Subcellular level spatial transcriptomics with PHOTON

The subcellular localization of RNA is closely linked to its function. Many RNA species are partitioned into organelles and other subcellular compartments for storage, processing, translation, or degradation. Thus, capturing the subcellular spatial distribution of RNA would directly contribute to the understanding of RNA functions and regulation. Here, we present PHOTON, a method which combines high resolution imaging with high throughput sequencing to achieve spatial transcriptome profiling at subcellular resolution. We demonstrate PHOTON as a versatile tool to accurately capture the transcriptome of target cell types in situ at the tissue level such as granulosa cells in the ovary, as well as RNA content within subcellular compartments such as the nucleoli, the mitochondria, and the stress granules. Using PHOTON, we also reveal the functional role of m<sup>6</sup>A modifications on mRNA partitioning into stress granules. These results collectively demonstrate that PHOTON is a flexible and generalizable platform for understanding subcellular molecular dynamics through the transcriptomic lens.

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Publication Details

Journal
Nature Communications
Published
2025-05-14
DOI
https://doi.org/10.1038/s41467-025-59801-3
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.00

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article

Subcellular level spatial transcriptomics with PHOTON

Qiqi Cao, Haiqi Chen, Sarah Mangiameli, Shreya Rajachandran et al.
Nature Communications
RNA modifications and cancer
article

Subcellular level spatial transcriptomics with PHOTON

Qiqi Cao, Haiqi Chen, Sarah Mangiameli, Shreya Rajachandran, Qianlan Xu, Xin Zhang, Fei Chen
article en

Abstract

The subcellular localization of RNA is closely linked to its function. Many RNA species are partitioned into organelles and other subcellular compartments for storage, processing, translation, or degradation. Thus, capturing the subcellular spatial distribution of RNA would directly contribute to the understanding of RNA functions and regulation. Here, we present PHOTON, a method which combines high resolution imaging with high throughput sequencing to achieve spatial transcriptome profiling at subcellular resolution. We demonstrate PHOTON as a versatile tool to accurately capture the transcriptome of target cell types in situ at the tissue level such as granulosa cells in the ovary, as well as RNA content within subcellular compartments such as the nucleoli, the mitochondria, and the stress granules. Using PHOTON, we also reveal the functional role of m<sup>6</sup>A modifications on mRNA partitioning into stress granules. These results collectively demonstrate that PHOTON is a flexible and generalizable platform for understanding subcellular molecular dynamics through the transcriptomic lens.

Nature CommunicationsVol. 16(1)
Broad Institute (US), Harvard University (US), Southwestern Medical Center (US), The University of Texas Southwestern Medical Center (US)
National Institutes of Health, National Human Genome Research Institute
Zero hunger
Openalex Percentile: Top 90%
RNA modifications and cancer
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