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10X Genomics chromium droplet-based sc/snrna-seq
Chromium Droplet Based Sc/Snrna Seq, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/sc+snrna+seq/chromium+droplet+based+sequencing+platform/pmc11864978-39-18-9
Average 90 stars, based on 1 article reviews
chromium droplet-based sc/snrna-seq - by Bioz Stars, 2026-10
90/100 stars

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Related Articles

other:

Article Title: Epigenetic regulation during cancer transitions across 11 tumour types.
Article Snippet: GRCh38 references used for sc/snRNA-seq (refdata-gex-GRCh38-2020-A) and snATAC-seq and snMultiome-seq (refdata-cellranger-arc-GRCh382020-A-2.0.0) analyses are freely available from the 10x Genomics website (https://support.10xgenomics.com).

Single Cell:

Article Title: Comparative single-cell analyses identify shared and divergent features of human and mouse kidney development.
Article Snippet: .. For sc/snRNA-seq, ChromiumSingle Cell 3’ Reagent Kits v2/3 reagents kits (10X Genomics, v2; PN-120237, v3; PN-100075) were used to generate single cell 3’ gene expression libraries according to manufacturer’s instructions (10X genomics, v2; CG00052, v3; CG000183). ..

Gene Expression:

Article Title: Comparative single-cell analyses identify shared and divergent features of human and mouse kidney development.
Article Snippet: .. For sc/snRNA-seq, ChromiumSingle Cell 3’ Reagent Kits v2/3 reagents kits (10X Genomics, v2; PN-120237, v3; PN-100075) were used to generate single cell 3’ gene expression libraries according to manufacturer’s instructions (10X genomics, v2; CG00052, v3; CG000183). ..



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Phenotypic differences between ATRX knockout and wildtype gliomas in an IDH-mutant background. A A schematic overview of the murine studies. B An enzymatic cleavage assay, indicating homozygous knockout in ATRX exon 9 (Top), a Western blot showing complete loss of ATRX protein (bottom). C Fluorometric 2-HG detection assay, comparing wildtype IDH1 and IDH1R132H overexpression in ATRX-KO SB28 cells, * t test p <0.05. D Representative BLI images of ATRX-KO and wildtype intercranial tumors. E BLI timeseries. F Percentages of tumor-infiltrating monocytic-lineage cells expressing the given markers in ATRX-KO vs. wildtype, in an IDH1R132H background. G (Top) Differential expression test of <t>snRNA-seq</t> data via MAST, comparing tumor-infiltrating monocytic-lineage cells between ATRX-KO and wildtype tumors in an IDH1R132H background. (Bottom) Differential expression test of snRNA-seq data via MAST, comparing neoplastic cells between ATRX-KO and ATRX-wildtype tumors in an IDH1R132H background. H Differential peaks from scATAC-seq data called between neoplastic cells from ATRX-KO and ATRX-wildtype tumors with an IDH1R132H background. Peaks are called via MACS at p <0.05 and represented as a heatmap (bottom) and moving average (top) of reads per 10 bp, in a 2 Kbp window around the transposase cut site. I ScATAC-seq motif enrichment in differential peaks between ATRX-KO and ATRX-wildtype neoplastic cells. Motif frequency relative to a genome-wide background was scored via HOMER. J ) Extracellular-matrix invasion assay, comparing ATRX-KO and wildtype cells with an IDH1R132H background
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Image Search Results


Phenotypic differences between ATRX knockout and wildtype gliomas in an IDH-mutant background. A A schematic overview of the murine studies. B An enzymatic cleavage assay, indicating homozygous knockout in ATRX exon 9 (Top), a Western blot showing complete loss of ATRX protein (bottom). C Fluorometric 2-HG detection assay, comparing wildtype IDH1 and IDH1R132H overexpression in ATRX-KO SB28 cells, * t test p <0.05. D Representative BLI images of ATRX-KO and wildtype intercranial tumors. E BLI timeseries. F Percentages of tumor-infiltrating monocytic-lineage cells expressing the given markers in ATRX-KO vs. wildtype, in an IDH1R132H background. G (Top) Differential expression test of snRNA-seq data via MAST, comparing tumor-infiltrating monocytic-lineage cells between ATRX-KO and wildtype tumors in an IDH1R132H background. (Bottom) Differential expression test of snRNA-seq data via MAST, comparing neoplastic cells between ATRX-KO and ATRX-wildtype tumors in an IDH1R132H background. H Differential peaks from scATAC-seq data called between neoplastic cells from ATRX-KO and ATRX-wildtype tumors with an IDH1R132H background. Peaks are called via MACS at p <0.05 and represented as a heatmap (bottom) and moving average (top) of reads per 10 bp, in a 2 Kbp window around the transposase cut site. I ScATAC-seq motif enrichment in differential peaks between ATRX-KO and ATRX-wildtype neoplastic cells. Motif frequency relative to a genome-wide background was scored via HOMER. J ) Extracellular-matrix invasion assay, comparing ATRX-KO and wildtype cells with an IDH1R132H background

Journal: Genome Biology

Article Title: ATRX regulates glial identity and the tumor microenvironment in IDH-mutant glioma

doi: 10.1186/s13059-021-02535-4

Figure Lengend Snippet: Phenotypic differences between ATRX knockout and wildtype gliomas in an IDH-mutant background. A A schematic overview of the murine studies. B An enzymatic cleavage assay, indicating homozygous knockout in ATRX exon 9 (Top), a Western blot showing complete loss of ATRX protein (bottom). C Fluorometric 2-HG detection assay, comparing wildtype IDH1 and IDH1R132H overexpression in ATRX-KO SB28 cells, * t test p <0.05. D Representative BLI images of ATRX-KO and wildtype intercranial tumors. E BLI timeseries. F Percentages of tumor-infiltrating monocytic-lineage cells expressing the given markers in ATRX-KO vs. wildtype, in an IDH1R132H background. G (Top) Differential expression test of snRNA-seq data via MAST, comparing tumor-infiltrating monocytic-lineage cells between ATRX-KO and wildtype tumors in an IDH1R132H background. (Bottom) Differential expression test of snRNA-seq data via MAST, comparing neoplastic cells between ATRX-KO and ATRX-wildtype tumors in an IDH1R132H background. H Differential peaks from scATAC-seq data called between neoplastic cells from ATRX-KO and ATRX-wildtype tumors with an IDH1R132H background. Peaks are called via MACS at p <0.05 and represented as a heatmap (bottom) and moving average (top) of reads per 10 bp, in a 2 Kbp window around the transposase cut site. I ScATAC-seq motif enrichment in differential peaks between ATRX-KO and ATRX-wildtype neoplastic cells. Motif frequency relative to a genome-wide background was scored via HOMER. J ) Extracellular-matrix invasion assay, comparing ATRX-KO and wildtype cells with an IDH1R132H background

Article Snippet: Differential expression for the 10X Genomics-based sc/snRNA-seq data was performed via MAST [ ].

Techniques: Knock-Out, Mutagenesis, Cleavage Assay, Western Blot, Detection Assay, Over Expression, Expressing, Genome Wide, Invasion Assay

ATRX loss induces a global loss of CTCF, correlated gene dysregulation, and protects glioma cells from therapy-induced senescence. A Anti-CTCF single-cell CUT&Tag in SB28+IDH1R132H cells with ATRX KO or ATRX-wildtype scrambled control. Reads per 10 bp are shown as heatmaps (bottom) and summarized as averages (top) in a neighborhood of JASPAR CTCF motif sites. B CTCF motif frequencies in scCUT&Tag peaks, represented as standardized deviances from a data-driven null distribution via ChromVAR, for ATRX KO vs. wildtype cells (top), *** t test p < 1e−16. Numbers of, and overlap between, peaks in ATRX KO and wildtype datasets. C Browser shots of CTCF scCUT&Tag read pile-ups with significant peaks and genes annotated. D The percentages of NSC chromatin-loops affected, directly or indirectly, by CTCF loss upon ATRX KO (top). A Q-Q plot of the average ATRX-KO/WT cell-averaged log fold-changes in gene expression for each chromatin loop determined from NSC Hi-C data. Values on the y -axis are represented as percentages of a corresponding null distribution (Methods). The x -axis quantiles are provided by a Beta distribution fit to the inter-quartile range of y -axis percentiles. Loops containing specific genes are annotated. E Browser shots of a chromatin loop containing VEGFA and closeup of one boundary domain (left). A null distribution of average ATRX-KO/WT cell-averaged log fold-changes in gene expression measured via snRNA-seq in vivo in neoplastic cells, taken across all consecutive windows of four adjacent genes in chromosome 17. The loop containing VEGFA and the percentile of its average log fold-change are annotated (right-top). Violin plots of Vegfa expression in ATRX KO and WT neoplastic cells, in vivo, *MAST q < 0.05 (right-bottom). F As in E , except for a loop containing TNC. G Fluorometric assay for β-galactosidase activity in ATRX-KO and scrambled-control SB28 cells, both expressing IDH1R132H, post-treatment with one of Doxorubicin or CDKi. Error bars indicate standard error. * t test p < 0.05. B As in A , but for patient-derived ATRX/IDH1 double-mutant cells (SF10602) compared with an ATRX-wildtype, IDH1-mutant control (SF10417). Cells were treated with one of Temozolomide, Imatinib, Doxorubicin, or CDKi. C Visualization of β-galactosidase expression in ATRX-KO and scrambled-control SB28 cells, both expressing IDH1R132H, before and after treatment with CDKi. H Model of gene dysregulation due to CTCF disruption in chromatin-loop boundaries

Journal: Genome Biology

Article Title: ATRX regulates glial identity and the tumor microenvironment in IDH-mutant glioma

doi: 10.1186/s13059-021-02535-4

Figure Lengend Snippet: ATRX loss induces a global loss of CTCF, correlated gene dysregulation, and protects glioma cells from therapy-induced senescence. A Anti-CTCF single-cell CUT&Tag in SB28+IDH1R132H cells with ATRX KO or ATRX-wildtype scrambled control. Reads per 10 bp are shown as heatmaps (bottom) and summarized as averages (top) in a neighborhood of JASPAR CTCF motif sites. B CTCF motif frequencies in scCUT&Tag peaks, represented as standardized deviances from a data-driven null distribution via ChromVAR, for ATRX KO vs. wildtype cells (top), *** t test p < 1e−16. Numbers of, and overlap between, peaks in ATRX KO and wildtype datasets. C Browser shots of CTCF scCUT&Tag read pile-ups with significant peaks and genes annotated. D The percentages of NSC chromatin-loops affected, directly or indirectly, by CTCF loss upon ATRX KO (top). A Q-Q plot of the average ATRX-KO/WT cell-averaged log fold-changes in gene expression for each chromatin loop determined from NSC Hi-C data. Values on the y -axis are represented as percentages of a corresponding null distribution (Methods). The x -axis quantiles are provided by a Beta distribution fit to the inter-quartile range of y -axis percentiles. Loops containing specific genes are annotated. E Browser shots of a chromatin loop containing VEGFA and closeup of one boundary domain (left). A null distribution of average ATRX-KO/WT cell-averaged log fold-changes in gene expression measured via snRNA-seq in vivo in neoplastic cells, taken across all consecutive windows of four adjacent genes in chromosome 17. The loop containing VEGFA and the percentile of its average log fold-change are annotated (right-top). Violin plots of Vegfa expression in ATRX KO and WT neoplastic cells, in vivo, *MAST q < 0.05 (right-bottom). F As in E , except for a loop containing TNC. G Fluorometric assay for β-galactosidase activity in ATRX-KO and scrambled-control SB28 cells, both expressing IDH1R132H, post-treatment with one of Doxorubicin or CDKi. Error bars indicate standard error. * t test p < 0.05. B As in A , but for patient-derived ATRX/IDH1 double-mutant cells (SF10602) compared with an ATRX-wildtype, IDH1-mutant control (SF10417). Cells were treated with one of Temozolomide, Imatinib, Doxorubicin, or CDKi. C Visualization of β-galactosidase expression in ATRX-KO and scrambled-control SB28 cells, both expressing IDH1R132H, before and after treatment with CDKi. H Model of gene dysregulation due to CTCF disruption in chromatin-loop boundaries

Article Snippet: Differential expression for the 10X Genomics-based sc/snRNA-seq data was performed via MAST [ ].

Techniques: Expressing, Hi-C, In Vivo, Activity Assay, Derivative Assay, Mutagenesis