Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

m6A modulates neuronal functions and sex determination in Drosophila

Nature volume 540, pages 242–247 (2016)Cite this article

Subjects

Abstract

N6-methyladenosine RNA (m6A) is a prevalent messenger RNA modification in vertebrates. Although its functions in the regulation of post-transcriptional gene expression are beginning to be unveiled, the precise roles of m6A during development of complex organisms remain unclear. Here we carry out a comprehensive molecular and physiological characterization of the individual components of the methyltransferase complex, as well as of the YTH domain-containing nuclear reader protein in Drosophila melanogaster. We identify the member of the split ends protein family, Spenito, as a novel bona fide subunit of the methyltransferase complex. We further demonstrate important roles of this complex in neuronal functions and sex determination, and implicate the nuclear YT521-B protein as a main m6A effector in these processes. Altogether, our work substantially extends our knowledge of m6A biology, demonstrating the crucial functions of this modification in fundamental processes within the context of the whole animal.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Drosophila m6A methyltransferase complex is enriched in the nervous system.
Figure 2: m6A controls alternative splicing via YT521-B.
Figure 3: YT521-B and the methyltransferase complex control fly behaviour.
Figure 4: YT521-B and the methyltransferase complex regulate Sxl splicing.
Figure 5: Nito is a novel member of the methyltransferase complex.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

References

  1. Motorin, Y. & Helm, M. RNA nucleotide methylation. Wiley Interdiscip. Rev. RNA 2, 611–631 (2011)

    CAS  PubMed  Google Scholar 

  2. Fu, Y., Dominissini, D., Rechavi, G. & He, C. Gene expression regulation mediated through reversible m6A RNA methylation. Nature Rev. Genet. 15, 293–306 (2014)

    Article  CAS  Google Scholar 

  3. Meyer, K. D. & Jaffrey, S. R. The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nature Rev. Mol. Cell Biol. 15, 313–326 (2014)

    Article  CAS  Google Scholar 

  4. Dominissini, D. et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485, 201–206 (2012)

    Article  ADS  CAS  Google Scholar 

  5. Meyer, K. D. et al. Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 149, 1635–1646 (2012)

    Article  CAS  Google Scholar 

  6. Schwartz, S. et al. High-resolution mapping reveals a conserved, widespread, dynamic mRNA methylation program in yeast meiosis. Cell 155, 1409–1421 (2013)

    Article  CAS  Google Scholar 

  7. Li, Y. et al. Transcriptome-wide N6-methyladenosine profiling of rice callus and leaf reveals the presence of tissue-specific competitors involved in selective mRNA modification. RNA Biol. 11, 1180–1188 (2014)

    Article  Google Scholar 

  8. Lin, S. & Gregory, R. I. Methyltransferases modulate RNA stability in embryonic stem cells. Nature Cell Biol. 16, 129–131 (2014)

    Article  CAS  Google Scholar 

  9. Schwartz, S. et al. Perturbation of m6A writers reveals two distinct classes of mRNA methylation at internal and 5′ sites. Cell Reports 8, 284–296 (2014)

    Article  CAS  Google Scholar 

  10. Wang, X. et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 505, 117–120 (2014)

    Article  ADS  Google Scholar 

  11. Wang, Y. et al. N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells. Nature Cell Biol. 16, 191–198 (2014)

    Article  CAS  Google Scholar 

  12. Alarcón, C. R. et al. HNRNPA2B1 is a mediator of m6A-dependent nuclear RNA processing events. Cell 162, 1299–1308 (2015)

    Article  Google Scholar 

  13. Liu, N. et al. N6-methyladenosine-dependent RNA structural switches regulate RNA–protein interactions. Nature 518, 560–564 (2015)

    Article  ADS  CAS  Google Scholar 

  14. Meyer, K. D. et al. 5′ UTR m6A promotes Cap-independent translation. Cell 163, 999–1010 (2015)

    Article  CAS  Google Scholar 

  15. Wang, X. et al. N6-methyladenosine modulates messenger RNA translation efficiency. Cell 161, 1388–1399 (2015)

    Article  CAS  Google Scholar 

  16. Zhou, J. et al. Dynamic m6A mRNA methylation directs translational control of heat shock response. Nature 526, 591–594 (2015)

    Article  ADS  CAS  Google Scholar 

  17. Wang, X. & He, C. Reading RNA methylation codes through methyl-specific binding proteins. RNA Biol. 11, 669–672 (2014)

    CAS  Google Scholar 

  18. Liu, J. et al. A METTL3–METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nature Chem. Biol. 10, 93–95 (2014)

    Article  ADS  CAS  Google Scholar 

  19. Ping, X. L. et al. Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177–189 (2014)

    Article  CAS  Google Scholar 

  20. Jia, G. et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nature Chem. Biol. 7, 885–887 (2011)

    CAS  Google Scholar 

  21. Fu, Y. et al. FTO-mediated formation of N6-hydroxymethyladenosine and N6-formyladenosine in mammalian RNA. Nature Commun. 4, 1798 (2013)

    Article  ADS  Google Scholar 

  22. Hess, M. E. et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nature Neurosci. 16, 1042–1048 (2013)

    Article  CAS  Google Scholar 

  23. Zheng, G. et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol. Cell 49, 18–29 (2013)

    Article  CAS  Google Scholar 

  24. Batista, P. J. et al. m6A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 15, 707–719 (2014)

    Article  CAS  Google Scholar 

  25. Geula, S. et al. m6A mRNA methylation facilitates resolution of naive pluripotency toward differentiation. Science 347, 1002–1006 (2015)

    Article  ADS  CAS  Google Scholar 

  26. Hongay, C. F. & Orr-Weaver, T. L. Drosophila Inducer of MEiosis 4 (IME4) is required for Notch signaling during oogenesis. Proc. Natl Acad. Sci. USA 108, 14855–14860 (2011)

    Article  ADS  CAS  Google Scholar 

  27. Zhong, S. et al. MTA is an Arabidopsis messenger RNA adenosine methylase and interacts with a homolog of a sex-specific splicing factor. Plant Cell 20, 1278–1288 (2008)

    Article  CAS  Google Scholar 

  28. Bodi, Z. et al. Adenosine methylation in Arabidopsis mRNA is associated with the 3′ end and reduced levels cause developmental defects. Front. Plant Sci. 3, 48 (2012)

    Article  CAS  Google Scholar 

  29. Shah, J. C. & Clancy, M. J. IME4, a gene that mediates MAT and nutritional control of meiosis in Saccharomyces cerevisiae. Mol. Cell. Biol. 12, 1078–1086 (1992)

    Article  CAS  Google Scholar 

  30. Clancy, M. J., Shambaugh, M. E., Timpte, C. S. & Bokar, J. A. Induction of sporulation in Saccharomyces cerevisiae leads to the formation of N6-methyladenosine in mRNA: a potential mechanism for the activity of the IME4 gene. Nucleic Acids Res. 30, 4509–4518 (2002)

    Article  CAS  Google Scholar 

  31. Agarwala, S. D., Blitzblau, H. G., Hochwagen, A. & Fink, G. R. RNA methylation by the MIS complex regulates a cell fate decision in yeast. PLoS Genet. 8, e1002732 (2012)

    Article  CAS  Google Scholar 

  32. Wang, P., Doxtader, K. A. & Nam, Y. Structural basis for cooperative function of Mettl3 and Mettl14 methyltransferases. Mol. Cell 63, 306–317 (2016)

    Article  CAS  Google Scholar 

  33. Wang, X. et al. Structural basis of N6-adenosine methylation by the METTL3–METTL14 complex. Nature 534, 575–578 (2016)

    Article  ADS  CAS  Google Scholar 

  34. Gabel, H. W. et al. Disruption of DNA-methylation-dependent long gene repression in Rett syndrome. Nature 522, 89–93 (2015)

    Article  ADS  CAS  Google Scholar 

  35. Götz, K. G. Visual guidance in Drosophila. Basic Life Sci. 16, 391–407 (1980)

    PubMed  Google Scholar 

  36. Strauss, R., Hanesch, U., Kinkelin, M., Wolf, R. & Heisenberg, M. No-bridge of Drosophila melanogaster: portrait of a structural brain mutant of the central complex. J. Neurogenet. 8, 125–155 (1992)

    Article  CAS  Google Scholar 

  37. Clough, E. & Oliver, B. Genomics of sex determination in Drosophila. Brief. Funct. Genomics 11, 387–394 (2012)

    CAS  Google Scholar 

  38. Granadino, B., Campuzano, S. & Sánchez, L. The Drosophila melanogaster fl(2)d gene is needed for the female-specific splicing of Sex-lethal RNA. EMBO J. 9, 2597–2602 (1990)

    Article  CAS  Google Scholar 

  39. Hilfiker, A., Amrein, H., Dübendorfer, A., Schneiter, R. & Nöthiger, R. The gene virilizer is required for female-specific splicing controlled by Sxl, the master gene for sexual development in Drosophila. Development 121, 4017–4026 (1995)

    CAS  PubMed  Google Scholar 

  40. Patil, D. P. et al. m6A RNA methylation promotes XIST-mediated transcriptional repression. Nature 537, 369–373 (2016)

    Article  ADS  CAS  Google Scholar 

  41. Kondo, S. & Ueda, R. Highly improved gene targeting by germline-specific Cas9 expression in Drosophila. Genetics 195, 715–721 (2013)

    Article  CAS  Google Scholar 

  42. Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007)

    Article  CAS  Google Scholar 

  43. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004)

    Article  CAS  Google Scholar 

  44. Astigarraga, S., Hofmeyer, K., Farajian, R. & Treisman, J. E. Three Drosophila liprins interact to control synapse formation. J. Neurosci. 30, 15358–15368 (2010)

    Article  CAS  Google Scholar 

  45. Bahadorani, S. & Hilliker, A. J. Cocoa confers life span extension in Drosophila melanogaster. Nutr. Res. 28, 377–382 (2008)

    Article  CAS  Google Scholar 

  46. Oktaba, K. et al. Dynamic regulation by polycomb group protein complexes controls pattern formation and the cell cycle in Drosophila. Dev. Cell 15, 877–889 (2008)

    Article  CAS  Google Scholar 

  47. Littleton, J. T., Bellen, H. J. & Perin, M. S. Expression of synaptotagmin in Drosophila reveals transport and localization of synaptic vesicles to the synapse. Development 118, 1077–1088 (1993)

    CAS  PubMed  Google Scholar 

  48. Bluhm, A., Casas-Vila, N., Scheibe, M. & Butter, F. Reader interactome of epigenetic histone marks in birds. Proteomics 16, 427–436 (2016)

    Article  CAS  Google Scholar 

  49. Kellner, S. et al. Absolute and relative quantification of RNA modifications via biosynthetic isotopomers. Nucleic Acids Res. 42, e142 (2014)

    Article  Google Scholar 

  50. Deng, X. et al. Widespread occurrence of N6-methyladenosine in bacterial mRNA. Nucleic Acids Res. 43, 6557–6567 (2015)

    Article  CAS  Google Scholar 

  51. Poeck, B., Triphan, T., Neuser, K. & Strauss, R. Locomotor control by the central complex in Drosophila–An analysis of the tay bridge mutant. Dev. Neurobiol. 68, 1046–1058 (2008). 10.1002/dneu.20643

    Article  CAS  Google Scholar 

  52. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013)

    Article  CAS  Google Scholar 

  53. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008)

    Article  Google Scholar 

  54. Yu, G., Wang, L. G. & He, Q. Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank the Bloomington Drosophila Stock Center for fly reagents; the Drosophila Genomics Resource Center at Indiana University for plasmids; The Developmental Studies Hybridoma Bank and the Lehmann laboratory for antibodies; M. Soller for sharing unpublished data; members of the J.-Y.R. laboratory for helpful discussion; A. Dold and V. Morin for experimental help; the IMB Genomics; the IMB Genomics, Proteomics and Bioinformatics Core facilities for support; and Bioinformatics Core facilities for support; and R. Ketting, N. Soshnikova, R. Strauss, J. Treisman and K. Zarnack for critical reading of the manuscript. Research in the laboratory of J.-Y.R. is supported by the Marie Curie CIG 334288 and the Deutsche Forschungsgemeinschaft (DFG) SPP1935 grant RO 4681/4-1. L.S. is funded by the Rhineland-Palatinate program Gene RED. The project was also supported by a DFG grant (HE 3397/13-1, SPP1784) to M.H.

Author information

Authors and Affiliations

  1. Institute of Molecular Biology (IMB), Mainz, 55128, Germany

    Tina Lence, Junaid Akhtar, Marc Bayer, Nastasja Kreim, Miguel A. Andrade-Navarro & Jean-Yves Roignant

  2. Institute of Pharmacy and Biochemistry, Johannes Gutenberg University of Mainz, Mainz, 55128, Germany

    Katharina Schmid & Mark Helm

  3. Institute of Zoology III (Neurobiology), Johannes Gutenberg University of Mainz, Mainz, 55128, Germany

    Laura Spindler & Burkhard Poeck

  4. Department of Cell Biology, Kimmel Center for Biology and Medicine of the Skirball Institute, NYU School of Medicine, 540 First Avenue, New York, 10016, New York, USA

    Cheuk Hei Ho

  5. Faculty of Biology, Johannes Gutenberg University of Mainz, Mainz, 55128, Germany

    Miguel A. Andrade-Navarro

Authors
  1. Tina Lence
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junaid Akhtar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marc Bayer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Katharina Schmid
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Laura Spindler
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Cheuk Hei Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nastasja Kreim
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Miguel A. Andrade-Navarro
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Burkhard Poeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mark Helm
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jean-Yves Roignant
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.L. and J.-Y.R. conceived the idea. T.L. designed and performed the experiments. J.A. performed the YT521-B RNA immunopreciptation experiment and M.B. generated the YT521-B allele. K.S. and M.H. performed the LC–MS/MS quantification of m6A levels. L.S. and B.P. carried out the Buridan analysis. C.H.H. performed NMJ staining and analysis. M.A.A.-N. performed the phylogenetic analysis. N.K. performed the computational analysis. T.L. and J.-Y.R. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Jean-Yves Roignant.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Characterization of the Drosophila m6A methyltransferase complex.

a, Calibration curve for m6A nucleoside versus stable isotope labelled internal standard from digested Escherichia coli RNA. Areas under the curve (AUCs) are taken from MS/MS chromatograms. Amounts of 1–500 fmol m6A were evaluated. b, Calibration curve for external calibration of adenosine (A) nucleoside from 2–500 pmol. AUCs are extracted from chromatograms generated by ultraviolet detection. c, Phylogenetic analysis of METTL3 homologues. Each Drosophila (D.m) sequence clusters with the corresponding human (H.s), Danio rerio (D.r) and fungal orthologue. Fungi probably lost ancestral versions of individual methyltransferases with these families, with Schizosaccharomyces pombe (S.p) keeping only one orthologue (METTL4) and Saccharomyces cerevisiae (S.c) keeping the two other (METTL3 and METTL14). METTL3, METTL14 and METTL4 orthologues are indicated in green, blue and purple, respectively. See Methods for details about the tree construction. d, Box plots of average expression (rpkm) for all genes expressed by at least 1 rpkm in different conditions. Red dots indicate the position of m6A components in comparison to other expressed genes. Bottom, relative expression of target genes upon different knockdowns (KDs). The mean ± s.d. of three technical measurements from three biological replicates is shown. e, Relative vir mRNA expression and levels of m6A in mRNA during Drosophila development. Number of hours post-fertilization for different embryo, larval and pupal stages is indicated on the x axis. vir expression correlates with m6A levels. The mean ± s.d. of three technical measurements from three biological replicates is shown. f, LC–MS/MS quantification of m6A levels in either control samples or in mRNA extracts depleted for the indicated proteins. Vir depletion affects m6A levels to the same extent as Fl(2)d knockdown. The mean ± s.d. of three technical measurements from three biological replicates is shown for fl(2)d and mean ± s.d. of three technical measurements from two biological replicates for vir. g, Co-immunoprecipitation of Myc–Vir with HA–Ime4 and HA–Fl(2)d. Extracts from S2R+ cells expressing HA-tagged proteins either with Myc alone or with Myc–Vir were immunoprecipitated using Myc-specific beads. Expression of indicated proteins was monitored by western blot analysis using anti-Myc and anti-HA antibodies. RNaseT1 treatment before immunoprecipitation is indicated at the bottom. h, Co-immunoprecipitation studies were carried out with lysates prepared from S2R+ cells co-expressing Myc–dMettl14 and HA–Ime4 upon control (Ctr) or Fl(2)d knockdown. For control experiments, S2R+ cells were transfected with Myc alone and HA–Ime4. Lysates were immunoprecipitated using anti-Myc antibody and then detected with anti-Myc and anti-HA antibodies. Knockdown of Fl(2)d weakens the interaction between Ime4 and dMettl14. i, Western blots showing Ime4 and dMettl14 protein expression levels in extracts from indicated genotypes. Tubulin is used as a loading control.

Extended Data Figure 2 m6A quantification, MeRIP-seq validation and sequence features of m6A sites in Drosophila mRNA.

a, Scatter plot of counts per million (CPM) values for intersected MeRIP peaks. The peaks have at least a support of 3 CPM in one of the replicates. b, qPCR validation of MeRIP peaks. Enrichment is calculated over a negative region in the Rpl15 transcript. The mean ± s.d. of three technical measurements from two replicates is shown. c, Sequence motifs enriched in a fraction of m6A peaks, analysis performed by Homer.

Extended Data Figure 3 Significant fold changes and correspondence between biological replicates of RNA-seq data.

a, Average versus mean–difference plots (MA-plots) show the moderated estimation of fold change and dispersion for RNA-seq data in the different knockdown conditions (adjusted P value < 0.05). The significant values are highlighted in red. b, Spearman sample-to-sample correlation based on gene expression profiles. c, Spearman sample-to-sample correlation based on splicing levels. d, Empirical cumulative distribution function (ECDF) plot of fold changes (log2) upon Ime4/dMettl14 double knockdown over control separated between m6A targets and non-targets. Values are shown between −0.5 and 0.5. The distributions were compared using Wilcoxon rank sum test (P value = 9.9 × 10−4). e, Fold change upon Ime4/dMettl14 double knockdown versus control separated into genes without m6A peaks (non-targets) or containing m6A peaks within the CDS (CDS) or within a 300-bp window around the start or stop codon. Only genes considered for differential expression testing according to DESeq2 default filters are shown. f, Representation of differentially spliced events in the different knockdowns. Selection of 5′ alternative splice sites and increase in intron retention are the two most enriched classes. Classification of splicing changes upon knockdown of the unrelated EJC component eIF4AIII is shown for comparison.

Extended Data Figure 4 Gene ontology term enrichment analysis.

a–e, Significant GO terms (adjusted P value < 0.05) of differentially expressed genes in Ime4 knockdown (a), dMettl14 knockdown (b), Fl(2)d knockdown (c), CG6422 knockdown (d) and YT521-B knockdown (e) cells versus control S2R+ cells. Analysis was performed using the Bioconductor package of GOstats.

Extended Data Figure 5 m6A nuclear components control fl(2)d splicing.

a, UCSC Genome Browser screenshots of fl(2)d showing normalized RNA-seq data from control and indicated knockdown samples in S2R+ cells. The gene architecture of fl(2)d is shown at the top, with thin blue boxes representing the 5′ and 3′ UTRs, thick blue boxes representing the CDS, and thin lines representing introns. Exon numbers are indicated at the top. Signals are displayed as RPM. b, Usage of different 5′ splice sites in exon 1 of fl(2)d transcript and skipping of exon 2 upon different knockdowns. Analysis by semi-quantitative RT–PCR using primers in exon 1 and 3 (red arrows in the scheme). Quantification is indicated underneath the gel. ss1, splice site 1; ss2, splice site 2; ss3, splice site3.

Extended Data Figure 6 Characterization of Drosophila YTH components.

a, Phylogenetic analysis. Sequences from Ustilago hordei (a basidiomycota fungi) were used, in the absence of appropriate sequences from S. cerevisiae, and worked as outliers for each cluster to show the separation between the two major groups. b, Relative expression of YT521-B and CG6422 transcripts and levels of m6A in mRNA during Drosophila development. Number of hours post-fertilization for different embryo, larval and pupal stages is indicated on the x axis. The mean ± s.d. of three technical measurements from three biological replicates is shown. c, Dot-blot assay using biotinylated probe from prolactin transcripts with or without m6A RNA modification. Protein extracts from S2R+ cells transfected with either Myc–GFP or Myc–YT521-B were analysed for binding specificity to the crosslinked probes. Left, methylene-blue staining of crosslinked probes. Right, immunostaining using anti-Myc or anti-m6A antibody. YT521-B protein shows the same enrichment to the methylated probe as anti-m6A antibody. d, Pull-down using biotinylated m6A probe from prolactin transcripts and protein extracts from S2R+ cells transfected with either Myc–GFP or Myc–YT521-B. The same probe lacking the methylation was used as a negative control. Left, western blot using anti-Myc antibody. Right, dot blot using anti-Strep-HRP antibody. The binding of Myc–YT521-B is increased with the methylated probe. Three independent experiments show similar results. e, Walking behaviour in Buridan’s paradigm in heterozygous and transheterozygous YT521-B mutants. Left, median angular displacements from the direct approach to one of the stripes. Right, median fraction of time spent walking during a 15 min test period (Kruskal–Wallis analysis of variance with a Bonferroni correction). Fifteen female flies per genotype were used in both assays. NS, not significant; *P < 0.05; **P < 0.01; ***P < 0.001.

Extended Data Figure 7 Genetic characterization of Ime4, dMettl14 and YT521-B.

a–c, Top, Ime4 (a), dMettl14 (b) and YT521-B (c) loci with indicated deletions. Bottom, loss of function for Ime4 and dMettl14 were monitored by western blot using respective endogenous antibodies, while anti-Tubulin antibody was used as a loading control. To analyse YT521-B deletion, PCR using genomic DNA from heterozygous or homozygous YT521-BΔN mutant flies was loaded on agarose gel. d, Scheme of the dMettl14 protein showing the conserved MT-A70 domain. The frameshift position caused by the guide RNA-induced deletions and the molecular nature of the allele are indicated below. e, Representative confocal images of muscle-6/7 NMJ synapses of abdominal hemisegment A2 for the indicated genotypes labelled with anti-DLG (magenta), anti-Synaptotagmin (green) and HRP (red) to reveal the synaptic vesicles and the neuronal membrane. Bottom, quantification of normalized bouton number (total number of boutons/muscle surface area (μm2 × 1,000)) and normalized Synaptotagmin area (total Synaptotagmin-positive area (μm2)/muscle surface area (μm2 × 1,000)) of NMJ 6/7 in A3 of the indicated genotypes. Error bars show mean ± s.e.m. P values were determined with a Student’s t-test. The number of boutons and of active zones per boutons are increased upon Ime4 knockout. MSA, muscle surface area.

Extended Data Figure 8 Ime4 mutant flies have reduced locomotion and shortened lifespan but apparent normal ovarian development.

a, Ovarian immunostaining of indicated genotypes. DAPI (blue) stains nucleus, Vasa protein (Vasa) (green) shows the germ cells and Orb protein (Orb) (red) the oocyte. Only one oocyte per egg chamber is seen in control and mutant ovaries, arguing against encapsulation defects. b, Survival curves of adult Drosophila. The lifespan of Ime4Δcat mutant flies (purple) and Ime4Δcat mutant flies expressing Ime4 cDNA ubiquitously (green) were quantified for both females and males. c, Walking behaviour in Buridan’s paradigm in Ime4Δcat mutant flies or Ime4Δcat mutant flies expressing Ime4 cDNA ubiquitously (Tub-GAL4), in neurons (elav-GAL4) or in muscles (24B-GAL4). Left, median angular displacements from the direct approach to one of the stripes. Right, median fraction of time spent walking during a 15 min test period. Fifteen female flies per genotype. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001 (Kruskal–Wallis analysis of variance with a Bonferroni correction).

Extended Data Figure 9 m6A components fine-tune the sex determination pathway via YT521-B.

a, Quantification of RT–qPCR experiments from RNA extracts of whole females using primers spanning exons 2 and 4 (top), as well as exons 2 and 3 (bottom) to quantify the levels of the Sxl female and male isoforms, respectively. The mean ± s.d. of three technical measurements from two biological replicates is shown. b, Top, msl-2 genome architecture with thin blue boxes representing the 5′ and 3′ UTRs, thick blue boxes representing the CDSs and thin lines representing introns. Arrowheads display the position of primers used for quantification. Bottom, spliced isoforms for msl-2 were monitored by RT–PCR and PCR extracts were loaded on agarose gel. The quantification of three biological replicates is shown below as mean ± s.d. c, Top, tra genome architecture with thin blue boxes representing the 5′ and 3′ UTRs, thick blue boxes representing the CDSs and thin lines representing introns. Arrowheads display the position of primers used for quantification. Bottom, spliced isoforms for tra were monitored by RT–PCR and PCR extracts were loaded on agarose gels. The quantification of three biological replicates is shown below as mean ± s.d. L, long isoform; S, short isoform. d, Table indicating the percentage of males and females hatching for the indicated genotypes. Ime4 interacts genetically with Sxl to control female survival. e, Bar chart showing the number of differentially spliced genes upon knockout (KO) of Ime4 and YT521-B in adult females. f, Venn diagram showing the overlap of targets in the indicated knockout. g, Pie charts showing distribution of splicing events in the different knockout conditions. Intron retention is overrepresented upon knockout of Ime4 and YT521-B in vivo.

Extended Data Figure 10 RNA interference screen identifies Nito as a new member of the methyltransferase complex.

a, SILAC-coupled mass spectrometry analysis using YT521-B–Myc as a bait. Scatterplot of normalized forward versus inverted reverse experiments plotted on a log2 scale. The threshold was set to a twofold enrichment (blue dashed line). Proteins in the top right quadrant are enriched in both duplicates. b, mRNA quantification of fl(2)d isoforms after knockdown of potential YT521-B-interacting proteins. Three proteins, Hrb27C, Qkr58E-1 and Nito, in addition to m6A components, control fl(2)d splicing in the same direction. Data points of three technical replicates are shown. c–f, mRNA quantification of m6A-regulated transcripts including Hairless (a), Aldh-III (b), CG8929 (c), hts (d) upon knockdown of indicated components. Nito controls m6A splicing events. The quantification of three technical replicates from two biological experiments is shown as mean ± s.d. g, Co-immunoprecipitation studies were carried out with lysates prepared from S2R+ cells co-expressing Myc–Qkr58E-1, Myc–Hrb27C and HA–YT521-B. For control, S2R+ cells were transfected with Myc alone and HA–YT521-B. Myc-containing proteins were immunoprecipitated using a Myc antibody and then immunoblotted with anti-Myc and anti-HA antibodies. h, Co-immunoprecipitation of Myc–Qkr58E-1 with HA–YT521-B with or without RNaseT1. Extracts from S2R+ cells expressing HA–YT521-B either with Myc control or with Myc–Qkr58E-1 were immunoprecipitated using Myc-specific beads. Expression of indicated proteins was monitored by immunoblotting using anti-Myc and anti-HA antibodies. i, Relative nito mRNA expression and levels of m6A in mRNA during Drosophila development. Number of hours post-fertilization for different embryo, larval and pupal stages is indicated on the x axis. nito expression correlates with m6A levels. The mean ± s.d. of three technical measurements from three biological replicates are shown. j, Relative expression of indicated transcripts upon control, Nito and Vir knockdown. Vir and Nito knockdowns do not reduce expression of other components of the methlytransferase complex. The mean ± s.d. of three technical measurements from two biological replicates is shown.

Supplementary information

Supplementary Figure 1

Uncropped scans with protein size indications in kDa and DNA size indicators in bp. (PDF 5074 kb)

Supplementary Table 1

Analysis of the transcriptome wide m6A profile in S2R+ cells. (XLS 612 kb)

Supplementary Table 2

Fl(2)d KD versus LacZ KD in S2R+ cells. (XLS 626 kb)

Supplementary Table 3

Ime4 KD versus LacZ KD in S2R+ cells (XLS 164 kb)

Supplementary Table 4

Ime4/dMettl14 KD versus LacZ KD in S2R+ cells. (XLS 369 kb)

Supplementary Table 5

dMettl14 KD versus LacZ KD in S2R+ cells. (XLS 92 kb)

Supplementary Table 6

Ime4 KO (ImeDcat) in adult heads of 1-2 day old females. (XLS 455 kb)

Supplementary Table 7

Comparison of transcripts affected upon Ime4 KO in adult heads with transcripts containing m6A peak(s) in S2R+ cells. (XLSX 64 kb)

Supplementary Table 8

Candidate proteins enriched by 2-fold in the YT521-Myc IP pull down in S2R+ cells. (XLSX 84 kb)

Supplementary Table 9

Primers used for dsRNA synthesis. (XLSX 102 kb)

Supplementary Table 10

Mass transitions and QQQ parameters of the monitored modifications. (XLSX 33 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lence, T., Akhtar, J., Bayer, M. et al. m6A modulates neuronal functions and sex determination in Drosophila. Nature 540, 242–247 (2016). https://doi.org/10.1038/nature20568

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature20568

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing