Genome-wide comparison of DNA hydroxymethylation in mouse embryonic stem cells and neural progenitor cells by a new comparative hMeDIP-seq method - PubMed (original) (raw)
Genome-wide comparison of DNA hydroxymethylation in mouse embryonic stem cells and neural progenitor cells by a new comparative hMeDIP-seq method
Li Tan et al. Nucleic Acids Res. 2013 Apr.
Abstract
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.
Figures
Figure 1.
Schematic diagram of the comparative hMeDIP-seq method.
Figure 2.
Differential Tet1/2/3 gene expression and global 5hmC levels in ESCs and NPCs. (a) RT-qPCR analysis of Tet1, Tet2 and Tet3 mRNA levels in ESCs and NPCs (mean values ± SD, n = 3). (b) Immunofluorescence analysis of 5hmC levels in ESCs and NPCs. Bar: 50 μm. (c) Dot blot analysis of the global 5hmC levels in the gDNA of ESCs and ESC-derived NPCs. One hundred fifty nanogram gDNA for each dot. (d) The relative 5hmC signal of dot blot and comparative hMeDIP-seq in ESCs and NPCs. *The ratio of hMeDIP/Input reads numbers in ESCs was set as 100%. (e) Distribution of 5hmC in TSS ± 5 kb and gene body regions in ESCs. (f) Distribution of 5hmC in TSS ± 5 kb and gene body regions in NPCs.
Figure 3.
Correlation between DNA hydroxymethylation and gene expression in ESCs and NPCs. (a) Genes were separated into five groups (from high to low) according to their expression levels in ESCs: top 20%; 20–40%; 40–60%; 60–80%; bottom 20%. The average 5hmC densities of the five groups of genes were plotted across the promoter or gene body regions. Left: TSS ± 5 kb regions. Right: gene body regions. (b) Genes were also separated into five groups according to their expression levels in NPCs. The average 5hmC densities of the five groups of genes were plotted across the promoter or gene body regions. Left: TSS ± 5 kb regions. Right: gene body regions. (c) Genes were classified into two groups with respect to the presence (5hmC+) or absence (5hmC−) of 5hmC peak(s) at their promoters (TSS ± 1 kb) or in gene body regions (from TSS + 1 kb to TES) in ESCs. Gene expression levels were compared between ‘5hmC+’ and ‘5hmC−’ groups. Left: promoter, P = 0; Right: gene body region, P = 1.08358e-13. *P < 0.01. (d) Genes were classified into two groups with respect to the presence (5hmC+) or absence (5hmC−) of 5hmC peak(s) at their promoters (TSS ± 1 kb) or in gene body regions (from TSS + 1 kb to TES) in NPCs. Gene expression levels were compared between ‘5hmC+’ and ‘5hmC−’ groups. Left: promoter, P = 0.0001; Right: gene body region, P = 0. *P < 0.01.
Figure 4.
Identification of DHMRs between ESCs and NPCs. (a) All 5hmC peaks called from the pooled hMeDIP-seq data were separated into three groups: down-regulated (log2 5hmC density ratio ≤ −1), up-regulated (log2 5hmC density ratio ≥ 1) and no significant change (−1 < log2 5hmC density ratio < 1) 5hmC peaks. (b–e) UCSC genome (mmp9) browser screen shots, hMeDIP-qPCR and glucMS-qPCR validation (mean values ± SD, n = 3) of two representative DHMRs with de-hydroxymethylation (Ankrd23 and Hist1h2aa) and two representative DHMRs with de novo hydroxymethylation (Ftl1 and Irf2bp2). (f) Percentages of pooled 5hmC peaks, ‘gain of 5hmC’ peaks and ‘loss of 5hmC’ peaks located at different genomic features.
Figure 5.
Relationship between the changes in DNA hydroxymethylation and gene expression during neural differentiation. (a) Down- and up-regulated genes during neural differentiation were sorted (NPC versus ESC, log2 mRNA expression ratio ≤ −1 or ≥1). The changes in 5hmC peak density at promoters (TSS ± 1 kb) in down- and up-regulated genes were compared during neural differentiation (P = 0). *P < 0.01. (b) The changes in 5hmC peak density at gene body regions (from TSS + 1 kb to TES) in down- and up-regulated genes were compared during neural differentiation (P = 0). *P < 0.01. (c) Dot plotting of the alteration in 5hmC peak density at promoters and the gene expression change during neural differentiation. The changes in 5hmC peak density at promoters (TSS ± 1 kb) were plotted on the y-axis and the corresponding gene expression changes were plotted on the _x_-axis. R2 = 0.0048. (d) Dot plotting of the alteration in 5hmC peak density in gene body regions and the gene expression change during neural differentiation. The changes in 5hmC peak density in gene body regions (from TSS + 1 kb to TES) were plotted on the _y_-axis and the corresponding gene expression changes were plotted on the _x_-axis. R2 = 0.0059.
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