Single-nucleus multiple-organ chromatin accessibility mapping in the rat

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1. 

   GigaScience

   Feb 24, 2026

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further …

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further investigations of the cell composition and gene regulatory networks throughout the rat body.HighlightsGeneration of a single-cell atlas of chromatin accessibility in nine organs of the ratCharacterization of cell type- and organ-specific transcription factors (TFs)Dynamics of chromatin accessibility in developing T cells revealed by cross-organ analysisConservation and specificity of gene expression patterns among humans, mice, and rats revealed by cross-species analysisCompeting Interest StatementThe authors have declared no competing interest.Footnotes↵10 Lead contact

   This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giag013), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

   Reviewer 3：

   In this study, Ronghai Li and colleagues constructed an extensive multi-organ single-nucleus chromatin accessibility atlas of the model organism Rattus norvegicus. The authors generated a comprehensive dataset encompassing 115,723 single-nucleus chromatin accessibility profiles across nine organs (thyroid, thymus, heart, lung, liver, spleen, kidney, pancreas, and ovary). Each organ was profiled in duplicate or triplicate, thereby ensuring reproducibility and robustness of the dataset. The authors also performed rigorous preprocessing and filtering steps, which provided a high-quality foundation for downstream analyses.

   The downstream analyses were multifaceted and thoughtfully executed in the following steps: 1) Low-dimensional visualization of all cells within the atlas, represented by organs, which led to the identification of six major cell types; 2) A census of the distribution of major cell types across the analyzed organs; 3) Integration with existing mouse single-cell RNA-seq atlases to refine cell type annotations (77 cell subtypes) and ensure cross-species comparability; 4) Inference of transcription factor activities from open chromatin profiles, providing important insights into gene regulatory mechanisms.

   Building upon these analyses, the authors focused on shared and organ-specific features of endothelial and stromal cells, thereby highlighting both conserved and divergent regulatory programs. Finally, through integration of human, rat, and mouse scRNA- and scATAC-seq atlases for the heart and kidney, they investigated cross-species similarities and differences in gene expression and regulatory patterns, further strengthening the relevance and translational potential of this resource.

   In my opinion, the manuscript by Ronghai Li et al. is well written, the data are of very high quality, and the study represents a significant data resource. The rat (Rattus norvegicus) is a widely used and indispensable model organism in biomedical research, particularly for studies related to disease onset, progression, and therapeutic development. The generation of this single-nucleus chromatin accessibility atlas, together with the comprehensive analyses provided, constitutes a valuable resource for dissecting organ- and tissue-specific regulatory landscapes. This work not only enhances our understanding of gene regulation across organs but also facilitates cross-species comparisons that will be of great importance for translational research. I therefore strongly support acceptance of the manuscript by Ronghai Li et al. for publication in GigaScience., contingent only upon minor revisions as outlined below:

   Minor revisions:

   1. While the data preprocessing and analysis steps are clearly described in the Methods section, the code used for data analysis is currently available only upon request. I believe that future readers and, in particular, potential users of this valuable resource would greatly benefit if the analysis code were made publicly accessible. Open availability of the code would not only enhance transparency and reproducibility but also facilitate broader adoption of the dataset. This is especially important as new single-cell ATAC-seq and RNA-seq datasets become available, since ready access to the analysis pipeline will accelerate and streamline future studies that build upon the provided atlas.

   2. Line 131: Stromal cells, immune cells, and endothelial cells from different organs tend to be clustered together (i.e., by cel type) rather than clustered according to the organ of origin or sample batch (Figure 1E). and Line 137: However, these cells tended to cluster by organ rather than by cell type (Figure 1E).

   This observation can be clearly seen in the UMAPs (Figure 1C-D), but not in the census plot (Figure 1E). I therefore recommend revising the figure reference to (Figure 1C-D) to improve accuracy and clarity for the reader.

   1. Authors often assess, across manuscript, whether cells cluster in a cell type-specific or organ-specific manner. For immune and epithelial cells, however, the conclusions can be confounded, as they vary depending on the analytical method used (e.g., scATAC-seq alone versus integration with scRNA-seq data). Could the authors elaborate on the robustness of these observations with respect to the choice of UMAP parameters, particularly the number of features included and the dimensionality of the LSI applied?

   2. The authors used the CIS-BP database of transcription factor motifs to assess cell type-specific transcription factor activities. However, JASPAR, which is a curated database, is more commonly used in scATAC-seq studies. Could the authors clarify the rationale for choosing CIS-BP over JASPAR?

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2. 

   GigaScience

   Feb 24, 2026

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further …

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further investigations of the cell composition and gene regulatory networks throughout the rat body.HighlightsGeneration of a single-cell atlas of chromatin accessibility in nine organs of the ratCharacterization of cell type- and organ-specific transcription factors (TFs)Dynamics of chromatin accessibility in developing T cells revealed by cross-organ analysisConservation and specificity of gene expression patterns among humans, mice, and rats revealed by cross-species analysisCompeting Interest StatementThe authors have declared no competing interest.

   This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giag013), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

   Reviewer 2：

   In this manuscript, Li et al. present a single-nucleus rat atlas of chromatin accessibility, with over 110,000 cells measured. They annotate cell types, compare types across organs, and identify organ-specific or shared features, inferring transcription factors and gene regulatory programs. They also integrate human and mouse tissue to validate many of these findings. I found the manuscript to be of value for many biologists due to the addition of an exhaustive effort to characterize cells in the rat, however the actual analyses and findings are not entirely novel. However, that is not the overall goal of the manuscript, so my enthusiasm remains high. Specific comments are as follows:

   • The introduction is quite short and relatively shallow, with very little justification for the use of a rat atlas. The authors should elaborate on this justification and provide a more comprehensive overview of the use of these atlases in greater detail, rather than just providing a list of undefined analyses which may not be familiar to the reader.
   • The authors extracted tissues from a single rat. Although it is beneficial to have a deep characterization of an individual, such a small sample size would not be the best representation for an entire atlas (this is mentioned in the limitations).
   • The authors could consider integrating other rat snATAC-seq data sets, of which several exist.
   • The TSS enrichment scores and number of fragments are negatively correlated, why is that?
   • How reliable are the identified doublets? If the authors run the algorithm to detect doublets on individual samples or replicates versus all samples, are the same cells identified?
   • Figure 1 has icons and images which are quite small.
   • The authors mention LSI dimensionality reduction for clustering, but then display everything with UMAP which is known to distort distances.
   • UMAP is also notoriously bad at handling batch effects, which seem to be present in this atlas. Has any effort been used to mitigate this issue? It would be better to use an alternative visualization that maintains distances.
   • How reliable are the cell types from the automated annotator given the relationships in the hierarchical clustering? For example, "Immature_T_cell"s are more closely clustered with "Goblet" cells than "Thymic_T_Cell"s, and these types of relationships are throughout the tree. Additional validation should be completed, including at minimum a gene expression scoring of markers for each of these cell types to see if they match the annotation.
   • To determine the organ specificity of different cell types, the authors can additionally look at, for instance, alveolar / interstitial macrophages in the lung or another tissue or tissue resident fibroblasts, comparing those specific cell types rather than alveolar vs. any other epithelial cell type.
   • The finding that endothelial clusters were mostly grouped by organs should be verified in the context of batch correction. The authors could also consider clustering befor dimensionality reduction and using consensus clustering using subsampling.
   • l. 369: CMs not defined.
   • l. 396: ECs not defined.
   • "sc" and "sn" used interchangeably (e.g. Figure 5A), which should be "snATAC-seq".
   • l. 445: The central dogma of molecular biology defined here is stated incorrectly and should be fixed or removed, although it appears irrelevant for the discussion.

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3. 

   GigaScience

   Feb 24, 2026

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further …

   SummaryThe chromatin accessibility landscape is the basis of cell-specific gene expression. We generated a multiorgan, 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), the dynamics of T-cell developmental trajectories across organs, and the conservation and specificity of gene expression patterns across species. These findings provide a foundation for further investigations of the cell composition and gene regulatory networks throughout the rat body.HighlightsGeneration of a single-cell atlas of chromatin accessibility in nine organs of the ratCharacterization of cell type- and organ-specific transcription factors (TFs)Dynamics of chromatin accessibility in developing T cells revealed by cross-organ analysisConservation and specificity of gene expression patterns among humans, mice, and rats revealed by cross-species analysisCompeting Interest StatementThe authors have declared no competing interest.

   This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giag013), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

   Reviewer 1：

   Li et al presents a manuscript where they generated a snATAC-seq atlas of 9 major organs in adult rat and integrated the atlas with mouse and human scRNA-seq and scATAC-seq data, revealing that chromatin accessbility is largely conserved between celltypes across species and that there also tissue-specific regulation in some celltypes even when they are common across several tissues. Overall, this looks like a great carefully analysed and annotated resource that would be useful for the community. I appreciate the amount of work that went into curating and analysing this dataset and i thought that the manuscript was very well written and clear.

   I think the most interesting finding is in figure 3 where the authors found unique TFs regulating the same cell-types but in different organs. However, the analysis ends abruptly other than listing these TFs. Can the authors comment on what are the functional consequences/associations of these tissue-specific TFs, perhaps in the discussion?

   The raw data is deposited into a database and can be openly downloaded but i find that the lack of processed data e.g. processed and labelled expression matrices or objects may prevent the adoption of this data by the community as it is a lengthy process to reach the author's conclusions. The authors might also want to consider incorporating an interactive platform for users to explore and navigate this dataset.

   While i appreciate that the authors have detailed in their manuscripts how they performed the data analysis, i would still encourage the authors to upload their scripts/notebooks to an open code repository otherwise again it would be prohibitive for adoption by the community as it is.

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4. 

   Version published to 10.1101/2024.11.11.622900 on bioRxiv

   Nov 11, 2024