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    10X Genomics single cell transcriptomes methods
    a , Optic lobe cross-section , with drawings of unicolumnar (orange shades) and multicolumnar (blue) neurons. Dashed lines: boundaries between layers. A: anterior, L: lateral, M: medial, P: posterior. b, Approach followed to produce the adult dataset. c, Pearson correlation between the average gene expression of the adult dataset clusters (x-axis) and the <t>transcriptome</t> of isolated Lawf1 neurons (Methods). d, tSNE visualization of the final adult dataset, using 120 principal components calculated on the log-normalized integrated gene expression. The 61 identified neuronal clusters are labeled by their standard abbreviation, G1–16: glial clusters, LQ: low-quality cells, G/LQ1–4: glial clusters with some features of low-quality cells, *: clusters with less confident annotations . e, Approximate time frames of different steps of optic lobe development, and tSNE visualizations of the pupal datasets. Colors match to the adult dataset as classified by the neural network. f, Multi-task neural network classifier used at each stage to sequentially match developing cells to the adult clusters, as detailed in .
    Single Cell Transcriptomes Methods, supplied by 10X Genomics, 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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    Average 86 stars, based on 1 article reviews
    single cell transcriptomes methods - by Bioz Stars, 2026-09
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    1) Product Images from "Neuronal diversity and convergence in a visual system developmental atlas"

    Article Title: Neuronal diversity and convergence in a visual system developmental atlas

    Journal: Nature

    doi: 10.1038/s41586-020-2879-3

    a , Optic lobe cross-section , with drawings of unicolumnar (orange shades) and multicolumnar (blue) neurons. Dashed lines: boundaries between layers. A: anterior, L: lateral, M: medial, P: posterior. b, Approach followed to produce the adult dataset. c, Pearson correlation between the average gene expression of the adult dataset clusters (x-axis) and the transcriptome of isolated Lawf1 neurons (Methods). d, tSNE visualization of the final adult dataset, using 120 principal components calculated on the log-normalized integrated gene expression. The 61 identified neuronal clusters are labeled by their standard abbreviation, G1–16: glial clusters, LQ: low-quality cells, G/LQ1–4: glial clusters with some features of low-quality cells, *: clusters with less confident annotations . e, Approximate time frames of different steps of optic lobe development, and tSNE visualizations of the pupal datasets. Colors match to the adult dataset as classified by the neural network. f, Multi-task neural network classifier used at each stage to sequentially match developing cells to the adult clusters, as detailed in .
    Figure Legend Snippet: a , Optic lobe cross-section , with drawings of unicolumnar (orange shades) and multicolumnar (blue) neurons. Dashed lines: boundaries between layers. A: anterior, L: lateral, M: medial, P: posterior. b, Approach followed to produce the adult dataset. c, Pearson correlation between the average gene expression of the adult dataset clusters (x-axis) and the transcriptome of isolated Lawf1 neurons (Methods). d, tSNE visualization of the final adult dataset, using 120 principal components calculated on the log-normalized integrated gene expression. The 61 identified neuronal clusters are labeled by their standard abbreviation, G1–16: glial clusters, LQ: low-quality cells, G/LQ1–4: glial clusters with some features of low-quality cells, *: clusters with less confident annotations . e, Approximate time frames of different steps of optic lobe development, and tSNE visualizations of the pupal datasets. Colors match to the adult dataset as classified by the neural network. f, Multi-task neural network classifier used at each stage to sequentially match developing cells to the adult clusters, as detailed in .

    Techniques Used: Gene Expression, Isolation, Labeling

    a. The proportions of UMIs from mitochondrial genes per cell (n = number of cells in each library, indicated on the right) and the total number of cells passing filters in each of the 15 libraries comprising the adult dataset. Names indicated correspond to the names in the Seurat object provided (Adult.rds, GSE142787). Boxplots display the first, second and third quartiles. Whiskers extend from the box to the highest or lowest values in the 1.5 inter-quartile range, and outlying datapoints are represented by a dot. b, Origin of the cells in the final adult clusters, colored as in (a). Green arrows: clusters whose unique library distribution can be explained by variable contamination from surrounding tissues (cluster 3 is photoreceptors, 112 is likely Kenyon Cells from the central brain) or the number of lamina neuropils dissociated (clusters 107, 108, 109 are lamina neurons). Red arrows: clusters likely enriched in low quality transcriptomes, as they are enriched in cells from libraries with high number of mitochondrial genes (38, 120, 192) or high number of cells sequenced (102, likely corresponding to multiplets). Brackets: Glial clusters, some of them enriched in libraries with high number of mitochondrial genes as ambient RNA is more similar to RNA from glial vs . neuronal cells . c, Number of clusters obtained with different pairs of clustering parameters. Red rectangle: pair of parameters used. d, Left: Legend as in . Right: Number of isolated neuronal type transcriptomes matching to 1–5 of our adult clusters, for each pair of parameters in (c), which we used as a measure of the biological relevance of our clusters. Matching was defined by the presence of a correlation gap above 0.05 (Methods). We took into account any correlation gap between the 6 best correlated clusters, since similar cell types or overclustering can affect the size of the first correlation gap as illustrated on the left graphs. Red rectangle: pair of parameters used. e, tSNE visualization of the adult optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cell colors indicate the cluster they belonged to before we merged artificially split clusters (red circles, Methods). f, Heatmap showing scaled log-normalized non-integrated expression of the top20 cluster markers between the merged clusters. Merged clusters had almost indistinguishable gene expression patterns, but often differed by their proportions of UMI from mitochondrial genes per cell or the expression levels of the genes highlighted in red, which are enriched in the “ambient RNA cluster” 192 (see also ).
    Figure Legend Snippet: a. The proportions of UMIs from mitochondrial genes per cell (n = number of cells in each library, indicated on the right) and the total number of cells passing filters in each of the 15 libraries comprising the adult dataset. Names indicated correspond to the names in the Seurat object provided (Adult.rds, GSE142787). Boxplots display the first, second and third quartiles. Whiskers extend from the box to the highest or lowest values in the 1.5 inter-quartile range, and outlying datapoints are represented by a dot. b, Origin of the cells in the final adult clusters, colored as in (a). Green arrows: clusters whose unique library distribution can be explained by variable contamination from surrounding tissues (cluster 3 is photoreceptors, 112 is likely Kenyon Cells from the central brain) or the number of lamina neuropils dissociated (clusters 107, 108, 109 are lamina neurons). Red arrows: clusters likely enriched in low quality transcriptomes, as they are enriched in cells from libraries with high number of mitochondrial genes (38, 120, 192) or high number of cells sequenced (102, likely corresponding to multiplets). Brackets: Glial clusters, some of them enriched in libraries with high number of mitochondrial genes as ambient RNA is more similar to RNA from glial vs . neuronal cells . c, Number of clusters obtained with different pairs of clustering parameters. Red rectangle: pair of parameters used. d, Left: Legend as in . Right: Number of isolated neuronal type transcriptomes matching to 1–5 of our adult clusters, for each pair of parameters in (c), which we used as a measure of the biological relevance of our clusters. Matching was defined by the presence of a correlation gap above 0.05 (Methods). We took into account any correlation gap between the 6 best correlated clusters, since similar cell types or overclustering can affect the size of the first correlation gap as illustrated on the left graphs. Red rectangle: pair of parameters used. e, tSNE visualization of the adult optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cell colors indicate the cluster they belonged to before we merged artificially split clusters (red circles, Methods). f, Heatmap showing scaled log-normalized non-integrated expression of the top20 cluster markers between the merged clusters. Merged clusters had almost indistinguishable gene expression patterns, but often differed by their proportions of UMI from mitochondrial genes per cell or the expression levels of the genes highlighted in red, which are enriched in the “ambient RNA cluster” 192 (see also ).

    Techniques Used: Isolation, Gene Expression, Expressing

    a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated Repo+ (glial marker) or Elav+ (neuronal marker) populations. LQ = clusters containing a proportion of cells with features of lower quality transcriptomes. b, Violin plots of features tending to be higher (proportions of UMI from mitochondrial genes) or lower (number of UMIs or genes per cell) in low quality cells , . c, Heatmap showing the scaled log-normalized non-integrated expression of the top5 cluster markers of the adult dataset. The first 5 neuronal adult clusters (1 to 6, cluster 1 and 2 having been merged) are plotted for reference as they clearly have specific gene expression patterns. Clusters 38, 85, 102 and 120 present much less defined gene expression patterns and likely contain low quality neuronal transcriptomes (see also ). Clusters 188 and 189 could be further separated in two groups with different gene expression patterns, as illustrated by the dashed line in the insert. Cluster 191 expresses several markers found in no other clusters and likely correspond to neither glia nor optic-lobe neuron. Cluster 192 expresses mainly low levels of glia-specific genes, without specific markers. It likely corresponds to ambient RNA, which would be enriched in RNA from burst glial cells.
    Figure Legend Snippet: a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated Repo+ (glial marker) or Elav+ (neuronal marker) populations. LQ = clusters containing a proportion of cells with features of lower quality transcriptomes. b, Violin plots of features tending to be higher (proportions of UMI from mitochondrial genes) or lower (number of UMIs or genes per cell) in low quality cells , . c, Heatmap showing the scaled log-normalized non-integrated expression of the top5 cluster markers of the adult dataset. The first 5 neuronal adult clusters (1 to 6, cluster 1 and 2 having been merged) are plotted for reference as they clearly have specific gene expression patterns. Clusters 38, 85, 102 and 120 present much less defined gene expression patterns and likely contain low quality neuronal transcriptomes (see also ). Clusters 188 and 189 could be further separated in two groups with different gene expression patterns, as illustrated by the dashed line in the insert. Cluster 191 expresses several markers found in no other clusters and likely correspond to neither glia nor optic-lobe neuron. Cluster 192 expresses mainly low levels of glia-specific genes, without specific markers. It likely corresponds to ambient RNA, which would be enriched in RNA from burst glial cells.

    Techniques Used: Expressing, Isolation, Marker, Gene Expression

    a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated neurons , . We represented Dm3, Tm9, T4 and T5 before their split into Dm3a/b, Tm9v/d, T4/T5ab and T4/T5cd. When two transcriptomes were published for a given neuronal type, the one presenting the highest correlation gap is displayed in this figure. R1–8: average gene expression of all photoreceptors . KC: Kenyon Cells, cluster 112 therefore likely corresponds to contamination from the central brain. b, Legend as in (a). We indicated several matching clusters to highlight the high similarity between LC cells transcriptomes, which explains the lower correlation gaps observed for these neurons. c, Left: Legend as in (a). Right: mixture modelling of Pm3 markers (y axis). Clusters are spread on the x-axis, with the probability of expression of the markers figured by the size of the black dots.
    Figure Legend Snippet: a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated neurons , . We represented Dm3, Tm9, T4 and T5 before their split into Dm3a/b, Tm9v/d, T4/T5ab and T4/T5cd. When two transcriptomes were published for a given neuronal type, the one presenting the highest correlation gap is displayed in this figure. R1–8: average gene expression of all photoreceptors . KC: Kenyon Cells, cluster 112 therefore likely corresponds to contamination from the central brain. b, Legend as in (a). We indicated several matching clusters to highlight the high similarity between LC cells transcriptomes, which explains the lower correlation gaps observed for these neurons. c, Left: Legend as in (a). Right: mixture modelling of Pm3 markers (y axis). Clusters are spread on the x-axis, with the probability of expression of the markers figured by the size of the black dots.

    Techniques Used: Expressing, Isolation, Gene Expression

    a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells colors indicate the clusters they belonged to according to unsupervised clustering (a), or the adult clusters they were classified as by the neural network (b, same as in ). Black circles indicate high granularity regions, where less frequent cell types were grouped together by unsupervised clustering but could be resolved accurately by the neural network (b). c, Same as in (a-b) but cells are named and colored by the adult cluster they were classified as by Seurat label transfer (Methods). d, tSNE visualizations (same as c) including only the cells that were assigned inconsistent identities by Seurat and the neural network. Highest rates of inconsistencies were observed in the center (LQ cells), in L1 and L2 clusters (red ellipses), in most glia clusters (green ellipses), the TE neurons and a glia-like cluster (identity 214, ) with no adult correspondence (blue ellipses). e-f, tSNE visualizations of 56,902 cells sequenced from whole fly brains , using 120 principal components calculated on the log-normalized gene expression. e, Cells are named and colored by the clusters they were classified as by our neural network. f, Cells are named by the cluster identities from the original study and colored by the confidence score they received from our neural network. Black circles mark the following central brain clusters (from left to right): Poxn, OPN, clock neurons and dopaminergic neurons, that all received low scores from the neural network. Kenyon cells (red circles) were assigned with high confidence as our adult dataset was contaminated by them (cluster 112).
    Figure Legend Snippet: a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells colors indicate the clusters they belonged to according to unsupervised clustering (a), or the adult clusters they were classified as by the neural network (b, same as in ). Black circles indicate high granularity regions, where less frequent cell types were grouped together by unsupervised clustering but could be resolved accurately by the neural network (b). c, Same as in (a-b) but cells are named and colored by the adult cluster they were classified as by Seurat label transfer (Methods). d, tSNE visualizations (same as c) including only the cells that were assigned inconsistent identities by Seurat and the neural network. Highest rates of inconsistencies were observed in the center (LQ cells), in L1 and L2 clusters (red ellipses), in most glia clusters (green ellipses), the TE neurons and a glia-like cluster (identity 214, ) with no adult correspondence (blue ellipses). e-f, tSNE visualizations of 56,902 cells sequenced from whole fly brains , using 120 principal components calculated on the log-normalized gene expression. e, Cells are named and colored by the clusters they were classified as by our neural network. f, Cells are named by the cluster identities from the original study and colored by the confidence score they received from our neural network. Black circles mark the following central brain clusters (from left to right): Poxn, OPN, clock neurons and dopaminergic neurons, that all received low scores from the neural network. Kenyon cells (red circles) were assigned with high confidence as our adult dataset was contaminated by them (cluster 112).

    Techniques Used: Gene Expression

    tSNE visualizations of all optic lobe single-cell transcriptomes acquired for this study, using 120 principal components calculated on the log-normalized integrated gene expression. The cells are named and colored consistently at all stages by the neural network classifications with manual adjustments as detailed in . Blue ellipses: Dm3 and Tm9 neuronal subtypes, which could only be resolved at P50 and earlier.
    Figure Legend Snippet: tSNE visualizations of all optic lobe single-cell transcriptomes acquired for this study, using 120 principal components calculated on the log-normalized integrated gene expression. The cells are named and colored consistently at all stages by the neural network classifications with manual adjustments as detailed in . Blue ellipses: Dm3 and Tm9 neuronal subtypes, which could only be resolved at P50 and earlier.

    Techniques Used: Gene Expression

    a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network (NN) or by (b) the log-normalized non-integrated expression of Fs (green), dimm (blue), and skl (red), which are co-expressed in TE neurons (red ellipses). c , Violin plot of log-normalized non-integrated prt expression in all clusters at P50. TE neuron clusters are indicated by circle. d , R10D10-Gal4 co-expression with anti-Prt staining in a P50 optic lobe (n=15 neurons). Scale bar: 10 μm. e , FLEXAMP memory cassette labeling of R10D10-Gal4 in an adult optic lobe (n=28 brains) with anti-NCad staining. Scale bar: 30 μm. f, R10D10-Gal4 expression pattern in L3 optic lobe (n=15 brains), with anti-NCad, anti-Bsh and anti-Hth staining. Arrow: Bsh + , Hth - neurons labeled by R10D10-Gal4 . Scale bar: 30 μm. g-h, R10D10-Gal4 sparse expression at P30 (n=40 neurons), with anti-NCad, anti-Bsh and anti-Hth staining. Scale bars = 5 μm (g) and 15 μm (h). d/pMe: distal/proximal Medulla, Lo: Lobula, Lp: Lobula plate. I , Co-labeling of R10D10-LexA expression and bsh-Gal4 FLEXAMP memory cassette with anti-nCad staining in a P50 optic lobe (n=13 brains). Dashed ellipses: TE neurons. Scale bar: 20 μm.
    Figure Legend Snippet: a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network (NN) or by (b) the log-normalized non-integrated expression of Fs (green), dimm (blue), and skl (red), which are co-expressed in TE neurons (red ellipses). c , Violin plot of log-normalized non-integrated prt expression in all clusters at P50. TE neuron clusters are indicated by circle. d , R10D10-Gal4 co-expression with anti-Prt staining in a P50 optic lobe (n=15 neurons). Scale bar: 10 μm. e , FLEXAMP memory cassette labeling of R10D10-Gal4 in an adult optic lobe (n=28 brains) with anti-NCad staining. Scale bar: 30 μm. f, R10D10-Gal4 expression pattern in L3 optic lobe (n=15 brains), with anti-NCad, anti-Bsh and anti-Hth staining. Arrow: Bsh + , Hth - neurons labeled by R10D10-Gal4 . Scale bar: 30 μm. g-h, R10D10-Gal4 sparse expression at P30 (n=40 neurons), with anti-NCad, anti-Bsh and anti-Hth staining. Scale bars = 5 μm (g) and 15 μm (h). d/pMe: distal/proximal Medulla, Lo: Lobula, Lp: Lobula plate. I , Co-labeling of R10D10-LexA expression and bsh-Gal4 FLEXAMP memory cassette with anti-nCad staining in a P50 optic lobe (n=13 brains). Dashed ellipses: TE neurons. Scale bar: 20 μm.

    Techniques Used: Gene Expression, Expressing, Staining, Labeling

    a-b, tSNE visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network or by (b) the log-normalized non-integrated expression of dpn (green), ase (blue), and grim (red). Circles match to those of . c, UMAP visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are colored by the log-normalized non-integrated expression of nerfin-1 (green), Hey (blue), and vfl (red) d, UMAP visualization of Tm3 and T1 cells (above and below the dashed line, respectively) from all stages sequenced in this study, using 25 principal components calculated on the log-normalized non-integrated gene expression. Cells are colored by their developmental stage. e, Ventral and dorsal Transient Extrinsic (TE) neurons as well as transient photoreceptors (PRs) line the edges of all optic lobe neuropils and express Follistatin ( Fs ). Moreover, TE and at least 3 other neuronal types express Wnt4 in the ventral medulla/lobula but express Wnt10 in the dorsal part of these neuropils. f, The transcriptome of neurons from the same neuronal type but produced days apart converge towards a similar transcriptomic state, which they reach by P30. Moreover, the inter-neuronal type transcriptomic diversity is highest during P40-P70.
    Figure Legend Snippet: a-b, tSNE visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network or by (b) the log-normalized non-integrated expression of dpn (green), ase (blue), and grim (red). Circles match to those of . c, UMAP visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are colored by the log-normalized non-integrated expression of nerfin-1 (green), Hey (blue), and vfl (red) d, UMAP visualization of Tm3 and T1 cells (above and below the dashed line, respectively) from all stages sequenced in this study, using 25 principal components calculated on the log-normalized non-integrated gene expression. Cells are colored by their developmental stage. e, Ventral and dorsal Transient Extrinsic (TE) neurons as well as transient photoreceptors (PRs) line the edges of all optic lobe neuropils and express Follistatin ( Fs ). Moreover, TE and at least 3 other neuronal types express Wnt4 in the ventral medulla/lobula but express Wnt10 in the dorsal part of these neuropils. f, The transcriptome of neurons from the same neuronal type but produced days apart converge towards a similar transcriptomic state, which they reach by P30. Moreover, the inter-neuronal type transcriptomic diversity is highest during P40-P70.

    Techniques Used: Gene Expression, Expressing, Produced

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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-cell <t>transcriptome</t> analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.
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    Single-Cell RNA Sequencing Revealed That DP MΦs Had High Expression of Retnla Cardiac CD45 + immune cells were sorted from the sham group, 1 week post-TAC group (acute stress phase), and 9 weeks post-TAC group (chronic heart failure phase), and single-cell <t>transcriptomic</t> analysis was performed using the 10X Genomics platform. (A) Uniform manifold approximation and projection dimensionality reduction analysis identified that mononuclear MΦs consisted of Lyve1 hi MΦs, Lyve1 hi MHCⅡ hi MΦs, MHCⅡ hi MΦs, and monocytes after reclustering under “Lyve1score” and “MHCⅡscore” dimensions. (B) Nineteen representative differentially expressed genes are plotted as a heatmap. (C) The percentage of MΦ subsets among the total MΦs across conditions. (D) Volcano plots of differentially expressed genes across conditions including both up-regulated and down-regulated genes (minimum percentage: 0.1; logFC threshold: 0.1; adjusted P value < 0.05). Genes of interest are highlighted in red. (E) The percentage of Retlna-positive cells among the MΦ subsets detected with flow cytometry. (F) The relative expression levels of Retnla and Mgl2 in heart tissues were measured by quantitative polymerase chain reaction 3 days after diphtheria toxin injection between the sham and TAC groups (4 weeks post-TAC) using a DP MΦ–reduced model (TAC reduced). Values were analyzed by using analysis of variance with Tukey post hoc analysis. (G) Pathway enrichment analysis (gProfiler, Gene Ontology biological processes) using differentially expressed genes across conditions. ∗∗ P < 0.01; ∗∗∗ P < 0.001. avg = average; FC = fold change; mRNA = messenger RNA; other abbreviations as in <xref ref-type=Figure 1 , Figure 2 , Figure 3 . " width="250" height="auto" />
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    Image Search Results


    Single-cell transcriptome analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.

    Journal: iScience

    Article Title: Single-cell transcriptomics of neuroinflammation and cerebrovascular endothelial cells in the aged rat hippocampus

    doi: 10.1016/j.isci.2025.113332

    Figure Lengend Snippet: Single-cell transcriptome analysis of the microglia (A) UMAP shows the distribution of each subtype of microglia. (B) The sector graph shows the composition of cells in subclusters by groups. (C) Violin plot depicts the expression levels of known core signature genes for each microglia subcluster. (D) Representative immunofluorescence double staining images of NFKBIA (red), IBA1 (green), and nuclei were labeled with DAPI located in hippocampus in the NC and LPS groups. Scale bar = 75 μm or 25 μm. Quantitative analysis of the proportion of NFKBIA + cells in microglia (IBA1+) in hippocampal DG subregion. Data are shown as mean ± SEM, independent samples t-test, n = 4, ∗∗ p < 0.01. (E) Marker genes enriched KEGG pathway analyses in various microglia subpopulations. (F) GO analysis shows the top five signaling pathways across the four subpopulations, MG0, MG4, MG5 and MG7.

    Article Snippet: Based on these results, we conducted single-cell transcriptome analysis (scRNA-seq) on aging rat hippocampus on day 3 after LPS or vehicle injection using the 10X Genomics platform to examine changes in the neuroinflammatory microenvironment ( H).

    Techniques: Expressing, Immunofluorescence, Double Staining, Labeling, Marker, Protein-Protein interactions

    Single-cell transcriptome analysis of the cerebral vascular endothelial cells (A–C) UMAP plot and bar plot showing the distribution of 6 subpopulations of cerebral vascular endothelial cells in the LPS and NC groups. (D) Violin plot shows the gene expression related to vascular origin (arterial, venous, and capillary), including arterial endothelial cell marker genes Fbln5, Bmx, Efnb2 , Vegfc . The venous endothelial cells highly expressed gene Nr2f and capillary endothelial cells highly expressed gene Rgcc and Slc16a1 . (E) Expression profiles of EC0 Marker genes including Mfge8, Lrg1, Lgals9, Cldn5, Ocln, Tjp1, Ddit4/Redd1, Mfsd2a are shown using the UMAP visualization approach. (F) Marker genes in the EC0 subpopulation are enriched with GO functional analysis. (G) Volcano plot depicts the DEGs at overall level of cerebral vascular endothelial cells between LPS and NC groups. DEGs (|log2(fold change)| > 1, p Value FDR <0.05, Difference = |pct.1- pct.2 | > 0.2) were colored (red for upregulated DEGs and blue for downregulated DEGs. (H and I) GO analysis shows the upregulated signaling pathway at overall level of cerebral vascular endothelial cells and EC0 subpopulation respectively.

    Journal: iScience

    Article Title: Single-cell transcriptomics of neuroinflammation and cerebrovascular endothelial cells in the aged rat hippocampus

    doi: 10.1016/j.isci.2025.113332

    Figure Lengend Snippet: Single-cell transcriptome analysis of the cerebral vascular endothelial cells (A–C) UMAP plot and bar plot showing the distribution of 6 subpopulations of cerebral vascular endothelial cells in the LPS and NC groups. (D) Violin plot shows the gene expression related to vascular origin (arterial, venous, and capillary), including arterial endothelial cell marker genes Fbln5, Bmx, Efnb2 , Vegfc . The venous endothelial cells highly expressed gene Nr2f and capillary endothelial cells highly expressed gene Rgcc and Slc16a1 . (E) Expression profiles of EC0 Marker genes including Mfge8, Lrg1, Lgals9, Cldn5, Ocln, Tjp1, Ddit4/Redd1, Mfsd2a are shown using the UMAP visualization approach. (F) Marker genes in the EC0 subpopulation are enriched with GO functional analysis. (G) Volcano plot depicts the DEGs at overall level of cerebral vascular endothelial cells between LPS and NC groups. DEGs (|log2(fold change)| > 1, p Value FDR <0.05, Difference = |pct.1- pct.2 | > 0.2) were colored (red for upregulated DEGs and blue for downregulated DEGs. (H and I) GO analysis shows the upregulated signaling pathway at overall level of cerebral vascular endothelial cells and EC0 subpopulation respectively.

    Article Snippet: Based on these results, we conducted single-cell transcriptome analysis (scRNA-seq) on aging rat hippocampus on day 3 after LPS or vehicle injection using the 10X Genomics platform to examine changes in the neuroinflammatory microenvironment ( H).

    Techniques: Gene Expression, Marker, Expressing, Functional Assay

    Single-Cell RNA Sequencing Revealed That DP MΦs Had High Expression of Retnla Cardiac CD45 + immune cells were sorted from the sham group, 1 week post-TAC group (acute stress phase), and 9 weeks post-TAC group (chronic heart failure phase), and single-cell transcriptomic analysis was performed using the 10X Genomics platform. (A) Uniform manifold approximation and projection dimensionality reduction analysis identified that mononuclear MΦs consisted of Lyve1 hi MΦs, Lyve1 hi MHCⅡ hi MΦs, MHCⅡ hi MΦs, and monocytes after reclustering under “Lyve1score” and “MHCⅡscore” dimensions. (B) Nineteen representative differentially expressed genes are plotted as a heatmap. (C) The percentage of MΦ subsets among the total MΦs across conditions. (D) Volcano plots of differentially expressed genes across conditions including both up-regulated and down-regulated genes (minimum percentage: 0.1; logFC threshold: 0.1; adjusted P value < 0.05). Genes of interest are highlighted in red. (E) The percentage of Retlna-positive cells among the MΦ subsets detected with flow cytometry. (F) The relative expression levels of Retnla and Mgl2 in heart tissues were measured by quantitative polymerase chain reaction 3 days after diphtheria toxin injection between the sham and TAC groups (4 weeks post-TAC) using a DP MΦ–reduced model (TAC reduced). Values were analyzed by using analysis of variance with Tukey post hoc analysis. (G) Pathway enrichment analysis (gProfiler, Gene Ontology biological processes) using differentially expressed genes across conditions. ∗∗ P < 0.01; ∗∗∗ P < 0.001. avg = average; FC = fold change; mRNA = messenger RNA; other abbreviations as in <xref ref-type=Figure 1 , Figure 2 , Figure 3 . " width="100%" height="100%">

    Journal: JACC: Basic to Translational Science

    Article Title: TIMD4 hi MHCⅡ hi Macrophages Preserve Heart Function Through Retnla

    doi: 10.1016/j.jacbts.2024.08.009

    Figure Lengend Snippet: Single-Cell RNA Sequencing Revealed That DP MΦs Had High Expression of Retnla Cardiac CD45 + immune cells were sorted from the sham group, 1 week post-TAC group (acute stress phase), and 9 weeks post-TAC group (chronic heart failure phase), and single-cell transcriptomic analysis was performed using the 10X Genomics platform. (A) Uniform manifold approximation and projection dimensionality reduction analysis identified that mononuclear MΦs consisted of Lyve1 hi MΦs, Lyve1 hi MHCⅡ hi MΦs, MHCⅡ hi MΦs, and monocytes after reclustering under “Lyve1score” and “MHCⅡscore” dimensions. (B) Nineteen representative differentially expressed genes are plotted as a heatmap. (C) The percentage of MΦ subsets among the total MΦs across conditions. (D) Volcano plots of differentially expressed genes across conditions including both up-regulated and down-regulated genes (minimum percentage: 0.1; logFC threshold: 0.1; adjusted P value < 0.05). Genes of interest are highlighted in red. (E) The percentage of Retlna-positive cells among the MΦ subsets detected with flow cytometry. (F) The relative expression levels of Retnla and Mgl2 in heart tissues were measured by quantitative polymerase chain reaction 3 days after diphtheria toxin injection between the sham and TAC groups (4 weeks post-TAC) using a DP MΦ–reduced model (TAC reduced). Values were analyzed by using analysis of variance with Tukey post hoc analysis. (G) Pathway enrichment analysis (gProfiler, Gene Ontology biological processes) using differentially expressed genes across conditions. ∗∗ P < 0.01; ∗∗∗ P < 0.001. avg = average; FC = fold change; mRNA = messenger RNA; other abbreviations as in Figure 1 , Figure 2 , Figure 3 .

    Article Snippet: Figure 5 Single-Cell RNA Sequencing Revealed That DP MΦs Had High Expression of Retnla Cardiac CD45 + immune cells were sorted from the sham group, 1 week post-TAC group (acute stress phase), and 9 weeks post-TAC group (chronic heart failure phase), and single-cell transcriptomic analysis was performed using the 10X Genomics platform. (A) Uniform manifold approximation and projection dimensionality reduction analysis identified that mononuclear MΦs consisted of Lyve1 hi MΦs, Lyve1 hi MHCII hi MΦs, MHCII hi MΦs, and monocytes after reclustering under “Lyve1score” and “MHCIIscore” dimensions. (B) Nineteen representative differentially expressed genes are plotted as a heatmap. (C) The percentage of MΦ subsets among the total MΦs across conditions. (D) Volcano plots of differentially expressed genes across conditions including both up-regulated and down-regulated genes (minimum percentage: 0.1; logFC threshold: 0.1; adjusted P value < 0.05).

    Techniques: RNA Sequencing, Expressing, Flow Cytometry, Real-time Polymerase Chain Reaction, Injection