Journal: Frontiers in Immunology

Article Title: Single-cell RNA sequencing of leukocytes at the maternal-fetal interface in physiological and pathological Nodal-deficient pregnancies

doi: 10.3389/fimmu.2026.1611813

Figure Lengend Snippet: Changes in the abundance and gene expression profile of leukocytes in Nodal Δ/Δ females. (A) t-SNE of all Ptprc + cells at the Nodal loxP/loxP (n=2) and Nodal Δ/Δ (n=2) maternal-fetal interface. (B) Proportion of cell types in each sample. Notably, the proportion of maternal neutrophils, non-classical monocytes and PAMM1a cells was significantly decreased in Nodal Δ/Δ females, while the proportion of M2 and PAMM2 cells was increased (FDR<0.05). (C) The number of significant differentially expressed genes (DEGs) (adjusted P-value<0.1) in all immune cell clusters at the d10.5 maternal-fetal interface between Nodal loxP/loxP and Nodal Δ/Δ females.

Article Snippet: Probe hybridization was performed on approximately 500,000 cells/sample using the Chromium Fixed RNA Mouse Transcriptome Kit (10X Genomics Cat. No. PN-1000497) following protocol # CG000527 .

Techniques: Gene Expression

Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: a , UMAP of GCs, colored by seven GC subtypes (Progenitor, Preantral 1, Preantral 2, Mitotic 1, Mitotic 2, Antral Mural and Atretic). b , Feature plots of representative subtype markers on the UMAP. c , Monocle3 pseudotime trajectory inferred for GCs, with the principal graph overlaid and direction indicated from progenitor toward antral mural cells. d , Heatmap of representative genes showing coordinated expression changes along the progenitor-to-mural trajectory (expression shown as z-scores). e , Heatmap of Hallmark ssGSEA scores across granulosa subtypes (z-scored per gene set). f , H&E image of a Stereo-seq FF V1.3 mouse ovary section (6-8 weeks old), with representative regions (α–θ) indicated. Scale bar, 100 μm. g , Cell2location-based spatial mapping of GC subtypes at cell-bin resolution. h , Zoom-in views of representative regions (α, β, γ, and θ) showing H&E morphology and spatial expression of selected marker genes. Scale bar, 50 μm.

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques: Expressing, Marker

Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: Spatial maps showing cell2location-predicted localization of each annotated cell subtype on the Stereo-seq FF V1.3 ovary section (6–8 weeks old), displayed separately by subtype. Scale bar, 100 μm

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques:

Journal: bioRxiv

Article Title: STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial Transcriptomics

doi: 10.64898/2026.02.26.708370

Figure Lengend Snippet: Performance of STCS on high-resolution Stereo-seq mouse brain data. A) Tissue images and segmentations. Left: original H&E image; Center: nuclei segmentation mask; Right: Single-cell Segmented slide by STCS (colored by cell class, defined as higher-level groupings of CellTypist-predicted cell types. B) Spatial continuity metrics. Left: Cell-class coherence across neighborhood size. computed as the proportion of spatially nearest neighbors sharing the same cell-class label at each neighborhood size. Higher values indicate greater spatial consistency of cell-class assignments within local tissue contexts. Middle: CHAOS scores computed at the Leiden cluster level. Right: CHAOS scores computed at the cell-class level. Lower CHAOS scores indicate better spatial organization. The center line represents the median CHAOS score and the box spans the interquartile range. The annotated text are µ ± σ . C) Gene Level metrics. Left: Cell-class label-transfer accuracy to a scRNA-seq reference across varying numbers of highly variable genes (HVGs), assessing how reliably reconstructed spatial cells recover reference-defined transcriptional identities and the robustness of predictions based on different selected features. Right: Distribution of gene-expression cosine similarity between reconstructed cells and scRNA-seq reference profiles across cell classes, quantifying transcriptomic agreement. Cosine similarity was computed between each reconstructed cell’s expression profile and the mean expression profile of its assigned cell class in the scRNA-seq reference. Center lines indicate medians and boxes span the interquartile range. The annotated text are µ ± σ . D) Cell-type composition accuracy. Left: Cell-type richness between methods and a single-cell reference data. Right: Absolute error in estimated cellclass proportions compared to the reference. Lower values indicate closer agreement with the cellular composition of the reference data. The annotated text are µ ± σ and center lines indicate median.

Article Snippet: The Stereo-seq whole mouse brain dataset is available from STOmics ( https://en.stomics.tech/col1241/index.html ).

Techniques: Single Cell, Gene Expression, Expressing