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Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in <t>cardiomyocytes</t> (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .
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Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in <t>cardiomyocytes</t> (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .
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Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in <t>cardiomyocytes</t> (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .
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Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in <t>cardiomyocytes</t> (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .
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Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in <t>H9C2</t> cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group
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Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in <t>H9C2</t> cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group
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Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in <t>H9C2</t> cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group
Ac16 Human Cardiomyocyte, supplied by ATCC, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Miltenyi Biotec neonatal cardiomyocyte isolation kit
Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in <t>H9C2</t> cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group
Neonatal Cardiomyocyte Isolation Kit, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in cardiomyocytes (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .

Journal: iScience

Article Title: Recruitment of transcriptional effectors by Cas9 creates cis -regulatory elements and demonstrates distance-dependent transcriptional regulation

doi: 10.1016/j.isci.2025.114040

Figure Lengend Snippet: Cardiac-specific open putative regulatory elements are distributed around cardiac genes (A) A density histogram of CM-specific open chromatin distribution around the TSS of 221 highly enriched cardiac genes, showing high density of cardiac-specific open chromatin very close to the TSS with nonlinear decay at greater distances (Kbp). (B) Same data as in (A) presented as a map where the 221 loci were centered around the highly enriched cardiac genes TSS and the distribution of CM-specific open chromatin was plotted in a window of ±100 Kbp. (C) Analysis of expression of six selected highly enriched cardiac genes in cardiomyocytes (blue) and fibroblasts (green) using DE-seq2 normalized RNA-seq counts on a logarithmic scale, showing two orders of magnitude higher expression in cardiomyocytes for these genes ( n = 3 for cardiomyocytes and n = 2 for fibroblasts, black bars show the mean expression). (D) Heatmap showing the major cardiac transcription factors are very lowly expressed in fibroblasts. Data from RNA-seq with each column representing a different biological sample ( n = 6 and 4 for cardiomyocytes and fibroblasts, respectively. See also .

Article Snippet: Primary cultures of neonatal rat ventricular cardiomyocytes (CM) were isolated from 1 to 3 day old male and female Wistar rat pups using the neonatal cardiomyocyte isolation system (Worthington Biochemical Corporation) according to the manufacturer’s instructions.

Techniques: Expressing, RNA Sequencing

Recruitment of activation domain upregulates gene expression in a distance-dependent manner from multiple genomic sites. Activation maps shown as multi-track diagrams of six cardiomyocyte-specific gene loci spanning 140 Kbp each (A–C) Mybpc3 , Tnni1 , and Rcan1 , activated by sgRNA combination I. (D–F) Myh7 , Cox6a2 , and Myl3 , activated by sgRNA combination II. The TSS of each index gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; activation track showing index gene fold change activation following dCas9-VPR targeting to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh in FIB (scale of activation for the track is shown in square brackets, average fold activation from each gRNA site in black bars, red dots over bars indicate SEM, all black bars have two-tailed t-test p < 0.05 vs. control, and sites with non-significant p > 0.05 activation are shown as pink bars on the negative scale for visibility, n = 3 for all sites); ATAC-seq and H3K27ac ChIP-seq tracks are shown for FIB in greens and CM in blue. HiC maps for each locus are shown above, with aqua colored lines indicating insulation locus boundaries. See also and .

Journal: iScience

Article Title: Recruitment of transcriptional effectors by Cas9 creates cis -regulatory elements and demonstrates distance-dependent transcriptional regulation

doi: 10.1016/j.isci.2025.114040

Figure Lengend Snippet: Recruitment of activation domain upregulates gene expression in a distance-dependent manner from multiple genomic sites. Activation maps shown as multi-track diagrams of six cardiomyocyte-specific gene loci spanning 140 Kbp each (A–C) Mybpc3 , Tnni1 , and Rcan1 , activated by sgRNA combination I. (D–F) Myh7 , Cox6a2 , and Myl3 , activated by sgRNA combination II. The TSS of each index gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; activation track showing index gene fold change activation following dCas9-VPR targeting to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh in FIB (scale of activation for the track is shown in square brackets, average fold activation from each gRNA site in black bars, red dots over bars indicate SEM, all black bars have two-tailed t-test p < 0.05 vs. control, and sites with non-significant p > 0.05 activation are shown as pink bars on the negative scale for visibility, n = 3 for all sites); ATAC-seq and H3K27ac ChIP-seq tracks are shown for FIB in greens and CM in blue. HiC maps for each locus are shown above, with aqua colored lines indicating insulation locus boundaries. See also and .

Article Snippet: Primary cultures of neonatal rat ventricular cardiomyocytes (CM) were isolated from 1 to 3 day old male and female Wistar rat pups using the neonatal cardiomyocyte isolation system (Worthington Biochemical Corporation) according to the manufacturer’s instructions.

Techniques: Activation Assay, Gene Expression, Control, Quantitative RT-PCR, Two Tailed Test, ChIP-sequencing, Insulation

Activation with endogenous activation domains has similar features to activation with viral-derived activation domains (A) Diagram of CRISPR activators composed of dCas tethered to the activation domains of VP64, p65, and Rta (dCas9-VPR, top) or dCas tethered to the activation domains of the endogenous cardiac transcription factors GATA4, NKX2-5, and TBX5 (dCas9-GNT, bottom). (B) Activation maps as multi-track diagrams of two cardiomyocyte-specific gene loci ( Tnni1 and Cox6a2 ) are shown in a 70 Kbp window around the TSS. Tracks showing (from top to bottom): HiC maps for each locus, with aqua-colored lines indicating insulation locus boundaries; the genomic track with exons and introns in blue; activation tracks showing target gene average fold activation following dCas9-GNT in blue bars or activation with dCas9-VPR in black bars targeted to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh in FIB (scale of activation for the track is shown in square brackets, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3); tracks of ATAC-seq and H3K27ac ChIP-seq are shown for FIB in green and CM in blue. Diagram shows similar activation by dCas9-GNT and dCas9-VPR from distal sites lacking open chromatin or H3K27ac marks. (C) A diagram of the Myh7 locus with a genomic track showing exons and introns in blue and ATAC-seq and H3K27ac ChIP-seq track in CM and FIB. A distal site, 15 Kbp from the TSS, marked by a red dot and cross-hatched lines, was activated by dCas9-GNT in FIB. We then assessed the H3K27ac marks at the distal site of activation and at the promoter of these genes (red arrow). (D) qRT-PCR results show that dCas9-GNT targeting the 15 Kbp distal sites induce strong activation of Myh7 in FIB. Data are shown as fold activation vs. non-targeting gRNA control normalized to Gapdh; data are represented as mean ± SEM ( n = 3, ∗two-tailed t-test p < 0.005). (E) ChIP-qPCR analysis of H3K27ac activation marks shows increased chromatin modification of both the distal activation site and the gene proximal promoter following activation of the distal site by dCas9-GNT. For each promoter and distal site, two separate primer pairs were used, amplifying regions ∼300 bp apart. Data are represented as mean ± SEM ( n = 5–8 for each primer pair in N = 2–3 independent experiments, ∗two-tailed t-test p < 0.05). See also .

Journal: iScience

Article Title: Recruitment of transcriptional effectors by Cas9 creates cis -regulatory elements and demonstrates distance-dependent transcriptional regulation

doi: 10.1016/j.isci.2025.114040

Figure Lengend Snippet: Activation with endogenous activation domains has similar features to activation with viral-derived activation domains (A) Diagram of CRISPR activators composed of dCas tethered to the activation domains of VP64, p65, and Rta (dCas9-VPR, top) or dCas tethered to the activation domains of the endogenous cardiac transcription factors GATA4, NKX2-5, and TBX5 (dCas9-GNT, bottom). (B) Activation maps as multi-track diagrams of two cardiomyocyte-specific gene loci ( Tnni1 and Cox6a2 ) are shown in a 70 Kbp window around the TSS. Tracks showing (from top to bottom): HiC maps for each locus, with aqua-colored lines indicating insulation locus boundaries; the genomic track with exons and introns in blue; activation tracks showing target gene average fold activation following dCas9-GNT in blue bars or activation with dCas9-VPR in black bars targeted to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh in FIB (scale of activation for the track is shown in square brackets, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3); tracks of ATAC-seq and H3K27ac ChIP-seq are shown for FIB in green and CM in blue. Diagram shows similar activation by dCas9-GNT and dCas9-VPR from distal sites lacking open chromatin or H3K27ac marks. (C) A diagram of the Myh7 locus with a genomic track showing exons and introns in blue and ATAC-seq and H3K27ac ChIP-seq track in CM and FIB. A distal site, 15 Kbp from the TSS, marked by a red dot and cross-hatched lines, was activated by dCas9-GNT in FIB. We then assessed the H3K27ac marks at the distal site of activation and at the promoter of these genes (red arrow). (D) qRT-PCR results show that dCas9-GNT targeting the 15 Kbp distal sites induce strong activation of Myh7 in FIB. Data are shown as fold activation vs. non-targeting gRNA control normalized to Gapdh; data are represented as mean ± SEM ( n = 3, ∗two-tailed t-test p < 0.005). (E) ChIP-qPCR analysis of H3K27ac activation marks shows increased chromatin modification of both the distal activation site and the gene proximal promoter following activation of the distal site by dCas9-GNT. For each promoter and distal site, two separate primer pairs were used, amplifying regions ∼300 bp apart. Data are represented as mean ± SEM ( n = 5–8 for each primer pair in N = 2–3 independent experiments, ∗two-tailed t-test p < 0.05). See also .

Article Snippet: Primary cultures of neonatal rat ventricular cardiomyocytes (CM) were isolated from 1 to 3 day old male and female Wistar rat pups using the neonatal cardiomyocyte isolation system (Worthington Biochemical Corporation) according to the manufacturer’s instructions.

Techniques: Activation Assay, Derivative Assay, CRISPR, Insulation, Control, Quantitative RT-PCR, Two Tailed Test, ChIP-sequencing, ChIP-qPCR, Modification

Recruitment of repression domain represses gene expression in a distance-dependent manner from multiple genomic loci (A) Multi-track diagrams of two cardiomyocyte specific gene loci ( Mybpc3 and Myh7 ) spanning 140 Kbp each. TSS of each gene is shown in red arrows. HiC maps for each locus are shown, with aqua-colored lines indicating insulation boundaries. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; repression track showing index gene % repression in CM following dCas9-KRAB targeting to the genomic site with targeting versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh (scale of repression 0–100% in square brackets, average % repression from each gRNA site in black bars, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3). Activation track showing the same index gene activation in FIB following dCas9-VPR targeting to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh (scale of activation for the track is shown in square brackets, average fold activation from each gRNA site in black bars, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3). ATAC-seq and H3K27ac ChIP-seq tracks are shown for FIB in green and CM in blue. Diagram shows that like activation, repression can be achieved at a distance, by targeting non-regulatory chromatin, and can cross insulation boundaries. (B) Scatterplot of gene fold activation in FIB by dCas9-VPR as a function of % repression by dCas9-KRAB in CM as measured by RT-qPCR for multiple gRNA targeting sites in the Mybpc3 and Myh7 loci. Each dot represents the average of n = 3 measurements in CM and FIB. Plot shows activation and repression from these sites are generally correlated. A linear regression line is shown (Spearman’s Rho 0.34, n = 17). See also and ; .

Journal: iScience

Article Title: Recruitment of transcriptional effectors by Cas9 creates cis -regulatory elements and demonstrates distance-dependent transcriptional regulation

doi: 10.1016/j.isci.2025.114040

Figure Lengend Snippet: Recruitment of repression domain represses gene expression in a distance-dependent manner from multiple genomic loci (A) Multi-track diagrams of two cardiomyocyte specific gene loci ( Mybpc3 and Myh7 ) spanning 140 Kbp each. TSS of each gene is shown in red arrows. HiC maps for each locus are shown, with aqua-colored lines indicating insulation boundaries. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; repression track showing index gene % repression in CM following dCas9-KRAB targeting to the genomic site with targeting versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh (scale of repression 0–100% in square brackets, average % repression from each gRNA site in black bars, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3). Activation track showing the same index gene activation in FIB following dCas9-VPR targeting to the genomic site versus non-targeting gRNA control, as measured by RT-qPCR normalized to Gapdh (scale of activation for the track is shown in square brackets, average fold activation from each gRNA site in black bars, red dots over bars indicate SEM, only bars with two-tailed t-test p < 0.05 vs. control are shown, n = 3). ATAC-seq and H3K27ac ChIP-seq tracks are shown for FIB in green and CM in blue. Diagram shows that like activation, repression can be achieved at a distance, by targeting non-regulatory chromatin, and can cross insulation boundaries. (B) Scatterplot of gene fold activation in FIB by dCas9-VPR as a function of % repression by dCas9-KRAB in CM as measured by RT-qPCR for multiple gRNA targeting sites in the Mybpc3 and Myh7 loci. Each dot represents the average of n = 3 measurements in CM and FIB. Plot shows activation and repression from these sites are generally correlated. A linear regression line is shown (Spearman’s Rho 0.34, n = 17). See also and ; .

Article Snippet: Primary cultures of neonatal rat ventricular cardiomyocytes (CM) were isolated from 1 to 3 day old male and female Wistar rat pups using the neonatal cardiomyocyte isolation system (Worthington Biochemical Corporation) according to the manufacturer’s instructions.

Techniques: Gene Expression, Insulation, Control, Quantitative RT-PCR, Two Tailed Test, Activation Assay, ChIP-sequencing

Recruitment of activation and repression domains controls gene expression in a distance-dependent manner from multiple genomic sites in human cells (A) Repression maps shown as multi-track diagrams in two cardiomyocyte-specific gene loci (MYBPC3 and MYH7), spanning 150 Kbp each. The TSS of each gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; repression showing index gene % repression in iPSC-CM following Ad-dCas9-KRAB targeting versus non-targeting sgRNA control, measured by RT-qPCR normalized to GAPDH. ENCODE ATAC-seq and H3K27ac-seq tracks in hiPSC are shown in blue and red, respectively. Scale of repression 0%–100% in square brackets, average % repression from each sgRNA site in black bars, red dots over black bars represent SEM, only bards with two-tailed t-test p < 0.05 versus control are shown, n = 3 biological replicates. (B) Activation maps in human HEK293 fibroblasts shown as multi-track diagram of 3 CM-specific genes (TNNI1, COX6A2, and RCAN1) spanning 150 Kbp each. The TSS of each gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue, fold change activation following dCas9-VPR targeting versus non-targeting sgRNA control, measured by RT-qPCR normalized to GAPDH. ENCODE DNAse and H3K27ac-seq tracks in fibroblast cells are shown in blue and red, respectively. The scale for activation for the track is shown in square brackets, average fold activation for each sgRNA site in black bars, and red dots over black bars indicate SEM. All black bars have two-tailed t-test p < 0.05 versus control, n = 3 biological replicates.

Journal: iScience

Article Title: Recruitment of transcriptional effectors by Cas9 creates cis -regulatory elements and demonstrates distance-dependent transcriptional regulation

doi: 10.1016/j.isci.2025.114040

Figure Lengend Snippet: Recruitment of activation and repression domains controls gene expression in a distance-dependent manner from multiple genomic sites in human cells (A) Repression maps shown as multi-track diagrams in two cardiomyocyte-specific gene loci (MYBPC3 and MYH7), spanning 150 Kbp each. The TSS of each gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue; repression showing index gene % repression in iPSC-CM following Ad-dCas9-KRAB targeting versus non-targeting sgRNA control, measured by RT-qPCR normalized to GAPDH. ENCODE ATAC-seq and H3K27ac-seq tracks in hiPSC are shown in blue and red, respectively. Scale of repression 0%–100% in square brackets, average % repression from each sgRNA site in black bars, red dots over black bars represent SEM, only bards with two-tailed t-test p < 0.05 versus control are shown, n = 3 biological replicates. (B) Activation maps in human HEK293 fibroblasts shown as multi-track diagram of 3 CM-specific genes (TNNI1, COX6A2, and RCAN1) spanning 150 Kbp each. The TSS of each gene is shown in red arrows. Tracks showing (from top to bottom): the genomic track with exons and introns in blue, fold change activation following dCas9-VPR targeting versus non-targeting sgRNA control, measured by RT-qPCR normalized to GAPDH. ENCODE DNAse and H3K27ac-seq tracks in fibroblast cells are shown in blue and red, respectively. The scale for activation for the track is shown in square brackets, average fold activation for each sgRNA site in black bars, and red dots over black bars indicate SEM. All black bars have two-tailed t-test p < 0.05 versus control, n = 3 biological replicates.

Article Snippet: Primary cultures of neonatal rat ventricular cardiomyocytes (CM) were isolated from 1 to 3 day old male and female Wistar rat pups using the neonatal cardiomyocyte isolation system (Worthington Biochemical Corporation) according to the manufacturer’s instructions.

Techniques: Activation Assay, Gene Expression, Control, Quantitative RT-PCR, Two Tailed Test

Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in H9C2 cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group

Journal: Inflammation

Article Title: Higenamine Hydrochloride Ameliorates Diabetic Cardiomyopathy Through RhoA/MEK/ERK Pathway

doi: 10.1007/s10753-025-02403-4

Figure Lengend Snippet: Effect of HGN on HG-induced inflammation, oxidative stress, fibrosis and apoptosis in H9C2 cells. A Immunoblotting for IL-6, IL-1β (GAPDH as reference, n = 6). B-D Quantification of IL-6, IL-1β, tnf-α mRNA. E Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). F-H Quantification of GPX4, NRF2, Keap1. I Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). J-L Quantification of TGF-β1, α-SMA, Collagen I. M Immunoblotting for BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9 (GAPDH as control, n = 6). N-Q Quantification of BCL2, Caspase-3, Pro-caspase-9, Cleaved caspase-9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group

Article Snippet: H9C2 mouse cardiomyocytes (CRL-1446; BSL 1; ATCC) were carefully maintained in a 37 °C, 5% CO2 and humidified incubator.

Techniques: Western Blot, Control

Effect of HGN on RhoA inhibition of inflammation, oxidative stress, fibrosis and apoptosis in H9C2 cells. A Immunoblotting for RhoA (GAPDH as reference, n = 6). B Quantification of RhoA. C Immunoblotting for IL−6, TNF-α, IL−1β (GAPDH as reference, n = 6). D-F Quantification of IL−6, TNF-α, IL−1β. G Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). H-J Quantification of GPX4, NRF2, Keap1. K Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). L-N Quantification of TGF-β1, α-SMA, Collagen I. O Immunoblotting for BCL2, Pro-Caspase−3, Cleaved Caspase−3, Pro-Caspase−9, Cleaved Caspase−9, RhoA (GAPDH as control, n = 6). P-S Quantification of BCL2, Pro-Caspase−3, Cleaved Caspase−3, Pro-Caspase−9, Cleaved Caspase−9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group

Journal: Inflammation

Article Title: Higenamine Hydrochloride Ameliorates Diabetic Cardiomyopathy Through RhoA/MEK/ERK Pathway

doi: 10.1007/s10753-025-02403-4

Figure Lengend Snippet: Effect of HGN on RhoA inhibition of inflammation, oxidative stress, fibrosis and apoptosis in H9C2 cells. A Immunoblotting for RhoA (GAPDH as reference, n = 6). B Quantification of RhoA. C Immunoblotting for IL−6, TNF-α, IL−1β (GAPDH as reference, n = 6). D-F Quantification of IL−6, TNF-α, IL−1β. G Immunoblotting for GPX4, NRF2, Keap1 (GAPDH as control, n = 6). H-J Quantification of GPX4, NRF2, Keap1. K Immunoblotting for TGF-β1, α-SMA, Collagen I (GAPDH as control, n = 6). L-N Quantification of TGF-β1, α-SMA, Collagen I. O Immunoblotting for BCL2, Pro-Caspase−3, Cleaved Caspase−3, Pro-Caspase−9, Cleaved Caspase−9, RhoA (GAPDH as control, n = 6). P-S Quantification of BCL2, Pro-Caspase−3, Cleaved Caspase−3, Pro-Caspase−9, Cleaved Caspase−9. Significance: ns ( p > 0.05), * ( p < 0.05), ** ( p < 0.01), *** ( p < 0.001), **** ( p < 0.0001) vs. STZ group

Article Snippet: H9C2 mouse cardiomyocytes (CRL-1446; BSL 1; ATCC) were carefully maintained in a 37 °C, 5% CO2 and humidified incubator.

Techniques: Inhibition, Western Blot, Control