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g9a inhibitor unc0631  (MedChemExpress)


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    MedChemExpress g9a inhibitor unc0631
    A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and <t>G9a</t> inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.
    G9a Inhibitor Unc0631, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 94/100, based on 4 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/g9a inhibitor unc0631/product/MedChemExpress
    Average 94 stars, based on 4 article reviews
    g9a inhibitor unc0631 - by Bioz Stars, 2026-02
    94/100 stars

    Images

    1) Product Images from "Lamin A/C maintains genome topology and regulates transcriptional programs essential for virus-driven B cell activation"

    Article Title: Lamin A/C maintains genome topology and regulates transcriptional programs essential for virus-driven B cell activation

    Journal: bioRxiv

    doi: 10.64898/2026.01.12.699161

    A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and G9a inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.
    Figure Legend Snippet: A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and G9a inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.

    Techniques Used: RNA Sequencing, Expressing, Inhibition, ChIP-sequencing, Activation Assay, Protein-Protein interactions

    A) Drug screening assay on WT and lamin A/C KO cells treated with a library of PI3K inhibitors. Each compound was tested at 10, 1, 0.1, and 0.01 μM. Cell viability was assessed by measuring luminescence and converting the luminescence values to % toxicity. The graph shows the correlation between the log IC 50 in WT and KO cells for each compound. B) Acalisib dose-response curve in WT and lamin A/C KO cells. Toxicity was calculated using a luminescence assay, where the luminescence values were converted to % toxicity. Treatment with bortezomib (1 μM) was included as a positive control (100% toxicity); 0% toxicity corresponded to the RLU values of negative controls (0.1% DMSO). IC 50 values for acalisib in WT and lamin A/C KO cells are indicated. C) Cell viability (% live cells) assessed by counting the number of live cells interacting with the green dye calcein AM in WT and lamin A/C KO cells after treating for 72 hours with the PI3K inhibitor (PI3Ki) acalisib (0.1 µM) or control (Ctrl, 0.1% DMSO). Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01). Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. D) Cell viability (% live cells) assessed by counting the number of live WT cells interacting with calcein AM in samples treated with control (Ctrl, 0.1% DMSO), a G9a inhibitor (G9ai, 1 µM), acalisib (PI3Ki, 0.01 µM), or their combination. Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01) Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. E) Representative fluorescence microscope images of WT cells treated for 72 hours with control (Ctrl, 0.1% DMSO), G9a inhibitor (1 µM), acalisib (0.01 µM), or their combination and stained using calcein AM.
    Figure Legend Snippet: A) Drug screening assay on WT and lamin A/C KO cells treated with a library of PI3K inhibitors. Each compound was tested at 10, 1, 0.1, and 0.01 μM. Cell viability was assessed by measuring luminescence and converting the luminescence values to % toxicity. The graph shows the correlation between the log IC 50 in WT and KO cells for each compound. B) Acalisib dose-response curve in WT and lamin A/C KO cells. Toxicity was calculated using a luminescence assay, where the luminescence values were converted to % toxicity. Treatment with bortezomib (1 μM) was included as a positive control (100% toxicity); 0% toxicity corresponded to the RLU values of negative controls (0.1% DMSO). IC 50 values for acalisib in WT and lamin A/C KO cells are indicated. C) Cell viability (% live cells) assessed by counting the number of live cells interacting with the green dye calcein AM in WT and lamin A/C KO cells after treating for 72 hours with the PI3K inhibitor (PI3Ki) acalisib (0.1 µM) or control (Ctrl, 0.1% DMSO). Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01). Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. D) Cell viability (% live cells) assessed by counting the number of live WT cells interacting with calcein AM in samples treated with control (Ctrl, 0.1% DMSO), a G9a inhibitor (G9ai, 1 µM), acalisib (PI3Ki, 0.01 µM), or their combination. Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01) Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. E) Representative fluorescence microscope images of WT cells treated for 72 hours with control (Ctrl, 0.1% DMSO), G9a inhibitor (1 µM), acalisib (0.01 µM), or their combination and stained using calcein AM.

    Techniques Used: Drug discovery, Luminescence Assay, Positive Control, Control, Fluorescence, Microscopy, Software, Staining



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    g9a inhibitor unc0631  (MedChemExpress)
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    MedChemExpress g9a inhibitor unc0631
    A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and <t>G9a</t> inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.
    G9a Inhibitor Unc0631, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/g9a inhibitor unc0631/product/MedChemExpress
    Average 94 stars, based on 1 article reviews
    g9a inhibitor unc0631 - by Bioz Stars, 2026-02
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    unc0631 g9a/gpl inhibitor  (Selleck Chemicals)
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    Selleck Chemicals unc0631 g9a/gpl inhibitor
    A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and <t>G9a</t> inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.
    Unc0631 G9a/Gpl Inhibitor, supplied by Selleck Chemicals, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Image Search Results


    A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and G9a inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.

    Journal: bioRxiv

    Article Title: Lamin A/C maintains genome topology and regulates transcriptional programs essential for virus-driven B cell activation

    doi: 10.64898/2026.01.12.699161

    Figure Lengend Snippet: A) Overlap of deregulated genes (DEG) in RNA-Seq analysis between lamin A/C KO and G9a inhibitor treatment in WT cells. The overlap was statistically significant (p < 10 -16 ). B) Concordant regulation of the genes whose expression was altered by both lamin A/C KO and G9a inhibition. Data are represented using log 2 fold changes, and significantly regulated genes are depicted in red (upregulated) and blue (downregulated). The correlation coefficient (R = 0.73) indicates a strong positive correlation between the datasets. C) and D) H3K9me2 ChIP-Seq signal across the gene body of the 1,857 common targets between lamin A/C KO and G9a inhibition in WT cells. Increased deposition of H3K9me2 mark on the 927 targets that were downregulated in KO cells compared with WT (C), and no significant difference in H3K9me2 deposition on the 930 upregulated genes (D). Peaks at ± 3 kb from the transcription starting site (TSS) and the transcription end site (TES). E) and F) Ingenuity Pathway Analysis of the 1,857 common targets between lamin A/C KO and G9a inhibitor-treated WT cells, showing the top deregulated pathways (E) and upstream transcriptional regulators (F). Red indicates activation and blue inhibition. Data are shown as a function of the predicted z-score. G-I) Heat-maps of RNA-Seq data from WT, G9a inhibitor-treated WT, and lamin A/C KO cells showing genes in the PI3K, glycolysis, and c-myc signaling pathways whose expression was concordantly altered (false discovery rate [FDR] < 5%) by lamin A/C KO and G9a inhibition. Color code represents different fold change (FC) values, with upregulated genes shown in red and downregulated genes shown in blue.

    Article Snippet: Treatment with the G9a inhibitor UNC0631 (Med Chem Express, HY-13808) was given 72 h before collection at a concentration of 1 μM.

    Techniques: RNA Sequencing, Expressing, Inhibition, ChIP-sequencing, Activation Assay, Protein-Protein interactions

    A) Drug screening assay on WT and lamin A/C KO cells treated with a library of PI3K inhibitors. Each compound was tested at 10, 1, 0.1, and 0.01 μM. Cell viability was assessed by measuring luminescence and converting the luminescence values to % toxicity. The graph shows the correlation between the log IC 50 in WT and KO cells for each compound. B) Acalisib dose-response curve in WT and lamin A/C KO cells. Toxicity was calculated using a luminescence assay, where the luminescence values were converted to % toxicity. Treatment with bortezomib (1 μM) was included as a positive control (100% toxicity); 0% toxicity corresponded to the RLU values of negative controls (0.1% DMSO). IC 50 values for acalisib in WT and lamin A/C KO cells are indicated. C) Cell viability (% live cells) assessed by counting the number of live cells interacting with the green dye calcein AM in WT and lamin A/C KO cells after treating for 72 hours with the PI3K inhibitor (PI3Ki) acalisib (0.1 µM) or control (Ctrl, 0.1% DMSO). Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01). Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. D) Cell viability (% live cells) assessed by counting the number of live WT cells interacting with calcein AM in samples treated with control (Ctrl, 0.1% DMSO), a G9a inhibitor (G9ai, 1 µM), acalisib (PI3Ki, 0.01 µM), or their combination. Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01) Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. E) Representative fluorescence microscope images of WT cells treated for 72 hours with control (Ctrl, 0.1% DMSO), G9a inhibitor (1 µM), acalisib (0.01 µM), or their combination and stained using calcein AM.

    Journal: bioRxiv

    Article Title: Lamin A/C maintains genome topology and regulates transcriptional programs essential for virus-driven B cell activation

    doi: 10.64898/2026.01.12.699161

    Figure Lengend Snippet: A) Drug screening assay on WT and lamin A/C KO cells treated with a library of PI3K inhibitors. Each compound was tested at 10, 1, 0.1, and 0.01 μM. Cell viability was assessed by measuring luminescence and converting the luminescence values to % toxicity. The graph shows the correlation between the log IC 50 in WT and KO cells for each compound. B) Acalisib dose-response curve in WT and lamin A/C KO cells. Toxicity was calculated using a luminescence assay, where the luminescence values were converted to % toxicity. Treatment with bortezomib (1 μM) was included as a positive control (100% toxicity); 0% toxicity corresponded to the RLU values of negative controls (0.1% DMSO). IC 50 values for acalisib in WT and lamin A/C KO cells are indicated. C) Cell viability (% live cells) assessed by counting the number of live cells interacting with the green dye calcein AM in WT and lamin A/C KO cells after treating for 72 hours with the PI3K inhibitor (PI3Ki) acalisib (0.1 µM) or control (Ctrl, 0.1% DMSO). Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01). Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. D) Cell viability (% live cells) assessed by counting the number of live WT cells interacting with calcein AM in samples treated with control (Ctrl, 0.1% DMSO), a G9a inhibitor (G9ai, 1 µM), acalisib (PI3Ki, 0.01 µM), or their combination. Data come from 2 experiments with 4 biological replicates each (*, p ≤ 0.05; **, p ≤ 0.01) Sample acquisition and analysis were conducted using a fluorescence microscope. Fluorescence was quantified using the ImageJ software. E) Representative fluorescence microscope images of WT cells treated for 72 hours with control (Ctrl, 0.1% DMSO), G9a inhibitor (1 µM), acalisib (0.01 µM), or their combination and stained using calcein AM.

    Article Snippet: Treatment with the G9a inhibitor UNC0631 (Med Chem Express, HY-13808) was given 72 h before collection at a concentration of 1 μM.

    Techniques: Drug discovery, Luminescence Assay, Positive Control, Control, Fluorescence, Microscopy, Software, Staining