Journal: bioRxiv

Article Title: OmicGlaze: Spatial Multi-Omic Mapping of Traumatic Brain Injury

doi: 10.64898/2026.03.30.715462

Figure Lengend Snippet: A A focal blunt injury was induced in the upper right hemisphere of the mouse brain. Serial coronal sections were obtained at the mid-hippocampal level, with adjacent sections allocated for histological analysis (hematoxylin and eosin staining and Nissl staining), spatial RNA sequencing (spatial RNA-seq), and spatial ATAC sequencing (spatial ATAC-seq). B Image of a Nissl-stained section adjacent to the TBI_03 sample used for sequencing, illustrating tissue morphology. The left side corresponds to the uninjured hemisphere, and the right side to the injured hemisphere. C Zoomed-in view of the isocortex on the uninjured side of panel B. Scale bar represents 250 µm. D Zoomed-in view of the isocortex on the injured side of panel B. Scale bar represents 250 µm. E Spatial distribution of the number of detected genes per spot in the Control_01 sample. Each dot represents a 55-micron spot on the Visium slide (11 x 11 mm 2 ). F - H Spatial distribution of the number of detected genes per spot in the TBI_01, TBI_02, and TBI_03 samples. I Spatial region annotation of the TBI_03 sample, highlighting 14 anatomical regions. Abbreviations: CNU, cerebral nuclei; CTX_ISO, isocortex; CTX_OLF, olfactory cortex; CTX_RSP, retrosplenial area; CTX_SP, cortical subplate; HPF_CA_PYR, hippocampal formation cornu ammonis pyramidal layer; HPF_DG_GCL, hippocampal formation dentate gyrus granule cell layer; HPF_other, the polymorphic layer and molecular layer of hippocampus; HY, hypothalamus; LM, leptomeninges; TH, thalamus; VS, ventricular systems. J Unsupervised clustering of the integrated dataset comprising Control_01, TBI_01, TBI_02, and TBI_03 samples, colored by brain regions as defined in panel I. K Heatmap showing the expression levels of the top five marker genes for each of the 14 annotated regions in Control_01. Each row represents one gene and each column under the same color represents one region. Selected marker genes are labeled on the plot: Adora2a (marker for CNU region), Apod (fiber tracts), Satb2 (CTX_ISO region), Dlk1 (HY region), Synop2 (TH region), Hopx ( HPF_other region), Nrep (CTX_RSP region), Ttr (VS region), and Gpr151 (habenula region).

Article Snippet: Using the Visium V1 platform (10X Genomics), Swaro et al . profiled the transcriptomic landscape at 7 days post TBI [ ], and Kounelis-Wuillaume et al . examined dynamic gene expression signatures at both 2 and 7 days post-injury, both highlighted the immune cell activation in injury responses [ , ].

Techniques: Staining, RNA Sequencing, Sequencing, Control, Olfactory, Expressing, Marker, Labeling

Journal: Communications Biology

Article Title: SpaCross deciphers spatial structures and corrects batch effects in multi-slice spatially resolved transcriptomics

doi: 10.1038/s42003-025-08810-5

Figure Lengend Snippet: A Histological image (left) and manually annotated spatial domains (right) for the human breast cancer (BRCA) dataset from 10x Visium. B Boxplot comparisons of Moran’s I and Geary’s C metrics for SVGs identified by SpaCross and baseline methods on the BRCA dataset. Mann-Whitney U tests were used to assess statistical significance. C Spatial domain maps on the BRCA dataset generated by SpaCross and representative baseline methods. D Spatial domain identification results on the mouse primary visual cortex (MVC) dataset (STARmap), including manual annotation (top-left) and results from SpaCross and baseline methods. E UMAP visualizations and PAGA trajectories of learned embeddings on the MVC dataset, shown for SpaCross and baseline methods. F Evolution of hybrid spatial-semantic graphs during SpaCross optimization on the MVC dataset. Left: gene expression similarity graph based on PCA-derived correlations. Right: hybrid graphs at epochs 50, 100, and 300, showing progressive refinement of intra-domain structure. G Spatial domain identification results on the mouse somatosensory cortex (MSC) dataset (osmFISH), including manual annotation (leftmost) and spatial domains identified by SpaCross and baseline methods.

Article Snippet: All data sets used in this article are publicly available: (1) Human dorsolateral prefrontal cortex data captured using 10X Visium technology can be downloaded from http://research.libd.org/spatialLIBD/ . (2) Human breast cancer data obtained with 10x Visium technology can be downloaded from https://www.10xgenomics.com/datasets/human-breast-cancer-block-a-section-1-1-standard-1-1-0 . (3) Mouse olfactory bulb tissue data generated by the Stereo-seq and Slide-seqV2 platforms can be accessed from https://github.com/JinmiaoChenLab/SEDR_analyses/tree/master/data and https://singlecell.broadinstitute.org/single_cell/study/SCP815 , respectively. (4) The spatial transcriptomic data of the mouse embryo obtained with Stereo-seq technology can be downloaded from https://db.cngb.org/stomics/mosta/ . (5) The mouse primary visual cortex (V1) STARmap dataset is available at https://www.starmapresources.com/data . (6) The mouse brain somatosensory cortex osmFISH dataset can be downloaded from http://linnarssonlab.org/osmFISH . (7) The mouse hypothalamus dataset from MERFISH can be downloaded from 10.5061/dryad.8t8s248. (8) The mouse whole brain dataset profiled by the ST platform can be downloaded from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147747 .

Techniques: MANN-WHITNEY, Generated, Gene Expression, Derivative Assay