digital image correlation analysis using ncorr software Search Results


91
Sino Biological ncor1
Ncor1, supplied by Sino Biological, used in various techniques. Bioz Stars score: 91/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc ncorr 2d digital image correlation matlab software toolbox
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GitHub Inc ncorr v.1.2
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GitHub Inc matlabbased software program ncorr v.1.2
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MIDAC Corporation class i hdacs
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Proteintech ncor
GPX4 suppression is regulated by a repressive complex <t>containing</t> <t>MBD2,</t> MAZ, HDAC3 and <t>NCoR.</t> (a) Peak plot showing the ATAC-seq peak at the Gpx4 locus (Chr10: 80051488–80056439) in ovarian tissues from control (Ctrl, blue) and DHEA-treated (DHEA, red) mice. Orange boxes and asterisks denote regions with increased chromatin accessibility. (b) A heatmap displays the top six transcription factors (TFs) binding to the Gpx4 promoter region in the ATAC-seq analysis, along with the mRNA expression identified by RNA-seq analysis, and the predicted TF motifs and E-values are shown on the right. (c) Schematic representation of the Gpx4 promoter region showing the MAZ binding motif relative to the transcription start site (TSS). (Below) MAZ binding footprint enrichment at the Gpx4 locus in Ctrl (blue) and DHEA-treated (red) mice. Primary ovarian granulosa cells (GCs) were treated with 50 μM DHEA for 48 h in vitro to establish the PCOS model. (d) Western blot analysis of MAZ, NCoR and HDAC3 protein expression in DHEA-treated GCs. GAPDH served as a loading control. Blots are representative of one sample per group. Quantification was presented as means ± SEM, n = 3. ∗ P < 0.05, Student's t-test. (e) Co-immunoprecipitation (Co-IP) assay. Cell lysates were immunoprecipitated (IP) with isoform-matched immunoglobulin (Ig) or antibodies (IP Ab) to MBD2, MAZ, HDAC3, or NCoR, and then immunoprecipitants were assessed for MBD2, MAZ, HDAC3, or NCoR by western blotting reciprocally (the upper panel). The non-IP lysates (Input) were assayed for GAPDH as input controls. (f) Immunofluorescence co-staining was used to determine the expression and localization of MAZ (green), NCoR (red), and HDAC3 (magenta) within GCs. (g) Quantification of protein co-localization from the magnified region in ( f ). (h) Chromatin immunoprecipitation (ChIP) assay. DHEA-treated GCs were in presence or absence of KCC-07 (KCC, 10 μM, 48 h), and the cell lysates were immunoprecipitated with isoform-matched immunoglobulin or antibodies to MBD2, MAZ, NCoR, HDAC3, or pan-acetylated lysine (Pan-Ace), respectively. The genomic DNA (Input) and the antibody-bound DNAs were PCR-amplified with primers covering the MAZ motif on Gpx4 promoter. The PCR products of representative sample per group were analyzed on 1.5 % agarose gels. Quantitative analysis was shown on the right. Data were presented as mean ± SEM, n = 4. ∗ P < 0.05, one-way ANOVA. (i) Western blot analysis. (Left) HDAC3 and GPX4 protein expression in DHEA-treated GCs in the presence or absence of the HDAC3 inhibitor RGFP966 (RGFP, 10 μM, 48 h). (Middle) MAZ and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or MAZ-targeting (si-MAZ) siRNA, followed by treatment with or without DHEA. (Right) NCoR and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or NCoR-targeting (si-NCoR) siRNA, followed by DHEA treatment. GAPDH was as a loading control. (j) Quantifications of ( i ). Data were presented as mean ± SEM, n = 3. ∗ P < 0.05, one-way ANOVA. (k) Schematic model of Gpx4 transcriptional repression. A transcriptional repressive complex orchestrated by MBD2, MAZ, HDAC3, and NCoR binds to the hypermethylated Gpx4 promoter, leading to transcriptional suppression.
Ncor, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/digital+image+correlation+analysis+using+ncorr+software/pmc12861256-120-21-23?v=Proteintech
Average 93 stars, based on 1 article reviews
ncor - by Bioz Stars, 2026-07
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OriGene anti ncor 2
GPX4 suppression is regulated by a repressive complex <t>containing</t> <t>MBD2,</t> MAZ, HDAC3 and <t>NCoR.</t> (a) Peak plot showing the ATAC-seq peak at the Gpx4 locus (Chr10: 80051488–80056439) in ovarian tissues from control (Ctrl, blue) and DHEA-treated (DHEA, red) mice. Orange boxes and asterisks denote regions with increased chromatin accessibility. (b) A heatmap displays the top six transcription factors (TFs) binding to the Gpx4 promoter region in the ATAC-seq analysis, along with the mRNA expression identified by RNA-seq analysis, and the predicted TF motifs and E-values are shown on the right. (c) Schematic representation of the Gpx4 promoter region showing the MAZ binding motif relative to the transcription start site (TSS). (Below) MAZ binding footprint enrichment at the Gpx4 locus in Ctrl (blue) and DHEA-treated (red) mice. Primary ovarian granulosa cells (GCs) were treated with 50 μM DHEA for 48 h in vitro to establish the PCOS model. (d) Western blot analysis of MAZ, NCoR and HDAC3 protein expression in DHEA-treated GCs. GAPDH served as a loading control. Blots are representative of one sample per group. Quantification was presented as means ± SEM, n = 3. ∗ P < 0.05, Student's t-test. (e) Co-immunoprecipitation (Co-IP) assay. Cell lysates were immunoprecipitated (IP) with isoform-matched immunoglobulin (Ig) or antibodies (IP Ab) to MBD2, MAZ, HDAC3, or NCoR, and then immunoprecipitants were assessed for MBD2, MAZ, HDAC3, or NCoR by western blotting reciprocally (the upper panel). The non-IP lysates (Input) were assayed for GAPDH as input controls. (f) Immunofluorescence co-staining was used to determine the expression and localization of MAZ (green), NCoR (red), and HDAC3 (magenta) within GCs. (g) Quantification of protein co-localization from the magnified region in ( f ). (h) Chromatin immunoprecipitation (ChIP) assay. DHEA-treated GCs were in presence or absence of KCC-07 (KCC, 10 μM, 48 h), and the cell lysates were immunoprecipitated with isoform-matched immunoglobulin or antibodies to MBD2, MAZ, NCoR, HDAC3, or pan-acetylated lysine (Pan-Ace), respectively. The genomic DNA (Input) and the antibody-bound DNAs were PCR-amplified with primers covering the MAZ motif on Gpx4 promoter. The PCR products of representative sample per group were analyzed on 1.5 % agarose gels. Quantitative analysis was shown on the right. Data were presented as mean ± SEM, n = 4. ∗ P < 0.05, one-way ANOVA. (i) Western blot analysis. (Left) HDAC3 and GPX4 protein expression in DHEA-treated GCs in the presence or absence of the HDAC3 inhibitor RGFP966 (RGFP, 10 μM, 48 h). (Middle) MAZ and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or MAZ-targeting (si-MAZ) siRNA, followed by treatment with or without DHEA. (Right) NCoR and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or NCoR-targeting (si-NCoR) siRNA, followed by DHEA treatment. GAPDH was as a loading control. (j) Quantifications of ( i ). Data were presented as mean ± SEM, n = 3. ∗ P < 0.05, one-way ANOVA. (k) Schematic model of Gpx4 transcriptional repression. A transcriptional repressive complex orchestrated by MBD2, MAZ, HDAC3, and NCoR binds to the hypermethylated Gpx4 promoter, leading to transcriptional suppression.
Anti Ncor 2, supplied by OriGene, used in various techniques. Bioz Stars score: 91/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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anti ncor 2 - by Bioz Stars, 2026-07
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Broad Institute Inc lentiviral shrna sequences targeting smrt ( ncor2)
Depletion of <t>NCOR</t> vs. SMRT differentially alters gene expression (transcriptome). (A) Principal Component Analysis (PCA) illustrating the transcriptional outcomes in NCOR-vs. SMRT-depleted RAW cells ( n =3). (B) Heatmap displaying differentially expressed genes in NCOR-vs. SMRT-depleted RAW cells, categorized in six clusters to show the different regulation patterns. Representative genes from each gene cluster are highlighted. Data significance for gene expression was determined using DESeq2. (C) Network of the top enriched KEGG pathways for each of the six gene clusters. (D) Heatmap showing the transcriptome-based TF activity analysis for each gene cluster. (E) Heatmaps illustrating selected genes in NCOR-depleted (top panel) and in SMRT-depleted (bottom panel) RAW cells and BMDMs. (F) Barplots showing enriched up- and down-regulated KEGG pathways in shNCOR BMDMs and shSMRT BMDMs.
Lentiviral Shrna Sequences Targeting Smrt ( Ncor2), supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Promega gal4dbd-ncorc
Depletion of <t>NCOR</t> vs. SMRT differentially alters gene expression (transcriptome). (A) Principal Component Analysis (PCA) illustrating the transcriptional outcomes in NCOR-vs. SMRT-depleted RAW cells ( n =3). (B) Heatmap displaying differentially expressed genes in NCOR-vs. SMRT-depleted RAW cells, categorized in six clusters to show the different regulation patterns. Representative genes from each gene cluster are highlighted. Data significance for gene expression was determined using DESeq2. (C) Network of the top enriched KEGG pathways for each of the six gene clusters. (D) Heatmap showing the transcriptome-based TF activity analysis for each gene cluster. (E) Heatmaps illustrating selected genes in NCOR-depleted (top panel) and in SMRT-depleted (bottom panel) RAW cells and BMDMs. (F) Barplots showing enriched up- and down-regulated KEGG pathways in shNCOR BMDMs and shSMRT BMDMs.
Gal4dbd Ncorc, supplied by Promega, 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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BioCarta biocarta_ppara
List of multi-gene mutational events with pathway level expression change.
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List of multi-gene mutational events with pathway level expression change.
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Image Search Results


GPX4 suppression is regulated by a repressive complex containing MBD2, MAZ, HDAC3 and NCoR. (a) Peak plot showing the ATAC-seq peak at the Gpx4 locus (Chr10: 80051488–80056439) in ovarian tissues from control (Ctrl, blue) and DHEA-treated (DHEA, red) mice. Orange boxes and asterisks denote regions with increased chromatin accessibility. (b) A heatmap displays the top six transcription factors (TFs) binding to the Gpx4 promoter region in the ATAC-seq analysis, along with the mRNA expression identified by RNA-seq analysis, and the predicted TF motifs and E-values are shown on the right. (c) Schematic representation of the Gpx4 promoter region showing the MAZ binding motif relative to the transcription start site (TSS). (Below) MAZ binding footprint enrichment at the Gpx4 locus in Ctrl (blue) and DHEA-treated (red) mice. Primary ovarian granulosa cells (GCs) were treated with 50 μM DHEA for 48 h in vitro to establish the PCOS model. (d) Western blot analysis of MAZ, NCoR and HDAC3 protein expression in DHEA-treated GCs. GAPDH served as a loading control. Blots are representative of one sample per group. Quantification was presented as means ± SEM, n = 3. ∗ P < 0.05, Student's t-test. (e) Co-immunoprecipitation (Co-IP) assay. Cell lysates were immunoprecipitated (IP) with isoform-matched immunoglobulin (Ig) or antibodies (IP Ab) to MBD2, MAZ, HDAC3, or NCoR, and then immunoprecipitants were assessed for MBD2, MAZ, HDAC3, or NCoR by western blotting reciprocally (the upper panel). The non-IP lysates (Input) were assayed for GAPDH as input controls. (f) Immunofluorescence co-staining was used to determine the expression and localization of MAZ (green), NCoR (red), and HDAC3 (magenta) within GCs. (g) Quantification of protein co-localization from the magnified region in ( f ). (h) Chromatin immunoprecipitation (ChIP) assay. DHEA-treated GCs were in presence or absence of KCC-07 (KCC, 10 μM, 48 h), and the cell lysates were immunoprecipitated with isoform-matched immunoglobulin or antibodies to MBD2, MAZ, NCoR, HDAC3, or pan-acetylated lysine (Pan-Ace), respectively. The genomic DNA (Input) and the antibody-bound DNAs were PCR-amplified with primers covering the MAZ motif on Gpx4 promoter. The PCR products of representative sample per group were analyzed on 1.5 % agarose gels. Quantitative analysis was shown on the right. Data were presented as mean ± SEM, n = 4. ∗ P < 0.05, one-way ANOVA. (i) Western blot analysis. (Left) HDAC3 and GPX4 protein expression in DHEA-treated GCs in the presence or absence of the HDAC3 inhibitor RGFP966 (RGFP, 10 μM, 48 h). (Middle) MAZ and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or MAZ-targeting (si-MAZ) siRNA, followed by treatment with or without DHEA. (Right) NCoR and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or NCoR-targeting (si-NCoR) siRNA, followed by DHEA treatment. GAPDH was as a loading control. (j) Quantifications of ( i ). Data were presented as mean ± SEM, n = 3. ∗ P < 0.05, one-way ANOVA. (k) Schematic model of Gpx4 transcriptional repression. A transcriptional repressive complex orchestrated by MBD2, MAZ, HDAC3, and NCoR binds to the hypermethylated Gpx4 promoter, leading to transcriptional suppression.

Journal: Redox Biology

Article Title: Methylation reader MBD2-mediated GPX4 transcriptional repression drives ovarian granulosa cell ferroptosis in PCOS

doi: 10.1016/j.redox.2026.104034

Figure Lengend Snippet: GPX4 suppression is regulated by a repressive complex containing MBD2, MAZ, HDAC3 and NCoR. (a) Peak plot showing the ATAC-seq peak at the Gpx4 locus (Chr10: 80051488–80056439) in ovarian tissues from control (Ctrl, blue) and DHEA-treated (DHEA, red) mice. Orange boxes and asterisks denote regions with increased chromatin accessibility. (b) A heatmap displays the top six transcription factors (TFs) binding to the Gpx4 promoter region in the ATAC-seq analysis, along with the mRNA expression identified by RNA-seq analysis, and the predicted TF motifs and E-values are shown on the right. (c) Schematic representation of the Gpx4 promoter region showing the MAZ binding motif relative to the transcription start site (TSS). (Below) MAZ binding footprint enrichment at the Gpx4 locus in Ctrl (blue) and DHEA-treated (red) mice. Primary ovarian granulosa cells (GCs) were treated with 50 μM DHEA for 48 h in vitro to establish the PCOS model. (d) Western blot analysis of MAZ, NCoR and HDAC3 protein expression in DHEA-treated GCs. GAPDH served as a loading control. Blots are representative of one sample per group. Quantification was presented as means ± SEM, n = 3. ∗ P < 0.05, Student's t-test. (e) Co-immunoprecipitation (Co-IP) assay. Cell lysates were immunoprecipitated (IP) with isoform-matched immunoglobulin (Ig) or antibodies (IP Ab) to MBD2, MAZ, HDAC3, or NCoR, and then immunoprecipitants were assessed for MBD2, MAZ, HDAC3, or NCoR by western blotting reciprocally (the upper panel). The non-IP lysates (Input) were assayed for GAPDH as input controls. (f) Immunofluorescence co-staining was used to determine the expression and localization of MAZ (green), NCoR (red), and HDAC3 (magenta) within GCs. (g) Quantification of protein co-localization from the magnified region in ( f ). (h) Chromatin immunoprecipitation (ChIP) assay. DHEA-treated GCs were in presence or absence of KCC-07 (KCC, 10 μM, 48 h), and the cell lysates were immunoprecipitated with isoform-matched immunoglobulin or antibodies to MBD2, MAZ, NCoR, HDAC3, or pan-acetylated lysine (Pan-Ace), respectively. The genomic DNA (Input) and the antibody-bound DNAs were PCR-amplified with primers covering the MAZ motif on Gpx4 promoter. The PCR products of representative sample per group were analyzed on 1.5 % agarose gels. Quantitative analysis was shown on the right. Data were presented as mean ± SEM, n = 4. ∗ P < 0.05, one-way ANOVA. (i) Western blot analysis. (Left) HDAC3 and GPX4 protein expression in DHEA-treated GCs in the presence or absence of the HDAC3 inhibitor RGFP966 (RGFP, 10 μM, 48 h). (Middle) MAZ and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or MAZ-targeting (si-MAZ) siRNA, followed by treatment with or without DHEA. (Right) NCoR and GPX4 protein expression in GCs transfected with negative- (si-Ctrl) or NCoR-targeting (si-NCoR) siRNA, followed by DHEA treatment. GAPDH was as a loading control. (j) Quantifications of ( i ). Data were presented as mean ± SEM, n = 3. ∗ P < 0.05, one-way ANOVA. (k) Schematic model of Gpx4 transcriptional repression. A transcriptional repressive complex orchestrated by MBD2, MAZ, HDAC3, and NCoR binds to the hypermethylated Gpx4 promoter, leading to transcriptional suppression.

Article Snippet: The lysates of ovaries were immunoprecipitated with antibodies to MBD2 (ab188474, Abcam, UK), MAZ (21068-1-AP, Proteintech, USA), HDAC3 (A19537, ABclonal, China), NCoR (20018-1-AP, Proteintech, USA), or an isotype-matched immunoglobulin (Ig) followed by Protein A/G Magnetic Beads (PB101, Vazyme, China), and then immunoprecipitants were assayed by Western blot with antibodies to MBD2, MAZ, HDAC3 or NCoR, respectively.

Techniques: Control, Binding Assay, Expressing, RNA Sequencing, In Vitro, Western Blot, Co-Immunoprecipitation Assay, Immunoprecipitation, Immunofluorescence, Staining, Chromatin Immunoprecipitation, Amplification, Transfection

Granulosa GPX4 deletion blocks the anti-ferroptotic and ovary-protective effects of MBD2 inhibition in PCOS mice. Gpx4 fl/fl and Gpx4 GC−/− mice were grouped into oil vehicle control (Ctrl), DHEA (60 mg/kg, 21 days)-treated (DHEA), and DHEA-treated with KCC-07 (KCC, 10 mg/kg) treatment (KCC/DHEA) mice ( n = 6). (a) Representative photomicrographs of ovarian sections. Ovarian sections were stained with hematoxylin-eosin (HE; upper panels), Masson trichrome (middle panels), and TUNEL assay (lower panels). Asterisks indicate corpora lutea; black arrows indicate preantral follicles; yellow arrows indicate collagen deposits; white arrows indicate TUNEL-positive cells. (b) Quantification of ( a ). Box-and-whisker plots with data points ( n = 6). ∗ P < 0.05, two-way ANOVA. (c) Western blot analysis of GPX4, 4-HNE, Collagen I (Col1α) and α-SMA protein expression in ovarian tissues. GAPDH served as a loading control. Blots are representative of two samples per group. (d) Quantification of ( c ). Data were presented as mean ± SEM, n = 6. ∗ P < 0.05, two -way ANOVA. (e) A schematic diagram of sequential MBD2 elevation, formation of a transcriptional repressive complex with MAZ, NCoR and HDAC3, binding to the DNMT-hypermethylated Gpx4 promoter, suppression of Gpx4 transcription, and granulosa cell ferroptosis that promotes polycystic ovary syndrome (PCOS) (dashed lines). Conversely, MBD2 inhibition with KCC-07 blocks GPX4 suppression and ferroptotic PCOS (solid lines).

Journal: Redox Biology

Article Title: Methylation reader MBD2-mediated GPX4 transcriptional repression drives ovarian granulosa cell ferroptosis in PCOS

doi: 10.1016/j.redox.2026.104034

Figure Lengend Snippet: Granulosa GPX4 deletion blocks the anti-ferroptotic and ovary-protective effects of MBD2 inhibition in PCOS mice. Gpx4 fl/fl and Gpx4 GC−/− mice were grouped into oil vehicle control (Ctrl), DHEA (60 mg/kg, 21 days)-treated (DHEA), and DHEA-treated with KCC-07 (KCC, 10 mg/kg) treatment (KCC/DHEA) mice ( n = 6). (a) Representative photomicrographs of ovarian sections. Ovarian sections were stained with hematoxylin-eosin (HE; upper panels), Masson trichrome (middle panels), and TUNEL assay (lower panels). Asterisks indicate corpora lutea; black arrows indicate preantral follicles; yellow arrows indicate collagen deposits; white arrows indicate TUNEL-positive cells. (b) Quantification of ( a ). Box-and-whisker plots with data points ( n = 6). ∗ P < 0.05, two-way ANOVA. (c) Western blot analysis of GPX4, 4-HNE, Collagen I (Col1α) and α-SMA protein expression in ovarian tissues. GAPDH served as a loading control. Blots are representative of two samples per group. (d) Quantification of ( c ). Data were presented as mean ± SEM, n = 6. ∗ P < 0.05, two -way ANOVA. (e) A schematic diagram of sequential MBD2 elevation, formation of a transcriptional repressive complex with MAZ, NCoR and HDAC3, binding to the DNMT-hypermethylated Gpx4 promoter, suppression of Gpx4 transcription, and granulosa cell ferroptosis that promotes polycystic ovary syndrome (PCOS) (dashed lines). Conversely, MBD2 inhibition with KCC-07 blocks GPX4 suppression and ferroptotic PCOS (solid lines).

Article Snippet: The lysates of ovaries were immunoprecipitated with antibodies to MBD2 (ab188474, Abcam, UK), MAZ (21068-1-AP, Proteintech, USA), HDAC3 (A19537, ABclonal, China), NCoR (20018-1-AP, Proteintech, USA), or an isotype-matched immunoglobulin (Ig) followed by Protein A/G Magnetic Beads (PB101, Vazyme, China), and then immunoprecipitants were assayed by Western blot with antibodies to MBD2, MAZ, HDAC3 or NCoR, respectively.

Techniques: Inhibition, Control, Staining, TUNEL Assay, Whisker Assay, Western Blot, Expressing, Binding Assay

Depletion of NCOR vs. SMRT differentially alters gene expression (transcriptome). (A) Principal Component Analysis (PCA) illustrating the transcriptional outcomes in NCOR-vs. SMRT-depleted RAW cells ( n =3). (B) Heatmap displaying differentially expressed genes in NCOR-vs. SMRT-depleted RAW cells, categorized in six clusters to show the different regulation patterns. Representative genes from each gene cluster are highlighted. Data significance for gene expression was determined using DESeq2. (C) Network of the top enriched KEGG pathways for each of the six gene clusters. (D) Heatmap showing the transcriptome-based TF activity analysis for each gene cluster. (E) Heatmaps illustrating selected genes in NCOR-depleted (top panel) and in SMRT-depleted (bottom panel) RAW cells and BMDMs. (F) Barplots showing enriched up- and down-regulated KEGG pathways in shNCOR BMDMs and shSMRT BMDMs.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Depletion of NCOR vs. SMRT differentially alters gene expression (transcriptome). (A) Principal Component Analysis (PCA) illustrating the transcriptional outcomes in NCOR-vs. SMRT-depleted RAW cells ( n =3). (B) Heatmap displaying differentially expressed genes in NCOR-vs. SMRT-depleted RAW cells, categorized in six clusters to show the different regulation patterns. Representative genes from each gene cluster are highlighted. Data significance for gene expression was determined using DESeq2. (C) Network of the top enriched KEGG pathways for each of the six gene clusters. (D) Heatmap showing the transcriptome-based TF activity analysis for each gene cluster. (E) Heatmaps illustrating selected genes in NCOR-depleted (top panel) and in SMRT-depleted (bottom panel) RAW cells and BMDMs. (F) Barplots showing enriched up- and down-regulated KEGG pathways in shNCOR BMDMs and shSMRT BMDMs.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: Gene Expression, Activity Assay

Depletion of NCOR vs. SMRT differentially alters chromatin accessibility (epigenome, candidate cis-regulatory elements). (A) PCA plot of ATAC-seq for NCOR-vs. SMRT- depleted cells ( n =3). (B-C) Distribution of shSMRT- ( B ) shNCOR- ( C ) specific upregulated regions between enhancer and promoter regions. The distribution is presented along the distance from the transcription start site (TSS) of the annotated gene. (D-E) Scatter plots presenting the correlation of the RNA-seq expression and the promoter peaks from ATAC-seq data in SMRT- ( D ) and NCOR- ( E ) depleted cells. Data significance for gene expression was determined using DESeq2. (F) Heatmap of all differentially accessible genomic regions based on ATAC-seq data in NCOR- vs. SMRT- depleted cells, categorized in the same six clusters as in . Representative genomic regions from each cluster with differential accessibility are highlighted. ( G ) TF-binding site motif analysis of the SMRT-specific, NCOR- specific, and commonly repressed peaks. ( H ) IGV genome-browser tracks representing the NCOR, SMRT and H3K27ac ChIP-seq peaks in WT cells and the ATAC-seq changes in NCOR- vs. SMRT- depleted cells at the Pdcd1 (top panel) and Abca1 (bottom panel) loci. The statistically significantly changed peaks are highlighted with blue shadow.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Depletion of NCOR vs. SMRT differentially alters chromatin accessibility (epigenome, candidate cis-regulatory elements). (A) PCA plot of ATAC-seq for NCOR-vs. SMRT- depleted cells ( n =3). (B-C) Distribution of shSMRT- ( B ) shNCOR- ( C ) specific upregulated regions between enhancer and promoter regions. The distribution is presented along the distance from the transcription start site (TSS) of the annotated gene. (D-E) Scatter plots presenting the correlation of the RNA-seq expression and the promoter peaks from ATAC-seq data in SMRT- ( D ) and NCOR- ( E ) depleted cells. Data significance for gene expression was determined using DESeq2. (F) Heatmap of all differentially accessible genomic regions based on ATAC-seq data in NCOR- vs. SMRT- depleted cells, categorized in the same six clusters as in . Representative genomic regions from each cluster with differential accessibility are highlighted. ( G ) TF-binding site motif analysis of the SMRT-specific, NCOR- specific, and commonly repressed peaks. ( H ) IGV genome-browser tracks representing the NCOR, SMRT and H3K27ac ChIP-seq peaks in WT cells and the ATAC-seq changes in NCOR- vs. SMRT- depleted cells at the Pdcd1 (top panel) and Abca1 (bottom panel) loci. The statistically significantly changed peaks are highlighted with blue shadow.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: RNA Sequencing, Expressing, Gene Expression, Binding Assay, ChIP-sequencing

Depletion of NCOR vs. SMRT differentially alters H3K27ac (epigenome, enhancers). (A) PCA plot illustrating the H3K27ac ChIP-seq results for NCOR- vs. SMRT- depleted cells ( n =2). Two independent ChIP-seq experiments were performed, and all results were merged to eliminate batch effect. (B) Heatmap displaying the z-normalized counts of the leading 2000 H3K27ac peaks driving PC1. Representative genomic regions are highlighted. (C) Heatmap of all H3K27ac peaks in shGFP, shSMRT and shNCOR macrophages. Up- and downregulated peaks are plotted independently ( n =2). (D) Motif analysis of the upregulated H3K27ac peaks in NCOR- vs. SMRT- depleted cells, intersected with NCOR/SMRT peaks. (E) IGV genome browser tracks of H3K27ac ChIP-seq (basal condition) at Pdcd1 , Abca1 and Ptgs1 loci. NCOR, SMRT, PU.1, JunB, and CBP ChIP-seq data are used to annotate enhancer regions. Up- and downregulated H3K27ac peaks are highlighted. (F) RT-qPCR analysis of Pdcd1 and Abca1 expression in NCOR- vs. SMRT- depleted cells ( n =3). (G) IGV genome browser tracks of ATAC-seq and H3K27ac and H4K5ac ChIP-seq (basal condition) at the Rarb locus. Up- and downregulated peaks are highlighted with a blue shadow. (H) RNA-seq tag counts (-RPKM) of nuclear receptor gene expression in NCOR- vs. SMRT- depleted macrophages ( n =3). Unpaired t test was used to determine data significance for gene expression in the qPCRs. All data are represented as mean ± SEM. Data significance for gene expression in RNA-seq was determined using DESeq2. * P < 0.05, ** P < 0.01, *** P < 0.001.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Depletion of NCOR vs. SMRT differentially alters H3K27ac (epigenome, enhancers). (A) PCA plot illustrating the H3K27ac ChIP-seq results for NCOR- vs. SMRT- depleted cells ( n =2). Two independent ChIP-seq experiments were performed, and all results were merged to eliminate batch effect. (B) Heatmap displaying the z-normalized counts of the leading 2000 H3K27ac peaks driving PC1. Representative genomic regions are highlighted. (C) Heatmap of all H3K27ac peaks in shGFP, shSMRT and shNCOR macrophages. Up- and downregulated peaks are plotted independently ( n =2). (D) Motif analysis of the upregulated H3K27ac peaks in NCOR- vs. SMRT- depleted cells, intersected with NCOR/SMRT peaks. (E) IGV genome browser tracks of H3K27ac ChIP-seq (basal condition) at Pdcd1 , Abca1 and Ptgs1 loci. NCOR, SMRT, PU.1, JunB, and CBP ChIP-seq data are used to annotate enhancer regions. Up- and downregulated H3K27ac peaks are highlighted. (F) RT-qPCR analysis of Pdcd1 and Abca1 expression in NCOR- vs. SMRT- depleted cells ( n =3). (G) IGV genome browser tracks of ATAC-seq and H3K27ac and H4K5ac ChIP-seq (basal condition) at the Rarb locus. Up- and downregulated peaks are highlighted with a blue shadow. (H) RNA-seq tag counts (-RPKM) of nuclear receptor gene expression in NCOR- vs. SMRT- depleted macrophages ( n =3). Unpaired t test was used to determine data significance for gene expression in the qPCRs. All data are represented as mean ± SEM. Data significance for gene expression in RNA-seq was determined using DESeq2. * P < 0.05, ** P < 0.01, *** P < 0.001.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: ChIP-sequencing, Quantitative RT-PCR, Expressing, RNA Sequencing, Gene Expression

Genome-wide chromatin co-occupancy of NCOR and SMRT (cistrome). (A) Genome-wide correlation analysis: peaks from NCOR and SMRT ChIP-seq experiments were merged for Pearson correlation test. (B) NCOR and SMRT peak distribution between enhancer and promoter regions. The distribution is presented along the distance from the TSS of the annotated gene. (C-D) Venn diagrams displaying the binding overlap between NCOR, SMRT and the TFs PU.1 ( C ) and JunB ( D ) in macrophages. (E-G) Peak coverage plots of NCOR/SMRT common or specific peaks and the corresponding motif enrichment in macrophages. (H-I) IGV genome browser tracks of H3K27ac, SMRT, NCOR and other related regulatory proteins ChIP-seq at common marked genes Ccl2 ( H ) and Abcg1 ( I ) loci. The representative superenhancer (SE) and promoter regions of both Ccl2 and Abcg1 genes are highlighted with blue shadow.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Genome-wide chromatin co-occupancy of NCOR and SMRT (cistrome). (A) Genome-wide correlation analysis: peaks from NCOR and SMRT ChIP-seq experiments were merged for Pearson correlation test. (B) NCOR and SMRT peak distribution between enhancer and promoter regions. The distribution is presented along the distance from the TSS of the annotated gene. (C-D) Venn diagrams displaying the binding overlap between NCOR, SMRT and the TFs PU.1 ( C ) and JunB ( D ) in macrophages. (E-G) Peak coverage plots of NCOR/SMRT common or specific peaks and the corresponding motif enrichment in macrophages. (H-I) IGV genome browser tracks of H3K27ac, SMRT, NCOR and other related regulatory proteins ChIP-seq at common marked genes Ccl2 ( H ) and Abcg1 ( I ) loci. The representative superenhancer (SE) and promoter regions of both Ccl2 and Abcg1 genes are highlighted with blue shadow.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: Genome Wide, ChIP-sequencing, Binding Assay

Reciprocal influence of NCOR and SMRT at the cistrome level. (A-B) Heatmap showing NCOR (A) and SMRT (B) occupancy in NCOR- vs. SMRT- depleted cells. The peak center in each plot represents the SMRT or NCOR peaks for each individual plot ( n =2). (C) MA plot displaying SMRT peak changes in NCOR-depleted cells. Upregulated and downregulated peaks are highlighted ( n =2). Key inflammatory and metabolic target genes are labeled. Significantly altered peaks were identified using DESeq2. (D-E) Distribution of up (D) and down (E) -regulated SMRT binding to promoters and enhancers in NCOR-depleted cells. The distribution is presented along the distance from the TSS of the annotated gene. (F-G) Motif analysis of up (F) and down (G) -regulated SMRT peaks in NCOR-depleted cells. (H) Boxplots comparing the distribution of the ATAC-seq tags between shNCOR/shSMRT and control and the SMRT ChIP-seq tags between shNCOR and control. The comparison is done for SMRT upregulated peaks (left panel) and for SMRT downregulated peaks (right panel). (I) Boxplots presenting the distribution of the ATAC-seq tags between shNCOR/shSMRT and control and the NCOR ChIP-seq tags between shSMRT and control. (J-K) IGV genome browser tracks showing SMRT ChIP-seq at Abca1 and Ccl2 loci. The corresponding H3K27ac ChIP-seq is used to illustrate the epigenome alterations ( n =2). Wilcox test and DESeq2 were used to determine data significance for gene expression.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Reciprocal influence of NCOR and SMRT at the cistrome level. (A-B) Heatmap showing NCOR (A) and SMRT (B) occupancy in NCOR- vs. SMRT- depleted cells. The peak center in each plot represents the SMRT or NCOR peaks for each individual plot ( n =2). (C) MA plot displaying SMRT peak changes in NCOR-depleted cells. Upregulated and downregulated peaks are highlighted ( n =2). Key inflammatory and metabolic target genes are labeled. Significantly altered peaks were identified using DESeq2. (D-E) Distribution of up (D) and down (E) -regulated SMRT binding to promoters and enhancers in NCOR-depleted cells. The distribution is presented along the distance from the TSS of the annotated gene. (F-G) Motif analysis of up (F) and down (G) -regulated SMRT peaks in NCOR-depleted cells. (H) Boxplots comparing the distribution of the ATAC-seq tags between shNCOR/shSMRT and control and the SMRT ChIP-seq tags between shNCOR and control. The comparison is done for SMRT upregulated peaks (left panel) and for SMRT downregulated peaks (right panel). (I) Boxplots presenting the distribution of the ATAC-seq tags between shNCOR/shSMRT and control and the NCOR ChIP-seq tags between shSMRT and control. (J-K) IGV genome browser tracks showing SMRT ChIP-seq at Abca1 and Ccl2 loci. The corresponding H3K27ac ChIP-seq is used to illustrate the epigenome alterations ( n =2). Wilcox test and DESeq2 were used to determine data significance for gene expression.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: Labeling, Binding Assay, Control, ChIP-sequencing, Comparison, Gene Expression

Influence of SMRT on NCOR subcellular localization. (A) Immunofluorescent (IF) staining showing the subcellular localization of SMRT in NCOR-depleted RAW cells; blue: DAPI, green: SMRT, scale bar: 2μm. (B) Immunofluorescent staining showing the subcellular localization of NCOR in SMRT-depleted RAW cells; blue: DAPI, green: NCOR, scale bar: 2μm. (C) Immunofluorescent double staining showing the subcellular localization of NCOR and SMRT in NCOR- and SMRT- depleted BMDMs; blue: DAPI, purple: NCOR, green: SMRT, scale bar: 2μm. (D) Subcellular fragmentation WB analysis of NCOR, SMRT, HDAC3 and GPS2 in NCOR- vs SMRT- depleted RAW cells. (E) Model of the compressor complex alterations upon NCOR vs. SMRT depletion in macrophages.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Influence of SMRT on NCOR subcellular localization. (A) Immunofluorescent (IF) staining showing the subcellular localization of SMRT in NCOR-depleted RAW cells; blue: DAPI, green: SMRT, scale bar: 2μm. (B) Immunofluorescent staining showing the subcellular localization of NCOR in SMRT-depleted RAW cells; blue: DAPI, green: NCOR, scale bar: 2μm. (C) Immunofluorescent double staining showing the subcellular localization of NCOR and SMRT in NCOR- and SMRT- depleted BMDMs; blue: DAPI, purple: NCOR, green: SMRT, scale bar: 2μm. (D) Subcellular fragmentation WB analysis of NCOR, SMRT, HDAC3 and GPS2 in NCOR- vs SMRT- depleted RAW cells. (E) Model of the compressor complex alterations upon NCOR vs. SMRT depletion in macrophages.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: Staining, Double Staining

Depletion of NCOR vs. SMRT differentially reprograms macrophage activation in response to multiple signals. (A-C) IGV genome browser tracks displaying H3K27ac increase in Pdcd1 , Arg1 , and Abca1 loci in response to LPS, IL4 or GW3965 treatment. Specific target epigenome regions are highlighted for each treatment. (D-F) Integration of CUT&Tag data for NCOR vs. SMRT depletion in LPS (D) , IL4 (E) or GW3965 (F) treated macrophages. The shNCOR-specific upregulated peaks are highlighted in orange and the shSMRT-specific upregulated peaks are highlighted in blue. (G-I) RT-qPCR analysis of related gene expression in LPS (G) , IL4 (H) and GW3965 (I) treatment in NCOR- vs. SMRT- depleted cells ( n =3). Unpaired t test was used to determine data significance for gene expression. All data were represented as mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001.

Journal: bioRxiv

Article Title: Nonredundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

doi: 10.1101/2025.05.13.653058

Figure Lengend Snippet: Depletion of NCOR vs. SMRT differentially reprograms macrophage activation in response to multiple signals. (A-C) IGV genome browser tracks displaying H3K27ac increase in Pdcd1 , Arg1 , and Abca1 loci in response to LPS, IL4 or GW3965 treatment. Specific target epigenome regions are highlighted for each treatment. (D-F) Integration of CUT&Tag data for NCOR vs. SMRT depletion in LPS (D) , IL4 (E) or GW3965 (F) treated macrophages. The shNCOR-specific upregulated peaks are highlighted in orange and the shSMRT-specific upregulated peaks are highlighted in blue. (G-I) RT-qPCR analysis of related gene expression in LPS (G) , IL4 (H) and GW3965 (I) treatment in NCOR- vs. SMRT- depleted cells ( n =3). Unpaired t test was used to determine data significance for gene expression. All data were represented as mean ± SEM. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001.

Article Snippet: We designed lentiviral shRNA sequences targeting NCOR ( Ncor1 ) (clone IDs: shNCOR-1 TRCN0000350169, shNCOR-2 TRCN0000310755) and SMRT ( Ncor2 ) (clone IDs: shSMRT-1 TRCN0000238140, shSMRT-2 TRCN0000238139) using the GPP Web Portal (Broad Institute).

Techniques: Activation Assay, Quantitative RT-PCR, Gene Expression

List of multi-gene mutational events with pathway level expression change.

Journal: BioMed Research International

Article Title: Pathway-Driven Discovery of Rare Mutational Impact on Cancer

doi: 10.1155/2014/171892

Figure Lengend Snippet: List of multi-gene mutational events with pathway level expression change.

Article Snippet: BIOCARTA_PPARA , NCOR1, EHHADH , 21 , −4.562 , 0.007.

Techniques: Expressing