Abstract
T cell antigen-receptor (TCR) signaling controls the development, activation and survival of T cells by involving several layers and numerous mechanisms of gene regulation. N6-methyladenosine (m6A) is the most prevalent messenger RNA modification affecting splicing, translation and stability of transcripts. In the present study, we describe the Wtap protein as essential for m6A methyltransferase complex function and reveal its crucial role in TCR signaling in mouse T cells. Wtap and m6A methyltransferase functions were required for the differentiation of thymocytes, control of activation-induced death of peripheral T cells and prevention of colitis by enabling gut RORγt+ regulatory T cell function. Transcriptome and epitranscriptomic analyses reveal that m6A modification destabilizes Orai1 and Ripk1 mRNAs. Lack of post-transcriptional repression of the encoded proteins correlated with increased store-operated calcium entry activity and diminished survival of T cells with conditional genetic inactivation of Wtap. These findings uncover how m6A modification impacts on TCR signal transduction and determines activation and survival of T cells.
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Data availability
RNA-seq, m6A-CLIP and YTHDF2-iCLIP datasets have been deposited in the Gene Expression Omnibus under the accession no. GSE188854. All data are available from the corresponding author upon reasonable request. Source data are provided with this paper.
References
Daley, S. R., Teh, C., Hu, D. Y., Strasser, A. & Gray, D. H. D. Cell death and thymic tolerance. Immunol. Rev. 277, 9–20 (2017).
Zhan, Y., Carrington, E. M., Zhang, Y., Heinzel, S. & Lew, A. M. Life and death of activated T cells: how are they different from naïve T cells? Front. Immunol. 8, 1809 (2017).
Pasparakis, M. & Vandenabeele, P. Necroptosis and its role in inflammation. Nature 517, 311–320 (2015).
Trebak, M. & Kinet, J. P. Calcium signalling in T cells. Nat. Rev. Immunol. 19, 154–169 (2019).
Feske, S. et al. A mutation in Orai1 causes immune deficiency by abrogating CRAC channel function. Nature 441, 179–185 (2006).
Picard, C. et al. STIM1 mutation associated with a syndrome of immunodeficiency and autoimmunity. N. Engl. J. Med. 360, 1971–1980 (2009).
Lacruz, R. S. & Feske, S. Diseases caused by mutations in ORAI1 and STIM1. Ann. N.Y. Acad. Sci. 1356, 45–79 (2015).
Hogan, P. G., Chen, L., Nardone, J. & Rao, A. Transcriptional regulation by calcium, calcineurin, and NFAT. Genes Dev. 17, 2205–2232 (2003).
Xiao, S. et al. FasL promoter activation by IL-2 through SP1 and NFAT but not Egr-2 and Egr-3. Eur. J. Immunol. 29, 3456–3465 (1999).
Rengarajan, J. et al. Sequential involvement of NFAT and Egr transcription factors in FasL regulation. Immunity 12, 293–300 (2000).
Dzialo-Hatton, R., Milbrandt, J., Hockett, R. D. Jr. & Weaver, C. T. Differential expression of Fas ligand in Th1 and Th2 cells is regulated by early growth response gene and NF-AT family members. J. Immunol. 166, 4534–4542 (2001).
La Rovere, R. M., Roest, G., Bultynck, G. & Parys, J. B. Intracellular Ca2+ signaling and Ca2+ microdomains in the control of cell survival, apoptosis and autophagy. Cell Calcium 60, 74–87 (2016).
Kim, K. D. et al. ORAI1 deficiency impairs activated T cell death and enhances T cell survival. J. Immunol. 187, 3620–3630 (2011).
Desvignes, L. et al. STIM1 controls T cell-mediated immune regulation and inflammation in chronic infection. J. Clin. Invest. 125, 2347–2362 (2015).
Zaccara, S., Ries, R. J. & Jaffrey, S. R. Reading, writing and erasing mRNA methylation. Nat. Rev. Mol. Cell Biol. 20, 608–624 (2019).
Fu, Y., Dominissini, D., Rechavi, G. & He, C. Gene expression regulation mediated through reversible m6A RNA methylation. Nat. Rev. Genet. 15, 293–306 (2014).
Shulman, Z. & Stern-Ginossar, N. The RNA modification N6-methyladenosine as a novel regulator of the immune system. Nat. Immunol. 21, 501–512 (2020).
Gao, Y. et al. m6A modification prevents formation of endogenous double-stranded RNAs and deleterious innate immune responses during hematopoietic development. Immunity 52, 1007–1021.e1008 (2020).
Li, H. B. et al. m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways. Nature 548, 338–342 (2017).
Tong, J. et al. m6A mRNA methylation sustains Treg suppressive functions. Cell Res. 28, 253–256 (2018).
Yao, Y. et al. METTL3-dependent m6A modification programs T follicular helper cell differentiation. Nat. Commun. 12, 1333 (2021).
Grenov, A.C. et al. The germinal center reaction depends on RNA methylation and divergent functions of specific methyl readers. J. Exp. Med. 218, e20210360 (2021).
Sprent, J. & Surh, C. D. Writer’s block: preventing m6A mRNA methylation promotes T cell naivety. Immunol. Cell Biol. 95, 855–856 (2017).
Cao, G., Li, H. B., Yin, Z. & Flavell, R. A. Recent advances in dynamic m6A RNA modification. Open Biol. 6, 160003 (2016).
Zaccara, S. & Jaffrey, S. R. A unified model for the function of YTHDF proteins in regulating m6A-modified mRNA. Cell 181, 1582–1595.e1518 (2020).
Lasman, L. et al. Context-dependent functional compensation between Ythdf m6A reader proteins. Genes Dev. 34, 1373–1391 (2020).
Liu, J. et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 10, 93–95 (2014).
Wang, P., Doxtader, K. A. & Nam, Y. Structural basis for cooperative function of Mettl3 and Mettl14 methyltransferases. Mol. Cell 63, 306–317 (2016).
Schöller, E. et al. Interactions, localization, and phosphorylation of the m6A generating METTL3–METTL14–WTAP complex. RNA 24, 499–512 (2018).
Knuckles, P. et al. Zc3h13/Flacc is required for adenosine methylation by bridging the mRNA-binding factor Rbm15/Spenito to the m6A machinery component Wtap/Fl(2)d. Genes Dev. 32, 415–429 (2018).
Yue, Y. et al. VIRMA mediates preferential m6A mRNA methylation in 3′UTR and near stop codon and associates with alternative polyadenylation. Cell Discov. 4, 10 (2018).
Bawankar, P. et al. Hakai is required for stabilization of core components of the m6A mRNA methylation machinery. Nat. Commun. 12, 3778 (2021).
Ping, X. L. et al. Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177–189 (2014).
Schwartz, S. et al. Perturbation of m6A writers reveals two distinct classes of mRNA methylation at internal and 5′ sites. Cell Rep. 8, 284–296 (2014).
Lu, T. X. et al. A new model of spontaneous colitis in mice induced by deletion of an RNA m6A methyltransferase component METTL14 in T cells. Cell Mol. Gastroenterol. Hepatol. 10, 747–761 (2020).
Borland, K. et al. Production and application of stable isotope-labeled internal standards for RNA modification analysis. Genes 10, 26 (2019).
Ohnmacht, C. et al. MUCOSAL IMMUNOLOGY. The microbiota regulates type 2 immunity through RORγt+ T cells. Science 349, 989–993 (2015).
Lin, Z. et al. Mettl3-/Mettl14-mediated mRNA N6-methyladenosine modulates murine spermatogenesis. Cell Res. 27, 1216–1230 (2017).
Kieper, W. C. et al. Recent immune status determines the source of antigens that drive homeostatic T cell expansion. J. Immunol. 174, 3158–3163 (2005).
Hoefig, K. P. et al. Defining the RBPome of primary T helper cells to elucidate higher-order Roquin-mediated mRNA regulation. Nat. Commun. 12, 5208 (2021).
Körtel, N. et al. Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning. Nucleic Acids Res. 49, e92 (2021).
Buchbender, A. et al. Improved library preparation with the new iCLIP2 protocol. Methods 178, 33–48 (2020).
Krakau, S., Richard, H. & Marsico, A. PureCLIP: capturing target-specific protein–RNA interaction footprints from single-nucleotide CLIP-seq data. Genome Biol. 18, 240 (2017).
Paris, J. et al. Targeting the RNA m6A reader YTHDF2 selectively compromises cancer stem cells in acute myeloid leukemia. Cell Stem Cell 25, 137–148.e136 (2019).
Zhu, Y. et al. The E3 ligase VHL promotes follicular helper T cell differentiation via glycolytic-epigenetic control. J. Exp. Med. 216, 1664–1681 (2019).
Little, N. A., Hastie, N. D. & Davies, R. C. Identification of WTAP, a novel Wilms’ tumour 1-associating protein. Hum. Mol. Genet. 9, 2231–2239 (2000).
Wang, X. et al. N6-Methyladenosine-dependent regulation of messenger RNA stability. Nature 505, 117–120 (2014).
Vaeth, M., Kahlfuss, S. & Feske, S. CRAC channels and calcium signaling in T cell-mediated immunity. Trends Immunol. 41, 878–901 (2020).
Li, S. et al. The transcription factors Egr2 and Egr3 are essential for the control of inflammation and antigen-induced proliferation of B and T cells. Immunity 37, 685–696 (2012).
Tummers, B. & Green, D. R. Caspase-8: regulating life and death. Immunol. Rev. 277, 76–89 (2017).
Lee, P. P. et al. A critical role for Dnmt1 and DNA methylation in T cell development, function, and survival. Immunity 15, 763–774 (2001).
Sledzinska, A. et al. TGF-β signalling is required for CD4+ T cell homeostasis but dispensable for regulatory T cell function. PLoS Biol. 11, e1001674 (2013).
Rubtsov, Y. P. et al. Regulatory T cell-derived interleukin-10 limits inflammation at environmental interfaces. Immunity 28, 546–558 (2008).
Hogquist, K. A. et al. T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27 (1994).
Barnden, M. J., Allison, J., Heath, W. R. & Carbone, F. R. Defective TCR expression in transgenic mice constructed using cDNA-based alpha- and beta-chain genes under the control of heterologous regulatory elements. Immunol. Cell Biol. 76, 34–40 (1998).
Busch, A., Brüggemann, M., Ebersberger, S. & Zarnack, K. iCLIP data analysis: a complete pipeline from sequencing reads to RBP binding sites. Methods 178, 49–62 (2020).
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Acknowledgements
We thank C. Keplinger (Helmholtz Zentrum München) and L. Esser (Ludwig-Maximilians−Universität) for excellent technical support. We thank the BMC Core Facility (Ludwig-Maximilians-Universität) for flow cytometry, H. Blum and S. Krebs (Ludwig-Maximilians-Universität) for mRNA- and CLIP-seq and N. Angstman for initial processing of sequencing data. The present study was supported by the German Research Foundation grant nos. HE3359/8-1 (#444891219), HE3359/7-1 (#432656284) and SFB 1054 (project A03, #210592381), SPP 1935 (#313381103) and TRR338 (project C02, #452881907) to V.H.
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T.I.-K. and V.H. designed the research and experiments with input from S.K., S.C., S.F., S.M., A.K. and J.K. T.I.-K., C.L., M.B., K.B. and G.A. performed the research. T.I.-K, C.L., M.B., K.B. and G.A. analyzed the data and S.C. analyzed the RNA-seq data. T.I.-K., G.C. and A.M. analyzed the CLIP data. R.M. performed experiments for histology. T.I.-K. and V.H. wrote the manuscript with critical input from S.F. and S.M.
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Nature Immunology thanks Ziv Shulman, Martin Turner and Monika Wolkers for their contribution to the peer review of this work. Primary Handling Editor: L. A. Dempsey in collaboration with the Nature Immunology team. Peer reviewer reports are available.
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Extended data
Extended Data Fig. 1 Wtap depletion in T cells induces inflammation of the gut.
a, b, d Deletion efficiency of floxed Wtap alleles in thymocytes and splenic T cells showing an immunoblot (a) with Wtap-specific antibodies using Gapdh as a loading control or flow cytometry (b, d) with Wtap-specific antibodies on the indicated subpopulations, CD4+ T cells from lamina propria of the colon (d). (n = 3 in a, n = 6 in b, d three independent experiments). c, qPCR analysis of the indicated cytokine gene expression within mRNA prepared from colon tissue. Results are to Ywhaz expression and presented relative to wild-type. (n = 3, representative of three independent experiments with technical triplicates). e, f, IFNγ and IL-17a production in CD4+ T cells from the colon. Percentages of IFNγ+IL-17a+ cells are shown in e. (WT, n = 4; KO, n = 9, three independent experiments). g, h Representative images of mice, spleen and lymph nodes from 5-week-old Wtapfl/-; Foxp3-Cre and Wtapfl/fl; Foxp3-Cre mice. Body weight is shown in the bottom (g). Scale bar, 10 mm. (h) (n = 2 biological replicates) i, H&E stained colon tissue from 4−week-old Wtapfl/-; Foxp3-Cre and Wtapfl/fl; Foxp3-Cre mice. Scale bar, 10 µm, magnification x10. (n = 3 biological replicates) j-m, Stainings to detect CD4+ T and Treg cells in spleen (j, k, l) and colon (m) from 5-week-old Foxp3-Cre and Wtapfl/fl; Foxp3-Cre mice. Numbers adjacent to outlined areas indicate the percentage of cells in each gate. (WT, n = 5-7; KO, n = 4, three independent experiments). n, Stainings to detect RORγt and Helios for CD4+YFP+Foxp3+ or YFP–Foxp3+ T cells in mLNs from female Wtapfl/fl; Foxp3-Crehet mice. (n = 3, two independent experiments). o, IFNγ and IL-17a production in Treg cells in lamina propria of the colon. Percentages of IFNγ+ or IL17a+ cells are shown in the right panel. (WT, n = 4; KO, n = 3 biological replicates). All data are presented as mean values ± s.e.m. Statistical analyses were performed using unpaired two-tailed Student’s t-test.
Extended Data Fig. 2 Analyzing Wtap effects on thymic Treg cells and intracellular TCRβ expression.
a, Staining to detect CD4+CD25+Foxp3+ Treg cells in thymus from 6-8-week-old Wtapfl/fl and Wtapfl/fl; Cd4−Cre mice. Numbers adjacent to outlined areas indicate the percentage of cells in each gate. (n = 6, three independent experiments). b, Intracellular staining of TCRβ on gated CD4SP CD24- or CD8SP CD24- thymocytes. (n = 3, two independent experiments). c, d, Flow cytometry analysis (c) and cellularity (d) of thymocytes from bone marrow chimeras, assessed for expression of CD4 and CD8 (right) after gating on CD45.1 or CD45.2 (left). Numbers adjacent to outlined areas indicate percentage of cells in each gate. (n = 3 individual mice in one experiment). e, f, Cellularity of thymocytes (Left), CD4SP or CD8 SP thymocytes (Right) from Wtapfl/fl and Wtapfl/fl; Cd4-Cre mice expressing a transgene encoding the MHC class I-restricted OT-I TCR (e) or the MHC class II-restricted OT-II TCR (f). (WT, n = 3; KO, n = 5, two independent experiments). All data are presented as mean values ± s.e.m. Statistical analyses were performed using unpaired two-tailed Student’s t-test.
Extended Data Fig. 3 Virma expression is essential for m6A modification.
Deletion efficiency of floxed Wtap alleles in splenic T cells showing flow cytometry with Wtap-specific antibodies on subsets gating on CD44 and CD62L in splenic CD4+ T cells. (n = 6, three independent experiments) b, Surface staining of TCRβ on subsets gating on CD44 and CD62L in splenic CD4+ T and CD8+ T cells. (n = 6, three independent experiments). c, Percentage of the different congenic marked hematopoietic CD45+ cells (c) and flow cytometry analysis of splenocytes (d) from bone marrow chimeras harbouring WT (CD45.1+) and Wtapfl/fl; Cd4-Cre (CD45.2+) hematopoietic cells, assessed for expression of CD4 and CD8 after identifying CD45.1 or CD45.2 congenic cells. Numbers adjacent to outlined areas indicate the percentages of cells in each gate. (n = 3 individual mice in one experiment). e, Surface staining of CD44 and CD62L on CD4+ and CD8+ T cells after gating on CD45.1 or CD45.2 congenic splenocytes of the bone marrow chimeras. Numbers adjacent to outlined areas indicate percentage of cells in each gate. (n = 3 individual mice in one experiment). f, Immunoblot analysis of Virma protein in extracts from MEF cells showing Gapdh as a loading control. (n = 3, two independent experiments). g, m6A abundance as determined by LC/MS/MS analysis in the oligo-dT-purified mRNAs of Virma-depleted and Cre expressing MEF cells. (n = 3 biological replicates), (mean ± s.e.m, unpaired two-tailed t-test). h, Stainings to identify CD4+CD25+Foxp3+ Treg cells among thymocytes of Virmafl/fl or Virmafl/fl; Cd4-Cre mice. Numbers adjacent to outlined areas indicate the percentages of cells in each gate. (WT, n = 5; KO, n = 4, two independent experiments).
Extended Data Fig. 4 The m6A methyltransferase complex controls T cell survival.
a, Flow cytometry of CD4+ and CD8+ T cells from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice stained with anti-WTAP antibody seven days after the last gavage. (n = 8, three independent experiments). b, c, Flow cytometry of cells from lymphoid organs of tamoxifen-gavaged Rag1−/− (b) or CD45.1 (c) mice 9 days after transfer of naive CD4+ T cells from Cd4-CreERt2 or Wtapfl/fl; Cd4-CreERt2 mice, assessed for expression of Wtap after gating on CD4 and TCRβ in b or CD45.1 and CD45.2 in c. (WT, n = 5; KO, n = 6, three independent experiments for spleen, WT, n = 3; KO, n = 4 two independent experiments for pLN and mLN, WT, n = 4; KO, n = 3, two independent experiments (f)). d, Histogram of Ki67 expression in CD4+ T cells from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice that received tamoxifen gavage and anti-CD3 antibody injection. (WT, n = 5; KO, n = 4, three independent experiments). e, Cellularity of pLNs from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice that received tamoxifen gavage and anti-CD3 antibody injection. (WT, n = 5; KO, n = 4, three independent experiments). (mean ± s.e.m, unpaired two-tailed t-test).
Extended Data Fig. 5 Analyzing TCR induced apoptosis and activation markers after Virma or Mettl3 deletion in CD4+ T cells.
a, Flow cytometry analysis of CTV-labelled CD4+ T cells from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice, stained with Annexin V on day 4. (n = 3 biological replicates). b, Flow cytometry of CD4+ T cells from Cd4-CreERt2 and Virmafl/fl; Cd4-CreERt2 mice, stained with anti-VIRMA antibody three days after the last gavage. (n = 6, thee independent experiments). c, Flow cytometry of CD4+ T cells from Cd4-CreERt2 and Virmafl/fl; Cd4-CreERt2 mice, stained with AnnexinV and LIVE/DEAD Fixable dye on day 4. Percentage of AnnexinV+ population is shown in the right. (n = 6, thee independent experiments). d. Flow cytometry of naive CD4+ T cells from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice, stained with AnnexinV and LIVE/DEAD Fixable dye on day 4. Percentage of AnnexinV+ population is shown in the right. (n = 10, thee independent experiments). e, f, Flow cytometry of naive CD4+ T cells from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice that received tamoxifen gavage (e) or CD4+ T cells transfected with sgRNA for Cd90.2 or Mettl3 (f), assessed for expression of phospho-Stat5 after the stimulation with IL7 (10 ng/ml). (n = 6, two independent experiments). g, Surface staining of activation marker CD5 and CD25 in CD4+ T cells. (n = 4 biological replicates). h-k, In vitro co-culture of naive OTII-CD4+ T cells (CD45.2) from Cd4-CreERt2 and Wtapfl/fl; Cd4-CreERt2 mice with mutant (R9) (h) or WT (i-k) OVA323-339 peptide-loaded splenocytes/lymphocytes (CD45.1). Surface staining of CD69 after gating on CD45.2+CD4+ population (h), percentage of CD45.1 and CD45.2 (i), CTV profiles (j) and AnnexinV staining (k) are shown. (n = 6, two independent experiments). All data are presented as mean values ± s.e.m. Statistical analyses were performed using unpaired two-tailed Student’s t-test.
Extended Data Fig. 6 Wtap depletion induces apoptosis in vitro.
a, Experimental scheme of in vitro deletion of Wtap induced by 4’-hydroxy-tamoxifen in iKO CD4+ T cells. b, Flow cytometry of CD4+ T cells prepared from in vitro 4’OH-tamoxifen induced Wtap deletion, stained with anti-WTAP antibody on day 4. c, Flow cytometry of iKO and control CD4+ T cells, stained with AnnexinV and LIVE/DEAD Fixable dye on day 4. Percentage of AnnexinV+ cell populations is shown in the right panel. (n = 5, two independent experiments). (mean ± s.e.m, unpaired two-tailed t-test). d, Measurement of m6A abundance on mRNAs in CD4+ T cells prepared from in vitro 4’OH-tamoxifen induced Wtap deletion. (n = 3 biological replicates). (mean ± s.e.m, unpaired two-tailed t-test).
Extended Data Fig. 7 Strategy and validation of the CLIP analyses.
a, Reproducibility of enriched peaks in m6A- or Ythdf2-iCLIP. Data were prepared from three biological replicate for m6A-CLIP and two replicate for Ythdf2-CLIP. b, Flow chart of the CLIP analysis. c, Venn diagram showing the overlap of m6A target mRNAs from Yao et al.21 and this study. d, Integrative Genomics Viewer (IGV) tracks of Tnf displaying m6A-CLIP and Ythdf2-CLIP reads distribution. The read coverage is shown for merged replicates.
Extended Data Fig. 8 Regulation of m6A modified mRNAs by Wtap deletion.
a, qPCR analysis of iKO and control CD4+ T cells. Results are presented relative to Ywhaz expression. (WT, n = 4; KO, n = 3, two independent experiments with technical triplicates). (mean ± s.e.m, unpaired two-tailed t-test). b, mRNA decay curves of Tnfrsf1b mRNA in iKO and control CD4+ T cells using Actinomycin D to terminate transcription of newly synthesized mRNAs. (n = 3, two to three independent experiments with technical triplicates). (mean ± s.e.m, two-way ANOVA).
Extended Data Fig. 9
a, Integrative Genomics Viewer (IGV) tracks displaying m6A-CLIP and Ythdf2-iCLIP read distribution. The read coverage is shown for merged replicates. b, Flow cytometry of CD4+ T cells transduced with eGFP, Orai1 or Ripk1 encoding retroviruses, stained with Thy1.1 two days after TCR re-stimulation. Grey histogram shows Thy1.1 negative cells. (n = 5-6, three independent experiments).
Extended Data Fig. 10 Exemplary gating strategy.
Cells were pre-gated on lymphocytes (FSC-A/SSC-A), single cells (FSC-H/FSC-W and SSC-H/SSC-W) and live cells (LIVE/DEAD staining -) prior to gating on cell populations of interest.
Supplementary information
Supplementary Information
Supplementary Table 3.
Supplementary Table 1
List of 1,577 DEGs.
Supplementary Table 2
List of genes identified by annotating each GO term.
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Ito-Kureha, T., Leoni, C., Borland, K. et al. The function of Wtap in N6-adenosine methylation of mRNAs controls T cell receptor signaling and survival of T cells. Nat Immunol 23, 1208–1221 (2022). https://doi.org/10.1038/s41590-022-01268-1
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DOI: https://doi.org/10.1038/s41590-022-01268-1
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