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. Author manuscript; available in PMC: 2017 Oct 13.
Published in final edited form as: Cell Rep. 2016 Apr 14;15(4):748–760. doi: 10.1016/j.celrep.2016.03.060

Functional characterization of DNA methylation in the oligodendrocyte lineage

Sarah Moyon 1,11, Jimmy L Huynh 1,2,11, Dipankar Dutta 3, Fan Zhang 1, Dan Ma 5, Seungyeul Yoo 2, Rebecca Lawrence 1, Michael Wegner 6, Gareth R John 3,4, Ben Emery 7, Catherine Lubetzki 8, Robin J M Franklin 5, Guoping Fan 9, Jun Zhu 2, Jeffrey L Dupree 10, Patrizia Casaccia 1,2,3,4
PMCID: PMC5063656  NIHMSID: NIHMS772372  PMID: 27149841

Summary

Oligodendrocytes derive from progenitors (OPC) through the interplay of epigenomic and transcriptional events. By integrating high-resolution methylomics, RNA-sequencing and multiple transgenic lines, this study defines the role of DNMT1 in developmental myelination. We detected hypermethylation of genes related to cell cycle and neurogenesis during differentiation of OPC and yet, genetic ablation of Dnmt1 resulted in inefficient OPC expansion and severe hypomyelination associated with ataxia and tremors in mice. This phenotype was not caused by lineage switch or massive apoptosis, but was characterized by a profound defect of differentiation, associated with changes in exon-skipping and intron-retention splicing events and by the activation of an endoplasmic reticulum stress response. Therefore, loss of Dnmt1 in OPC is not sufficient to induce a lineage switch, but acts as an important determinant of the coordination between RNA splicing and protein synthesis, necessary for myelin formation.

Introduction

Brain development requires the integration of cell lineage selection and cell number regulation. This is achieved by coordinating cell proliferation with lineage identity. DNA methylation is a well-recognized epigenetic modification that is carefully regulated during cell division and guarantees faithful transmission of information to the daughter cells. This enzymatic activity is modulated by three proteins: DNMT1 (maintenance DNA methyltransferase commonly associated with faithful transmission of genomic information from mother to daughter cells during cell division), DNMT3A and DNMT3B (de novo methyltransferases methylating specific cytosines during development). The activity of these enzymes in the brain is higher than any other adult tissue (Ono et al., 1993; Tawa et al., 1990), highlighting the importance of DNMTs in neural development (Lister et al., 2013; Smith and Meissner, 2013). This study addresses the role of DNA methylation in developmental myelination.

Genetic loss of Dnmt1 is lethal in mammals (Li et al., 1992) and zebrafish (Jacob et al., 2015), because rapidly proliferating cells need to retain a stable epigenetic signature and are eliminated by apoptosis if compromised (Jackson-Grusby et al., 2001; Unterberger et al., 2006). An example is the apoptotic elimination of neural stem cells and mitotic neuroblasts lacking Dnmt1 (Fan et al., 2001; Hutnick et al., 2009; Milutinovic et al., 2003). In contrast, inhibiting DNA methylation in astrocytes or Schwann cells is associated with precocious onset of differentiation, due to the unmasking of critical transcriptional regulatory sites in differentiation genes (Fan et al., 2005; Takizawa et al., 2001; Varela-Rey et al., 2014). In this study, we show that ablation of Dnmt1 in the oligodendrocyte lineage does not result in apoptosis or precocious myelination, but causes growth arrest of oligodendrocyte progenitors (OPC) and a severely disrupted patterns of alternative splicing with activation of an endoplasmic reticulum (ER) stress response, which precludes differentiation and results in severe and clinically symptomatic hypomyelination.

Results

Dynamic DNA methylation and DNA methyltransferases expression during oligodendrocyte differentiation

DNA methylation in proliferating progenitors has been shown to prevent untimely differentiation and to guarantee faithful transmission of genomic information from mother to daughter cells during replication (Fan et al., 2005; Probst et al., 2009; Sen et al., 2010; Varela-Rey et al., 2014). To begin characterizing the role of DNA methylation in oligodendrocyte lineage cells, we quantified 5-methylcytosine (5-mC) in developing white matter tracts during embryonic and postnatal development. Quantification of the percentage of OLIG2+ OPC expressing 5-mC (Figure 1A) revealed a greater proportion of highly methylated cells at late developmental time points (Figure 1B). A similar pattern was detected in cultured OPC during differentiation into oligodendrocytes (OL) (Figures 1C and 1D). To further understand the role of DNA methylation in OPC, we also evaluated the transcript (Figures 1E and 1F) and protein (Figure 1G) levels of the maintenance DNA methyltransferase Dnmt1 and the de novo methyltransferases Dnmt3a and Dnmt3b at two stages of development. While Dnmt1 levels decreased with differentiation, Dnmt3a levels did not significantly change and Dnmt3b levels were undetectable at either stage (data not shown).

Figure 1. Increased levels of DNA methylation and dynamic expression of DNA methyltransferases during oligodendrocyte development.

Figure 1

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(A) Immunostaining of DNA methylation using 5-mC antibody (green) and OLIG2 (red) in spinal cord sections revealed the presence of cells with low, medium and high 5-mC levels of staining intensity. (B) Quantification of 5-mC immunoreactive OLIG2+ cells in mouse developing spinal cord white matter at E17-18, P1, and P21. (C) Left: protocol for culturing proliferating OPC (PDGF + FGF) and inducing differentiation into OL (T3). Right: dot blot analysis for 5-mC and dsDNA as control. (D) Quantification of 5-mC levels relative to total dsDNA in OPC and OL. (E) Scheme of fluorescence-activated cell sorting of P2 PDGFRα-GFP OPC and P18 PLP-GFP OL. (F) Dnmt1 and Dnmt3a mRNA levels in sorted OPC and OL relative to OPC. (G) Representative image of nuclear DNMT1 and DNMT3A (green) immunostaining in OLIG2+ OPC and CC1+ OL (red). Scale bar = 10 μm. Data represent mean ± SEM. *p < 0.05 (ANOVA and Student's t-test).

To generate a genome-wide map of the DNA methylation landscape during the transition from OPC to OL, we used fluorescence-activated cell sorting (FACS) of brains from transgenic mice expressing GFP driven by oligodendrocyte lineage-specific promoters at postnatal day 2 (P2; Pdgfrα-GFP) and 18 (P18; Plp1-GFP) (Figure 2A). We previously characterized the Pdgfrα-GFP sorted OPC as expressing progenitor markers (e.g., Cspg4 and Pdgfrα) and not expressing myelin genes (e.g., Mog and Mag), while Plp1-GFP sorted OL were characterized by the expression of differentiation genes and absence of progenitor markers (Moyon et al., 2015). DNA methylation mapping was performed by enhanced reduced representation bisulfite sequencing (ERRBS), which combined restriction enzyme digestion (i.e. MspI) of genomic DNA with bisulfite sequencing, and provided single-base resolution and highly quantitative data on the methylation state of cytosines throughout the genome. The mean coverage was 1.47 million individual CpGs in the mouse genome (Table S1), with the majority detected at gene promoters (Figure S1C). Among those, we identified 62,807 differentially methylated CpGs as OPC differentiate (q-value < 0.01) with 29,707 hypomethylated and 33,100 hypermethylated CpGs. Regions containing at least 2 CpGs with a minimum difference of 10% between the two stages of differentiation were classified as differentially methylated regions (DMRs). This revealed clustering of CpGs into 7,386 DMRs characterizing the differentiation of OPC, with 2,385 hypermethylated regions (with an average methylation difference of 22.2% ± 8.5%) (Figure S1B). Biological replicates confirmed the reproducibility of the methylation state (Pearson's r > 0.9), while comparisons of DMRs in samples obtained at the two developmental time points displayed great disparity (Figure S1A), further supporting the large shift in the DNA methylome during differentiation. To determine the relationship between DNA methylation and transcription we performed RNA sequencing (RNA-Seq) on the same FACS-isolated populations (Table S2 and Figure 2). Separate clustering of the samples isolated at distinct time points, and differential expression of stage specific markers (Pdgfrα: -8.2 fold change, q-value = 5.5 × 10-220; Cspg4: -7.0 fold change, q-value = 4.5 × 10-169; Plp1: 2.3 fold change, q-value = 6.4 × 10-3; Mog: 4.9 fold change, q-value = 2.09 × 10-34; Mag: 2.4 fold change, q-value = 2.6 × 10-26) between the two populations confirmed the selectivity of our cell sorting (Figure S2A). The analysis revealed 3,204 upregulated (average fold-change = 3.6 ± 1.8) and 3,547 downregulated transcripts (average fold-change = 5.6 ± 2.4) during differentiation. Upregulated genes included GO categories related to lipid metabolism and axon ensheathment, while downregulated categories included cell cycle, cell migration and neuronal differentiation (Figures S2B and S2C). The overwhelming overlap (p < 10-244) of our dataset and the published in vitro RNA-Seq study (Zhang et al., 2014), further strengthened the validity of our analysis (Figure S2D).

Figure 2. Negative correlation between DNA methylation and transcript levels in oligodendroglial lineage cells.

Figure 2

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(A) Scheme of experimental approach used for RNA-sequencing and high resolution methylomics. (B) Quadrant plot of differentially methylated regions (DMRs) at gene promoters and differentially expressed genes (OL vs. OPC). X-axis refers to DNA methylation differences during differentiation. Y-axis indicates log2 fold-change of transcript levels. Horizontal (10% difference) and vertical (2-fold change) dashed lines identify four quadrants: (I) hypomethylated and upregulated genes (red circle), (II) hypomethylated and downregulated (black square), (III) hypermethylated and upregulated (black diamond) and (IV) hypermethylated and downregulated (green triangle). Colored genes in quadrants I and IV are characterized by statistically significant differences in methylation and transcript levels (p value indicated in each quadrant).. (C-D) Top gene ontology categories for hypomethylated and upregulated genes (red, C) and for hypermethylated and downregulated (green, D) genes. (E-F) The bar graphs represent statistically significant DNA methylation levels of individual CpGs (blue boxes over gene structures) in OPC (white bars) and OL (gray bars). Note the significantly decreased methylation of CpGs in myelin genes (E) and increased methylation in cell cycle and neuronal genes (F) during differentiation. Data are mean ± SEM. *p < 0.05, **p < 0.01 and ***p < 0.005 (False Discovery Rate). See also Figures S1 and S2.

To characterize the transcriptional consequences of genome-wide distribution of DNA methylation, we overlapped the differential transcript expression with DNA methylation differences at promoters and represented the analysis as quadrant plot, based on statistical power (Figure 2B). The most statistically significant differences (based on number of events and difference at the two developmental stages) were identified in two quadrants (I and IV). The highest significance was detected in quadrant IV (p=8.1×10-19) which defined hypermethylated genes with decreased expression during differentiation and included genes related to neuronal lineage (e.g., Pax6, Plxnb2, Camk1, Ephb2) and proliferation (e.g., Cdc6, Meis2) (Figures 2D and 2F). Quadrant I was also significant (p=2.5×10-7) and included hypomethylated genes with increased expression during differentiation, such as: lipid enzymes, myelin components (e.g., Mog, Mag) and enzymes enriched in the myelin compartment such as carbonic anhydrase II (Car2), as well as molecules associated with the differentiated state, such as the G-protein coupled receptor 37 (Gpr37) (Figures 2C and 2E). The other two quadrants (hypomethylated genes with decreased expression or hypermethylated genes with increased expression during differentiation) did not reach statistical significance and therefore were not pursued any further. Taken together these data highlight the relevance of DNA methylation in OPC for silencing genes related to cell proliferation and neuronal lineage.

Ablation of Dnmt1, but not Dnmt3a, in oligodendrocyte progenitors during development impairs differentiation and results in wide-spread myelination deficits

To define the functional role of DNA methylation in the oligodendrocyte lineage in vivo, we crossed the Dnmt1fl/fl and Dnmt3afl/fl lines with Olig1-cre to target embryonic progenitors and with the Cnp-cre line to target later stages of oligodendrocyte development. Littermates lacking cre expression were used as controls. The cell-specificity of gene ablation was confirmed by double immunofluorescence, using antibodies specific for DNMT1 (Figure 3A) or DNMT3A (Figure 3B) and those specific for cell markers. Lack of DNMT1 or DNMT3A immunoreactivity in OLIG2+ cells, but not in GFAP+ or NeuN+ cells, indicated lineage-selective ablation (Figures 3A and 3B). Both Olig1cre/+;Dnmt1fl/fl and Olig1cre/+;Dnmt3afl/fl mice appeared normal at birth; however by postnatal day 9, only the Olig1cre/+;Dnmt1fl/fl mice developed tremors and ataxia (Movie S1), eventually leading to decreased survival by the third postnatal week (Figure 3C). Both Olig1cre/+;Dnmt3afl/fl and Cnpcre/+;Dnmt1fl/fl mice showed no obvious phenotype (Figure 3C). Consistent with these observations, MBP staining of spinal cord sections at postnatal day 16 revealed a dramatic hypomyelination only in the Olig1cre/+;Dnmt1fl/fl mice (Figure 3D). Gross examination of Olig1cre/+;Dnmt1fl/fl mice at postnatal day 14 revealed only minor differences in body size (Figure 3E), but clear signs of hypomyelination of the spinal cord (see translucent spinal cord on Figure 3F) and brain stem (Figure 3G), which were confirmed by electron microscopy (Figure 3H and S3).

Figure 3. Conditional ablation of DNA methyltransferases in oligodendrocyte lineage cells results in widespread hypomyelination in the central nervous system of Olig1cre/+;Dnmt1fl/fl mice.

Figure 3

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(A-B) Double immunostaining of P16 spinal cord with antibodies for DNMT1 (red, A) or DNMT3A (red, B) and the cell-specific markers (green): OLIG2 for OL, GFAP for astrocytes, and NeuN for neurons. Note the absence of DNMT1 (A) or DNMT3A (B) in the oligodendrocyte lineage. Scale bar = 10 μm. (C) Kaplan–Meier survival curves for Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, Olig1+/+;Dnmt3afl/fl and Olig1cre/+;Dnmt3afl/fl mice, and Cnp+/+;Dnmt1fl/fl and Cnpcre/+;Dnmt1fl/fl mice. (D) Representative P16 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, Olig1+/+;Dnmt3afl/fl and Olig1cre/+;Dnmt3afl/fl mice, and Cnp+/+;Dnmt1fl/fl and Cnpcre/+;Dnmt1fl/fl mice stained for MBP (green) and OLIG2 (red). Scale bar = 100 μm. (E–G) Gross analysis of P14 Olig1cre/+;Dnmt1fl/fl mutants revealed minimal differences in body size compared to controls (E) and complete absence of white matter in spinal cord (F) and brain stem (circle in G). Scale bars = 600 μm (E) and 200 μm (F-G). (H) Electron micrograph analysis of P16 spinal cord and corpus callosum sections reveal severe hypomyelination in the Olig1cre/+;Dnmt1fl/fl mice. Scale bar = 1 μm. See also Figure S3 and Movie S1.

The hypomyelinated phenotype detected in Dnmt1 mutants is not attributable to fate-linage switch

Given the early activity of Olig1-cre at the pMN domain (Zhou and Anderson, 2002) and based on the detection of increased methylation and silencing of neuronal lineage related genes during OPC differentiation, it was important to determine whether the defective myelination phenotype detected in Olig1cre/+;Dnmt1fl/fl mice could be attributed to impaired specification. To address this question, we used two approaches. First, we processed spinal cord sections from mutants and control siblings at embryonic day 12.5 for immunohistochemistry using antibodies specific for motor neurons (i.e., MNX1), as well as ventral (i.e., NKX2.2) and dorsal (i.e., PAX6) markers. Quantification of immunoreactive cells revealed no differences in the number of OLIG2+ at the pMN domain or MNX1+ at the ventrolateral motor neuron domain (Figure 4A and 4B). The distribution and number of NKX2.2+ (Figure 4C) and PAX6+ cells (Figure 4D) was similar in mice of the two genotypes, and the boundaries with the OLIG2+ domain were preserved. We then conducted a fate mapping analysis crossing the ROSA26-loxSTOP-lox-TdTomato reporter line with the Olig1cre/+;Dnmt1fl/fl or Olig1cre/+;Dnmt1+/+ mice and stained spinal cord sections at postnatal day 14 with neuronal (NeuN) or astrocytic (GFAP) markers (Figure 4E and 4F). Only very few cells were identified by the reporter expression and staining for NeuN or GFAP, both in controls and mutants (NeuN controls = 2.5% ± 0.3%, mutants = 3.2% ± 1.0%; GFAP controls = 3.0% ± 0.4%, mutants = 3.7% ± 0.6%), suggesting that only very few OPC differentiated in neurons or astrocytes in the absence of Dnmt1.

Figure 4. Normal cell specification in Olig1cre/+;Dnmt1fl/fl spinal cord.

Figure 4

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(A) Representative confocal image of E12.5 spinal cord sections from Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and MNX1 (green) and quantification of MNX1+ cells in control (white bars) and mutants (gray bars). (B) Quantification of OLIG2+ cells in controls and mutants. (C) Representative E12.5 spinal cord sections stained for OLIG2 (red) and NKX2.2 (green) and relative quantification in controls and mutants. (D) Representative E12.5 spinal cord sections, stained for OLIG2 (red) and PAX6 (green) and relative quantification in controls and mutants. (E-F) Representative P14 spinal cord sections of RosaTdTomato;Olig1cre/+;Dnmt1+/+ and RosaTdTomato;Olig1cre/+;Dnmt1fl/fl mice, stained for NeuN (E) or GFAP (F) and percentage of NeuN+/TdTomato+ (E) or GFAP+/TdTomato+ (F) cells among the TdTomato+ cells. Scale bar = 150μm. Data are mean ± SEM. *p < 0.05 (ANOVA and Student's t-test).

Dnmt1 dependent hypomyelination consequent to defective differentiation

To define the potential cause of the hypomyelinating phenotype, we conducted a quantitative immunohistochemical study of the developing spinal cord from embryonic day 16.5 to postnatal day 16 using antibodies specific for OLIG2 and PDGFRα to label OPC, CC1 to label newly generated oligodendrocytes and MBP to label myelinating cells. While a similar number of progenitors was detected in the embryonic spinal cord, a 27% reduction in the number of OPCs was detected in the mutant spinal cords (Figure 5A) and brains (Figure S4A) starting from postnatal day 2. A greater reduction was observed for newly generated OL (Figure 5B and S4B) and an even more dramatic impairment was detected when quantifying myelinating MBP+ cells (Figure 5C and S4C), which represent a later stage of differentiation. The cell-autonomous nature of this defect was further validated in vitro which revealed defective differentiation of mutant OPC compared to controls (Figure 5D). Together these data support the critical importance of DNMT1 in the oligodendrocyte lineage to coordinate the late stages of differentiation into myelin forming cells.

Figure 5. Impaired oligodendrocyte progenitor cell differentiation in Olig1cre/+;Dnmt1fl/fl mice.

Figure 5

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(A) Representative P16 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and PDGFRα (green) and quantification of PDGFRα+/OLIG2+ cells at indicated time points. Scale bar =40μm. (B) Representative image of P16 spinal cord sections stained for OLIG2 (red) and CC1 (green) and relative quantification. Scale bar =100μm. (C) Representative image of P16 spinal cord sections of mutants and controls, stained for OLIG2 (red) and MBP (green) and relative quantification, showing extensive hypo-myelination. Scale bar =100μm. (D) Schematic of immunopanning from Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl P6 cortex to assess in vitro differentiation, and quantification of the number of CC1+/OLIG2+ and MBP+/OLIG2+ cells in T3 medium. Data are mean ± SEM. *p < 0.05, **p < 0.01 and ***p < 0.005 (ANOVA). See also Figure S4.

To begin understanding the mechanisms underlying the very modest decrease in progenitor numbers and the almost complete absence of myelin detected by electron microscopy, we processed spinal cord sections from controls and mutants at multiple developmental time points for TUNEL (data not shown) or for the presence of active cleaved Caspase 3. An accurate assessment of apoptotic nuclei is difficult in vivo, due to rapid clearance and despite the detection towards modestly increased apoptosis at postnatal day 9, the measurable differences did not reach statistical significance (Figure 6A). An alternative explanation for the reduced OPC number was impaired proliferation. Co-labeling of OPC with antibodies specific for OLIG2 or PDGFRα and markers of proliferation (i.e., Ki67) or of mitotic activity (i.e., phosphorylated histone H3) (Figures 6B and 6D) identified a clear proliferation defect in mutants. This result was cell-intrinsic, as it was also detected in cultured OPC (Figures 6C and 6E). We concluded that the lower number of OPC in the developing spinal cord of mutant mice compared to age-matched controls could, at least in part, be attributed to defective expansion of the progenitor pool in the absence of Dnmt1. Since this phenotype was associated with the detection of concurrent hypomethylation and increased transcripts for genes modulating mitosis (e.g., Meis2, Cdc6) together with those inhibiting the cell cycle (e.g., Cdkn1a), and with the downregulation of positive regulators of proliferation (e.g., Pdgfrα, Rbl2, Mcm7) (Figure 6F and 6G), we reasoned that OPC might had activated strategies to counteract the consequences of Dnmt1 ablation after escaping apoptosis. The transcriptional changes leading to opposing effects on proliferation suggested the potential activation of a genotoxic response, possibly resulting in growth arrest. This was validated by the detection of phosphorylated H2AX immunoreactivity, a histone mark demarcating regions of chromatin with double strand DNA breaks (Unterberger et al., 2006), both in vivo (Figure 6H) and in vitro (Figure 6I).

Figure 6. Proliferation defect and genotoxic damage in Olig1cre/+;Dnmt1fl/fl oligodendrocyte progenitors.

Figure 6

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(A) Representative P9 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1c re/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and cleaved-CASPASE3 (green) and quantification of cCASPASE3+ cells in the spinal cord at the indicated time points. (B) Representative P9 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and Ki67 (green) and quantification of Ki67+/OLIG2+ cells at P2 and P9. (C) Representative Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl immunopanned OPC, stained for PDGFRα (red) and Ki67 (green) and quantification of the number of Ki67+/PDGFRα+ cells in PDGF + FGF medium. (D) Representative P9 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and phospho-H3 (green) and quantification of phospho-H3+/OLIG2+ cells at P9. (E) Representative Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl immunopanned OPC, stained for OLIG2 (red) and phospho-H3 (green) and quantification of the number of phophos-H3+/OLIG2+ cells in PDGF + FGF medium. White arrowheads indicate double-positive cells. (F) Methylation of individual CpGs assessed by MassARRAY EpiTYPER of Meis2 and Cdc6 reveal hypomethylation. In blue is the complete gene structure, including hypermethylated DMRs observed in differentiating OL (blue rectangles). Dotted lines identify the zoomed region containing the DMRs. Methylation levels of indicated CpGs is shown for control (white) and mutant (gray) sorted OPC. (G) Quantitative real-time PCR analysis of transcript levels of the indicated genes in P2 and P16 spinal cord of Olig1cre/+;Dnmt1fl/fl mice (gray) relative to the levels in controls (white). (H) Representative P9 spinal cord sections of Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl mice, stained for OLIG2 (red) and the genotoxic stress marker phospho-H2AX (green) with relative quantification. (I) Representative Olig1+/+;Dnmt1fl/fl and Olig1cre/+;Dnmt1fl/fl immunopanned OPC, stained for OLIG2 (red) and phospho-H2AX (green) and relative quantification in proliferating OPC. Scale bar = 25 μm. Data are mean ± SEM. *p < 0.05, **p < 0.01 and ***p < 0.005 (ANOVA and Student's t-test).

Ablation of Dnmt1 in oligodendrocyte progenitors activates an endoplasmic reticulum stress response at the late stage of differentiation, due to massive alteration of alternative splicing events

To better define the dramatic hypomyelinating phenotype of mutant mice, we conducted an unbiased transcriptomic analysis of OPC sorted from P5 Olig1+/+;Dnmt1fl/fl;Pdgfrα-GFP and Olig1cre/+;Dnmt1fl/fl;Pdgfrα-GFP using RNA-Seq (Figure S5A and Table S3). Loss of Dnmt1 resulted in 994 downregulated and 566 upregulated genes in mutant cells compared to controls (Tables S4 and S5). Downregulated genes included myelin genes, oligodendrocyte-specific factors and lipid metabolism enzymes (Figure S3B), which were further validated by quantitative PCR (Figure S3D). Upregulated gene categories included cell division and response to DNA stress (Figure S3C and Figure 6G). Consistent with the detection of normal lineage specification, we did not detect any upregulation of neuronally enriched gene categories. Because OL differentiation is characterized by alternatively spliced events (Kevelam et al., 2015; Nave et al., 1987), we interrogated our RNA-Seq dataset in control and mutant cells (Figure 7A). It has been suggested that DNA methylation in specific genomic regions is critical for exon skipping and intron retention splicing events (Gelfman et al., 2013; Yearim et al., 2015). Consistent with these data, we detected severe impairment of exon skipping and intron retention splicing in mutant OPC (Olig1cre/+;Dnmt1fl/fl;Pdgfrα-GFP) compared to wild type (Figure 7B). These events occurred in gene ontology categories identified as: myelination, lipid metabolism and cell cycle (Figure 7C). An example of splicing defects associated with defective DNA methylation is shown for the gene Mcm7, a ubiquitously expressed cell cycle gene characterized by intron retention (Figure 7D). Hypermethylated CpGs in wild-type OPC within the spliced regions were associated with intron splicing while hypomethylated CpGs in mutant cells were associated with intron-retention (Figure 7E). Together these data provided molecular validation of the relationship between aberrant DNA methylation and alternatively spliced defect as suggested by the RNA-Seq analysis.

Figure 7. Ablation of Dnmt1 in oligodendrocyte progenitors results in aberrant alternative splicing events and endoplasmic reticulum stress.

Figure 7

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(A) Histogram and pie chart showing respectively number and proportion of alternative splicing events during normal oligodendrocyte development (classified in 5 categories). (B) Histogram and pie chart respectively showing number and proportion of alternative splicing events in mutant OPC compared to controls. (C) Gene ontology of genes alternatively spliced in mutant Olig1cre/+;Dnmt1fl/fl OPC compared to Olig1+/+;Dnmt1fl/fl OPC. (D) Validation of retained-intron splicing of Mcm7 in Olig1cre/+;Dnmt1fl/fl OPC by PCR. (E) Methylation differences in individual CpGs between control (white) and mutant (gray) DNA isolated from OPC and assessed by MassARRAY EpiTYPER. (F) Ultrastructural analysis identifies a dilated ER with inclusions (red arrows) in Olig1cre/+;Dnmt1fl/fl mice, compared to Olig1+/+;Dnmt1fl/fl controls (blue arrows). (G) Quantitative real-time PCR analysis of genes involved in ER stress response, including the ATF6, PERK, and IRE1 pathways, analyzed in P2, P9 and P16 spinal cord of controls (Olig1+/+;Dnmt1fl/fl) and mutants (Olig1cre/+;Dnmt1fl/fl). (H) Quantitative real-time PCR analysis of ER stress response target genes assessed in P9 spinal cord of Cnp+/+;Dnmt1fl/fl and Cnpcre/+;Dnmt1fl/fl mice. Data are mean ± SEM. *p < 0.05, **p < 0.01 and ***p < 0.005. (ANOVA). See also Figure S5.

It is likely that aberrant splicing might change protein conformation (Kevelam et al., 2015; Yura et al., 2006), and lead to the potential accumulation of incorrectly folded proteins inducing endoplasmic reticulum (ER) stress. Consistent with this possibility we observed dilated ER in mutant oligodendrocytes, with characteristic and unique electron-dense inclusions (Figure 7F), suggestive of protein accumulations and activation of ER stress response. This interpretation was further supported by the detection of specific downstream targets of ER response pathways in mutant mice, including: Bip (downstream of ATF6), Chop (downstream of PERK) and spliced Xbp1 (downstream of the IRE1 pathway) (Figure 7G). The ER stress response was only detected in Olig1cre/+;Dnmt1fl/fl mice, as ablation of Dnmt1 at later stages in Cnpcre/+;Dnmt1fl/fl mice did not induce any change (Figure 7H). These results suggested that Dnmt1 ablation in OPCs resulted in inappropriate protein folding, likely consequent to the dramatic changes in alternative splicing events detected in mutants.

Overall this study supports a role for DNA methylation in oligodendrocyte differentiation that goes beyond the repression of progenitor stage genes, and includes the regulation of alternative splicing events at later stages of differentiation, which are critical for the attainment of the myelinating phenotype.

Discussion

OPC are the last cells to differentiate in the developing CNS, and their maturation is characterized by silencing of alternative lineages and genome-wide deposition of repressive histone K9 and K27 methylation marks (Liu et al., 2015a; Sher et al., 2008, 2012). Our genome-wide analysis of differentially methylated genes during the differentiation of OPC into OL directly sorted from developing brains revealed hypermethylation at the promoter of OPC-specific genes in response to mitogens (such as Pdgfra), as well as regulators of DNA replication (such as Cdc6), and neuronal lineage genes (such as Pax6). This suggested that DNA methylation contributes to the transition of OPC to OL by regulating cell cycle exit and possibly lineage choice decisions. The concept of fine-tuning of the DNA methylome during mammalian brain developmet was previously suggested (Kessler et al., 2016; Lister et al., 2013) and we had predicted two potential outcomes to the ablation of Dnmts in OPC: increased OPC proliferation and potential lineage choice switch. In neural stem cells Dnmt1 ablation led to decreased survival and astroglial differentiation (Fan et al., 2001), in astrocytes it led to precocious differentiation (Fan et al., 2005; He et al., 2005).

Interestingly, none of the predicted outcomes was observed in mice with Dnmt1 ablation in the oligodendrocyte lineage. Despite hypomethylation of myelin genes, OPC did not undergo precocious differentiation. Given the relationship between cell cycle exit and differentiation (Magri et al., 2014), a potential explanation for the mouse phenotype was the possible retention of OPC in a proliferative state, which was suggested by the hypomethylation of genes regulating DNA replication (e.g., Meis2, Cdc6). However, mutant OPC exited from the cell cycle and inefficiently differentiated, despite the removal of the “methylation brake” on the promoter of myelin genes. Reduced OPC proliferation was associated with the detection of phoshorylated histone H2AX, a measure of genotoxic stress (Albino et al., 2009; Lawless et al., 2010). This was consistent with the idea that DNMT1 plays a critical role in the fidelity of transmission of epigenetic information from mother to daughter cells during cell division (Fan et al., 2001; Probst et al., 2009; Sen et al., 2010). In its absence, specific “sensors” induce double strand DNA breaks and activate specific kinases that in turn phosphorylate the nucleosomal histones and mark these regions as “damaged” (Altaf et al., 2007; Méndez-Acuña et al., 2010; Rossetto et al., 2012). This initiates a response resulting in growth arrest or apoptosis in an attempt to contain the number of cells with aberrant information (Milutinovic et al., 2003; Unterberger et al., 2006). In contrast to other cell types (Fan et al., 2001; Jacob et al., 2015), OPC lacking Dnmt1 did not display massive apoptosis and we reasoned that this was likely due to the fact that OPC are the last cells to differentiate at the tail end of development, when all the other organs and systems are already in place, and altered DNA methylation in these cells may not represent an immediate threat to the overall health of the organism.

After exiting from the cell cycle, OPC only inefficiently differentiated into OL and they were unable to generate large amounts of myelin components, thereby resulting in a severely hypomyelinated phenotype, which could not be explained simply in terms of cell number reduction. We also did not detect increased expression of neuronal or astrocytic genes, indicative of a potential lineage switch. This was consistent with the results of fate mapping experiments and highlighted the reliance of lineage choices on multiple modalities of repression requiring the concerted cooperation of DNA methylation and repressive histone methylation marks occurring during OL differentiation (Liu et al., 2015b).

At the ultrastructural level, the preservation of axonal diameter in mutants, despite the absence of myelin suggested, at least in part, the preservation of signaling between OL and axons. However, the detection of enlarged endoplasmic reticulum cisternae and electron-dense inclusion bodies in mutant OLs was reminiscent of proteinaceous aggregates reported in other cell types (Ronzoni et al., 2010; Valetti et al., 1991) and suggested the activation of an ER stress response. A detailed molecular analysis of the three ER response pathways identified the sequential activation of the ATF6 and PERK pathway prior to the engagement of the IRE1 response (Hetz et al., 2013; Oslowski and Urano, 2011), validating the results of the ultrastructural data. A potential explanation for the activation of the ER stress response in oligodendroglial cells lacking Dnmt1 was suggested by RNA sequencing analysis that revealed a massive alteration of alternative splicing. Our analysis identified defective exon-skipping and intron-retention events in mutant cells, while other modalities of splicing, including alternative exons, 5′ or 3′ acceptor sites were not affected. It has been previously reported that differential methylation of CpGs in specific genomic areas results in defective splicing (Gelfman et al., 2013; Hnilicová and Staněk, 2011; Iannone and Valcárcel, 2013) and our study provides an in vivo validation, in the CNS, for this proposed model. We validated the co-occurrence of differential DNA methylation and altered retained-intron splicing in selected genes, supporting the concept that DNA methylation is tightly linked to this form of splicing events and its absence results in a wide rearrangement of RNA splicing events, which in turn may cause aberrant protein folding possibly leading to activation of an ER stress response.

We conclude that the role of DNMT1 in oligodendrocyte lineage cells is more complex than originally anticipated and encompasses regulation of the proliferative state of OPC, as well as a tight coordination between alternative splicing and protein synthesis in the generation of myelinating oligodendrocytes.

Experimental Procedures

Animals

All experiments according to IACUC-approved protocols. Dnmt1fl/fl (Fan et al., 2001; Jackson-Grusby et al., 2001) and Dnmt3afl/fl (Kaneda et al., 2004) mice on a C57BL/6 background were crossed with Olig1-cre (Jackson Laboratory) or Cnp-cre mice (Lappe-Siefke et al., 2003) or Rosa26-loxP-STOP-loxP-TdTomato (Jackson Laboratory).

Cell sorting

OPC were isolated from P2 Pdgfrα-GFP, P5 Olig1cre/+;Dnmt1fl/fl;Pdgfrα-GFP or Olig1+/+;Dnmt1fl/fl;Pdgfrα-GFP brains (Klinghoffer et al., 2002) and OL from P18 Plp1-GFP brains (Spassky et al., 1998) using fluorescence-activated cell sorting as described (Moyon et al., 2015).

DNA methylation analysis

ERRBS libraries were prepared from 50ng input DNA per biological replicate following a modified (Akalin et al., 2012) protocol (Gu et al., 2011) and sequenced using the Illumina HiSeq 2000 instrument. Differentially methylated regions were selected at a q-value < 0.05 and with a minimum mean difference of 10% per region. Differentially methylated regions were independently validated using MassARRAY EpiTYPER assays (Sequenom), as previously described (Huynh et al., 2014). Genomic DNA was sodium bisulfite-treated using an EpiTect Bisulfite Kit (Qiagen). See details and primers in Supplemental Information.

Gene expression analysis

Approximately 250ng of total RNA per sample was used for library construction with the TruSeq RNA Sample Prep Kit (Illumina) and sequenced using the Illumina HiSeq 2000 and the Illumina HiSeq 2500 instrument according to the manufacturer's instructions for 50 (OPC-OL) or 100 (Dnmt1cKO) bp paired end read runs. High-quality reads were aligned to the mouse reference genome (mm10), RefSeq exons, splicing junctions, and contamination databases (ribosome and mitochondria sequences) using the Burrows-Wheeler Aligner (BWA) algorithm. The read count for each RefSeq transcript was extracted using uniquely aligned reads to exon and splice-junction regions. The raw read counts were input into DESeq2 v1.2.5 (Anders and Huber, 2010), for normalizing the signal for each transcript and to ascertain differential gene expression with associated q-values. Differentially expressed genes were selected at a p-value < 0.05, and q-value < 0.01 with a fold change > 2 for the OPC-OL comparison only. To identify enriched gene functions, we computed hypergeometric p-values for over-representation of each biological process gene ontology (GO) category using GOrilla (Eden et al., 2009). For genome-wide annotation org.Mm.eg.db was used in the GOstats R package (Falcon and Gentleman, 2007).

To identify alternative splicing, we used a published Bayesian statistical framework on RNA-Seq data from either Pdgfrα-GFP and Plp1-GFP sorted cells or Olig1cre/+;Dnmt1fl/fl;Pdgfrα-GFP and Olig1+/+;Dnmt1fl/fl;Pdgfrα-GFP sorted cells (Shen et al., 2012). MATS can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns: skipped exons (SE), alternative 5′ splicing site (A5SS), alternative 3′ splicing site (A3SS), mutually exclusive exons (MXE), retained intron (RI). Spliced events between 2 conditions were defined by a p-value < 0.05. Additional details in supplemental information.

Electron microscopy and immunohistochemistry

For electron microscopy, mice were deeply anesthetized and transcardially perfused with 0.9% NaCl, followed by 0.1 M Millonig's solution containing 4% paraformaldehyde and 5% glutaraldehyde (pH 7.3) followed by 2 weeks of post-fixation in the same fixative solution at 4°C as previously described (He et al., 2007). For immunohistochemistry, animals were perfused with 4% paraformaldehyde and post-fixed overnight in the same solution at 4°C. Tissue samples were then transferred to 70% ethanol, sequentially dehydrated and embedded in paraffin. Immunohistochemistry was performed four to ten-micrometer sections. All images were acquired using a Zeiss Observer A1 fluorescent microscope or Zeiss LSM780 upright Confocal. Quantification was carried out on two-three sections per mouse and three-four mice for each age and genotype evaluated using ImageJ.

Primary oligodendrocyte progenitor cultures

Mouse OPC were isolated from P7 mice as described (Cahoy et al., 2008), plated in 24-well dishes and kept proliferating in PDGF-AA (10 ng/ml) and bFGF (20 ng/ml) or differentiated with T3 hormone (45 nM). Rat primary glial cells were generated from 2 to 3 day old SD rats (Harlan, UK) according to published procedures.

Statistical methods

A minimum of 3 replicates per group was used for each experiment. Unpaired student's t-test was used for cell counts and transcript levels for every two datasets following a normal distribution. Two-way ANOVA was used to compare three or more sets of data, including cell counts and MassARRAY data. For all graphs, error bars are mean±SEM.

Supplementary Material

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Acknowledgments

Thanks to A. Alonso, Y. Li, X. Zhang, Y. Xin and the Flow Cytometry Core CyPS (Pitie-Salpetriere Hospital, Paris) for experimental support. Thanks to Drs. A. Sharp, C. Watson, J. Feng, and L. Wrabetz for insightful discussions, and Dr. J. Svaren for comments on the manuscript. Supported by NIH-NINDS R37NS042925 and NS-R0152738 (P.C.), F31NS077504 (J.L.H.), UK Multiple Sclerosis Society (R.J.M.F.), and NIH-NIMH R01MH090948 (J.Z.). The authors declare no conflicts of interest.

Footnotes

Contact information: Patrizia Casaccia, patrizia.casaccia@mssm.edu

Author contributions: SM and JLH generated and characterized the conditional knock-out mice, performed the RT-qPCR, analyzed RNA-Seq and ERBSS data; SM and DD performed the lineage immunohistochemistry; SM alone performed FACS, EpiTYPER MassARRAY, immunocytochemistry; JLD performed the EM experiments; FZ performed the alternative splicing analysis; G.F. provided the flox mice; DM performed 5-mC reactivity experiments; SM, JLH, DM, SY, CL, RJMF, GRJ, BE, J Z and PC analyzed the data and provided comments; SM and PC wrote and revised the manuscript.

Accession numbers: Sequencing data deposited in NCBI's Gene Expression Omnibus Series accession number GSE66047.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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