limited. Here, we develop Ribosome-tethered In Situ Sequencing (Ribo-ISS), an imaging-based spatial translatomics technology that enables high-throughput mapping of ribosome-associated mRNAs in intact tissues. Ribo-ISS integrates ribosome-dependent molecular anchoring with multiplexed in situ sequencing, allowing specific detection of translation-associated transcripts without genetic manipulation or exogenous ribosome labeling. We demonstrate that Ribo-ISS achieves high specificity and enables single-cell spatial translatome profiling in mouse brain, accurately recapitulating major cell types and their anatomical organization. Applied to a sleep deprivation model, Ribo-ISS simultaneously resolved transcriptional and translational changes, revealing extensive transcription-translation uncoupling and distinct cell-type-specific translational responses. Ribo-ISS provides a scalable framework for investigating spatially organized translational programs and expands the capability of spatial omics toward understanding gene regulation beyond transcription. Graphical Abstract Ribo-ISS integrates ribosome-dependent molecular anchoring with multiplexed in situ sequencing, enabling specific detection of ribosome-bound transcripts in intact tissues without genetic manipulation or exogenous labeling. As an imaging-based spatial translatomics technology, it resolves translatome profiling at single-cell resolution. This scalable approach reveals spatial translational programs, extending spatial omics beyond transcription.