18 research outputs found
The chromatin remodeling enzyme Chd4 regulates genome architecture in the mouse brain
The mechanisms underlying gene regulation and genome architecture remain poorly understood. Here, the authors investigate the role of chromatin remodelling enzyme Chd4 in granule neurons of the mouse cerebellum and find that conditional knockout of Chd4 preferentially activates enhancers and modulates genome architecture at a genome-wide level
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Genome-wide comparison of DNA hydroxymethylation in mouse embryonic stem cells and neural progenitor cells by a new comparative hMeDIP-seq method
The genome-wide distribution patterns of the ‘6th base’ 5-hydroxymethylcytosine (5hmC) in many tissues and cells have recently been revealed by hydroxymethylated DNA immunoprecipitation (hMeDIP) followed by high throughput sequencing or tiling arrays. However, it has been challenging to directly compare different data sets and samples using data generated by this method. Here, we report a new comparative hMeDIP-seq method, which involves barcoding different input DNA samples at the start and then performing hMeDIP-seq for multiple samples in one hMeDIP reaction. This approach extends the barcode technology from simply multiplexing the DNA deep sequencing outcome and provides significant advantages for quantitative control of all experimental steps, from unbiased hMeDIP to deep sequencing data analysis. Using this improved method, we profiled and compared the DNA hydroxymethylomes of mouse ES cells (ESCs) and mouse ESC-derived neural progenitor cells (NPCs). We identified differentially hydroxymethylated regions (DHMRs) between ESCs and NPCs and uncovered an intricate relationship between the alteration of DNA hydroxymethylation and changes in gene expression during neural lineage commitment of ESCs. Presumably, the DHMRs between ESCs and NPCs uncovered by this approach may provide new insight into the function of 5hmC in gene regulation and neural differentiation. Thus, this newly developed comparative hMeDIP-seq method provides a cost-effective and user-friendly strategy for direct genome-wide comparison of DNA hydroxymethylation across multiple samples, lending significant biological, physiological and clinical implications
Genome-Wide Mapping of 5mC and 5hmC Identified Differentially Modified Genomic Regions in Late-Onset Severe Preeclampsia: A Pilot Study
<div><p>Preeclampsia (PE) is a leading cause of perinatal morbidity and mortality. However, as a common form of PE, the etiology of late-onset PE is elusive. We analyzed 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) levels in the placentas of late-onset severe PE patients (n = 4) and normal controls (n = 4) using a (hydroxy)methylated DNA immunoprecipitation approach combined with deep sequencing ([h]MeDIP-seq), and the results were verified by (h)MeDIP-qPCR. The most significant differentially methylated regions (DMRs) were verified by MassARRAY EppiTYPER in an enlarged sample size (n = 20). Bioinformatics analysis identified 714 peaks of 5mC that were associated with 403 genes and 119 peaks of 5hmC that were associated with 61 genes, thus showing significant differences between the PE patients and the controls (>2-fold, <i>p</i><0.05). Further, only one gene, <i>PTPRN2</i>, had both 5mC and 5hmC changes in patients. The ErbB signaling pathway was enriched in those 403 genes that had significantly different5mC level between the groups. This genome-wide mapping of 5mC and 5hmC in late-onset severe PE and normal controls demonstrates that both 5mC and 5hmC play epigenetic roles in the regulation of the disease, but work independently. We reveal the genome-wide mapping of DNA methylation and DNA hydroxymethylation in late-onset PE placentas for the first time, and the identified ErbB signaling pathway and the gene <i>PTPRN2</i> may be relevant to the epigenetic pathogenesis of late-onset PE.</p></div
MeDIP-qPCR (A) and hMeDIP-qPCR (B) validations (mean values±SEM, n = 4 per group, <i>p</i><0.05) of representative DMRs and DHMRs.
<p>(A) MeDIP-qPCR validation of <i>ACAP2</i>, <i>CLIC6</i>, <i>GATA4</i>, <i>PCDH9</i> and <i>PTPRN2</i>-A. (B)hMeDIP-qPCR validation of <i>CCDC149</i>, <i>PTPRN2</i>-B and <i>RBFOX1</i>. <i>ACAP2</i>:<i>p</i> = 0.0032; <i>CLIC6</i>: <i>p</i> = 0.0235; <i>GATA4</i>: <i>p</i> = 0.0429;<i>PCDH9</i>: <i>p</i> = 0.0081; <i>PTPRN2-A</i>: <i>p</i> = 0.0216; <i>CCDC149</i>: <i>p</i> = 0.0068; <i>PTPRN2-B</i>: <i>p</i> = 0.0018; <i>RBFOX1</i>: <i>p</i> = 0.0250.</p
MA plot of Case-Control contrast of (A) 5mC peaks and (B) 5hmC peaks normalized with tag density.
<p>The X axis indicates the normalized mean and the Y axis indicates the log2-fold change. Red is used to indicate significantly differently expressed observations (at least 2-fold density changes and <i>p</i>-value<0.05). The blue dots show no differential expression between the two groups.</p
Validation of the methylation status of candidate DMRs between the late-onset severe PE group and the normal group by MassARRAY EpiTYPER.
<p>(A) The methylation level of the CpG sites within <i>GATA4</i> amplicon. (B) The CpG methylation level sites within the <i>PCDH9</i> amplicon. (C) The methylation level of the CpG sites within <i>ACAP2</i> amplicon. (D) The CpG methylation sites within <i>CLIC6</i> amplicon. Data are shown as the means±SEM, n = 20 per group, *<i>p</i><0.05, **<i>p</i><0.01. <i>GATA4</i> amplicon: CpG_1, <i>p</i> = 0.0093; CpG_2, <i>p</i> = 0.0150; CpG_3, <i>p</i> = 0.5993; CpG_4, <i>p</i> = 0.0015; CpG_5, <i>p</i> = 0.9738; CpG_6, <i>p</i> = 0.0481; CpG_7.8, <i>p</i> = 0.0377; CpG_9, <i>p</i> = 0.0661.<i>PCDH9</i> amplicon: CpG_2, <i>p</i> = 0.6177; CpG_3, <i>p</i> = 0.1831; CpG_4, <i>p</i> = 0.0294; CpG_6, <i>p</i> = 0.0265; CpG_8, <i>p</i> = 0.0529; CpG_10, <i>p</i> = 0.8818; CpG_13, <i>p</i> = 0.0158. <i>ACAP2</i> amplicon: CpG_1, <i>p</i> = 0.0316; CpG_4, <i>p</i> = 0.0349; CpG_7.8, <i>p</i> = 0.3524. <i>CLIC6</i> amplicon: CpG_99, <i>p</i> = 0.0446; CpG_100, <i>p</i> = 0.0424; CpG_101.102, <i>p</i> = 0.5504; CpG_103, <i>p</i> = 0.7697; CpG_105.106, <i>p</i> = 0.0310; CpG_108.109, <i>p</i> = 1.0000; CpG_110.111, <i>p</i> = 0.0084.</p
Gene ontology groups displaying the significant GO-terms of DMRs and DHMRs (p<0.05).
<p>(A)The significant GO-terms of DMRs between the groups. (B)The significant GO-terms of DHMRs between the groups.</p
Genome-wide mapping of 5mC and 5hmC in placentas of late-onset severe PE and normal pregnant women.
<p>(A and C) Normalized DMR (A) and DHMR(C) tag density distribution across the gene body. Each gene body was normalized to 0%-100%. Normalized Tag density is plotted from 20% of upstream of TSSs to 20% downstream of TSSs(Transcription Start Sites). (B and D) Normalized DMR (B) and DHMR (D) tag density distribution at gene promoters. -5 kb to +5 kb relative to TSSs is shown.</p
Validation of the methylation status of <i>PTPRN2</i> in the two groups by MassARRAY EpiTYPER.
<p>(A)The overall methylation levels are displayed within amplicon A and amplicon B. (B,C) The average methylation of the CpG units of amplicon A and amplicon B are presented for late-onset severe PE and normal patients. Data are presented as means±SEM, n = 20 per group, *<i>p</i><0.05,**<i>p</i><0.01.A: Amplicon A, <i>p</i> = 0.0033;Amplicon B, <i>p</i> = 0.0017.B: Amplicon A: CpG_1, <i>p</i> = 0.0420; CpG_3, <i>p</i> = 0.4820; CpG_4, <i>p</i> = 0.1296; CpG_6, <i>p</i> = 0.2957; CpG_7, <i>p</i> = 0.6410; CpG_9, <i>p</i> = 0.0475, CpG_11, <i>p</i> = 0.0177; CpG_12.13, <i>p</i> = 0.0003. C: Amplicon B: CpG_1.2, <i>p</i> = 0.0134, CpG_3, <i>p</i> = 0.0210, CpG_4.5, <i>p</i> = 0.0185; CpG_6, <i>p</i> = 0.0163; CpG_7, <i>p</i> = 0.0019; CpG_8, <i>p</i> = 0.0001; CpG_9, <i>p</i> = 0.1268; CpG_10, <i>p</i> = 0.0192; CpG_11, <i>p</i> = 0.0583.</p