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, 9 (4), e1003439

Mouse Oocyte Methylomes at Base Resolution Reveal Genome-Wide Accumulation of non-CpG Methylation and Role of DNA Methyltransferases

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Mouse Oocyte Methylomes at Base Resolution Reveal Genome-Wide Accumulation of non-CpG Methylation and Role of DNA Methyltransferases

Kenjiro Shirane et al. PLoS Genet.

Abstract

DNA methylation is an epigenetic modification that plays a crucial role in normal mammalian development, retrotransposon silencing, and cellular reprogramming. Although methylation mainly occurs on the cytosine in a CG site, non-CG methylation is prevalent in pluripotent stem cells, brain, and oocytes. We previously identified non-CG methylation in several CG-rich regions in mouse germinal vesicle oocytes (GVOs), but the overall distribution of non-CG methylation and the enzymes responsible for this modification are unknown. Using amplification-free whole-genome bisulfite sequencing, which can be used with minute amounts of DNA, we constructed the base-resolution methylome maps of GVOs, non-growing oocytes (NGOs), and mutant GVOs lacking the DNA methyltransferase Dnmt1, Dnmt3a, Dnmt3b, or Dnmt3L. We found that nearly two-thirds of all methylcytosines occur in a non-CG context in GVOs. The distribution of non-CG methylation closely resembled that of CG methylation throughout the genome and showed clear enrichment in gene bodies. Compared to NGOs, GVOs were over four times more methylated at non-CG sites, indicating that non-CG methylation accumulates during oocyte growth. Lack of Dnmt3a or Dnmt3L resulted in a global reduction in both CG and non-CG methylation, showing that non-CG methylation depends on the Dnmt3a-Dnmt3L complex. Dnmt3b was dispensable. Of note, lack of Dnmt1 resulted in a slight decrease in CG methylation, suggesting that this maintenance enzyme plays a role in non-dividing oocytes. Dnmt1 may act on CG sites that remain hemimethylated in the de novo methylation process. Our results provide a basis for understanding the mechanisms and significance of non-CG methylation in mammalian oocytes.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Abundant non-CG methylation in GVOs.
(A) Proportions of mCs in contexts of CG, CHG, and CHH. Data for mCs at positions covered at least 4× on the same strand were used, and those with more than 100× coverage were excluded. (B) Levels of methylation at CG and non-CG sites. Non-CG sites were further divided into different tri- (CHG and CHH) and di-nucleotide sequences (CA, CT, and CC). (C) Bases neighboring the highly methylated (≥30%) non-CG sites.
Figure 2
Figure 2. Relationship between CG methylation and non-CG methylation in GVOs.
(A) Levels of CG methylation and non-CG methylation across the entire chromosome 4 in a non-overlapping sliding window of 50 kb. The two strands were separately analyzed for non-CG methylation. (B) Correlation between the levels of CG methylation and non-CG methylation in 10-kb non-overlapping sliding windows across the genome was indicated using Spearman's rank correlation coefficient. (C) Effect of CG on non-CG methylation at positions immediately upstream and downstream of mC sites. Blue, orange, and gray bars indicate the levels of non-CG methylation around CG sites with at least 10× coverage with methylation levels of 80–100%, 40–60%, and 0–20%, respectively. (D) Levels of CG methylation and non-CG methylation relative to gene structure. The upstream and downstream regions (10-kb each) were split into 10 non-overlapping windows to determine the methylation levels. The intragenic or coding regions were divided into 20 small windows for methylation analysis.
Figure 3
Figure 3. Strand asymmetry in methylation at CG and non-CG sites.
(A) Fractions of CG and CAG/CTG sites showing strand asymmetry in methylation (hemimethylation) in GVOs, Dnmt1-KO, and Dnmt3b-KO. The data were taken from CG and CAG/CTG sites with methylation levels of ≥70% and ≥40%, respectively, on at least one strand, with a read depth of at least 10× for both strands (left). Bar charts show the hemimethylated fractions (right). Statistical differences in methylation between the strands were calculated using Fisher's exact test (p<0.05). Note that most CAG/CTG sites are hemimethylated in all samples and that CG sites show increased hemimethylation in Dnmt1-KO. (B) CG sites hemimethylated in Dnmt1-KO but not in GVOs. Dnmt1-KO demonstrated an increase in hemimethylated CG sites (orange, left), most of which were fully methylated in GVOs.
Figure 4
Figure 4. Comparison of the methylomes in NGOs, GVOs, and Dnmt-KO.
(A) Overall levels of CG methylation and non-CG methylation in NGOs, GVOs, Dnmt1-KO, Dnmt3a-KO, Dnmt3b-KO, and Dnmt3L-KO. The data were not corrected for the bisulfite non-conversion rate (0.43–0.87, see Table 1). Thus, NGOs, Dnmt3a-KO, and Dmt3L-KO may actually have no or very little non-CG methylation. (B) Profiles of non-CG methylation along chromosome 4 determined using a non-overlapping sliding window of 50 kb in all samples. The data for the two strands are shown separately above and below the horizontal line.
Figure 5
Figure 5. CG and non-CG methylation levels in different genomic elements in NGOs, GVOs, Dnmt3a-KO, and Dnmt3L-KO.
(A) Levels of CG methylation and non-CG methylation in intragenic and intergenic regions. Intragenic regions are further divided into 5′UTRs, exons, introns, and 3′UTRs according to the RefSeq annotations. (B) Levels of CG methylation and non-CG methylation in different types of repetitive elements. Annotation for repetitive elements was obtained from the UCSC Genome Browser.

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Grant support

This work was supported in part by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (MEXT) (grant 20062010 to HS, 222228004 and S0801025 to TK), Kyushu University Interdisciplinary Programs in Education and Projects in Research Development (P&P) to HS, and the Research Program of Innovative Cell Biology by Innovative Technology (Cell Innovation) to TI from MEXT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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