Journal: bioRxiv

Article Title: Cross-species single-cell atlases chart progression, therapy-driven remodelling and immune evasion in pancreatic cancer

doi: 10.64898/2026.03.19.712924

Figure Lengend Snippet: a) Schematic overview of the experimental design. Mouse PDAC cell lines were clonally barcoded using a lentiviral library (1), expanded and orthotopically transplanted into syngeneic immunocompetent mice (2–3), followed by scRNA-seq profiling of resultant tumours (4). Expressed barcode tracing enabled unambiguous separation of malignant (TAG⁺) from host-derived non-malignant cells (right panel, UMAPs depicting barcoded (TAG + ) (top) and malignant (bottom) cells). b-e) UMAPs of the integrated Mouse PDAC Atlas coloured by dataset (b), sex (c), treatment type (d), and model (orthotopic syngeneic immunocompetent allografts vs. autochthonous GEMMs (e). f) Sample-wise cell-type composition across treatment types, datasets, and models. Autochthonous tumours were dominated by classical epithelial-like malignant states, whereas orthotopic allografts displayed greater heterogeneity with an enrichment of EMT, hypoxic, and mesenchymal programs. g ) Level 3 hierarchical annotation of the Mouse Atlas using the same multi-tiered scheme as the Human Atlas, resolving lymphoid, myeloid, stromal, endocrine, exocrine, endothelial, and malignant compartments. h-j) Substate resolution of major immune and stromal lineages: CD4⁺ T cells (h), CD8⁺ T cells (i), and macrophages (j), showing distinct regulatory, effector, angiogenic, and lipid-processing programs. k) Validation of double-positive (DP) CD4⁺CD8⁺ T cells at the transcriptomics level (transcription density plots, left panel) and at the protein level by flow cytometry (right panel). l) UMAP showing DP T cells coloured by species (left) and Pearson correlation of mouse DP T cell gene expression against the human DP T cell archetype (right).

Article Snippet: For clonal and state-fate analysis by single-cell RNA-seq, primary mouse PDAC cells were clonally tagged with expressed DNA barcodes using the LARRY Barcode Library (Addgene #140024; RRID: Addgene 140024) .

Techniques: Derivative Assay, Biomarker Discovery, Transcriptomics, Flow Cytometry, Gene Expression

Journal: Communications Biology

Article Title: RNA isoform diversity, splicing variants and switching in single cells of the Alzheimer’s disease brain

doi: 10.1038/s42003-026-09759-9

Figure Lengend Snippet: a Schematic representation of experimental workflow for single-nucleus short-read RNA-sequencing and Kinnex long-read RNA-sequencing. Figure 1a. was partially created with BioRender. https://BioRender.com/c44n540 . b UMAP plot colored by cell type assignments. c Bar plot showing the proportions of each cell type in AD and ND samples (ns: not significant; Two-sided t-test). d Differentially expressed genes (DEGs) identified across different cell types in AD and ND samples (absolute log2 fold change > 0.25 and adjusted p -value < 0.05, Wilcoxon Rank Sum test with Bonferroni correction). e–h Circos plots of five selected Gene Ontology (GO) terms for excitatory neurons, microglia, oligodendrocytes, and astrocytes with associated genes (false discovery rate (FDR) of <0.05 with the Benjamini-Hochberg (BH) test). Conserved GO terms are shown in the same color.

Article Snippet: Single-nucleus barcoded cDNA libraries were generated using the 10X Genomics Single Cell 3’ v3.1 kit.

Techniques: RNA Sequencing