Journal: Scientific Reports

Article Title: Differences in DNA Methylation and Functional Expression in Lactase Persistent and Non-persistent Individuals

doi: 10.1038/s41598-018-23957-4

Figure Lengend Snippet: Pyrosequencing of DNA methylation at cg20242066. ( A ) Schematic of LCT proximal promoter with location of cg20242066 upstream of the first three exons of the gene. The genomic coordinate of cg20242066 is also given (genome build hg19). ( B) DNA methylation quantification in CC vs. C/T vs. TT individuals, as well as in ( C) Phenotypically Persistent (PER) and Non-persistent (NON-PER) individuals. Student’s T-test was calculated for inter-group comparisons (*p < 0.05; **p < 0.001). Number of individuals in each group is given in parenthesis. ( D) Correlation between DNA methylation at cg20242066 and lactase enzymatic activity (enzymatic activity data from Baffour-Awuah et al . ). ( E) Correlation between DNA methylation at cg20242066 and LCT gene expression ( LCT gene expression data from Baffour-Awuah et al . ).

Article Snippet: Figure 3 Pyrosequencing of DNA methylation at cg20242066. ( A ) Schematic of LCT proximal promoter with location of cg20242066 upstream of the first three exons of the gene.

Techniques: DNA Methylation Assay, Activity Assay, Gene Expression

Journal: Scientific Reports

Article Title: Differences in DNA Methylation and Functional Expression in Lactase Persistent and Non-persistent Individuals

doi: 10.1038/s41598-018-23957-4

Figure Lengend Snippet: Correlation between DNA methylation at the LCT enhancer and cg20242066. ( A ) Lactase enzymatic activity according to the genotype of the individual at −13910C > T (rs4988235). Student’s T-test was calculated for inter-group comparisons (*p < 0.05; **p < 0.001). ( B) Correlation between DNA methylation at the LCT promoter cg20242066 and LCT enhancer.

Article Snippet: Figure 3 Pyrosequencing of DNA methylation at cg20242066. ( A ) Schematic of LCT proximal promoter with location of cg20242066 upstream of the first three exons of the gene.

Techniques: DNA Methylation Assay, Activity Assay

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: MGMT promoter methylation trends in pyrosequencing samples . ( A ) Frequency of positive results for all glioma samples above and below the cutoff value of VAF = 0.325. ( B ) Cumulative mean frequency of positive test results as a function of VAF. ( C ) Trends in cumulative mean MGMT promoter pyrosequencing score with increasing VAF. ( D ) Mean MGMT promoter pyrosequencing scores above and below VAF = 0.325. Similar results are shown for each tumor subtype, including IDH-wildtype glioblastoma ( E - H ), IDH-mutant astrocytoma ( I - L ) and IDH-mutant and 1p/19q co-deleted oligodendroglioma ( M - P ). (Horizontal dashed black lines: mean values for cohort; Horizontal solid red lines: MGMT positivity cutoff of 10.0%; Vertical dashed black lines: cutoff values identified by Cutoff Finder; Vertical dashed red lines: cutoff values identified by multi-part linear regression; Panels A, E, I, M: Fisher’s exact test; Panels D, H, L, P: unpaired Student’s T-test; pyroseq: pyrosequencing; *p < 0.05; ****p < 0.0001)

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Methylation, Mutagenesis

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: MGMT promoter methylation trends in DNA methylation array samples . ( A ) Frequency of positive results for all glioma array samples above and below the cutoff of VAF = 0.245. ( B ) Cumulative mean frequency of positive results for all glioma array samples as a function of VAF. ( C ) Frequency of positive results for GBM array samples above and below the cutoff of TERT VAF = 0.325. ( D ) Cumulative mean frequency of positive results in GBM array samples as a function of TERT VAF. ( E ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 10.0% versus GBM array samples. ( F ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 7.28% versus GBM array samples. ( G ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF < 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF < 0.325. ( H ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF ≥ 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF ≥ 0.325. ( I ) Frequency of positive results for IDHmut astrocytoma above and below the cutoff of IDH VAF = 0.325 (left), by methylation class match (center), and above and below the cutoff of classifier score = 0.955 (right). ( J ) Cumulative mean frequency of positive results in IDHmut astrocytoma array samples as a function of IDH VAF (Fisher’s exact test for panels A, C, E, F, G, H, I; GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma)

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Methylation, DNA Methylation Assay, Mutagenesis

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Driver mutation VAF , MGMT promoter methylation scores, and tumor cellularity . ( A ) Linear regression of MGMT promoter pyrosequencing score versus driver mutation VAF for all glioma samples. ( B ) Linear regression of MGMT promoter pyrosequencing score versus TERT promoter mutation VAF for GBM. ( C ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut astrocytoma. ( D ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut oligodendroglioma. ( E ) Linear regression of microscopically estimated cellularity versus cellularity calculated from driver mutation VAF (2×VAF×100%) for all glioma samples. ( F ) Differences between microscopically estimated cellularity and cellularity calculated from VAF (Y-axis) plotted as a function of VAF (X-axis), for all glioma samples. ( G ) TERT promoter mutation VAF by ddPCR in high versus low cellularity areas of GBM tissue samples. ( H ) MGMT promoter methylation score by ddPCR in high versus low cellularity areas of GBM tissue samples (GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma, IDHmut oligodendroglioma: IDH-mutant and 1p/19q co-deleted oligodendroglioma, pyroseq: pyrosequencing, ddPCR: droplet digital PCR)

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Mutagenesis, Methylation, Digital PCR

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Methylation, DNA Methylation Assay, Digital PCR

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Central hypothesis . MGMT promoter methylation is pathologic, and occurs only in tumor cells. Cellular glioma samples are rich in DNA from tumor cells, whereas paucicellular glioma samples contain a large fraction of DNA from non-tumor cells, which can “dilute” positive methylation signals from tumor cell DNA, leading to false-negative results

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Methylation

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Patient cohort characteristics

Article Snippet: Fig. 5 False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques: Pyrosequencing Assay, Methylation, Mutagenesis

Journal: Nature Communications

Article Title: Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat

doi: 10.1038/s41467-021-27141-7

Figure Lengend Snippet: A UTX protein level in iBAT of C57BL/6 J mice fed with HFD for 12 and 24 weeks ( n = 3/group). *indicates statistical significance between chow and HFD by two-tailed unpaired Student’s t -test. B Analysis of UTX protein levels and myogenic marker gene expression patterns in iBAT of HFD-fed mice for 1 week, 4 weeks, 12 weeks, 24 weeks, and 1 year. For UTX protein, n = 3/group. For Myod1 , Myog, and Myh1 gene expression, n = 8/group. C Negative correlations between UTX protein levels and myogenic marker gene expression in iBAT of mice fed HFD for 1 week, 4 weeks, 12 weeks, 24 weeks, and 52 weeks ( n = 15/group) as analyzed by Spearman’s rank correlation coefficient test, p = 0.029 between UTX protein and Myod1 mRNA, p = 0.002 between UTX protein and Myog mRNA, and p < 0.0001 between UTX protein and Myh1 mRNA. D Heatmap of myogenic marker gene expression from iBAT of wild-type mice fed chow or HFD. E Quantitative RT-PCR analysis of myogenic marker gene expression in iBAT of chow- or HFD-fed wild-type C57BL/6J mice ( n = 7/group). *Indicates statistical significance between Chow and HFD by Mann–Whitney’s nonparametric U test. F Representative IHC staining of MyHC in iBAT of chow- or HFD-fed wild-type C57BL/6J mice ( n = 3 replicates for each group). G OCR of primary brown adipocytes isolated from chow- or HFD-fed wild-type C57BL/6J mice ( n = 24 for chow, n = 19 for HFD). *Indicates statistical significance between chow and HFD by two-tailed unpaired Student’s t -test. All data are expressed as mean ± SEM.

Article Snippet: K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group).

Techniques: Two Tailed Test, Marker, Gene Expression, Quantitative RT-PCR, Immunohistochemistry, Isolation

Journal: Nature Communications

Article Title: Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat

doi: 10.1038/s41467-021-27141-7

Figure Lengend Snippet: A RRBS profiling of DNA methylation level at MyoD1 promoter in iBAT of D1KO and fl/fl mice. B , C Ucp1 ( B , n = 4/group) and Myod1 ( C , n = 4/group) expression in iBAT of mice during late embryonic and postnatal development. *Indicates statistical significance vs. 17E with one-way ANOVA followed by Fisher’s LSD multiple comparisons test; in ( B ), F (7,24) = 48.31, p < 0.0001, and in ( C ), F (7,24) = 10.54, p < 0.0001. D , E Ucp1 ( D ) and Myod1 ( E ) expression in iBAT of mice during cold exposure ( n = 3/group). *indicates statistical significance vs. Time 0 with one-way ANOVA followed by Fisher’s LSD multiple comparisons test; in ( D ), F (3,8) = 6.406, p = 0.016, and in ( E ), F (3,8) = 25.096, p < 0.0001. F Ucp1 , Prdm16 and myogenic marker gene expression in iBAT and gastrocnemius (GAS) muscle ( n = 4/group). *Indicates statistical significance between iBAT and GAS as analyzed by two-tailed unpaired Student’s t -test, except for Myod1 and Atp2a1 , which were analyzed by Mann–Whitney’s nonparametric U test. G Pyrosequencing analysis of DNA methylation level at Myod1 promoter in iBAT and GAS muscle ( n = 4/group). *Indicates statistical significance between iBAT and GAS as analyzed by Mann–Whitney’s nonparametric U test. H ChIP assay of DNMT1 binding to Myod1 promoter in undifferentiated BAT1 preadipocytes and differentiated BAT1 brown adipocytes ( n = 4/group). *indicates statistical significance by two-tailed unpaired Student’s t -test. I ChIP assay of DNMT1 binding to Myod1 promoter in iBAT from HFD- or LFD-fed mice ( n = 6/group). *Indicates statistical significance by two-tailed unpaired Student’s t -test. J Pyrosequencing analysis of DNA methylation levels at Myod1 promoter in BAT1 brown adipocytes transfected with scramble or Dnmt1 siRNA ( n = 6/group). *Indicates statistical significance between iBAT and GAS as analyzed by Mann–Whitney’s nonparametric U test. K Quantitative RT-PCR analysis of myogenic marker gene and BAT gene expression in BAT1 brown adipocytes transfected with scramble, Dnmt1 , Myod1 , or Dnmt1 + Myod1 siRNA ( n = 4/group). *Indicates statistical significance among groups. For Dnmt1 and Myod1, statistical significance was analyzed by Kruskal–Wallis non-parametric ANOVA H test by rank followed by Pairwise Comparisons test between groups, H(3) = 13.560, p = 0.004 for Dnmt1 , and H(3) = 13.097, p = 0.004 for Myod1 . For Ucp1 , Pgc1α , Myog and Acta1 , statistical significance was analyzed by one-way ANOVA followed by Fisher’s LSD multiple comparisons test: for Ucp1 , F (3,12) = 45.139, p < 0.0001; for Pgc1α , F (3,12) = 51.81, p < 0.0001; for Myog , F (3,12) = 33.178, p < 0.0001; for Acta1 , F (3,12) = 20.045, p < 0.0001. L , M Myod1 ( L ) and BAT-specific gene expression ( M ) in Myod1 -overexpressed BAT1 brown adipocytes treated with PBS or isoproterenol (Iso). n = 6/group. *indicates statistical significance analyzed by Kruskal–Wallis non-parametric ANOVA H test by rank followed by Pairwise Comparisons test between groups. In ( L ), H(3) = 17.613, p = 0.001. In ( M ), for Ucp1 , H(3) = 21.6, p < 0.0001; for Prdm16 , H(3) = 17.553, p = 0.001; for Pgc1α , H(3) = 20.309, p < 0.0001; for Elovl3 , H(3) = 19.62, p < 0.0001; for Cpt1b , H(3) = 18.033, p < 0.0001; for Cidea , H(3) = 18.023, p < 0.0001; for pgc1β , H(3) = 21.367, p < 0.0001; for Acox1 , H(3) = 16.847, p = 0.001; for Cox1 , H(3) = 19.807, p = 0.0009. For ( J – M ), BAT1 cells were differentiated into brown adipocytes as described under Methods. Scramble or targeting siRNAs, or control or Myod1 overexpressing plasmids were transfected into day 4 differentiated BAT1 cells using Amaxa Nucleofector II Electroporator with an Amaxa cell line nucleofector kit L. Cells were harvested 2 days after for pyrosequencing or gene expression analysis. All data are expressed as mean ± SEM.

Article Snippet: K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group).

Techniques: DNA Methylation Assay, Expressing, Marker, Gene Expression, Two Tailed Test, Binding Assay, Transfection, Quantitative RT-PCR, Control

Journal: Nature Communications

Article Title: Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat

doi: 10.1038/s41467-021-27141-7

Figure Lengend Snippet: A Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 adipocytes transfected with lentiviral vectors expressing dCas9-TET1CD along with lentiviral vectors expressing either Myod1 -targeting gRNA or scramble non-targeting gRNA ( n = 4/group). *indicates statistical significance between the two groups by two-tailed unpaired Student’s t -test. B Quantitative PCR analysis of Myod1 and BAT-specific gene expression in BAT1 adipocytes transfected with lentiviral vectors expressing dCas9-TET1CD along with lentiviral vectors expressing either Myod1 -targeting gRNA or scramble non-targeting gRNA ( n = 4/group). *indicates statistical significance between the two groups by two-tailed unpaired Student’s t -test. For ( A , B ), 4-day differentiated BAT brown adipocytes were transfected with lentiviral vectors FUW-dCas9-TET1CD along with lentiviral vectors pgRNA-mCherry encoding either scramble-gRNA or Myod1-targeting gRNA using Amaxa Nucleofector II Electroporator with an Amaxa cell line nucleofector kit L. Cells were harvested 2 days after for pyrosequencing ( A ) or gene expression ( B ) analysis. C , D Body weight ( C ) and Body composition ( D ) in mice with iBAT injection of lentiviruses expressing dCas9-TET1CD plus lentiviruses expressing either targeting Myod1-gRNA-mCherry or non-targeting scramble-gRNA-mCherry ( n = 4/group). *indicates statistical significance between the two groups by two-tailed unpaired Student’s t -test. E – G Methylation levels at Myod1 promoter ( E , n = 8/group), Myogenic marker gene expression (F, n = 7 for dCas9 + scramble, and 5 for dCas9 + Myod1 gRNA), and BAT-specific gene expression ( G , n = 7 for dCas9+scramble, and 6 for dCas9 + Myod1 gRNA) in iBAT of mice with iBAT injection of lentiviruses expressing dCas9-TET1CD plus lentiviruses expressing either targeting Myod1-gRNA-mCherry or non-targeting scramble-gRNA-mCherry. *Indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test in ( E ), ( F ) and ( G ). ( H ) Representative IHC staining of UCP1 (upper panel) and MyHC (lower panel) in iBAT of mice with iBAT injection of lentiviruses expressing dCas9-TET1CD plus lentiviruses expressing either targeting Myod1-gRNA-mCherry or non-targeting scramble-gRNA-mCherry ( n = 3 replicates). For ( C – H ), 3-month-old chow-fed male C57BL/6J mice were bilaterally injected with lentiviruses expressing dCas9-TET1CD plus lentiviruses expressing either targeting Myod1-gRNA-mCherry or non-targeting scramble-gRNA-mCherry into iBAT for up to 2 months. All data are expressed as mean ± SEM.

Article Snippet: K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group).

Techniques: DNA Methylation Assay, Transfection, Expressing, Two Tailed Test, Real-time Polymerase Chain Reaction, Gene Expression, Injection, Methylation, Marker, Immunohistochemistry

Journal: Nature Communications

Article Title: Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat

doi: 10.1038/s41467-021-27141-7

Figure Lengend Snippet: A Comparison of genome-wide alterations in chromatin accessibility landscape assessed by ATAC-seq with the corresponding gene expression assessed by RNA-seq in iBAT of UTXKO and fl/Y mice fed HFD for 12 weeks ( n = 3 replicates per group). B ATAC-seq analysis of chromatin accessibility at Prdm16 gene locus in iBAT of UTXKO and fl/Y mice fed HFD for 12 weeks ( n = 3 replicates per group). C Quantitative RT-PCR analysis of Prdm16 mRNA in iBAT of LFD- or HFD-fed mice ( n = 8/Group). *Indicates statistical significance between the two groups by two-tailed unpaired Student’s t -test. D , E ChIP assay of UTX binding to Prdm16 promoter ( D , n = 4/group) and ChIP assay of H3K27me3 levels at Prdm16 promoter ( E , n = 4/group) in iBAT of LFD- or HFD-fed mice. *Indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test in ( D ) and two-tailed unpaired Student’s t -test in ( E ). F ChIP assay of H3K27me3 levels at Prdm16 promoter in control or Utx knockdown BAT1 brown adipocytes treated with isoproterenol ( n = 4/Group). *Indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test. G – H Pyrosequencing analysis of DNA methylation at Myod1 promoter ( G , n = 6/group) and Myod1 expression ( H , n = 8/group) in BAT1 brown adipocytes transfected with scramble or Utx siRNA. *Indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test in ( G ) and two-tailed unpaired Student’s t -test in ( H ). I , J Pyrosequencing analysis of DNA methylation at Myod1 promoter ( I , n = 4/group) and Myod1 expression ( J , n = 8 for Scramble and 7 for Prdm16 siRNA) in BAT1 brown adipocytes transfected with scramble or Prdm16 siRNA. *Indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test in ( I ) and two-tailed unpaired Student’s t -test in ( J ). K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group). *indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test. All data are expressed as mean ± SEM.

Article Snippet: K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group).

Techniques: Comparison, Genome Wide, Gene Expression, RNA Sequencing, Quantitative RT-PCR, Two Tailed Test, Binding Assay, Control, Knockdown, DNA Methylation Assay, Expressing, Transfection

Journal: Nature Communications

Article Title: Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat

doi: 10.1038/s41467-021-27141-7

Figure Lengend Snippet: A ChIP assay of DNMT1 binding to Myod1 promoter in control or Prdm16 knockdown BAT1 brown adipocytes treated with or without isoproterenol ( n = 4/group). Data are expressed as mean ± SEM. Indicates statistical significance between different treatments analyzed by Kruskal–Wallis non-parametric ANOVA H test by rank followed by Pairwise Comparisons test between groups, H(3) = 9.816, p = 0.020. B Co-IP of DNMT1 and FLAG-PRDM16 in HEK293T cells. Data are representative from two independent experiments. C Co-IP of DNMT1 and various fragments of PRDM16. HA-tagged fragments of PRDM16 were expressed along with full-length DNMT1 in HEK293T cells. Cell lysates were immunoprecipitated with anti-DNMT1 antibodies followed by immunoblotting with HA or DNMT1 antibodies. Color-coded domain architecture of PRDM16 shows a PR/SET domain (PR), an N-terminal zinc-finger domain containing seven C2H2 zinc finger motifs (ZF1), a proline rich domain (PRR), a repression domain (RD), a second C-terminal zinc-finger domain containing three C2H2 zinc finger motifs (ZF2), and an acidic activation domain (AD). Data are representative from two independent experiments. D Co-IP of PRDM16 and various fragments of DNMT1. HA-tagged fragments of DNMT1 were expressed along with full-length PRDM16 in HEK293T cells. Cell lysates were immunoprecipitated with anti-HA antibodies followed by immunoblotting with HA or PRDM16 antibodies. Color-coded domain architecture of DNMT1 shows the N-terminal independently folded domain (NTD), replication foci-targeting sequence (RFTS) domain, a Zn-finger like CXXC motif, two bromo adjacent homology (BAH1 and BAH2) domains, and the catalytic domain. Data are representative from two independent experiments. E DNMT1 protein levels in Prdm16-overexpressed HEK293T cells treated with cycloheximide (CHX) (60 µg/ml) for various time. Data are representative from two independent experiments. F The interaction between PRDM16 and DNMT1 on Myod1 promoter in Prdm16 overexpressed BAT1 brown adipocytes measured by ChIP and Re-ChIP assay via sequential immunoprecipitation of PRDM16 and then DNMT1 ( n = 4/group). Data are expressed as mean ± SEM. *Indicates statistical significance between two groups by Mann–Whitney’s nonparametric U test. G , H Expression of miR-133a , miR133b , miR-206 and miR-1 in iBAT of female D1KO and fl/fl mice fed with a regular chow diet ( G , n = 4 for fl/fl and 6 for D1KO) and in BAT1 brown adipocytes with Myod1 overexpression ( H , n = 6/group). Data are expressed as mean ± SEM. *indicates statistical significance between the two groups by Mann–Whitney’s nonparametric U test in ( G ) and by two-tailed unpaired student’s t -test in ( H ). I , J Dnmt1 and miR-133a expression ( I ) and BAT-specific gene expression ( J ) in BAT1 brown adipocytes transfected with Dnmt1 siRNA, miR-133a inhibitor or both ( J ) ( n = 3/group). Data are expressed as mean ± SEM. *Indicates statistical significance analyzed by one-way ANOVA followed by Fisher’s LSD multiple comparisons test. In ( I ), for Dnm1 expression, F = (3,8) = 4.62, p = 0.037; for miR-133 expression, F (3,8) = 21.370, p < 0.0001. In ( J ), for Ucp1 expression, F = (3,8) = 4.827, p = 0.033; for Prdm16 expression, F = (3,8) = 10.863, p = 0.003; for Pgc1β expression, F (3,8) = 11.213, p = 0.003. K Schematic illustration of the interaction between UTX-regulated PRDM16 and DNMT1 in the maintenance of brown fat identity and suppression of myogenic remodeling in mature brown adipocytes. In brief, in mature brown adipocytes, UTX maintains the persistent demethylation of the repressive mark H3K27me3 at Prdm16 promoter, leading to high expression of Prdm16 ; PRDM16 then recruits the DNA methyltransferase DNMT1 to Myod1 promoter, causing Myod1 promoter hypermethylation, and suppressing Myod1 expression. In addition, reduced Myod1 expression relieves the inhibition on Prdm16 by miR-133, further increasing Prdm16 expression. The interaction between PRDM16 and DNMT1 coordinately serves to maintain brown adipocyte identity while repressing myogenic remodeling in mature brown adipocytes, thus promoting their active brown adipocyte thermogenic function. Suppressing this interaction by HFD feeding induces brown adipocyte-to-myocyte remodeling, which limits brown adipocyte thermogenic capacity and compromises diet-induced thermogenesis, leading to the development of obesity.

Article Snippet: K Pyrosequencing analysis of DNA methylation at Myod1 promoter in BAT1 brown adipocytes transfected with pSPORT6 or pSPORT6 encoding Prdm16 overexpressing plasmids ( n = 4/group).

Techniques: Binding Assay, Control, Knockdown, Co-Immunoprecipitation Assay, Immunoprecipitation, Western Blot, Activation Assay, Sequencing, Expressing, Over Expression, Two Tailed Test, Gene Expression, Transfection, Inhibition

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Example of how some gene regions were chosen for examination in this study on the basis of available RRBS DNA methylation profiles for breast cancer cell lines and normal cell cultures and tissues visualized in the UCSC Genome Browser . a The EN1 gene structure with exons as heavy horizontal bars; b , the aligned CpG islands in the illustrated region.; c , DNA methylation (ENCODE/RRBS/HudsonAlpha) profiles for the indicated cell cultures and normal tissues using an 11-color, semi-continuous scale (see color key) to indicate the average DNA methylation levels at each monitored CpG site; d , aligned transcription results indicating that the non-transformed breast cancer cell line is not transcribing this gene irrespective of its lack of DNA methylation. Paradoxically, normal myoblasts are transcribing it despite some upstream DNA methylation. All data are from ENCODE

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: DNA Methylation Assay, Transformation Assay

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Mean percent methylation by gene and tissue type from the Breast Cancer Care in Chicago study

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation, Control

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Mean percent methylation and 95 % error bars by gene and tissue type for the DNA regions listed in Table . a DNA methylation analysis of samples from the Breast Cancer Care in Chicago study (2005-2008) as determined by our bisulfite pyrosequencing. Control samples (reduction mammoplasty) from unaffected women are represented by green bars, cancer-adjacent, histologically normal samples by blue bars and cancer samples by red bars. b Bioinformatic analysis of DNA methylation of breast cancer samples and paired non-cancerous adjacent samples from The Cancer Genome Atlas (TCGA). Paired non-cancerous adjacent samples are represented by blue bars and cancer samples by red bars. In both panels, promoter sequences are displayed first, followed by upstream sequences, then introns and lastly, DNA repeats

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation, DNA Methylation Assay, Control

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Adjusted differences in mean % methylation comparing adjacent (referent) to cancer tissue, overall and stratified by ER/PR status

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation