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Structured Review

10X Genomics visium-spg cdna library generation
(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide <t>cDNA</t> synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.
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Images

1) Product Images from "Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex"

Article Title: Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

Journal: GEN biotechnology

doi: 10.1089/genbio.2023.0019

(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.
Figure Legend Snippet: (A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Techniques Used: Control, Gene Expression, Staining, Imaging, Immunofluorescence, cDNA Synthesis, Generated, Blocking Assay

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Sequencing:

Article Title: Spatial Isoforms Reveal the Mechanisms of Metastasis
Article Snippet: .. Based on a previous SiT workflow, full‐length 10X Genomics Visium cDNA libraries were split for Illumina sequencing and ONT sequencing. .. [ ] We generated 320–410 million reads per sample from Illumina sequencing and 45–83 million reads per sample from ONT sequencing (Table , Supporting Information).



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A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length <t>cDNA</t> library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The <t>Visium</t> full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.
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(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide <t>cDNA</t> synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.
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(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide <t>cDNA</t> synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.
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Metastatic lymph nodes in ESCC exhibit expansive enrichment of T cells and macrophages. A) Spatial transcriptomic spots of all three samples: Before, After, and AfterLN. The colors indicate the niches of each sample. B) Boxplot of the contact frequency of spatial niches in each sample. P value was calculated by an unpaired two‐tailed Student's t‐test, n (Before) = 21 413, n (After) = 32 618, n (AfterLN) = 33 246. C) CD74, C1QC , and CXCL13 expression were labeled by RNAscope in situ hybridization. Left: HE; Middle: <t>10X</t> RNAscope; Right: 20X RNAscope. DAPI: blue, C1QC : green, CD74 : pink, CXCL13 : red, Merge: white. D) Boxplot of the colocalization of the cell fraction with CD74 , C1QC , and CXCL13 expression between the tumor and LN samples when the enrichment calculation cutoff is 0.6. P value was calculated by an unpaired two‐tailed Student's t‐test. E) Circular plot of the cell‐cell interactions between niches in the three samples. The colors indicate the niche. The area of each bond indicates the frequency of interaction. F) Spatial trajectory of subclusters in niches 4–6. Arrows show the direction of the trajectory. G) Tree plot of the trajectory of subclusters in niches 4–6.
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Metastatic lymph nodes in ESCC exhibit expansive enrichment of T cells and macrophages. A) Spatial transcriptomic spots of all three samples: Before, After, and AfterLN. The colors indicate the niches of each sample. B) Boxplot of the contact frequency of spatial niches in each sample. P value was calculated by an unpaired two‐tailed Student's t‐test, n (Before) = 21 413, n (After) = 32 618, n (AfterLN) = 33 246. C) CD74, C1QC , and CXCL13 expression were labeled by RNAscope in situ hybridization. Left: HE; Middle: <t>10X</t> RNAscope; Right: 20X RNAscope. DAPI: blue, C1QC : green, CD74 : pink, CXCL13 : red, Merge: white. D) Boxplot of the colocalization of the cell fraction with CD74 , C1QC , and CXCL13 expression between the tumor and LN samples when the enrichment calculation cutoff is 0.6. P value was calculated by an unpaired two‐tailed Student's t‐test. E) Circular plot of the cell‐cell interactions between niches in the three samples. The colors indicate the niche. The area of each bond indicates the frequency of interaction. F) Spatial trajectory of subclusters in niches 4–6. Arrows show the direction of the trajectory. G) Tree plot of the trajectory of subclusters in niches 4–6.
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Metastatic lymph nodes in ESCC exhibit expansive enrichment of T cells and macrophages. A) Spatial transcriptomic spots of all three samples: Before, After, and AfterLN. The colors indicate the niches of each sample. B) Boxplot of the contact frequency of spatial niches in each sample. P value was calculated by an unpaired two‐tailed Student's t‐test, n (Before) = 21 413, n (After) = 32 618, n (AfterLN) = 33 246. C) CD74, C1QC , and CXCL13 expression were labeled by RNAscope in situ hybridization. Left: HE; Middle: <t>10X</t> RNAscope; Right: 20X RNAscope. DAPI: blue, C1QC : green, CD74 : pink, CXCL13 : red, Merge: white. D) Boxplot of the colocalization of the cell fraction with CD74 , C1QC , and CXCL13 expression between the tumor and LN samples when the enrichment calculation cutoff is 0.6. P value was calculated by an unpaired two‐tailed Student's t‐test. E) Circular plot of the cell‐cell interactions between niches in the three samples. The colors indicate the niche. The area of each bond indicates the frequency of interaction. F) Spatial trajectory of subclusters in niches 4–6. Arrows show the direction of the trajectory. G) Tree plot of the trajectory of subclusters in niches 4–6.
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(A) Scatter plot showing correlation of RNA and protein expression in iWAT after 11 days of exercise training. Negr1 is highlighted with a red box. (B-C) <t>Visium</t> images (B) and relative individual violin plots (C) showing the Negr1 expression level across the cell clusters detected in iWAT from sedentary ( left ) and exercise training ( right ). (D) Representative whole-tissue images of iWAT from sedentary ( top ) and trained ( bottom ) mice immunolabeled with TH ( green ) and NEGR1( magenta ). Maximum intensity projection from a 1000 μm z-stack and High-magnification view of ROI are shown (a-b).
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(A) Scatter plot showing correlation of RNA and protein expression in iWAT after 11 days of exercise training. Negr1 is highlighted with a red box. (B-C) <t>Visium</t> images (B) and relative individual violin plots (C) showing the Negr1 expression level across the cell clusters detected in iWAT from sedentary ( left ) and exercise training ( right ). (D) Representative whole-tissue images of iWAT from sedentary ( top ) and trained ( bottom ) mice immunolabeled with TH ( green ) and NEGR1( magenta ). Maximum intensity projection from a 1000 μm z-stack and High-magnification view of ROI are shown (a-b).
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A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length cDNA library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The procedure to simulate single-cell long reads sequencing as a benchmark dataset. Different number of transcripts are first simulated under the guidance of a cell isoform expression dataset. Each transcript is then amplified according to their GC ratio. Then, the sequencing errors and truncations are introduced to mimic the Nanopore sequencing data quality. B The procedure to generate the real benchmark dataset. The left plot shows the sequencing for Jurkat cells: The 10× full-length cDNA library was randomly split into two parts, one for Pacbio and one for Nanopore. Sequences from Pacbio was processed by their official tool isoseq, while Nanopore sequencing was processed by other methods for single-cell isoform quantification. The output from each method is then compared with the isoform quantification from Isoseq by correlation. The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore. The Ilumina sequencing is used to guide the cell barcode and UMI recovery to generate a confident single-cell isoform quantification. Methods to be benchmarked are applied only to the Nanopore data. The output from each method is then compared with the confident isoform quantification by correlation. C The per cell Spearman correlation on simulated data across different data quality for 220 cells. D The per-cell Spearman correlation on the full transcriptome simulated data across different down-sampling rates for 918 cells. E The per cell Spearman correlation on the real data: the upper one is the result on the Jurkat cells (5881 cells) and the bottom one is the result on the MOB (918 cells). Boxplots are defined as in Fig. . Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Sequencing, Expressing, Amplification, Nanopore Sequencing, cDNA Library Assay, Sampling

A The UMAP of the colorectal cancer metastasis to the liver (CRCLM) single cell data, each point is a cell colored by its cell type definition. B The paired VISIUM sequencing for the same CRCLM sample. The left plot shows the histology, indicating the tumor region. The right plot shows the dominant cell type in each spot. C The relationship between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ means the mean of percent-spliced-in for an exon across the cell population, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ means the inter-cell heterogeneity of this exon. The histograms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ are colored by their \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ . The dots above each histogram show the alternative splicing across the cell population. The dot filled in red means the target exon is preserved in the isoforms in this cell, while the dot filled in white means the target exon is spliced out. The circle filled in red gradient means the cell expresses both isoforms. D ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons in CRCLM single cell data, the color indicates the confidence interval of ϕ estimation. E The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ distribution for exon 6 of MYL6 , which has a very high ϕ , indicating high intercell heterogeneity. In this histogram, x -axis shows the exon \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ and y -axis shows the cell frequency whose \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ value falls in this bin. As \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ estimation is influenced by the gene expression, the average gene expression for is bin is shown in color gradient. F The left plot shows the ψ distribution for exon 6 of MYL6 across cells, epithelial show the highest inclusion-level of this exon. The expression of two dominant isoforms across different cells are shown in the right heatmap, epithelial has higher expression of MYL6-218 compared to other cell types. G The sashimi plot shows the comparison of bulk expression of MYL6-207 and MYL6-218 between epithelial cells and other immune cells. H The spatial view of the expression for MYL6-218 (top) and MYL6-207 (bottom). The regions for myeloid cells are marked by black circles. Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The UMAP of the colorectal cancer metastasis to the liver (CRCLM) single cell data, each point is a cell colored by its cell type definition. B The paired VISIUM sequencing for the same CRCLM sample. The left plot shows the histology, indicating the tumor region. The right plot shows the dominant cell type in each spot. C The relationship between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ means the mean of percent-spliced-in for an exon across the cell population, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\phi$$\end{document} ϕ means the inter-cell heterogeneity of this exon. The histograms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ are colored by their \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ . The dots above each histogram show the alternative splicing across the cell population. The dot filled in red means the target exon is preserved in the isoforms in this cell, while the dot filled in white means the target exon is spliced out. The circle filled in red gradient means the cell expresses both isoforms. D ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons in CRCLM single cell data, the color indicates the confidence interval of ϕ estimation. E The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ distribution for exon 6 of MYL6 , which has a very high ϕ , indicating high intercell heterogeneity. In this histogram, x -axis shows the exon \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ and y -axis shows the cell frequency whose \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ value falls in this bin. As \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document} ψ estimation is influenced by the gene expression, the average gene expression for is bin is shown in color gradient. F The left plot shows the ψ distribution for exon 6 of MYL6 across cells, epithelial show the highest inclusion-level of this exon. The expression of two dominant isoforms across different cells are shown in the right heatmap, epithelial has higher expression of MYL6-218 compared to other cell types. G The sashimi plot shows the comparison of bulk expression of MYL6-207 and MYL6-218 between epithelial cells and other immune cells. H The spatial view of the expression for MYL6-218 (top) and MYL6-207 (bottom). The regions for myeloid cells are marked by black circles. Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Sequencing, Alternative Splicing, Gene Expression, Expressing, Comparison

A The spatial plot for the VISIUM slice, each spot is colored by the layer identification. B ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons, color indicates the confidence interval of ϕ . C The mean change vs. variance change of ψ for all significant meta-sites which are alternatively spliced across different layers. The point size indicates the significance after FDR control, while the color indicates in which layer this meta-site is alternatively spliced. D The ψ distribution for exon 3 of Plp1 , which has the highest ϕ and shows a bimodal distribution, indicating a low inter-cell heterogeneity. E Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 3 of Plp1 . Cells which have low expression (<3) of this gene and could not give a confident ψ estimation are the smallest points colored in gray. The gene expression for each spot is shown by the point size, while the ψ estimation is shown by the color gradient. F , G The alternative splicing for Plp1 in different layers. H The ψ distribution for exon 4 of Mapre3 , which has a relatively high ϕ and show a bimodal distribution, indicating a high inter-cell heterogeneity. I Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 4 of Mapre3 . J , K The alternative splicing for Mapre3 in different layers. Source data are provided in 10.5281/zenodo.15320816.

Journal: Nature Communications

Article Title: Single cell and spatial alternative splicing analysis with Nanopore long read sequencing

doi: 10.1038/s41467-025-60902-2

Figure Lengend Snippet: A The spatial plot for the VISIUM slice, each spot is colored by the layer identification. B ϕ vs . \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\psi }$$\end{document} ψ ¯ distribution for alternative spliced exons, color indicates the confidence interval of ϕ . C The mean change vs. variance change of ψ for all significant meta-sites which are alternatively spliced across different layers. The point size indicates the significance after FDR control, while the color indicates in which layer this meta-site is alternatively spliced. D The ψ distribution for exon 3 of Plp1 , which has the highest ϕ and shows a bimodal distribution, indicating a low inter-cell heterogeneity. E Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 3 of Plp1 . Cells which have low expression (<3) of this gene and could not give a confident ψ estimation are the smallest points colored in gray. The gene expression for each spot is shown by the point size, while the ψ estimation is shown by the color gradient. F , G The alternative splicing for Plp1 in different layers. H The ψ distribution for exon 4 of Mapre3 , which has a relatively high ϕ and show a bimodal distribution, indicating a high inter-cell heterogeneity. I Spatial plot of spots in the slice of mouse olfactory bulb. The spots are colored by ψ for exon 4 of Mapre3 . J , K The alternative splicing for Mapre3 in different layers. Source data are provided in 10.5281/zenodo.15320816.

Article Snippet: The right plot shows the sequencing for the mouse olfactory bulb: The Visium full-length cDNA library was randomly split into two parts, one for Illumina and one for Nanopore.

Techniques: Control, Expressing, Gene Expression, Alternative Splicing

(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Journal: GEN biotechnology

Article Title: Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

doi: 10.1089/genbio.2023.0019

Figure Lengend Snippet: (A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Article Snippet: Visium-SPG cDNA library generation and sequencing Immediately after slide imaging, each tissue section was permeabilized and processed for cDNA synthesis, amplification, and library construction according to the Visium Spatial Gene Expression User Guide (10x Genomics, Cat# CG000239 Rev B).

Techniques: Control, Gene Expression, Staining, Imaging, Immunofluorescence, cDNA Synthesis, Generated, Blocking Assay

Metastatic lymph nodes in ESCC exhibit expansive enrichment of T cells and macrophages. A) Spatial transcriptomic spots of all three samples: Before, After, and AfterLN. The colors indicate the niches of each sample. B) Boxplot of the contact frequency of spatial niches in each sample. P value was calculated by an unpaired two‐tailed Student's t‐test, n (Before) = 21 413, n (After) = 32 618, n (AfterLN) = 33 246. C) CD74, C1QC , and CXCL13 expression were labeled by RNAscope in situ hybridization. Left: HE; Middle: 10X RNAscope; Right: 20X RNAscope. DAPI: blue, C1QC : green, CD74 : pink, CXCL13 : red, Merge: white. D) Boxplot of the colocalization of the cell fraction with CD74 , C1QC , and CXCL13 expression between the tumor and LN samples when the enrichment calculation cutoff is 0.6. P value was calculated by an unpaired two‐tailed Student's t‐test. E) Circular plot of the cell‐cell interactions between niches in the three samples. The colors indicate the niche. The area of each bond indicates the frequency of interaction. F) Spatial trajectory of subclusters in niches 4–6. Arrows show the direction of the trajectory. G) Tree plot of the trajectory of subclusters in niches 4–6.

Journal: Advanced Science

Article Title: Spatial Isoforms Reveal the Mechanisms of Metastasis

doi: 10.1002/advs.202402242

Figure Lengend Snippet: Metastatic lymph nodes in ESCC exhibit expansive enrichment of T cells and macrophages. A) Spatial transcriptomic spots of all three samples: Before, After, and AfterLN. The colors indicate the niches of each sample. B) Boxplot of the contact frequency of spatial niches in each sample. P value was calculated by an unpaired two‐tailed Student's t‐test, n (Before) = 21 413, n (After) = 32 618, n (AfterLN) = 33 246. C) CD74, C1QC , and CXCL13 expression were labeled by RNAscope in situ hybridization. Left: HE; Middle: 10X RNAscope; Right: 20X RNAscope. DAPI: blue, C1QC : green, CD74 : pink, CXCL13 : red, Merge: white. D) Boxplot of the colocalization of the cell fraction with CD74 , C1QC , and CXCL13 expression between the tumor and LN samples when the enrichment calculation cutoff is 0.6. P value was calculated by an unpaired two‐tailed Student's t‐test. E) Circular plot of the cell‐cell interactions between niches in the three samples. The colors indicate the niche. The area of each bond indicates the frequency of interaction. F) Spatial trajectory of subclusters in niches 4–6. Arrows show the direction of the trajectory. G) Tree plot of the trajectory of subclusters in niches 4–6.

Article Snippet: Based on a previous SiT workflow, full‐length 10X Genomics Visium cDNA libraries were split for Illumina sequencing and ONT sequencing.

Techniques: Two Tailed Test, Expressing, Labeling, RNAscope, In Situ Hybridization

The CD74 isoform ratio revealed enrichment of CD8 + CXCL13 + T cells and C1QC + TAMs. A,H) Spatial distribution of the CD74‐ 201 isoform and CD74 ‐202 isoform in the After and AfterLN samples. The colors indicate the expression levels. B,I) Spatial distribution of the ratio of CD74 ‐202 isoform expression/ CD74 ‐201 isoform expression in the After and AfterLN samples. The color level indicates the ratio of CD74 ‐202 / CD74 ‐201 isoform expression. C,J) Spatial distribution of C1QC + TAMs, CD8 + CXCL13 + Tex cells in the After and AfterLN samples. D,K) C1QC + TAMs and CD8 + CXCL13 + Tex cells’ enrichment score distribution in the After and AfterLN samples. E,L) Pie charts of C1QC + TAMs and CD8 + CXCL13 + Tex cells enriched in low, medium, and high CD74 ‐202/ CD74 ‐201 ratio groups in the After and AfterLN samples. P values were calculated by a chi‐square test. In the After sample, n (low) = 57, n (medium) = 237, n (high) = 27. In the AfterLN sample, n (low) = 324, n (medium) = 969, n (high) = 15. F,M) Boxplots of enrichment scores in low, medium, and high CD74 ‐202 isoform expression/ CD74 ‐201 ratio groups in the After and AfterLN samples. P value was calculated by an unpaired two‐tailed Student's t‐test G,N) Boxplots of CD74 ‐202 / CD74 ‐201 ratio in enrichment spots (enrichment score > 0) and other spots in the After and AfterLN samples. P value was calculated by an unpaired two‐tailed Student's t‐test. O) Pie charts of C1QC + TAMs and CD8 + CXCL13 + Tex cells enriched in low, medium, and high CD74 ‐202/ CD74 ‐201 ratio groups in the validation samples. P value was calculated by a chi‐square test, n (low) = 82, n (medium) = 199, n (high) = 7. P) Boxplots of enrichment scores in low, medium, and high CD74 ‐202 isoform expression/ CD74 ‐201 ratio groups in the validation samples. P value was calculated by an unpaired two‐tailed Student's t‐test. Q) Boxplots of CD74 ‐202 / CD74 ‐201 ratio in enrichment spots (enrichment score > 0) and other spots in the validation samples. P value was calculated by an unpaired two‐tailed Student's t‐test. R) Detection of the CD74‐ 202 and CD74‐ 201 isoforms in the tumor and LN samples labeled by BaseScope hybridization technology. Left: HE; middle: 10X BaseScope; right: 20X BaseScope. Dark purple elements indicate counterstained nuclei. CD74‐ 201: pink, CD74‐ 202: turquoise. S) Boxplot of the ratio of CD74‐ 202 to CD74‐ 201 between tumors and LNs. P value was calculated by an unpaired two‐tailed Student's t‐test. T) Boxplot of the CD74‐ 202 count between tumors and LNs. P value was calculated by an unpaired two‐tailed Student's t‐test.

Journal: Advanced Science

Article Title: Spatial Isoforms Reveal the Mechanisms of Metastasis

doi: 10.1002/advs.202402242

Figure Lengend Snippet: The CD74 isoform ratio revealed enrichment of CD8 + CXCL13 + T cells and C1QC + TAMs. A,H) Spatial distribution of the CD74‐ 201 isoform and CD74 ‐202 isoform in the After and AfterLN samples. The colors indicate the expression levels. B,I) Spatial distribution of the ratio of CD74 ‐202 isoform expression/ CD74 ‐201 isoform expression in the After and AfterLN samples. The color level indicates the ratio of CD74 ‐202 / CD74 ‐201 isoform expression. C,J) Spatial distribution of C1QC + TAMs, CD8 + CXCL13 + Tex cells in the After and AfterLN samples. D,K) C1QC + TAMs and CD8 + CXCL13 + Tex cells’ enrichment score distribution in the After and AfterLN samples. E,L) Pie charts of C1QC + TAMs and CD8 + CXCL13 + Tex cells enriched in low, medium, and high CD74 ‐202/ CD74 ‐201 ratio groups in the After and AfterLN samples. P values were calculated by a chi‐square test. In the After sample, n (low) = 57, n (medium) = 237, n (high) = 27. In the AfterLN sample, n (low) = 324, n (medium) = 969, n (high) = 15. F,M) Boxplots of enrichment scores in low, medium, and high CD74 ‐202 isoform expression/ CD74 ‐201 ratio groups in the After and AfterLN samples. P value was calculated by an unpaired two‐tailed Student's t‐test G,N) Boxplots of CD74 ‐202 / CD74 ‐201 ratio in enrichment spots (enrichment score > 0) and other spots in the After and AfterLN samples. P value was calculated by an unpaired two‐tailed Student's t‐test. O) Pie charts of C1QC + TAMs and CD8 + CXCL13 + Tex cells enriched in low, medium, and high CD74 ‐202/ CD74 ‐201 ratio groups in the validation samples. P value was calculated by a chi‐square test, n (low) = 82, n (medium) = 199, n (high) = 7. P) Boxplots of enrichment scores in low, medium, and high CD74 ‐202 isoform expression/ CD74 ‐201 ratio groups in the validation samples. P value was calculated by an unpaired two‐tailed Student's t‐test. Q) Boxplots of CD74 ‐202 / CD74 ‐201 ratio in enrichment spots (enrichment score > 0) and other spots in the validation samples. P value was calculated by an unpaired two‐tailed Student's t‐test. R) Detection of the CD74‐ 202 and CD74‐ 201 isoforms in the tumor and LN samples labeled by BaseScope hybridization technology. Left: HE; middle: 10X BaseScope; right: 20X BaseScope. Dark purple elements indicate counterstained nuclei. CD74‐ 201: pink, CD74‐ 202: turquoise. S) Boxplot of the ratio of CD74‐ 202 to CD74‐ 201 between tumors and LNs. P value was calculated by an unpaired two‐tailed Student's t‐test. T) Boxplot of the CD74‐ 202 count between tumors and LNs. P value was calculated by an unpaired two‐tailed Student's t‐test.

Article Snippet: Based on a previous SiT workflow, full‐length 10X Genomics Visium cDNA libraries were split for Illumina sequencing and ONT sequencing.

Techniques: Expressing, Two Tailed Test, Labeling, Hybridization

(A) Scatter plot showing correlation of RNA and protein expression in iWAT after 11 days of exercise training. Negr1 is highlighted with a red box. (B-C) Visium images (B) and relative individual violin plots (C) showing the Negr1 expression level across the cell clusters detected in iWAT from sedentary ( left ) and exercise training ( right ). (D) Representative whole-tissue images of iWAT from sedentary ( top ) and trained ( bottom ) mice immunolabeled with TH ( green ) and NEGR1( magenta ). Maximum intensity projection from a 1000 μm z-stack and High-magnification view of ROI are shown (a-b).

Journal: bioRxiv

Article Title: Exercise Training Remodels Inguinal White Adipose Tissue Through Adaptations in Innervation, Vascularization and the Extracellular Matrix

doi: 10.1101/2022.08.09.503375

Figure Lengend Snippet: (A) Scatter plot showing correlation of RNA and protein expression in iWAT after 11 days of exercise training. Negr1 is highlighted with a red box. (B-C) Visium images (B) and relative individual violin plots (C) showing the Negr1 expression level across the cell clusters detected in iWAT from sedentary ( left ) and exercise training ( right ). (D) Representative whole-tissue images of iWAT from sedentary ( top ) and trained ( bottom ) mice immunolabeled with TH ( green ) and NEGR1( magenta ). Maximum intensity projection from a 1000 μm z-stack and High-magnification view of ROI are shown (a-b).

Article Snippet: All Visium cDNA libraries were indexed, pooled, and sequenced simultaneously on the Illumina NovaSeq6000 platform, supported by the BioMicro Center Core at MIT.

Techniques: Expressing, Immunolabeling