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Sequenom massarray dna methylation analysis
Massarray Dna Methylation Analysis, supplied by Sequenom, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/massarray+dna+methylation+analysis/massarray+quantitative+methylation+analysis/pmc09335189-30-3-2
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massarray dna methylation analysis - by Bioz Stars, 2026-09
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Related Articles

Methylation:

Article Title: Gender dimorphism in hepatocarcinogenesis—DNA methylation modification regulated X‐chromosome inactivation escape molecule XIST
Article Snippet: .. Methylation of CpG sites of the Xist first exon region in liver tissues between 10 WT and 10 Tet2 −/− female mice was quantified by Sequenom MassARRAY methylation profiling. ..

Article Title: Gender dimorphism in hepatocarcinogenesis—DNA methylation modification regulated X‐chromosome inactivation escape molecule XIST
Article Snippet: .. Methylation of XIST was detected by Sequenom MassARRAY methylation profiling between HCC tissues (T) and adjacent normal liver tissues (L). ..

Article Title: Exposure to Juvenile Stress Induces Epigenetic Alterations in the GABAergic System in Rats.
Article Snippet: .. Sequenom Epityper MassARRAY Methylation and Spectra Analysis Samples were desalted and spotted on a 384-alternative patch SpectroCHIP (Se- quenom, San Diego, CA, USA) using the MassARRAY nanodispenser, and spectra were analyzed by the MassARRAY Analyzer Compact matrix-assisted laser desorption/ioniza- tion–time of flight (MALDI-TOF MS) (Sequenom, San Diego, CA, USA). .. Spectra were elaborated by the Epityper 1.2 software (Sequenom, San Diego, CA, USA), which provides methylation values for each CpG unit as a percentage.

Article Title: DNA Hyper-methylation Associated With Schizophrenia May Lead to Increased Levels of Autoantibodies
Article Snippet: .. A Sequenom MassARRAY quantitative methylation assay was performed to measure the methylation levels of candidate DMS cg14341177 and cg13978347 in the discovery cohort. .. There are 4 CpG sites on cg14341177, in which the CpG2 site showed the most significant changes in methylation levels and seemed as the leading CpG site.

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..

other:

Article Title: Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis
Article Snippet: The methylation profiling was validated by two methods including Illumina-sequencing-based BSP and Sequenom MassARRAY® Methylation.

Article Title: Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis.
Article Snippet: For participants with methylation data, technical replication (see Technical replication of DNA methylation profiling in Additional file 1) was conducted: 194 participants were randomly chosen for Illumina sequencing-based BSP detection to verify the chip detection site results, and among these 194 participants, 20 were further randomly selected to undergo Sequenom MassARRAY® Methylation validation.

Expressing:

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..

Western Blot:

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..

Real-time Polymerase Chain Reaction:

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..

Agarose Gel Electrophoresis:

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..

Methylated DNA Immunoprecipitation:

Article Title: Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.
Article Snippet: .. Scale bar, 50 μm. (G and H) The expression of YY1 in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by western blot analysis. (I) Expression of YY1 and XIST in HCC-1016 cells (knocked down YY1 in HCC-1016 cells by transfecting siRNA) by qPCR. (J) XIST was quantified using DNA agarose gel electrophoresis. (K) The 5-methylcytosine (5mC) level in the XIST promoter region by MeDIP assay and qPCR. was quantified by Sequenom MassARRAY methylation profiling. ..



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Epigenome-wide <t>DNA</t> <t>methylation</t> analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.
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Epigenome-wide <t>DNA</t> <t>methylation</t> analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.
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Epigenome-wide DNA methylation analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: Epigenome-wide DNA methylation analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: DNA Methylation Assay, Methylation, Biomarker Discovery

FAEs inhibit DNA demethylation at the MIR-21 promoter in a specific and dose-dependent manner. Naïve (CD45RO−CCR7+) and memory (CD45RO+) CD4 T cells were isolated from human PBMCs by FACS. The baseline DNA methylation levels of naïve (NaïveBL) and memory CD4 T cells (MemoryBL) at the (A) MIR-21 and (B) TNF promoters were measured ex vivo by EpiTYPER™ MassARRAY®. Naïve and memory CD4 T cells were also cultured with or without MMF at the specified concentration and stimulated with anti-CD3 and anti-CD28 coated beads for 3 days either without polarization or under Th17 polarizing conditions, after which DNA methylation levels at the (A) MIR-21 and (B) TNF promoters were measured by EpiTYPER™ MassARRAY®. (A) MMF was able to inhibit DNA demethylation of the MIR-21 promoter in naïve CD4 T cells, but not in memory CD4 T cells, in a dose dependent manner. (B) DNA methylation at the TNF promoter was not significantly changed by MMF in either naïve or memory CD4 T cells. (C) MMF had an even greater hypermethylating effect on the MIR-21 locus of naïve CD4 T cells that were stimulated under Th17 polarizing conditions. (D) MMF was also able to inhibit the demethylation of the MIR-21 promoter of naïve (CD45RO−CCR7+) CD8 T cells after 3 days of activation with anti-CD3 and anti-CD28 coated beads in vitro under Tc17 polarizing conditions. MMF20 = 20 µM of MMF; MMF50 = 50 µM of MMF; Veh = vehicle.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: FAEs inhibit DNA demethylation at the MIR-21 promoter in a specific and dose-dependent manner. Naïve (CD45RO−CCR7+) and memory (CD45RO+) CD4 T cells were isolated from human PBMCs by FACS. The baseline DNA methylation levels of naïve (NaïveBL) and memory CD4 T cells (MemoryBL) at the (A) MIR-21 and (B) TNF promoters were measured ex vivo by EpiTYPER™ MassARRAY®. Naïve and memory CD4 T cells were also cultured with or without MMF at the specified concentration and stimulated with anti-CD3 and anti-CD28 coated beads for 3 days either without polarization or under Th17 polarizing conditions, after which DNA methylation levels at the (A) MIR-21 and (B) TNF promoters were measured by EpiTYPER™ MassARRAY®. (A) MMF was able to inhibit DNA demethylation of the MIR-21 promoter in naïve CD4 T cells, but not in memory CD4 T cells, in a dose dependent manner. (B) DNA methylation at the TNF promoter was not significantly changed by MMF in either naïve or memory CD4 T cells. (C) MMF had an even greater hypermethylating effect on the MIR-21 locus of naïve CD4 T cells that were stimulated under Th17 polarizing conditions. (D) MMF was also able to inhibit the demethylation of the MIR-21 promoter of naïve (CD45RO−CCR7+) CD8 T cells after 3 days of activation with anti-CD3 and anti-CD28 coated beads in vitro under Tc17 polarizing conditions. MMF20 = 20 µM of MMF; MMF50 = 50 µM of MMF; Veh = vehicle.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: Isolation, DNA Methylation Assay, Ex Vivo, Cell Culture, Concentration Assay, Activation Assay, In Vitro

FAE therapy modifies the metabolic-epigenetic interplay in multiple sclerosis to reduce pathogenic CCR6+ CD4 and CD8 T cells. (A) CD4 T cells from treatment naïve patients with multiple sclerosis exhibit low DNA methylation levels at the MIR-21 locus and high expression of CCR6. CD8 T cells from treatment naïve multiple sclerosis patients also exhibit high levels of CCR6. (B) FAE therapy epigenetically modulates the MIR-21 locus in CD4 and CD8 T cells, which results in hypermethylation and downregulation of miR-21 expression in FAE-treated Th17 and Tc17 cells. This in turn allows for the upregulation of SMAD7 in both CD4 and CD8 T cells, a miR-21-5p and miR-21-3p target with inhibitory feedback on the TGF-b signalling pathway. Finally, FAEs reduce CCR6 expression and lower this potentially pathogenic brain-homing CCR6+ CD4 and CD8 T cell population in FAE-treated multiple sclerosis patients.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: FAE therapy modifies the metabolic-epigenetic interplay in multiple sclerosis to reduce pathogenic CCR6+ CD4 and CD8 T cells. (A) CD4 T cells from treatment naïve patients with multiple sclerosis exhibit low DNA methylation levels at the MIR-21 locus and high expression of CCR6. CD8 T cells from treatment naïve multiple sclerosis patients also exhibit high levels of CCR6. (B) FAE therapy epigenetically modulates the MIR-21 locus in CD4 and CD8 T cells, which results in hypermethylation and downregulation of miR-21 expression in FAE-treated Th17 and Tc17 cells. This in turn allows for the upregulation of SMAD7 in both CD4 and CD8 T cells, a miR-21-5p and miR-21-3p target with inhibitory feedback on the TGF-b signalling pathway. Finally, FAEs reduce CCR6 expression and lower this potentially pathogenic brain-homing CCR6+ CD4 and CD8 T cell population in FAE-treated multiple sclerosis patients.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: DNA Methylation Assay, Expressing

ZNF582-AS1 expression was regulated by DNA methylation in ccRCC. a Detection of CpG islands in ZNF582-AS1 promoter and design of MSP primers. The horizontal axis of the curved lines represents the input sequence of ZNF582-AS1, and the vertical axis of the curved lines represents GC percentage. TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells. T refers to Tumor tissue of ccRCC, N refers to Adjacent normal kidney tissue. M = Methylated, U = Unmethylated

Journal: Journal of Experimental & Clinical Cancer Research : CR

Article Title: Downregulation of lncRNA ZNF582-AS1 due to DNA hypermethylation promotes clear cell renal cell carcinoma growth and metastasis by regulating the N(6)-methyladenosine modification of MT-RNR1

doi: 10.1186/s13046-021-01889-8

Figure Lengend Snippet: ZNF582-AS1 expression was regulated by DNA methylation in ccRCC. a Detection of CpG islands in ZNF582-AS1 promoter and design of MSP primers. The horizontal axis of the curved lines represents the input sequence of ZNF582-AS1, and the vertical axis of the curved lines represents GC percentage. TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells. T refers to Tumor tissue of ccRCC, N refers to Adjacent normal kidney tissue. M = Methylated, U = Unmethylated

Article Snippet: TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells.

Techniques: Expressing, DNA Methylation Assay, Sequencing, Comparison, Methylation

Summary of main projects in the PANINI network

Journal: Aging Clinical and Experimental Research

Article Title: Physical Activity and Nutrition INfluences In ageing (PANINI): consortium mission statement

doi: 10.1007/s40520-017-0823-7

Figure Lengend Snippet: Summary of main projects in the PANINI network

Article Snippet: 10. University of Bologna , Epigenetics of nutrition in ageing , DNA methylation analysis (gene-targeted) by Sequenom ® MassARRAY EpiTYPER platform , NU-AGE samples and new PANINI data , Changes in DNA methylation patterns induced by dietary and physical interventions. Development of a gene-targeted epigenetic clock.

Techniques: Battery, Activity Assay, Modification, DNA Methylation Assay, Variant Assay