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Globally reduced N6-methyladenosine (m6A) in C9ORF72-ALS/FTD dysregulates RNA metabolism and contributes to neurodegeneration

Nature Neuroscience volume 26, pages 1328–1338 (2023)Cite this article

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Abstract

Repeat expansion in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here we show that N6-methyladenosine (m6A), the most prevalent internal mRNA modification, is downregulated in C9ORF72-ALS/FTD patient-derived induced pluripotent stem cell (iPSC)-differentiated neurons and postmortem brain tissues. The global m6A hypomethylation leads to transcriptome-wide mRNA stabilization and upregulated gene expression, particularly for genes involved in synaptic activity and neuronal function. Moreover, the m6A modification in the C9ORF72 intron sequence upstream of the expanded repeats enhances RNA decay via the nuclear reader YTHDC1, and the antisense RNA repeats can also be regulated through m6A modification. The m6A reduction increases the accumulation of repeat RNAs and the encoded poly-dipeptides, contributing to disease pathogenesis. We further demonstrate that, by elevating m6A methylation, we could significantly reduce repeat RNA levels from both strands and the derived poly-dipeptides, rescue global mRNA homeostasis and improve survival of C9ORF72-ALS/FTD patient iPSC-derived neurons.

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Fig. 1: The expression of m6A methyltransferases and the m6A RNA modification levels are downregulated in C9ORF72-ALS/FTD.
Fig. 2: m6A hypomethylation dysregulates neuronal gene expression in C9ORF72-ALS/FTD.
Fig. 3: m6A hypomethylation increases mRNA half-life via YTHDF2 in iPSNs.
Fig. 4: The m6A modification in the repeat-containing intron modulates DPR protein production.
Fig. 5: YTHDC1 regulates the stability of C9ORF72 repeat-containing intron RNA via the NEXT decay pathway.
Fig. 6: m6A restoration rescues disease-related phenotypes in C9ORF72-ALS/FTD patient iPSNs.
Fig. 7: FTO inhibitor treatment mitigates disease phenotypes.

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Data availability

Requests for further information or resources and reagents should be directed to and will be filled by the lead author, Shuying Sun (shuying.sun@jhmi.edu). Plasmids generated in this study are available from the lead author upon reasonable request. The sequencing data (Supplementary Table 7) have been deposited at the National Center for Biotechnology Information under Gene Expression Omnibus accession number GSE203581. Source data are provided with this paper.

Code availability

This paper does not report original code.

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Acknowledgements

We thank Target ALS Postmortem Tissue Core and Johns Hopkins ALS Postmortem Tissue Core for providing postmortem human brain tissue samples. We thank T. Thompson from Answer ALS consortium for providing help and detailed data information. We thank M. Ward and his laboratory at the National Institutes of Health (NIH) for sharing the i3Neuron iPSC line and the i3Neuron differentiation protocols. We thank K. Talbot at the University of Oxford for providing the isogenic pair of patient iPSC lines. We thank L. Xue for help with the GP ELISA. We thank J. Rothstein and his laboratory for sharing control and patient iPSC lines and protocols. We thank Sun laboratory members for helpful discussions. This work is supported by the Johns Hopkins University Catalyst Award (S.S.); NIH grants R01NS107347 (S.S.), RF1NS113820 (S.S.), R21AG072078 (S.S.), RF1NS127925 (S.S.), HG008935 (C.H.), ES030546 (C.H.), K08NS104273 (L.H.) and R01NS123538 (L.H.); and the Packard Center for ALS Research (S.S.). Z.Z. was a recipient of the Milton Safenowitz Post-Doctoral Fellowship from the ALS Association, the Toffler Scholar Award and the Postdoc Development Grant from the Muscular Dystrophy Association. The Mass Spectrometry Facility of the University of Chicago is funded by the National Science Foundation (CHE-1048528). C.H. is an investigator of the Howard Hughes Medical Institute.

Author information

Author notes

  1. Jun Liu

    Present address: State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China

  2. These authors contributed equally: Yini Li, Xiaoyang Dou, Jun Liu, Yu Xiao.

Authors and Affiliations

  1. Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Yini Li, Zhe Zhang, Rong Wu, Xiujuan Fu, Yingzhi Ye & Shuying Sun

  2. Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Yini Li, Zhe Zhang, Lindsey Hayes, Rong Wu, Xiujuan Fu, Yingzhi Ye & Shuying Sun

  3. Department of Chemistry and Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA

    Xiaoyang Dou, Jun Liu, Yu Xiao & Chuan He

  4. Howard Hughes Medical Institute, Chicago, IL, USA

    Xiaoyang Dou, Jun Liu, Yu Xiao & Chuan He

  5. Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Lindsey Hayes

  6. Cellular and Molecular Physiology Graduate Program, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Yingzhi Ye

  7. Laboratory of Cellular and Developmental Biology, NIDDK Intramural Research Program, Bethesda, MD, USA

    Bing Yang

  8. Department of Neurology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA

    Lyle W. Ostrow

  9. Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA

    Chuan He

  10. Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Shuying Sun

  11. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Shuying Sun

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Contributions

Y.L., X.D., C.H. and S.S. contributed to the overall design of the study and wrote the paper. Y.L. performed most molecular and cellular biology experiments, with help from Y.X., J.L., Z.Z., R.W., X.F. and Y.Y., under the mentorship of S.S. and C.H. X.D. and Y.L. performed bioinformatic analysis of the high-throughput sequencing data. B.Y. performed blinded analysis of glutamate excitotoxicity. L.H. performed GP ELISA assay and analysis. L.W.O. advised on patient samples and provided key reagents.

Corresponding authors

Correspondence to Chuan He or Shuying Sun.

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Competing interests

C.H. is a scientific founder, a member of the scientific advisory board and an equity holder of Aferna Bio, Inc. and AccuaDX Inc.; a scientific co-founder and equity holder of Accent Therapeutics, Inc.; and a member of the scientific advisory board of Rona Therapeutics. All other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 m6A pathway-related gene expression in C9ORF72-ALS/FTD iPSNs.

a, Proteomic heatmap of the m6A pathway components in control (n = 26) and C9ORF72-ALS/FTD (n = 22) iPSNs. Data were normalized to the batch controls. b, Boxplots of the proteomic data in (a). Box plots indicate the interquartile range with the central line representing the median, and the vertical lines extend to the extreme values in the group. c, Western blotting (left) and quantification (right) of METTL3 and METTL14 expression in control and C9ORF72 iPSNs. Data are mean ± s.e.m. ***P = 0.0008 and 0.0003, respectively, by two-tailed t test. d, Relative RNA expression of neuronal marker genes (MAP2, PSD95 and TUBB3) was measured by RT-qPCR in control and C9 iPSNs, showing comparable neuron maturity between control and C9. Points represent individual control or patient lines. n = 6 in each group. Data are mean ± s.e.m. MAP2, P = 0.304; PSD95, P = 0.86; TUBB3, P = 0.716, by two-tailed t test.

Source data

Extended Data Fig. 2 METTL3 and METTL14 m6A methyltransferases were reduced in C9ORF72-ALS/FTD postmortem brain.

a, b, Immunohistochemistry (IHC) staining of METTL3 (a), METTL14 (b) at temporal cortex section of control and C9ORF72-ALS/FTD samples. Scale bar = 50 μm. c, Western blotting (top) and quantification (bottom) of METTL3, METTL14 using postmortem motor cortex tissue samples. *Non-specific bands. Points represent individual control or patient samples. n = 3 in each group. Data are mean ± s.e.m. *P = 0.0171, **P = 0.0011, by two-tailed t test.

Source data

Extended Data Fig. 3 Expression changes of the m6A ‘writer’ core components in sporadic ALS iPSNs.

a, Proteomic heatmap of the core components of m6A ‘writer’ complex in control (n = 19) and sporadic ALS (n = 93) iPSNs. Data were normalized to the batch controls. b, Boxplots of the proteomic data in (a). Box plots indicate the interquartile range with the central line representing the median, and the vertical lines extend to the extreme values in the group. c, UHPLC-QQQ-MS/MS quantification of the m6A/A ratio in poly-A mRNAs from control (n = 5) and sporadic ALS patient (n = 7) postmortem frontal cortex. Data are mean ± s.e.m. Points represent individual samples. *P = 0.0247 by two-tailed t test.

Source data

Extended Data Fig. 4 The repeat RNA induces downregulation of METTL3 and METTL14 expression.

a, Timeline for doxycycline-induced neuron differentiation, lentiviral transduction of transgenes to express repeats or DPRs, and functional analysis of i3Neurons. b, Relative RNA expression of METTL3 and METTL14 in i3Neurons expressing GFP control, modified poly-GA, modified poly-GR (with randomized codons), or (GGGGCC)160 repeats. METTL3: mGA, P = 0.1154; mGR, P = 0.9755; GC160, ****P < 0.0001. METTL14: mGA, P = 0.3892; mGR, P = 0.9853; GC160, **P = 0.0073. P values were calculated by one-way analysis of variance (ANOVA) with Tukey’s multiple comparisons c, Detection of GFP, modified poly-GA and modified poly-GR post lentiviral transduction in i3Neurons by Nano-Glo HiBiT bioluminescence measurement. The luciferase signal was normalized to the total protein level. i3Neurons without lentiviral infection served as the negative control. *P = 0.0148, **P = 0.0062, ***P = 0.0004, by two-tailed t test. d, Immunofluorescent staining of GFP, modified poly-GA or modified poly-GR in transduced i3Neurons. Neurons were stained using FLAG antibody against the C-terminal FLAG epitope tag in each construct. (b,c) Points represent three biological replicates. Data are mean ± s.e.m.

Source data

Extended Data Fig. 5 MeRIP-seq in control and C9ORF72-ALS/FTD iPSNs and postmortem motor cortex.

a, Venn diagram depicting the total number and overlaps of m6A peaks detected in control and C9ORF72-ALS/FTD groups of iPSN (top) and motor cortex (bottom). b, The most enriched consensus m6A motifs in all conditions. c, Metagene profiles of m6A peak density along transcripts with three non-overlapping segments (5’ UTR, CDS, and 3’ UTR) for control and C9ORF72-ALS/FTD groups. d, Principal component analysis (PCA) of control and C9ORF72-ALS/FTD samples. e, Gene Ontology (GO) enrichment analysis of hypomethylated genes that were identified in both iPSNs and motor cortex. P value was calculated by one-sided Fisher’s Exact test.

Extended Data Fig. 6 The impact of m6A hypomethylation on mRNAs.

a, b, Volcano plot of differentially expressed genes in C9ORF72-ALS/FTD compared to the control, in iPSNs (a) and postmortem motor cortex (b). Genes with significant changes are represented by orange (upregulated in C9) and blue (downregulated in C9) dots. iPSNs: n = 4 individual lines per group, 1212 upregulated vs 1168 downregulated. Motor cortex: n = 3 individual tissue samples per group, 1892 upregulated versus 1239 downregulated. P < 0.05, two-tailed Wald test. c, YTHDF2-RIP qPCR of selected YTHDF2 mRNA targets identified from the non-YTHDF2 bound RNAs. HPRT1 and SMARCA1 mRNAs have no m6A modification according to the MeRIP-seq results. Points represent individual iPSN lines. n = 3 in each group. Data are mean ± s.e.m. P = 0.7047 and 0.4001, respectively, by two-tailed t test. d, Cumulative distribution demonstrating the half-life of YTHDF2 targets between control and C9ORF72-ALS/FTD iPSNs. P value was calculated by a two-tailed non-parametric Wilcoxon-Matt-Whitney test. e, Gene Ontology (GO) enrichment analysis of hypomethylated YTHDF2 binding targets which also showed significantly increased half-life. P value was calculated by one-sided Fisher’s Exact test.

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Extended Data Fig. 7 m6A regulates C9ORF72 repeat-containing RNA.

a, IGV profile showing the m6A peaks (generated by comparing MeRIP against input) in control and C9ORF72-ALS/FTD iPSNs. Red arrow head represents the repeat expansion. b, Western blotting of METTL14 in control or METTL14 knockdown i3Neurons. *non-specific band. c, The relative basal expression of NLuc RNA in the HeLa Flp-In cells expressing the reporters as described in Fig. 4b. *P = 0.015 by two-tailed t test. d, The relative expression level of C9R-NLuc RNA upon knockdown of METTL14 in i3Neurons, measured by RT-qPCR and normalized to non-targeting shRNA control. ****P < 0.0001 by two-tailed t test. (c,d) Points represent three biological replicates. Data are mean ± s.e.m.

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Extended Data Fig. 8 The turnover of C9ORF72 repeat-containing RNA is regulated by m6A in i3Neurons.

a, RT-qPCR of C9 repeat RNA expression from the C9R-NLuc HeLa reporter upon knockdown of YTHDF2. P = 0.5418 by two-tailed t test. b, Relative DPR level was measured by luciferase assay upon YTHDF2 knockdown in the C9R-NLuc HeLa reporter. c, Western blotting of YTHDF2 in control or YTHDF2 knockdown HeLa Flp-In cells. P = 0.9456, 0.8801 and 0.9731, respectively, by one-way analysis of variance (ANOVA) with Tukey’s multiple comparisons. d, e, The relative expression level of YTHDC1 RNA (d) or C9R-NLuc RNA (e) upon knockdown of YTHDC1 by shRNA in i3Neurons. **P = 0.0046, ***P = 0.0006 by two-tailed t test. f, g, Relative DPR levels were measured by luciferase assay upon YTHDC1 knockdown (f) or ZCCHC8 knockdown (g) in the i3Neurons expressing the reporters in Fig. 4b. NLuc signal was normalized to the total protein level in each sample and the relative expression was compared to non-targeting shRNA control. ****P < 0.0001 by one-way analysis of variance (ANOVA) with Tukey’s multiple comparisons. h, Western blotting of ZCCHC8 in control or ZCCHC8 knockdown i3Neurons. Arrow points the expected size of ZCCHC8. (a, b, d-g) Data are mean ± s.e.m. Points represent three biological replicates.

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Extended Data Fig. 9 m6A hypomethylation of the endogenous C9 repeat-containing intron and YTHDC1 expression in the postmortem brain tissues.

a, MeRIP coupled with RT-qPCR of endogenous C9 repeat-containing intronic RNA in control and C9ORF72-ALS/FTD iPSNs. Points represent individual cell lines. n = 6 per group. *P = 0.0427. b, Representative IHC staining of YTHDC1 at temporal cortex section of control and C9ORF72-ALS/FTD samples. Scale bar = 50 μm. c, Western blotting (left) and quantification (right) of YTHDC1 using postmortem motor cortex tissue samples. n = 3 individuals per group. *Non-specific bands. *P = 0.0246. (a, c) Data are mean ± s.e.m. Points represent individual control or patient samples. P values were calculated by two-tailed t test.

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Extended Data Fig. 10 m6A restoration reduces glutamate-induced excitotoxicity in C9ORF72-ALS/FTD iPSNs.

a, RT-qPCR of METTL14 in C9ORF72-ALS/FTD iPSNs expressing exogenous METTL14 or GFP control. Data are mean ± s.e.m. Points represent individual cell lines. n = 6 in each group. ***P = 0.0006 by paired two-tailed t test. b, Western blotting of FTO in C9ORF72-ALS/FTD iPSNs upon knockdown of FTO by shRNA. *non-specific band. c, d, Representative images of Hoechst and propidium iodide (PI) staining of iPSNs in the glutamate-induced excitotoxicity assay. C9ORF72-ALS/FTD iPSNs were infected with lentivirus overexpressing METTL14 or GFP as negative control (c), or expressing FTO shRNA or non-targeting control shRNA (d).

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Supplementary information

Reporting Summary

41593_2023_1374_MOESM2_ESM.xlsx

Supplementary Table 1: Demographic information for lymphoblast lines. Supplementary Table 2: Demographic information for iPSC lines. Supplementary Table 3: Demographic information for frozen postmortem tissues. Supplementary Table 4: Demographic information for formalin-fixed, paraffin embedded (FFPE) tissue slides of temporal cortex. Supplementary Table 5: Sequences of qPCR primers and RT primer for antisense C9. Supplementary Table 6: Demographic information for Answer ALS and NeuroLINCS samples. Supplementary Table 7: High-throughput sequencing sample information.

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Li, Y., Dou, X., Liu, J. et al. Globally reduced N6-methyladenosine (m6A) in C9ORF72-ALS/FTD dysregulates RNA metabolism and contributes to neurodegeneration. Nat Neurosci 26, 1328–1338 (2023). https://doi.org/10.1038/s41593-023-01374-9

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