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(A) Schematic of human basal ganglia dissections and multimodal profiling by Droplet Paired-Tag and <t>MERFISH</t> spatial transcriptomics. (B) Workflow of nuclei isolation and library preparation for Droplet Paired-Tag. (C) UMAP embedding and clustering analysis of transcriptome modality from the Droplet Paired-Tag datasets, colored by group types. (D) The spatial maps of cell groups in each basal ganglia region identified using MERFISH with the probe set targeting ∼1,000 genes. (E) UMAP embedding and clustering analysis of H3K27ac profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (F) UMAP embedding and clustering analysis of H3K27me3 profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (G) UMAP embedding and clustering analysis of H3K9me3 profiles from the Droplet Paired-Tag datasets, colored by subclass types defined by corresponding single-cell transcriptome. (H) Genome browser tracks showing aggregated histone modification profiles for each class and MSN group within CN LGE GABA class at selected marker gene loci that were used for cell cluster annotation. (I) Bar plots showing, from left to right, total number of nuclei, relative contribution of donors, three histone modification marks distribution, and brain region distribution for each of the 61 cell groups identified in the Droplet Paired-Tag dataset.
Merfish Imaging, supplied by Vizgen Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Vizgen Inc merfish images
<t>MERFISH</t> spatial maps illustrate the alteration of intestinal epithelial cells. ( A ) Schematic plot of MERFISH data processing. ( B ) Typical regions of anatomical annotation and predicted cell types from snRNA-seq. Gene expression was shown with marker genes measured by MERFISH and imputed by the iSpatial algorithm. ( C ) Barplot showing the cell proportions in the crypt and villus regions in MERFISH datasets. ( D ) GO enrichment analysis of genes upregulated and downregulated in NEC in the crypt and villus regions. ( E ) Spatial mapping of crypt-villus domains showing centroid positions and cell numbers in control and NEC. ( F ) Subtype proximity analysis comparing lineage relationships between control and NEC.
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Vizgen Inc merfish microscopy images
( a ) BICCN <t>MERFISH,</t> Vizgen Brainmap, and Vizgen Liver biological replicates (rows top to bottom) have Pearson correlation coefficients (blue) larger than 0.47 for SPRAWL peripheral, radial, punctate, and central metrics (columns left to right). Randomly permuting gene labels in these datasets eliminates underlying spatial patterning and yields insignificant Pearson correlation coefficients (orange) between biological replicates. Dotted lines indicate zero-valued SPRAWL gene-cell type scores. ( b ) In the motor cortex (MOp) BRAIN Initiative Cell Census Network (BICCN) dataset 87% of gene/cell-type pairs have positive punctate RNA patterning (blue), compared to 50% in the gene-label permuted data (orange). Similarly extreme trends of 95% and 52% are observed for the radial metric. Cldn5 RNA is consistently highly punctate and radial in all cell-types that express it, depicted by purple x-axis ticks.
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Spatial Transcriptomics Inc image-based spatial transcriptomics merfish
( a ) BICCN <t>MERFISH,</t> Vizgen Brainmap, and Vizgen Liver biological replicates (rows top to bottom) have Pearson correlation coefficients (blue) larger than 0.47 for SPRAWL peripheral, radial, punctate, and central metrics (columns left to right). Randomly permuting gene labels in these datasets eliminates underlying spatial patterning and yields insignificant Pearson correlation coefficients (orange) between biological replicates. Dotted lines indicate zero-valued SPRAWL gene-cell type scores. ( b ) In the motor cortex (MOp) BRAIN Initiative Cell Census Network (BICCN) dataset 87% of gene/cell-type pairs have positive punctate RNA patterning (blue), compared to 50% in the gene-label permuted data (orange). Similarly extreme trends of 95% and 52% are observed for the radial metric. Cldn5 RNA is consistently highly punctate and radial in all cell-types that express it, depicted by purple x-axis ticks.
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Vizgen Inc merfish imaging data
( a ) BICCN <t>MERFISH,</t> Vizgen Brainmap, and Vizgen Liver biological replicates (rows top to bottom) have Pearson correlation coefficients (blue) larger than 0.47 for SPRAWL peripheral, radial, punctate, and central metrics (columns left to right). Randomly permuting gene labels in these datasets eliminates underlying spatial patterning and yields insignificant Pearson correlation coefficients (orange) between biological replicates. Dotted lines indicate zero-valued SPRAWL gene-cell type scores. ( b ) In the motor cortex (MOp) BRAIN Initiative Cell Census Network (BICCN) dataset 87% of gene/cell-type pairs have positive punctate RNA patterning (blue), compared to 50% in the gene-label permuted data (orange). Similarly extreme trends of 95% and 52% are observed for the radial metric. Cldn5 RNA is consistently highly punctate and radial in all cell-types that express it, depicted by purple x-axis ticks.
Merfish Imaging Data, supplied by Vizgen Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


(A) Schematic of human basal ganglia dissections and multimodal profiling by Droplet Paired-Tag and MERFISH spatial transcriptomics. (B) Workflow of nuclei isolation and library preparation for Droplet Paired-Tag. (C) UMAP embedding and clustering analysis of transcriptome modality from the Droplet Paired-Tag datasets, colored by group types. (D) The spatial maps of cell groups in each basal ganglia region identified using MERFISH with the probe set targeting ∼1,000 genes. (E) UMAP embedding and clustering analysis of H3K27ac profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (F) UMAP embedding and clustering analysis of H3K27me3 profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (G) UMAP embedding and clustering analysis of H3K9me3 profiles from the Droplet Paired-Tag datasets, colored by subclass types defined by corresponding single-cell transcriptome. (H) Genome browser tracks showing aggregated histone modification profiles for each class and MSN group within CN LGE GABA class at selected marker gene loci that were used for cell cluster annotation. (I) Bar plots showing, from left to right, total number of nuclei, relative contribution of donors, three histone modification marks distribution, and brain region distribution for each of the 61 cell groups identified in the Droplet Paired-Tag dataset.

Journal: bioRxiv

Article Title: Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal Ganglia

doi: 10.64898/2026.02.03.703645

Figure Lengend Snippet: (A) Schematic of human basal ganglia dissections and multimodal profiling by Droplet Paired-Tag and MERFISH spatial transcriptomics. (B) Workflow of nuclei isolation and library preparation for Droplet Paired-Tag. (C) UMAP embedding and clustering analysis of transcriptome modality from the Droplet Paired-Tag datasets, colored by group types. (D) The spatial maps of cell groups in each basal ganglia region identified using MERFISH with the probe set targeting ∼1,000 genes. (E) UMAP embedding and clustering analysis of H3K27ac profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (F) UMAP embedding and clustering analysis of H3K27me3 profiles from the Droplet Paired-Tag datasets, colored by group types defined by corresponding single-cell transcriptome. (G) UMAP embedding and clustering analysis of H3K9me3 profiles from the Droplet Paired-Tag datasets, colored by subclass types defined by corresponding single-cell transcriptome. (H) Genome browser tracks showing aggregated histone modification profiles for each class and MSN group within CN LGE GABA class at selected marker gene loci that were used for cell cluster annotation. (I) Bar plots showing, from left to right, total number of nuclei, relative contribution of donors, three histone modification marks distribution, and brain region distribution for each of the 61 cell groups identified in the Droplet Paired-Tag dataset.

Article Snippet: We selected 920 genes for MERFISH imaging on the Vizgen MERSCOPE Ultra platform.

Techniques: Spatial Transcriptomics, Isolation, Single Cell, Modification, Marker

(A) UMAP plot showing Droplet Paired-Tag transcriptome profiles of nine MSN groups. (B) UMAP plot showing MSNs profiles colored by brain region labels, highlighting regions along V–D axis (top) and A–P axis (bottom). (C) Stacked bars showing regional MSN group composition for each region along anatomical axes. (D) Genome browser tracks showing histone modification gradient changes along the V-D and A-P axis in both genes and their putative enhancers identified by the ABC model. (E) A–P axis gradients in expression of genes and modification–associated signal intensities of H3K27ac, H3K27me3 and H3K9me3 peaks for groups within STR D1 MSNs. (F) Droplet Paired-Tag gene expression and H3K27ac modification patterns of representative genes mapped to their predicted spatial location by integrative analysis with MERFISH. Left, the STXBP6 gene shows the spatial gradient pattern among the V-D axis in STR D2 MSNs. Right: the NPAS4 gene shows the spatial gradient pattern among the A-P axis in STR D1 MSNs. The left columns display the RNA expression from Droplet Paired-Tag. The right columns show the gene-body H3K27me3 signal density.

Journal: bioRxiv

Article Title: Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal Ganglia

doi: 10.64898/2026.02.03.703645

Figure Lengend Snippet: (A) UMAP plot showing Droplet Paired-Tag transcriptome profiles of nine MSN groups. (B) UMAP plot showing MSNs profiles colored by brain region labels, highlighting regions along V–D axis (top) and A–P axis (bottom). (C) Stacked bars showing regional MSN group composition for each region along anatomical axes. (D) Genome browser tracks showing histone modification gradient changes along the V-D and A-P axis in both genes and their putative enhancers identified by the ABC model. (E) A–P axis gradients in expression of genes and modification–associated signal intensities of H3K27ac, H3K27me3 and H3K9me3 peaks for groups within STR D1 MSNs. (F) Droplet Paired-Tag gene expression and H3K27ac modification patterns of representative genes mapped to their predicted spatial location by integrative analysis with MERFISH. Left, the STXBP6 gene shows the spatial gradient pattern among the V-D axis in STR D2 MSNs. Right: the NPAS4 gene shows the spatial gradient pattern among the A-P axis in STR D1 MSNs. The left columns display the RNA expression from Droplet Paired-Tag. The right columns show the gene-body H3K27me3 signal density.

Article Snippet: We selected 920 genes for MERFISH imaging on the Vizgen MERSCOPE Ultra platform.

Techniques: Modification, Expressing, Gene Expression, RNA Expression

MERFISH spatial maps illustrate the alteration of intestinal epithelial cells. ( A ) Schematic plot of MERFISH data processing. ( B ) Typical regions of anatomical annotation and predicted cell types from snRNA-seq. Gene expression was shown with marker genes measured by MERFISH and imputed by the iSpatial algorithm. ( C ) Barplot showing the cell proportions in the crypt and villus regions in MERFISH datasets. ( D ) GO enrichment analysis of genes upregulated and downregulated in NEC in the crypt and villus regions. ( E ) Spatial mapping of crypt-villus domains showing centroid positions and cell numbers in control and NEC. ( F ) Subtype proximity analysis comparing lineage relationships between control and NEC.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Molecular and Chromatin Accessibility Programs Underlying Epithelial Injury and Impaired Regeneration in Neonatal Necrotizing Enterocolitis

doi: 10.1016/j.jcmgh.2026.101730

Figure Lengend Snippet: MERFISH spatial maps illustrate the alteration of intestinal epithelial cells. ( A ) Schematic plot of MERFISH data processing. ( B ) Typical regions of anatomical annotation and predicted cell types from snRNA-seq. Gene expression was shown with marker genes measured by MERFISH and imputed by the iSpatial algorithm. ( C ) Barplot showing the cell proportions in the crypt and villus regions in MERFISH datasets. ( D ) GO enrichment analysis of genes upregulated and downregulated in NEC in the crypt and villus regions. ( E ) Spatial mapping of crypt-villus domains showing centroid positions and cell numbers in control and NEC. ( F ) Subtype proximity analysis comparing lineage relationships between control and NEC.

Article Snippet: MERFISH images were segmented using Vizgen’s post-processing tool (VPT) and with a deep learning algorithm, CellPose 2.0.

Techniques: Gene Expression, Marker, Control

Spatial transcriptomic profiling reveals disrupted tissue architecture and communication changes in NEC. ( A ) Volcano plots showing DEGs that are upregulated and downregulated in NEC within the crypt and ( B ) villus regions based on MERFISH datasets. ( C ) Spatial gradient comparison between control and NEC conditions. Scatter plot displaying gradient strength (deviance explained from GAMs) for each gene in control (x-axis) vs NEC (y-axis). Points above the diagonal ( dashed line ) indicate genes with stronger spatial gradients in NEC, whereas points below indicate weakened gradients. Genes are colored by category: gray (not significant), orange (disrupted in NEC), red (top 10 magnitude changes), and blue (marker genes of interest). Key genes are labeled, including differentiation markers (Vil1, Lgr4, Hnf4a, Rnf43), the stem cell marker Lgr6, proliferation markers (Birc5, Stmn1), Paneth cell marker (Spink4), and metabolic/transport genes showing the largest gradient changes (Dpyd, Immp2l, Pcsk5, Gm20275, Pard3b, Epb41l3, Ghr, Abcc2, Chka, Cubn). ( D ) Regional specificity of NEC transcriptional effects. Scatter plot comparing log2 FC (NEC vs control) in crypt (x-axis) vs villus (y-axis) compartments for all differentially expressed genes. Points are colored by significance category: red (significant in both regions; FDR <0.05), orange (crypt-specific), blue (villus-specific), and gray (not significant in either region). The diagonal dashed line indicates equal effects in both compartments. Points along the diagonal represent genes with concordant responses across tissue compartments, whereas off-diagonal points indicate region-specific or divergent responses. Top genes from each category are labeled. ( E ) Spatial expression patterns of top SVGs showing altered crypt-villus polarity. Representative genes are grouped by functional category: Vil1 (villin, enterocyte brush border marker), Lgr4 (differentiation/Wnt signaling), Spink4 (Paneth cell marker), Hnf4a (hepatocyte nuclear factor, master regulator of enterocyte differentiation), and Dpyd (dihydropyrimidine dehydrogenase, pyrimidine metabolism). Each panel shows expression in control ( top row ) and NEC ( bottom row ) tissue, with color intensity representing normalized expression level. ( F ) Spatial expression patterns of top region-specific DEGs. Sipa1l2 (signal-induced proliferation-associated 1 like 2) represents a villus-specific differentially expressed gene, whereas Trim30d (tripartite motif-containing 30D) represents a crypt-specific differentially expressed gene. ( G-I ) Cell–cell communication analysis by Cellchat illustrating differences in ( G ) secreted signaling, ( H ) ECM–receptor interactions, and ( I ) direct contact pathways between Control and NEC.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Molecular and Chromatin Accessibility Programs Underlying Epithelial Injury and Impaired Regeneration in Neonatal Necrotizing Enterocolitis

doi: 10.1016/j.jcmgh.2026.101730

Figure Lengend Snippet: Spatial transcriptomic profiling reveals disrupted tissue architecture and communication changes in NEC. ( A ) Volcano plots showing DEGs that are upregulated and downregulated in NEC within the crypt and ( B ) villus regions based on MERFISH datasets. ( C ) Spatial gradient comparison between control and NEC conditions. Scatter plot displaying gradient strength (deviance explained from GAMs) for each gene in control (x-axis) vs NEC (y-axis). Points above the diagonal ( dashed line ) indicate genes with stronger spatial gradients in NEC, whereas points below indicate weakened gradients. Genes are colored by category: gray (not significant), orange (disrupted in NEC), red (top 10 magnitude changes), and blue (marker genes of interest). Key genes are labeled, including differentiation markers (Vil1, Lgr4, Hnf4a, Rnf43), the stem cell marker Lgr6, proliferation markers (Birc5, Stmn1), Paneth cell marker (Spink4), and metabolic/transport genes showing the largest gradient changes (Dpyd, Immp2l, Pcsk5, Gm20275, Pard3b, Epb41l3, Ghr, Abcc2, Chka, Cubn). ( D ) Regional specificity of NEC transcriptional effects. Scatter plot comparing log2 FC (NEC vs control) in crypt (x-axis) vs villus (y-axis) compartments for all differentially expressed genes. Points are colored by significance category: red (significant in both regions; FDR <0.05), orange (crypt-specific), blue (villus-specific), and gray (not significant in either region). The diagonal dashed line indicates equal effects in both compartments. Points along the diagonal represent genes with concordant responses across tissue compartments, whereas off-diagonal points indicate region-specific or divergent responses. Top genes from each category are labeled. ( E ) Spatial expression patterns of top SVGs showing altered crypt-villus polarity. Representative genes are grouped by functional category: Vil1 (villin, enterocyte brush border marker), Lgr4 (differentiation/Wnt signaling), Spink4 (Paneth cell marker), Hnf4a (hepatocyte nuclear factor, master regulator of enterocyte differentiation), and Dpyd (dihydropyrimidine dehydrogenase, pyrimidine metabolism). Each panel shows expression in control ( top row ) and NEC ( bottom row ) tissue, with color intensity representing normalized expression level. ( F ) Spatial expression patterns of top region-specific DEGs. Sipa1l2 (signal-induced proliferation-associated 1 like 2) represents a villus-specific differentially expressed gene, whereas Trim30d (tripartite motif-containing 30D) represents a crypt-specific differentially expressed gene. ( G-I ) Cell–cell communication analysis by Cellchat illustrating differences in ( G ) secreted signaling, ( H ) ECM–receptor interactions, and ( I ) direct contact pathways between Control and NEC.

Article Snippet: MERFISH images were segmented using Vizgen’s post-processing tool (VPT) and with a deep learning algorithm, CellPose 2.0.

Techniques: Comparison, Control, Marker, Labeling, Expressing, Functional Assay

( a ) BICCN MERFISH, Vizgen Brainmap, and Vizgen Liver biological replicates (rows top to bottom) have Pearson correlation coefficients (blue) larger than 0.47 for SPRAWL peripheral, radial, punctate, and central metrics (columns left to right). Randomly permuting gene labels in these datasets eliminates underlying spatial patterning and yields insignificant Pearson correlation coefficients (orange) between biological replicates. Dotted lines indicate zero-valued SPRAWL gene-cell type scores. ( b ) In the motor cortex (MOp) BRAIN Initiative Cell Census Network (BICCN) dataset 87% of gene/cell-type pairs have positive punctate RNA patterning (blue), compared to 50% in the gene-label permuted data (orange). Similarly extreme trends of 95% and 52% are observed for the radial metric. Cldn5 RNA is consistently highly punctate and radial in all cell-types that express it, depicted by purple x-axis ticks.

Journal: eLife

Article Title: Statistical analysis supports pervasive RNA subcellular localization and alternative 3' UTR regulation

doi: 10.7554/eLife.87517

Figure Lengend Snippet: ( a ) BICCN MERFISH, Vizgen Brainmap, and Vizgen Liver biological replicates (rows top to bottom) have Pearson correlation coefficients (blue) larger than 0.47 for SPRAWL peripheral, radial, punctate, and central metrics (columns left to right). Randomly permuting gene labels in these datasets eliminates underlying spatial patterning and yields insignificant Pearson correlation coefficients (orange) between biological replicates. Dotted lines indicate zero-valued SPRAWL gene-cell type scores. ( b ) In the motor cortex (MOp) BRAIN Initiative Cell Census Network (BICCN) dataset 87% of gene/cell-type pairs have positive punctate RNA patterning (blue), compared to 50% in the gene-label permuted data (orange). Similarly extreme trends of 95% and 52% are observed for the radial metric. Cldn5 RNA is consistently highly punctate and radial in all cell-types that express it, depicted by purple x-axis ticks.

Article Snippet: For MERFISH and Vizgen, this data is the product of applying MERlin ( ) on the raw MERFISH microscopy images to align the images between sequencing rounds, call RNA spots, and perform cell segmentation using a seeded watershed approach described in a prior MERFISH work ( ).

Techniques:

( a ) Workflow to calculate median 3’ UTR length and spatial score per gene/cell-type. ( b ) Slc32a1 median centrality, ( c ) Cxcl14 radial, and ( d ) Nxph1 punctate SPRAWL scores from the BRAIN Initiative Cell Census Network (BICCN) MERFISH dataset correlate significantly with 3’ UTR length determined from 10 X scRNA-seq data by ReadZS. The left-column boxplots show individual SPRAWL cell scores as overlaid dots. The cell-types are sorted by increasing median score marked in red. The two cell-types with the highest and lowest median SPRAWL scores are plotted individually while the remaining cell-types are collapsed into the ‘Other’ category. Gene/cell examples are shown to the left of the boxplots for each extreme cell-type group. The density plots in the middle column show estimated 3’ UTR lengths for each read mapping within the annotated 3’ UTR, stratified by cell-type. Lengths were approximated as the distance between the annotated start of the 3’ UTR and the median read-mapping position. Each density plot is normalized by cell-type to show relative shifts in 3’ UTR length with median lengths depicted with red lines. The scatterplots show the significant correlations between the median SPRAWL score and the median 3’ UTR length. The two cell-types with the highest, and the two with the lowest SPRAWL median scores are highlighted.

Journal: eLife

Article Title: Statistical analysis supports pervasive RNA subcellular localization and alternative 3' UTR regulation

doi: 10.7554/eLife.87517

Figure Lengend Snippet: ( a ) Workflow to calculate median 3’ UTR length and spatial score per gene/cell-type. ( b ) Slc32a1 median centrality, ( c ) Cxcl14 radial, and ( d ) Nxph1 punctate SPRAWL scores from the BRAIN Initiative Cell Census Network (BICCN) MERFISH dataset correlate significantly with 3’ UTR length determined from 10 X scRNA-seq data by ReadZS. The left-column boxplots show individual SPRAWL cell scores as overlaid dots. The cell-types are sorted by increasing median score marked in red. The two cell-types with the highest and lowest median SPRAWL scores are plotted individually while the remaining cell-types are collapsed into the ‘Other’ category. Gene/cell examples are shown to the left of the boxplots for each extreme cell-type group. The density plots in the middle column show estimated 3’ UTR lengths for each read mapping within the annotated 3’ UTR, stratified by cell-type. Lengths were approximated as the distance between the annotated start of the 3’ UTR and the median read-mapping position. Each density plot is normalized by cell-type to show relative shifts in 3’ UTR length with median lengths depicted with red lines. The scatterplots show the significant correlations between the median SPRAWL score and the median 3’ UTR length. The two cell-types with the highest, and the two with the lowest SPRAWL median scores are highlighted.

Article Snippet: For MERFISH and Vizgen, this data is the product of applying MERlin ( ) on the raw MERFISH microscopy images to align the images between sequencing rounds, call RNA spots, and perform cell segmentation using a seeded watershed approach described in a prior MERFISH work ( ).

Techniques: