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<p>Subcellular RNA localization, including nuclear retention and apical-basal compartmentalization in polarized epithelia plays a central role in post-transcriptional regulation. However, methods for high-throughput mapping of mRNA localization within intact tissue sections remain limited. Here, we apply high-resolution spatial transcriptomics to systematically resolve intracellular mRNA localization across diverse mammalian tissues. We introduce a computational approach that leverages image-derived features to extract subcellular information from spatial data and quantifies transcript localization patterns. Using this framework, we map apical-basal mRNA localization and nuclear retention in gastrointestinal epithelia and in liver hepatocytes. Our analyses reveal conserved and tissue-specific localization signatures. This approach broadens the scope of spatial transcriptomics by enabling routine investigation of intracellular RNA distributions in both healthy and diseased tissues.</p>

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Subcellular mRNA localization patterns across tissues resolved with spatial transcriptomics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月20日

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  • Roy Novoselsky,
  • Ofra Golani,
  • Tal Barkai,
  • Merav Kedmi,
  • Inna Goliand,
  • Michal Fine,
  • Ilan Kent,
  • Ido Nachmany,
  • Shalev Itzkovitz

摘要

Subcellular RNA localization, including nuclear retention and apical-basal compartmentalization in polarized epithelia plays a central role in post-transcriptional regulation. However, methods for high-throughput mapping of mRNA localization within intact tissue sections remain limited. Here, we apply high-resolution spatial transcriptomics to systematically resolve intracellular mRNA localization across diverse mammalian tissues. We introduce a computational approach that leverages image-derived features to extract subcellular information from spatial data and quantifies transcript localization patterns. Using this framework, we map apical-basal mRNA localization and nuclear retention in gastrointestinal epithelia and in liver hepatocytes. Our analyses reveal conserved and tissue-specific localization signatures. This approach broadens the scope of spatial transcriptomics by enabling routine investigation of intracellular RNA distributions in both healthy and diseased tissues.