Mettl14 knockout decreases NSC proliferation and promotes premature NSC differentiation in vitro

To assess Mettl14 loss of function in vivo, we generated Mettl14–conditional knockout mice (Mettl14f/f) by flanking Mettl14 exon 2 with loxP sites. Cre-mediated exon 2 excision results in an out-of-frame mutation that abolishes Mettl14 function (Supplementary Fig. 1a,b). To assess whether the KO strategy deletes Mettl14 in vivo, we evaluated whether Mettl14 was deleted globally using EIIa-cre transgenic mice, which express Cre at zygotic stages (Supplementary Fig. 1c,d). Mettl14+/− heterozygotes were viable and fertile and exhibited no discernible morphological or growth abnormalities, whereas no Mettl14−/− offspring were observed after crosses of Mettl14+/− mice (Supplementary Table 1). We then collected embryos resulting from crosses of heterozygotes at embryonic day 7.5 (E7.5), E8.5 and E9.5 for genotyping. Mettl14−/− embryos were identified at Mendelian ratios when we combined genotyping results from all three stages (Supplementary Table 2). But most Mettl14−/− embryos were dead and many had regressed (Supplementary Fig. 1e), indicating that Mettl14 activity is required for early embryogenesis, a phenotype similar to that of global Mettl3-KO mice13. Of seven Mettl14−/− embryos identified at either E7.5 or E8.5, four were male and three were female, suggesting that phenotypes were not gender specific (Supplementary Fig. 1f).

We then assessed the potential effects of Mettl14 deletion in NSCs. To do so, we crossed Mettl14f/f mice with a Nestin-Cre transgenic line to generate Mettl14f/f;Nestin-Cre (Mettl14-cKO) mice and littermate controls, including Mettl14f/+;Nestin-cre(heterozygous) and Mettl14f/f (non-deleted) mice. Newborn pups were alive and showed no overt morphologic phenotypes (Supplementary Fig. 1g) and normal body weight (Supplementary Fig. 1h). However, all Mettl14-cKO mice were dead within the first neonatal week (Supplementary Fig. 1i). When we examined the brains of postnatal day 0 (P0) Mettl14-cKO pups, we observed no anomalies in gross anatomy, but we found moderately reduced cortical length (Fig. 1a,b). Hematoxylin and eosin (H&E) staining of coronal sections of P0 mouse brain revealed enlargement of the ventricle and a 23% decrease in cortical thickness in Mettl14-cKO brains relative to littermate Mettl14f/f controls (Fig. 1c,d). We next examined Mettl14 expression in RGCs by carrying out Mettl14 and Pax6 co-immunostaining on coronal sections of E17.5 brain from nondeleted, cKO and heterozygous mice. Mettl14 was readily detectible in Pax6+ cells in the cortex of nondeleted and heterozygous controls, but not in cKO mice (Fig. 1e). Together, these results suggest that Mettl14 is required for normal function of NSCs that serve as cortical progenitors.

Fig. 1: Mettl14 regulates the size of mouse cerebral cortex. a, Representative images of whole brains from Mettl14f/f (wild-type (WT); left), Mettl14f/f;Nestin-cre (KO; middle) and Mettl14f/+;Nestin-cre (heterozygous (Het); right) mice pups at P0; black arrows indicate cortex length and width. Scale bar represents 2 mm. b, Quantification of cortical length and width at P0; one-way ANOVA (WT: n = 16; KO: n = 7,; Het: n = 8 P0 brains; length, P = 2.559 × 10–5, F(2, 28) = 15.79; width, P = 0.0869, F (2, 28) = 2.669) followed by Bonferroni’s post hoc test (length, WT versus KO, P = 4.358 × 10–5, 95% confidence interval (C.I.) = 0.02383–0.06534, WT versus Het, P = 0.9999, 95% C.I. = –0.02521–0.01446; width, WT versus KO, P = 0.2141, 95% C.I. = –0.008986–0.05154, WT versus Het, P = 0.6633, 95% C.I. = –0.04098–0.01686). c, Representative images of coronal sections of P0 brains stained with H&E; black arrows indicate cortical thickness. Section shown in upper panel is from the same brain as the one below, but ~1,800 μm anterior to it. Scale bar represents 1 mm. d, Quantification of H&E staining, one-way ANOVA (n = 26 brain sections for all experimental groups; P = 2.9 × 10–14, F (2, 75) = 48.61) followed by Bonferroni’s post hoc test (WT versus KO, P = 4.9 × 10–14, 95% C.I. = 170.1–279.4, WT versus Het, P = 0.0678, 95% C.I. = –3.027–106.2). e, Coronal sections of E17.5 brains stained with antibodies against Mettl14 and Pax6. Similar results were obtained from three independent experiments. f, Coronal sections of E13.5, E15.5, E17.5 and P0 brains stained with anti-Mettl14. Similar results were obtained from three independent experiments. Scale bars represent 100 μm. Graphs represent the mean ± s.d. Dots represent data from individual data points. The horizontal lines in the box plots indicate medians, the box limits indicate first and third quantiles, and the vertical whisker lines indicate minimum and maximum values. ns, non-significant. ****P < 0.0001. Full size image

Next, we evaluated m6A function in isolated embryonic NSCs cultured in vitro. To determine which embryonic stages are appropriate to select Mettl14-deficient NSCs, we examined Mettl14 protein expression in coronal sections prepared from E13.5, E15.5, E17.5 and P0 brains from cKO, heterozygous and nondeleted control mice. Immunostaining revealed residual Mettl14 staining in the cerebral cortex at E13.5 in Mettl14-cKO brain, whereas Mettl14 signals in cortex were absent from E15.5 onward (Fig. 1f). Heterozygous mice showed Mettl14 signals comparable to those of nondeleted controls. Thus, for further analysis we chose E14.5 and E17.5 cortical NSCs and cultured them as neurospheres for 7 d before harvesting them for analysis.

We observed comparable phenotypes in subsequent in vitro analysis of E14.5 and E17.5 NSCs. Unless stated otherwise, our results are those of experiments conducted in E14.5 NSCs. Following confirmation of Mettl14 loss in KO NSCs by western blotting (Supplementary Fig. 2a), we assessed m6A levels from E14.5 neurospheres. Thin-layer chromatography (TLC) analysis revealed an almost total loss of m6A in polyA RNA isolated from Mettl14-KO versus nondeleted NSCs, whereas heterozygous cells displayed m6A levels comparable to those seen in nondeleted controls (Fig. 2a), suggesting that the KO system that we generated is ideal for studying m6A function in NSCs.

Fig. 2: Mettl14 regulates self-renewal of cortical NSCs from E14.5 brain in neurosphere culture. a, Two-dimensional thin-layer chromatography (2D-TLC) analysis of m6A levels in ribosome-depleted (Ribo-) PolyA RNAs isolated from E14.5 NSCs after 7 d of neurosphere culture. Dashed blue circles indicate m6A spots. Similar results were obtained from three independent experiments. b, Representative images of neurospheres formed from isolated E14.5 NSCs. c, Quantification of neurosphere number and area, one-way ANOVA (n = 12 cell cultures for all experimental groups; area, P = 9.15 × 10–13, F(2, 33) = 80.21; number, P = 0.0313, F(2, 33) = 3.853) followed by Bonferroni’s post hoc test (area, WT versus KO, P = 3.2475 × 10–11, 95% C.I. = 6,781–10,737, WT versus Het, P = 0.2855, 95% C.I. = –2,999–663.1; number, WT versus KO, P = 0.0724, 95% C.I. = –0.5596–15.39, WT versus Het, P = 0.9999, 95% C.I. = = –9.31–6.643). d, NSC growth curve. NSCs were plated at 200,000 cells per well in six-well plates and counted 2 and 4 d later; two-way ANOVA (n = 3 cell cultures for all experimental groups; P = 8.644 × 10–12, F(2, 18) = 143.6) followed by Bonferroni’s post hoc test (WT versus KO, P = 1.2905 × 10–11, 95% C.I. = 4.133–5.666, WT versus Het, P = 0.091, 95% C.I. = –0.09277–1.44). e, Growth curve of Mettl14-KO and nondeleted control NSCs transduced with indicated vectors. NSCs were plated in 96-well plates, and numbers were determined by MTT assay; two-way ANOVA (n = 3 cell cultures for all experimental groups; P = 1.413 × 10–20, F(3, 24) = 396.9) followed by Bonferroni’s post hoc test (WT-vector versus WT-FlagMettl14, P = 1.162 × 10–8, 95% C.I. = 0.02849–0.0514; WT-vector versus KO-vector, P = 1.7709 × 10–20, 95% C.I. = 0.1213–0.1442; WT-vector versus KO-FlagMettl14, P = 0.9999, 95% C.I. = –0.01183–0.01107). f, Immunostaining for anti-Tuj1 in NSCs cultured 7 d in vitro. Scale bar represents 100 μm. g, Quantification of immunostaining, one-way ANOVA (n = 3 fields for all experimental groups; P = 0.0004, F(2, 6) = 38.49) followed by Bonferroni’s post hoc test (WT versus KO, P = 0.0004, 95% C.I. = –85.13 to –38.65; WT versus Het, P = 0.9999, 95% C.I. = –28.37–18.11). Graphs represent the mean ± s.d. Dots represent data from individual data points. The horizontal lines in the box plots indicate medians, the box limits indicate first and third quantiles, and the vertical whisker lines indicate minimum and maximum values. ns, non-significant. ***P < 0.001, ****P < 0.0001. Full size image

To characterize KO versus control NSCs, we used a Celigo image cytometer and software to image neurospheres and assess their number and size. Although Mettl14-KO, heterozygous and nondeleted control NSCs derived from E14.5 embryos formed a similar number of neurospheres, neurosphere size, as reflected by neurosphere area in this system, decreased by ~55% in KO versus nondeleted control cells, whereas neurosphere size from heterozygous cells was comparable to that seen in nondeleted controls (Fig. 2b,c). Consistently, those same Mettl14-KO NSCs exhibited significantly decreased proliferation, as determined by cell-counting analysis (Fig. 2d). Similar proliferation defects were detected in NSCs taken from E17.5 Mettl14-cKO mice (Supplementary Fig. 2b). Annexin V flow cytometry (Supplementary Fig. 2c,d) and TUNEL (terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling) analysis (Supplementary Fig. 2e) of E14.5 NSCs confirmed that the effects were not a result of increased apoptosis. To ensure that proliferation defects were a result of Mettl14 deletion, we performed rescue experiments by overexpressing Flag-tagged Mettl14 in E14.5 KO NSCs. Western and dot blot analysis confirmed Mettl14 transgene expression (Supplementary Fig. 2f) and the restoration of m6A (Supplementary Fig. 2g). Notably, Mettl14 overexpression did not increase the proliferation of nondeleted NSC controls (Fig. 2e), but increased the proliferation of Mettl14-KO NSCs to rates comparable to that of controls (Fig. 2e). These results suggest that Mettl14 and concomitant m6A RNA modification regulate NSC proliferation, at least in vitro.

It is well established that decreased NSC proliferation is coupled with premature NSC differentiation14. Thus, we checked for the presence of cells expressing the neuronal marker Tuj1 in E14.5 NSCs cultured for 7 d as neurospheres. Immunostaining analysis revealed a 6.2-fold increase in the number of Tuj1+ cells in KO versus control NSCs (Fig. 2f,g), whereas the number of Tuj1+ cells was comparable between heterozygous and nondeleted controls, suggesting that Mettl14 loss leads to premature neuronal differentiation. Together, these results suggest that Mettl14 regulates NSC self-renewal.

To determine whether the loss of an m6A demethylase would have the opposite effect on NSC proliferation, we knocked down two reported m6A demethylases, Fto and Alkbh59,15, separately in wild-type NSCs. Reverse-transcription quantitative PCR (RT-qPCR) analysis showed high knockdown efficiency in each case, and western blots revealed a marked decrease in Fto and Alkbh5 protein levels in the respective knockdown cells (Supplementary Fig. 2h,i,k,l). Nonetheless, NSC proliferation in vitro was not altered by the loss of either protein (Supplementary Fig. 2j,m). Some reports suggest that changes in expression of either Fto or Alkbh5 have only moderate effects on m6A levels and that both factors likely regulate m6A modification of a subset of transcripts15,16,17. Our results suggest that mRNAs that function in NSC proliferation are not regulated by either Fto or Alkbh5.

The size of the cortical RGC pool is reduced in Mettl14-cKO mouse brain

We next examined the effect of Mettl14 on the proliferation of primary cortical stem cells or RGCs in vivo. To do so, we determined the number of S-phase cells in the cortex of E13.5, E15.5 or E17.5 Mettl14-cKO, heterozygous and nondeleted control embryos by injecting pregnant females with bromodeoxyuridine (BrdU) and harvesting embryos 0.5 h later, which detected only cells undergoing DNA replication at that time point. Immunostaining showed that the number of BrdU+ cells decreased by 19% in E15.5 Mettl14-cKO compared with nondeleted control brain (Supplementary Fig. 3a,d), and that number was 40% when analysis was conducted at E17.5 (Fig. 3a,d). Similarly, we also observed a 44% and 45% decrease in the number of cells expressing the mitotic marker phospho-histone H3 (PH3) at the apical membrane of the cortical VZ in cKO versus nondeleted control brain at E15.5 and E17.5, respectively (Supplementary Fig. 3b,d and Fig. 3b,d). To determine the number of RGCs, we assessed brain coronal sections at all three stages with the RGC marker Pax6. Consistently, we detected a 45% decrease in the number of Pax6+ RGCs in the VZ of E17.5 Mettl14-cKO brain versus controls (Fig. 3c,d) and a 14% decrease at E15.5 (Supplementary Fig. 3c,d). All experiments showed highly comparable results between heterozygous and nondeleted control RGCs (Fig. 3a–d and Supplementary Fig. 3a–d). We did not detect differences in BrdU, PH3 or Pax6 staining relative to that in nondeleted controls in the cortex of E13.5 Mettl14-cKO brains (Supplementary Fig. 3e–g), consistent with the finding that residual Mettl14 is present in cortex at E13.5 (Fig. 1f). Immunostaining with the apoptosis marker cleaved caspase-3 revealed no change in the number of apoptotic cells in the cortex of E17.5 and E15.5 Mettl14-cKO brains relative to nondeleted controls (Supplementary Fig. 3h,i). To understand how Mettl14 loss might affect RGC proliferation, we examined cell cycle progression and cell cycle exit of RGCs from the brains of E15.5 and E17.5 Mettl14-cKO versus control mice. We carried out sequential 5-iodo-2ʹ-deoxyuridine (IdU) and BrdU injection to evaluate cell cycle progression, followed by IdU and BrdU double-staining of cortical sections18. We then determined the percentage of IdU+BrdU– cells, which represented the cells that had progressed past S-phase, versus all IdU+ cells, a group that included both proliferating cells and cells that had left S-phase. We detected a 38% and 43% decrease in E15.5 and E17.5 Mettl14-cKO embryos, respectively, compared with the nondeleted control, suggesting that Mettl14 loss disrupts normal RGC cell cycle progression (Fig. 3e–g). Heterozygous and nondeleted control RGCs yielded comparable results (Fig. 3e–g). To determine whether Mettl14 loss alters cell cycle exit, we performed BrdU-Ki67 double-staining of cortical sections from the brains of mice pulsed with BrdU and analyzed 24 h later. Mettl14 loss resulted in a 50% and 39% decrease in cells exiting the cell cycle from E15.5 and E17.5 Mettl14-cKO embryos, respectively, versus nondeleted controls, suggesting that Mettl14 is required for normal RGC cell cycle exit (Fig. 3h–j). Heterozygous and nondeleted control RGCs yielded comparable results (Fig. 3h–j). Together, these data strongly suggest that Mettl14 regulates the RGC cell cycle and that the RGC pool in cortex is substantially reduced in Mettl14-cKO mice.

Fig. 3: Mettl14 knockout decreases RGC proliferation in vivo. a–c, Coronal sections of E17.5 brains stained with antibodies recognizing BrdU, PH3 and Pax6. Pregnant mothers received a BrdU pulse 30 min before embryo collection. d, Quantification of immunostaining from E17.5 sections. Numbers of Pax6+, BrdU+ and PH3+ cells were determined and normalized to those in comparable sections from nondeleted mice; one-way ANOVA (n = 3 brain sections for all experimental groups; Pax6+, P = 0.0005, F(2, 6) = 34.41; BrdU+, P = 0.0231, F(2, 6) = 7.531; PH3+, P = 0.0002, F(2, 6) = 47.73) followed by Bonferroni’s post hoc test (Pax6+, WT versus KO, P = 0.0004, 95% C.I. = 0.2814–0.6025, WT versus Het, P = 0.0584, 95% C.I. = –0.006443–0.3146; BrdU+, WT versus KO, P = 0.0194, 95% C.I. = 0.08378–0.7348, WT versus Het, P = 0.7612, 95% C.I. = –0.2218–0.4292; PH3+, WT versus KO, P = 0.0002, 95% C.I. = 0.2976–0.5796, WT versus Het, P = 0.2287, 95% C.I. = –0.05332–0.2288). e,f, Coronal sections of E15.5 (e) and E17.5 (f) brains stained with both anti-BrdU that recognizes BrdU only and anti-IdU that also recognizes BrdU. Pregnant mothers received one IdU injection, followed by one BrdU injection 1.5 h later. After another 0.5 h, the embryonic brains were collected for analysis. g, Quantification of the percentage of IdU+BrdU– cells, representing cells that left S-phase during the 1.5-h chase, among total IdU+ cells. One-way ANOVA (n = 3 brain sections for all experimental groups; E15.5, P = 0.0025, F(2, 6) = 19.21; E17.5, P = 0.0075, F(2, 6) = 12.35) followed by Bonferroni’s post hoc test (E15.5, WT versus KO, P = 0.0067, 95% C.I. = 2.835–12.6, WT versus Het, P = 0.5802, 95% C.I. = –6.787–2.973; E17.5, WT versus KO, P = 0.0107, 95% C.I. = 2.347–13.19, WT versus Het, P = 0.9999, 95% C.I. = –5.598–5.244). h,i, Coronal sections of E15.5 (h) and E17.5 (i) brains stained with antibodies recognizing Ki67 and BrdU. Pregnant mothers received one BrdU injection 24 h before embryo collection. j, Quantification of the percentage of BrdU+Ki67– cells, representing cells that exited the cell cycle during 24 h, among total BrdU+ cells. One-way ANOVA (n = 3 brain sections for all experimental groups; E15.5, P = 0.0173, F(2, 6) = 8.589; E17.5, P = 0.0016, F(2, 6) = 22.51) followed by Bonferroni’s post hoc test (E15.5, WT versus KO, P = 0.014, 95% C.I. = 4.493–29.92, WT versus Het, P = 0.6051, 95% C.I. = –7.885–17.54; E17.5, WT versus KO, P = 0.01, 95% C.I. = 3.932–21.2, WT versus Het, P = 0.1249, 95% C.I. = –15.28–1.99). k,l, Immunostaining of coronal sections of E17.5 brain with antibodies to the intermediate progenitor marker Tbr2 and the proneural marker Neurod2. Dashed white lines indicate border of VZ/SVZ area. Similar results were obtained from three independent experiments. Scale bars represent 100 μm. Graphs represent the mean ± s.d. Dots represent data from individual data points. ns, non-significant. *P < 0.05, **P < 0.01, ***P < 0.001. Full size image

We then examined RGC premature differentiation in the cortical VZ of E15.5 and E17.5 Mettl14-cKO brains using Eomes (Tbr2), a marker of intermediate progenitor cells located at the sub-ventricular zone (SVZ), and the proneural marker Neurod2 (ND2). Notably, patches of ND2+Tbr2+ cells were seen consistently at E15.5 and E17.5 in areas close to the apical surface of the cortical VZ of Mettl14-cKO brain, but were absent in comparably staged littermate controls (Supplementary Fig. 3j,k and Fig. 3k,l). Together, these data suggest that Mettl14 is required to prevent NSC premature differentiation and maintain the NSC pool in vivo.

Mettl14 deletion results in reduced numbers of late-born neurons

We next evaluated the effects of Mettl14 loss on cortical neurogenesis. In P0 mice, neurons differentiated from RGCs are found in six distinct cortical layers containing neuronal subtypes identifiable by specific markers. Thus, we stained coronal sections from cKO and comparably staged littermate controls at P0 for the following markers: Cux1, which is expressed in late-born neurons and is a marker of upper neuronal layers II–IV; Sox5, which is expressed in early-born neurons and is a marker of layer V; and Tbr1, which is expressed in postmitotic neurons and is a marker of layer VI to the subplate. Overall, layer organization was comparable in cKO and control mice. When we assessed layer thickness, the thickness of layers marked by Sox5 and Tbr1 did not differ significantly between genotypes (Fig. 4a,b). However, we observed a 70% decrease in the thickness of Cux1+ layers (II–IV) (Fig. 4a,b). To confirm the loss of neurons from these layers, we stained sections from P0 embryos for a different layer II–IV marker, Satb2, and observed an ~34% decrease in the number of Satb2+e neurons in cKO mice versus littermate controls (Fig. 4c,d). When we examined cortical Cux1 staining at E17.5, we detected a 22% reduction in the thickness of Cux1+ layers and a 50% reduction in the number of newly generated Cux1+ cells residing in a region between the VZ and layer IV in Mettl14-cKO mice versus controls (Fig. 4e,f). These results suggest that Mettl14 loss may deplete the progenitor pool in a way that is reflected by loss of late-born neurons.

Fig. 4: Mettl14 knockout decreases the number of late-born neurons. a, Coronal sections of P0 brains stained for the layer II–IV marker Cux1, the layer V marker Sox5 and the layer VI/subplate (SP) marker Tbr1. Dashed white lines mark borders of Cux1+ and Sox5+ neuronal layers. b, Quantification of thickness of Cux1+, Sox5+ and Tbr1+ neuronal layers; one-way ANOVA (n = 3 brain sections for all experimental groups; Cux1+, P = 2.689 × 10–7, F(2, 6) = 461.8; Sox5+, P = 0.115, F(2, 6) = 3.169; Tbr1+, P = 0.8865, F(2, 6) = 0.1229) followed by Bonferroni’s post hoc test (Cux1+, WT versus KO, P = 4 × 10–7, 95% C.I. = 84.39–105.9, WT versus Het, P = 0.9999, 95% C.I. = –10.97–10.52; Sox5+, WT versus KO, P = 0.1329, 95% C.I. = –14.18–101.2, WT versus Het, P = 0.9999, 95% C.I. = –55.32–60.06; Tbr1+, WT versus KO, P = 0.9999, 95% C.I. = –43.31–46.59, WT versus Het, P = 0.9999, 95% C.I. = –50.47–39.42). c, Coronal sections of P0 brains stained for the layer II–IV marker Satb2. d, Quantification of the number of Satb2+ cells; one-way ANOVA (n = 3 brain sections for all experimental groups; P = 0.00015, F(2, 6) = 53.83) followed by Bonferroni’s post hoc test (WT versus KO, P = 0.0003, 95% C.I. = 198.2–408.5; WT versus Het, P = 0.9186, 95% C.I. = –133.1–77.14). e, Coronal sections of E17.5 brains stained for Cux1; dashed white lines mark the border of the Cux1+ neuronal layer. f, Quantification of Cux1+ layer thickness within dashed white lines and of the average number of newly generated Cux1+ cells within 1 mm2, as measured from the VZ to the lower dashed white lines, at E17.5. One-way ANOVA (n = 3 brain sections for all experimental groups; thickness, P = 0.0019, F(2, 6) = 21.36; number, P = 0.0004, F(2, 6) = 36.75) followed by Bonferroni’s post hoc test (thickness, WT versus KO, P = 0.0025, 95% C.I. = 9.765–30.85, WT versus Het, P = 0.9999, 95% C.I. = –10.13–10.96; number, WT versus KO, P = 0.0004, 95% C.I. = 181.5–401.9, WT versus Het, P = 0.7499, 95% C.I. = –74.64–145.8). Scale bars represent 200 μm. Graphs represent the mean ± s.d. Dots represent data from individual data points. ns, non-significant. **P < 0.01, ***P < 0.001, ****P < 0.0001. Full size image

Mettl14 knockout leads to genome-wide changes in histone modification that perturb gene expression

To assess molecular mechanisms underlying m6A-regulated NSC activity, we cultured NSCs from E14.5 Mettl14-cKO, heterozygous and nondeleted control embryos for 7 d and performed RNA sequencing (RNA-seq). Mettl14-KO NSCs exhibited distinct gene expression profiles relative to nondeleted and heterozygous controls (which showed comparable profiles; Fig. 5a and Supplementary Table 3). Gene Ontology analysis (GO) suggested that the most significantly upregulated genes function in NSC differentiation, whereas downregulated genes are associated with cell proliferation (Fig. 5b,c and Supplementary Fig. 4a), changes that are reflective of observed phenotypes. We then evaluated potential mechanisms underlying these changes in gene expression. It is well established that m6A destabilizes transcripts4,13,19,20. However, we detected only a weak correlation between m6A loss and increase in transcript abundance (Supplementary Fig. 4b, Supplementary Tables 3 and 4), suggesting that different m6A-related mechanisms modulate mRNA levels. Given that modification of histone tails is a critical mechanism of gene regulation in mammalian cells21, we asked whether m6A RNA modification may also change histone modifications by performing western blotting on acid-extracted histones from KO versus control NSCs isolated at both E14.5 and E17.5. We evaluated a panel of well-studied histone modifications that have been reported to regulate stem cell activities, including histone H3 phosphorylation, histone H2A and H2B ubiquitination, three types of histone acetylation, and four types of histone methylation22,23,24,25,26,27,28,29,30,31,32,33. These histone marks are associated with either gene activation or repression. Representative western blots of E14.5 NSCs are shown in Fig. 5d. We quantified western blots from E14.5 and E17.5 by calculating the ratios of respective histone modifications to total H3 protein in KO, heterozygous and nondeleted control NSCs. Although we observed no significant change in any of the histone modifications that we tested between heterozygous and nondeleted control samples (Fig. 5d,e), we detected a significant increase in acetylation of histone H3 at lysine 27 (H3K27ac; 111% increase), trimethylation of histone H3 at lysine 4 (H3K4me3; 43% increase) and trimethylation of histone H3 at lysine 27 (H3K27me3; 71% increase) in Mettl14-KO NSCs versus nondeleted controls (Fig. 5d,e). These results suggest that m6A regulates specific histone modifications.

Fig. 5: m6A regulates NSC gene expression through histone modifications. a, Heat map analysis based on RNA-seq analysis in Mettl14-KO versus nondeleted control NSCs. b,c, GO analysis of genes down- and upregulated in Mettl14-KO versus nondeleted control E14.5 NSCs. GO analyses were performed by DAVID. Differentially expressed genes had an adjusted P < 0.01 and a twofold or greater expression difference. Among differentially expressed genes, 1,099 are upregulated and 1,487 are downregulated. Numbers of gene counts and exact P values for each GO term are listed in Supplementary Fig. 4a. d, Representative western blots of acid-extracted histones from E14.5 NSCs using antibodies recognizing H3K4me1, H3K4me3, H3K27me3, H3K9me3, H3K27ac, H3K9ac, H3ac, H2AK119Ubi, H2BK120Ubi and H3S28pho. The band sizes range from 17 to 23 kDa as expected for modified histones. For uncropped images, see Supplementary Fig. 6a. e, Quantitation of western blots from E14.5 and E17.5 NSCs. One-way ANOVA (n = 8 (WT), 12 (KO), or 8 (Het) independent NSC cultures; H3K4me1, P = 0.1123, F(2, 25) = 2.39; H3K4me3, P = 1.06442 × 10–9, F(2, 25) = 52.77; H3K9me3, P = 0.2096, F(2, 25) = 1.664; H3K27me3, P = 0.00013, F (2, 25) = 13.07; H3K9ac, P = 0.1461, F(2, 25) = 2.08; H3K27ac, P = 4.796 × 10–6, F(2, 25) = 20.8; H3ac, P = 0.3676, F(2, 25) = 1.042; H2AK119Ubi, P = 0.3592, F(2, 25) = 1.067; H2BK120Ubi, P = 0.1192, F(2, 25) = 2.319; H3S28pho, P = 0.5347, F(2, 25) = 0.642) followed by Bonferroni’s post hoc test (H3K4me1, WT versus KO, P = 0.2376, 95% C.I. = –0.4713–0.09065, WT versus Het, P = 0.9999, 95% C.I. = –0.2629–0.3527; H3K4me3, WT versus KO, P = 1.157 × 10–8, 95% C.I. = –0.5518 to –0.3128, WT versus Het, P = 0.9999, 95% C.I. = –0.134–0.1278; H3K9me3, WT versus KO, P = 0.4574, 95% C.I. = –0.3314–0.1054, WT versus Het, P = 0.9999, 95% C.I. = –0.1942–0.2842; H3K27me3, WT versus KO, P = 0.0008, 95% C.I. = –1.131 to –0.2956, WT versus Het, P = 0.9999, 95% C.I. = –0.3891–0.5256; H3K9ac, WT versus KO, P = 0.321, 95% C.I. = –0.4577–0.1121, WT versus Het, P = 0.1141, 95% C.I. = –0.5732–0.05098; H3K27ac, WT versus KO, P = 1.769 × 10–5, 95% C.I. = –1.591 to –0.6358, WT versus Het, P = 0.9999, 95% C.I. = –0.5908–0.4556; H3ac, WT versus KO, P = 0.6463, 95% C.I. = –0.4945–0.2007, WT versus Het, P = 0.9999, 95% C.I. = –0.3309–0.4307; H2AK119Ubi, WT versus KO, P = 0. 5288, 95% C.I. = –0.1242–0.3523, WT versus Het, P = 0.9999, 95% C.I. = –0.2759–0.2459; H2BK120Ubi, WT versus KO, P = 0.6171, 95% C.I. = –0.2165–0.5511, WT versus Het, P = 0.6457, 95% C.I. = –0.5982–0.2426; H3S28pho, WT versus KO, P = 0.9999, 95% C.I. = –0.2407–0.2961, WT versus Het, P = 0.8731, 95% C.I. = –0.3915–0.1965). f, Cell growth analysis based on an MTT assay of NSCs treated with vehicle/DMSO or the MLL1 inhibitor MM-102, the CBP/P300 inhibitor C646, or the Ezh2 inhibitor GSK343. Shown is the absorbance ratio of KO to nondeleted controls at each drug dose. One-way ANOVA (n = 3 independent experiments for all experimental groups; GSK343, P = 4.232 × 10–5, F(3, 8) = 38.47; C646, P = 0.0003, F(3, 8) = 23.43; MM-102, P = 0.0025, F(3, 8) = 11.91) followed by Bonferroni’s post hoc test (GSK343, c versus 1.25, P = 0.0035, 95% C.I. = –0.2477 to –0.05943, c versus 2.5, P = 0.0002, 95% C.I. = –0.3265 to –0.1383, c versus 5, P = 1.979 × 10–5, 95% C.I. = –0.4169 to –0.2287; C646, c versus 1.25, P = 0.0036, 95% C.I. = –0.1158 to –0.02744, c versus 2.5, P = 0.0236, 95% C.I. = –0.09574 to –0.007344, c versus 5, P = 0.000103, 95% C.I. = –0.1654 to –0.07702; MM-102, c versus 0.0625, P = 0.0507, 95% C.I. = –8.591 × 10–5 to 0.06086, c versus 1.25, P = 0.9999, 95% C.I. = –0.03858–0.02237, c versus 2.5, P = 0.0615, 95% C.I. = –0.05958–0.001368). Graphs represent the mean ± s.d. Dots represent data from individual data points. ns, non-significant. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Full size image

To determine whether these changes alter NSC proliferation, we searched for chemical inhibitors that antagonize activities associated with upregulated histone modifications to determine whether inhibitor treatment of E14.5 KO NSCs would rescue cell proliferation defects. Three inhibitors were commercially available: MM102, which inhibits mixed-lineage leukemia (MLL) function and H3K4me3 formation; C646, which inhibits the H3K27 acetyltransferase Crebbp (CBP)/p300 activity; and GSK343, which inhibits Ezh2-dependent H3K27me3 formation. We then seeded comparable numbers of NSCs of all three genotypes, added inhibitor or DMSO vehicle at day 0, and determined cell number via MTT assays 4 d later. After DMSO treatment, the number of KO NSCs was ~50% that of nondeleted controls, reflecting slower proliferation, as anticipated (Fig. 5f). GSK343 treatment at 1.25, 2.5 and 5 μM increased the ratios of KO to nondeleted control NSCs to 64%, 71% and 80%, respectively (Fig. 5f), whereas the percentages of heterozygous to nondeleted control NSCs were unchanged by GSK343 treatment (Supplementary Fig. 4c). These observations suggest that blocking the formation of H3K27me3 rescues the growth defects of KO NSCs. Increased ratios of KO versus nondeleted control NSCs were also seen after C646 treatment (Fig. 5f and Supplementary Fig. 4c), suggesting that blocking of H3K27ac also blocks the proliferation defects of KO NSCs. By contrast, treatment of E14.5 NSCs with MM102 had no effect (Fig. 5f and Supplementary Fig. 4c). These results suggest that m6A regulates NSC proliferation, at least in part, through H3K27me3 and H3K27ac modifications.

H3K27me3 marks gene promoters and is associated with silencing34,35, whereas H3K27ac, which is enriched at promoters and enhancers, is associated with gene activation36,37. Thus, we asked whether increased promoter H3K27me3 was associated with gene downregulation, whereas increased promoter/enhancer H3K27ac was associated with gene upregulation in E14.5 Mettl14-KO versus control NSCs. To do so, we performed H3K27me3 and H3K27ac ChIP-seq analysis on E14.5 KO versus nondeleted NSCs (Supplementary Tables 5 and 6) and correlated changes in gene expression with altered histone modification. In total, the intensity of 1,610 promoter/enhancer H3K27ac peaks, defined as peaks within a 10-kb region up- or downstream of a transcriptional start site (TSS), were significantly altered in KO versus control cells. Pearson correlation analysis showed a positive correlation between changes in peak intensity and changes in gene expression (r = 0.06195, P = 0.01292) in KO versus control NSCs, suggesting that H3K27ac functions in m6A-regulated gene activation. We also detected 434 altered H3K27me3 promoter peaks, defined as peaks within 2 kb upstream of a TSS, in KO versus control NSCs. Although in this case we did not detect a significant correlation between changes in peak intensity and gene expression (P = 0.05784) using all 434 genes, we detected a strongly negative Pearson correlation (r = –0.38804, P < 0.02) when we analyzed only downregulated genes (log 2 fold change ≤ –0.6) in KO versus control NSCs, suggesting that H3K27me3 levels are positively correlated to the repression of genes showing decreased expression.

To further assess the relevance of altered H2K27ac and H3K27me3 modifications to NSC gene expression, we asked whether altered transcript abundance seen in KO versus control NSCs could be rescued by treating cells with inhibitors of H2K27ac (C646) or of H3K27me3 (GSK343). Using overlaying ChIP-seq and RNA-seq data and coupling that to Ingenuity pathway analysis (IPA), we picked five differentiation-related genes showing increased H3K27ac and increased expression and five cell-proliferation related genes showing increased H3K27me3 but decreased expression for rescue experiment. Indeed, C646 treatment resulted in significantly decreased expression of the neuritogenesis regulators Kif26a38, Gas739 and Pdgfrb40, in KO NSCs when compared with that in nondeleted NSCs (Fig. 6a–c), whereas GSK343 treatment increased expression of the transcription factors Egr2 and Egr3, which are known to promote proliferation41 (Fig. 6d–f). These results suggest that m6A-regulated histone modification functions in NSC gene expression.

Fig. 6: H3K27ac inhibitor C646 and H3K27me3 inhibitor GSK343 rescue aberrant gene expression in KO versus nondeleted NSCs. a, H3K27ac ChIP-qPCR showing increased promoter and enhancer H3K27ac of Kif26a, Gas7 and Pdgfrb genes in E14.5 Mettl14-KO versus nondeleted NSCs. n = 4 independent experiments for all experimental groups; two-tailed unpaired t-test (Kif26a, P = 0.0006, t = 6.568, df = 6, 95% C.I. = 9.594–20.99; Gas7, P = 0.00013, t = 8.638, df = 6, 95% C.I. = 17.41–31.16; Pdgfrb, P = 0.0002, t = 8.395, df = 6, 95% C.I. = 9.27–16.9). b, RT-qPCR showing increased expression of Kif26a, Gas7 and Pdgfrb genes in E14.5 Mettl14-KO versus nondeleted NSCs. n = 3 independent experiments for all experimental groups; two-tailed unpaired t-test (Kif26a, P = 0.0002, t = 12.71, df = 4, 95% C.I. = 25.01–38.99; Gas7, P = 0.0002, t = 12.46, df = 4, 95% C.I. = 11.41–17.95; Pdgfrb, P = 0.0008, t = 9.08, df = 4, 95% C.I. = 2.957–5.563). c, RT-qPCR showing decreased expression of Kif26a, Gas7 and Pdgfrb genes in E14.5 Mettl14-KO versus nondeleted NSCs treated with H3K27ac inhibitor C646. One-way ANOVA (n = 3 independent experiments for all experimental groups; Kif26a, P = 0.0015, F(2, 6) = 23.04; Gas7, P = 0.0027, F(2, 6) = 18.67; Pdgfrb, P = 8.449 × 10–7, F(2, 6) = 314.3) followed by Bonferroni’s post hoc test (Kif26a, c versus 0.625, P = 0.0041, 95% C.I. = 6.126–22.47, c versus 1.25, P = 0.0014, 95% C.I. = 9.393–25.73; Gas7, c versus 0.625, P = 0.045, 95% C.I. = 0.05735–4.229, c versus 1.25, P = 0.0018, 95% C.I. = 2.207–6.379; Pdgfrb, c versus 0.625, P = 1.431 × 10–5, 95% C.I. = 1.75–2.663, c versus 1.25, P = 5.418 × 10–7, 95% C.I. = 3.384–4.296). d, H3K27me3 ChIP-qPCR showing increased H3K27me3 at promoters of Egr2 and Egr3 genes in E14.5 Mettl14-KO versus nondeleted NSCs. n = 4 independent experiments for all experimental groups; two-tailed unpaired t-test (Egr2, P = 0.0016, t = 5.463, df = 6, 95% C.I. = 5.412–14.19; Egr3, P = 0.0010, t = 5.928, df = 6, 95% C.I. = 5.007–12.05). e, RT-qPCR showing decreased expression of Egr2 and Egr3 genes in E14.5 Mettl14-KO versus nondeleted NSCs. n = 3 independent experiments for all experimental groups; two-tailed unpaired t-test (Egr2, P = 0.0052, t = 5.603, df = 4, 95% C.I. = –0.3789 to –0.1278; Egr3, P = 0.0009, t = 10.67, df = 4, 95% C.I. = –0.7855 to –0.4612). f, RT-qPCR showing increased expression of Egr2 and Egr3 genes in E14.5 Mettl14-KO versus nondeleted NSCs treated with H3K27me3 inhibitor GSK343. One-way ANOVA (n = 3 independent experiments for all experimental groups; Egr2, P = 0.0003, F(2, 6) = 44.49; Egr3, P = 0.01, F(2, 6) = 10.94) followed by Bonferroni’s post hoc test (Egr2, c versus 0.625, P = 0.0007, 95% C.I. = –0.4826 to –0.2041, c versus 1.25, P = 0.0002, 95% C.I. = –0.5526 to –0.2741; Egr3, c versus 0.625, P = 0.0519, 95% C.I. = –0.5627–0.002676, c versus 1.25, P = 0.0072, 95% C.I. = –0.7227 to –0.1573). Graphs represent the mean ± s.d. Dots represent data from individual data points. ns, non-significant. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Full size image

m6A regulates the stability of CBP and p300 transcripts

We then asked how m6A might regulate histone modifications. To do so, we first evaluated the presence of m6A on transcripts encoding the H3K27 acetyltransferases CBP and p300 and the polycomb repressive complex (PRC2) subunits Ezh2, Suz12 and Eed, which catalyze H3K27me3, by methylated RNA immunoprecipitation (meRIP). We detected a 20–30% enrichment of m6A over input in CBP (Crebbp) and p300 (Ep300) mRNAs, which was lost in E14.5 Mettl14-KO NSCs (Fig. 7a). In contrast, only a 0.4–0.6% enrichment of m6A was observed in Ezh2, Eed and Suz12 mRNAs, and the extremely low levels that we observed for Ezh2 and Eed persisted in KO cells (Supplementary Fig. 5), suggesting that the signals that we detected are a result of the immunoprecipitation background.

Fig. 7: m6A regulates mRNA stability of CBP and p300. a, m6A-meRIP-qPCR of CBP and p300 in Mettl14-KO versus control E14.5 NSCs. One-way ANOVA (n = 3 independent experiments for all experimental groups; CBP, P = 1.08 × 10–6, F(2, 6) = 289.4; p300, P = 3.961 × 10–7, F(2, 6) = 405.5) followed by Bonferroni’s post hoc test (CBP, WT versus KO, P = 1.697 × 10–6, 95% C.I. = 16.18–21.63, WT versus Het, P = 0.9999, 95% C.I. = –3.13–2.316; p300, WT versus KO, P = 1.113 × 10–6, 95% C.I. = 21.47–28.12, WT versus Het, P = 0.0086, 95% C.I. = –8.32 to –1.667). b, RT-qPCR of CBP and p300 transcripts in E14.5 NSCs cultured for 7 d in vitro; one-way ANOVA (n = 21 (WT), 33 (KO), or 21 (Het) independent experiments for all experimental groups; CBP, P = 2.380 × 10–21, F(2, 72) = 98.64; p300, P = 2.751 × 10–9, F(2, 72) = 26.24) followed by Bonferroni’s post hoc test (CBP, WT versus KO, P = 1.306 × 10–19, 95% C.I. = –1.252 to –0.8628, WT versus Het, P = 0.3029, 95% C.I. = –0.3512–0.07886; p300, WT versus KO, P = 5.254 × 10–9, 95% C.I. = –0.6356 to –0.3153, WT versus Het, P = 0.2011, 95% C.I. = –0.3058–0.04839). c, RT-qPCR of CBP and p300 transcripts in ActD-treated E14.5 NSCs. P values are generated by two-way ANOVA (n = 3 independent experiments for all experimental groups; CBP, P = 1.262 × 10–11, F(1, 12) = 602.5; p300, P = 8.738 × 10–10, F(1, 12) = 291.7) followed by Bonferroni’s post hoc test (CBP, 0 h, P = 0.9999, 95% C.I. = –0.05658–0.05658, 3 h, P = 1.714 × 10–8, 95% C.I. = –0.3518 to –0.2386, 6 h, P = 7.954 × 10–12, 95% C.I. = –0.6268 to –0.5136; p300, 0 h, P = 0.9999, 95% C.I. = –0.06777–0.06777, 3 h, P = 1.988 × 10–7, 95% C.I. = –0.3522 to –0.2167, 6 h, P = 1.50564 × 10–9, 95% C.I. = –0.5046 to –0.3691). d, A model in which m6A loss alters histone modifications partly through regulation of mRNA stability of histone modifiers, and altered histone modifications aberrantly repress proliferation-related genes and activate differentiation-related genes, resulting in loss of NSC ground state. Graphs represent the mean ± s.d. Dots represent data from individual data points. The horizontal lines in the box plots indicate medians, the box limits indicate first and third quantiles, and the vertical whisker lines indicate minimum and maximum values. ****P < 0.0001. Full size image

We then evaluated potential changes in the stability of CBP and p300 mRNAs. We observed a significant increase in both CBP and p300 mRNA levels in E14.5 Mettl14-KO versus control NSCs (Fig. 7b). We then assayed mRNA stability by treating E14.5 cultured KO and control NSCs with actinomycin D (ActD) to block transcription and harvesting cells 3 and 6 h later. Both CBP and p300 showed significantly increased mRNA stability in Mettl14-KO NSCs compared with nondeleted control NSCs (Fig. 7c), suggesting that m6A may regulate histone modification by destabilizing transcripts that encode histone modifiers.