Study design

Organs from the female reproductive tract (FRT) in C57BL/6 mice were sampled. Experimental timepoints were 3 months old mice across all four estrus phases, pregnant (decidualized) and aged (18 months, acyclic) mice. A total of 483,611 cells were sequenced using the 10X Chromium Gene Expression technology.

Schematic figure of the experimental setup

Contents of this app

The app allows to explore the cellular diversity and gene expression at the single-cell level of

In-depth analyses of gene expression patterns, transcription factor activity and cell-to-cell communcation are found at the following links or via the navigation bar on top of the page

Download links to raw and processed data can be found here.

For additional requests and questions please contact Duncan Odom d.odom A-T dkfz-heidelberg.de or Angela Goncalves a.goncalves A-T dkfz-heidelberg.de.

Cell atlas: Estrus cycle

Explore the cellular composition of the mouse female reproductive tract during the estrus cycle in young mice (3 months old)
To do so you may select one or multiple organ, phase of the estrus cycle and gene category.
Hovering the cursor on cells shows their identiy in a tooltip. Click and drag around cells to zoom in. Double click to zoom out again.

Pregnant mice

Single-cells from uterus sampled during pregnancy, shown together with uterine cells sampled during metestrus of young cycling mice.
Hovering the cursor on cells shows their identiy in a tooltip. Click and drag around cells to zoom in. Double click to zoom out again.

Cell atlas: Aged mice

Dataset of single cells from the 18 months old acyclic mice and cells sampled during diestrus in young mice.
Hovering the cursor on cells shows their identiy in a tooltip. Click and drag around cells to zoom in. Double click to zoom out again.

DEGs in cells from cycling mice

DEG analysis was performed using a multi-level generalised negative binomial regression model with random intercept. Normalised gene counts were used as the dependent variable, while estrus cycle phases were used as the independent variable, and sample label as random effect. Model was fitted gene-wise for each cell subpopulation.
To explore DEGs please select organ, cell type, contrast and significance threshold
Hovering the cursor on genes shows their identiy, p-value and log2-fold change in a tooltip. Click and drag around genes to zoom in. Double click to zoom out again. Using the search box, you can highlight genes of interest and show detailed per-gene results in a table or use the checkbox to show all significant genes.

DEGs in cells from aged mice

DEG analysis was performed using a multi-level generalised negative binomial regression model with random intercept. Normalised gene counts were used as the dependent variable, while age was used as the independent variable, and sample label as random effect. Model was fitted gene-wise for each cell subpopulation.
To explore DEGs please select organ, cell type, contrast and significance threshold
Hovering the cursor on genes shows their identiy, p-value and log2-fold change in a tooltip. Click and drag around genes to zoom in. Double click to zoom out again. Using the search box, you can highlight genes of interest and show detailed per-gene results in a table or use the checkbox to show all significant genes.

Differentially expressed genes in cycling fibroblasts

For each organ of the mouse female reproductive tract, we determined how gene expression changes in fibroblasts across the four phases of the estrus cycle. This panel shows the normalized expression values (Z-scores) for genes of selected pathways, or individual genes.

Transcription factor activity in fibroblasts of cycling mice

Z-scores of estimated activity scores of targets of transcription factors in fibroblasts in cycling mice. Results were generated using the Single-Cell Regulatory Network Inference and Clustering (SCENIC) method.
Hovering the cursor on tiles of the heatmap shows detailed properties. Click and drag around areas of the heatmap to zoom in. Double click to zoom out again.

Transcription factor activity in fibroblasts of aged mice

Log2-fold changes of estimated activity scores of transcription factors in fibroblasts of old mice compared to fibroblasts from young mice.
Results were generated using the Single-Cell Regulatory Network Inference and Clustering (SCENIC) method.
Hovering the cursor on tiles of the heatmap shows detailed properties. Click and drag around areas of the heatmap to zoom in. Double click to zoom out again.

Cell-to-cell communication

Z-scores of ligand-receptor products averaged across phases. Ligand expression is averaged across all cell-types; receptors are in selected cell types only. The X-axis shows the organ label and the Y-axis shows the ligand-receptor pairs or ligand-receptor-complex pairs.
To explore cell-to-cell communication scores please select cell type and ligand. Hovering the cursor on tiles of the heatmap shows detailed properties. Click and drag around areas of the heatmap to zoom in. Double click to zoom out again.

Cell-to-cell communication - aged mice

Log2-fold changes of ligand-receptor products in old mice compared to young mice. Ligand expression is averaged across all cell-types; receptors are in selected cell types only. The X-axis shows the organ label and the Y-axis shows the ligand-receptor pairs or ligand-receptor-complex pairs.
To explore cell-to-cell communication scores please select cell type and ligand. Hovering the cursor on tiles of the heatmap shows detailed properties. Click and drag around areas of the heatmap to zoom in. Double click to zoom out again.

Download links

scRNA-seq raw and processed data are available at:
Spatial Transcriptomics raw and processed data are available at:
Flow cytometry raw data together with the MIFlowCyt protocol are available at:
Imaging raw and processed data are available at:
Code used in this study is available in github repository:
For additional requests and questions please contact Duncan Odom d.odom A-T dkfz-heidelberg.de or Angela Goncalves a.goncalves A-T dkfz-heidelberg.de.

bioRxiv 2022.10.26.513823 | Version 0.5.5 | Imprint