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February 5, 2026GigaScience2 citationsOpen Access

Single-nucleus multiple-organ chromatin accessibility landscape in the adult rat

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RLRonghai LiSDShanshan DuanQDQiuting Deng

Key Points

  • The aim is to create a detailed chromatin accessibility landscape in adult rats to understand gene expression at the single-cell level.
  • Generated a multi-organ chromatin accessibility landscape using snATAC-seq from 110,000 individual rat cells.
  • Constructed 25 libraries from nine different organs in Rattus norvegicus.
  • Classified cells using gene activity scores combined with marker genes to identify 77 distinct cell types.
  • Identified 77 cell types correlated with those in mouse single-cell atlases, indicating conservation of cell classification.
  • Highlighted organ-specific features of endothelial and stromal cells as well as shared characteristics across organs.
  • Provided a foundation for understanding tissue-specific regulatory mechanisms and cross-species cell type annotation.

Abstract

Abstract The chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multi organ, single-nucleus chromatin accessibility landscape from the model organism Rattus norvegicus. For this single-cell atlas, we constructed 25 libraries via snATAC-seq from nine organs in the rat, with a total of over 110,000 cells. Cell classification integrating gene activity scores with known marker genes identified 77 cell types, which were strongly correlated with those in published mouse single-cell transcriptome atlases. We further investigated the enrichment of cell type- and organ-specific transcription factors (TFs), Shared and organ-specific features of endothelial and stromal cells, as well as cross-organ macrophage regulatory states, and the conservation and specificity of gene regulatory programs across species. Together, these findings provide a valuable foundation for dissecting tissue-specific regulatory logic and for advancing cross-organ and cross-species cell type annotation and functional inference in the rat model.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69843543f1d9ada3c1fb3dc1https://doi.org/10.1093/gigascience/giag013
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