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Dynamic Transcriptome, DNA Methylome, and DNA Hydroxymethylome Networks During T-Cell Lineage Commitment

  • Yoon, Byoung-Ha (Department of Functional Genomics, University of Science and Technology (UST)) ;
  • Kim, Mirang (Department of Functional Genomics, University of Science and Technology (UST)) ;
  • Kim, Min-Hyeok (Department of Biological Sciences, Korea Advanced Institute of Science and Technology) ;
  • Kim, Hee-Jin (Genome Editing Research Center, Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB)) ;
  • Kim, Jeong-Hwan (Genome Editing Research Center, Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB)) ;
  • Kim, Jong Hwan (Department of Functional Genomics, University of Science and Technology (UST)) ;
  • Kim, Jina (Department of Functional Genomics, University of Science and Technology (UST)) ;
  • Kim, Yong Sung (Department of Functional Genomics, University of Science and Technology (UST)) ;
  • Lee, Daeyoup (Department of Biological Sciences, Korea Advanced Institute of Science and Technology) ;
  • Kang, Suk-Jo (Department of Biological Sciences, Korea Advanced Institute of Science and Technology) ;
  • Kim, Seon-Young (Department of Functional Genomics, University of Science and Technology (UST))
  • Received : 2018.05.21
  • Accepted : 2018.10.18
  • Published : 2018.11.30

Abstract

The stepwise development of T cells from a multipotent precursor is guided by diverse mechanisms, including interactions among lineage-specific transcription factors (TFs) and epigenetic changes, such as DNA methylation and hydroxymethylation, which play crucial roles in mammalian development and lineage commitment. To elucidate the transcriptional networks and epigenetic mechanisms underlying T-cell lineage commitment, we investigated genome-wide changes in gene expression, DNA methylation and hydroxymethylation among populations representing five successive stages of T-cell development (DN3, DN4, DP, $CD4^+$, and $CD8^+$) by performing RNA-seq, MBD-seq and hMeDIP-seq, respectively. The most significant changes in the transcriptomes and epigenomes occurred during the DN4 to DP transition. During the DP stage, many genes involved in chromatin modification were up-regulated and exhibited dramatic changes in DNA hydroxymethylation. We also observed 436 alternative splicing events, and approximately 57% (252) of these events occurred during the DP stage. Many stage-specific, differentially methylated regions were observed near the stage-specific, differentially expressed genes. The dynamic changes in DNA methylation and hydroxymethylation were associated with the recruitment of stage-specific TFs. We elucidated interactive networks comprising TFs, chromatin modifiers, and DNA methylation and hope that this study provides a framework for the understanding of the molecular networks underlying T-cell lineage commitment.

Acknowledgement

Supported by : National Research Foundation (NRF)

References

  1. A Andrews, S. (2010). FastQC: a quality control tool for high throughput sequence data.
  2. Anders, S., and Huber, W. (2010). Differential expression analysis for sequence count data. Genome Biol 11, R106. https://doi.org/10.1186/gb-2010-11-10-r106
  3. Atamas, S.P., Choi, J., Yurovsky, V.V., and White, B. (1996). An alternative splice variant of human IL-4, IL-4 delta 2, inhibits IL-4-stimulated T cell proliferation. J. Immunol. 156, 435-441.
  4. Baek, S.J., Kim, M., Bae, D.H., Kim, J.H., Kim, H.J., Han, M.E., Oh, S.O., Kim, Y.S., and Kim, S.Y. (2016). Integrated epigenomic analyses of enhancer as well as promoter regions in gastric cancer. Oncotarget 7, 25620-25631.
  5. Bernstein, B.E., Meissner, A., and Lander, E.S. (2007). The mammalian epigenome. Cell 128, 669-681. https://doi.org/10.1016/j.cell.2007.01.033
  6. David-Fung, E.S., Butler, R., Buzi, G., Yui, M.A., Diamond, R.A., Anderson, M.K., Rowen, L., and Rothenberg, E.V. (2009). Transcription factor expression dynamics of early T-lymphocyte specification and commitment. Dev. Biol. 325, 444-467. https://doi.org/10.1016/j.ydbio.2008.10.021
  7. Feng, Y., and Rudensky, A.Y. (2015). DNA methylation secures CD4(+) and CD8(+) T cell lineage borders. Nature Immunol. 16, 681-683. https://doi.org/10.1038/ni.3207
  8. Germain, R.N. (2002). T-cell development and the CD4-CD8 lineage decision. Nature Reviews. Immunol. 2, 309-322. https://doi.org/10.1038/nri798
  9. Godfrey, D.I., Kennedy, J., Suda, T., and Zlotnik, A. (1993). A developmental pathway involving four phenotypically and functionally distinct subsets of CD3-CD4-CD8- triple-negative adult mouse thymocytes defined by CD44 and CD25 expression. J. Immunol. 150, 4244-4252.
  10. Guo, J.U., Su, Y., Zhong, C., Ming, G.L., and Song, H. (2011). Hydroxylation of 5-methylcytosine by TET1 promotes active DNA demethylation in the adult brain. Cell 145, 423-434. https://doi.org/10.1016/j.cell.2011.03.022
  11. Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P., Cheng, J.X., Murre, C., Singh, H., and Glass, C.K. (2010). Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576-589. https://doi.org/10.1016/j.molcel.2010.05.004
  12. Hon, G.C., Rajagopal, N., Shen, Y., McCleary, D.F., Yue, F., Dang, M.D., and Ren, B. (2013). Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nat. Genet. 45, 1198-1206. https://doi.org/10.1038/ng.2746
  13. Hon, G.C., Song, C.X., Du, T., Jin, F., Selvaraj, S., Lee, A.Y., Yen, C.A., Ye, Z., Mao, S.Q., Wang, B.A., et al. (2014). 5mC oxidation by Tet2 modulates enhancer activity and timing of transcriptome reprogramming during differentiation. Mol. Cell 56, 286-297. https://doi.org/10.1016/j.molcel.2014.08.026
  14. Huang, G., Zhang, P., Hirai, H., Elf, S., Yan, X., Chen, Z., Koschmieder, S., Okuno, Y., Dayaram, T., Growney, J.D., et al. (2008). PU.1 is a major downstream target of AML1 (RUNX1) in adult mouse hematopoiesis. Nat. Genet. 40, 51-60. https://doi.org/10.1038/ng.2007.7
  15. Huang, Y., Chavez, L., Chang, X., Wang, X., Pastor, W.A., Kang, J., Zepeda-Martinez, J.A., Pape, U.J., Jacobsen, S.E., Peters, B., et al. (2014). Distinct roles of the methylcytosine oxidases Tet1 and Tet2 in mouse embryonic stem cells. P. Nat. Acad. Sci. USA 111, 1361-1366. https://doi.org/10.1073/pnas.1322921111
  16. Ichiyama, K., Chen, T., Wang, X., Yan, X., Kim, B.S., Tanaka, S., Ndiaye-Lobry, D., Deng, Y., Zou, Y., Zheng, P., et al. (2015). The methylcytosine dioxygenase Tet2 promotes DNA demethylation and activation of cytokine gene expression in T cells. Immunity 42, 613-626. https://doi.org/10.1016/j.immuni.2015.03.005
  17. Ip, J.Y., Tong, A., Pan, Q., Topp, J.D., Blencowe, B.J., and Lynch, K.W. (2007). Global analysis of alternative splicing during T-cell activation. RNA 13, 563-572. https://doi.org/10.1261/rna.457207
  18. Kakaradov, B., Arsenio, J., Widjaja, C.E., He, Z., Aigner, S., Metz, P.J., Yu, B., Wehrens, E.J., Lopez, J., Kim, S.H., et al. (2017). Early transcriptional and epigenetic regulation of CD8(+) T cell differentiation revealed by single-cell RNA sequencing. Nat. Immunol. 18, 422-432. https://doi.org/10.1038/ni.3688
  19. Katz, Y., Wang, E.T., Airoldi, E.M., and Burge, C.B. (2010). Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat. Methods 7, 1009-1015. https://doi.org/10.1038/nmeth.1528
  20. Kim, M., and Costello, J. (2017). DNA methylation: an epigenetic mark of cellular memory. Exp. Mol. Med. 49, e322. https://doi.org/10.1038/emm.2017.10
  21. Kim, M., Park, Y.K., Kang, T.W., Lee, S.H., Rhee, Y.H., Park, J.L., Kim, H.J., Lee, D., Lee, D., Kim, S.Y., et al. (2014). Dynamic changes in DNA methylation and hydroxymethylation when hES cells undergo differentiation toward a neuronal lineage. Hum. Mol. Genet. 23, 657-667. https://doi.org/10.1093/hmg/ddt453
  22. Ko, M., An, J., and Rao, A. (2015). DNA methylation and hydroxymethylation in hematologic differentiation and transformation. Curr. Opin. Cell Biol. 37, 91-101. https://doi.org/10.1016/j.ceb.2015.10.009
  23. Komori, H.K., Hart, T., LaMere, S.A., Chew, P.V., and Salomon, D.R. (2015). Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation. J. Immunol. 194, 1565-1579. https://doi.org/10.4049/jimmunol.1401162
  24. Langmead, B., Trapnell, C., Pop, M., and Salzberg, S.L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25. https://doi.org/10.1186/gb-2009-10-3-r25
  25. Lee, P.P., Fitzpatrick, D.R., Beard, C., Jessup, H.K., Lehar, S., Makar, K.W., Perez-Melgosa, M., Sweetser, M.T., Schlissel, M.S., Nguyen, S., et al. (2001). A critical role for Dnmt1 and DNA methylation in T cell development, function, and survival. Immunity 15, 763-774. https://doi.org/10.1016/S1074-7613(01)00227-8
  26. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079. https://doi.org/10.1093/bioinformatics/btp352
  27. Lienhard, M., Grimm, C., Morkel, M., Herwig, R., and Chavez, L. (2014). MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments. Bioinformatics 30, 284-286. https://doi.org/10.1093/bioinformatics/btt650
  28. Lister, R., Pelizzola, M., Dowen, R.H., Hawkins, R.D., Hon, G., Tonti-Filippini, J., Nery, J.R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009). Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315-322. https://doi.org/10.1038/nature08514
  29. Mallory, M.J., Allon, S.J., Qiu, J., Gazzara, M.R., Tapescu, I., Martinez, N.M., Fu, X.D., and Lynch, K.W. (2015). Induced transcription and stability of CELF2 mRNA drives widespread alternative splicing during T-cell signaling. P. Nat. Acad. Sci. USA 112, E2139-2148. https://doi.org/10.1073/pnas.1423695112
  30. Martinez, N.M., Agosto, L., Qiu, J., Mallory, M.J., Gazzara, M.R., Barash, Y., Fu, X.D., and Lynch, K.W. (2015). Widespread JNK-dependent alternative splicing induces a positive feedback loop through CELF2-mediated regulation of MKK7 during T-cell activation. Genes Dev. 29, 2054-2066. https://doi.org/10.1101/gad.267245.115
  31. Mingueneau, M., Kreslavsky, T., Gray, D., Heng, T., Cruse, R., Ericson, J., Bendall, S., Spitzer, M.H., Nolan, G.P., Kobayashi, K., et al. (2013). The transcriptional landscape of ${\alpha}{\beta}$ T cell differentiation. Nat. Immunol. 14, 619-632. https://doi.org/10.1038/ni.2590
  32. Naito, T., Tanaka, H., Naoe, Y., and Taniuchi, I. (2011). Transcriptional control of T-cell development. Int. Immunol. 23, 661-668. https://doi.org/10.1093/intimm/dxr078
  33. Samstein, R.M., Arvey, A., Josefowicz, S.Z., Peng, X., Reynolds, A., Sandstrom, R., Neph, S., Sabo, P., Kim, J.M., Liao, W., et al. (2012). Foxp3 exploits a pre-existent enhancer landscape for regulatory T cell lineage specification. Cell 151, 153-166. https://doi.org/10.1016/j.cell.2012.06.053
  34. Sellars, M., Huh, J.R., Day, K., Issuree, P.D., Galan, C., Gobeil, S., Absher, D., Green, M.R., and Littman, D.R. (2015). Regulation of DNA methylation dictates Cd4 expression during the development of helper and cytotoxic T cell lineages. Nat. Immunol. 16, 746-754. https://doi.org/10.1038/ni.3198
  35. Serandour, A.A., Avner, S., Oger, F., Bizot, M., Percevault, F., Lucchetti-Miganeh, C., Palierne, G., Gheeraert, C., Barloy-Hubler, F., Peron, C.L., et al. (2012). Dynamic hydroxymethylation of deoxyribonucleic acid marks differentiation-associated enhancers. Nucleic Acids Res. 40, 8255-8265. https://doi.org/10.1093/nar/gks595
  36. Smith, Z.D., and Meissner, A. (2013). DNA methylation: roles in mammalian development. Nature reviews. Genetics 14, 204-220. https://doi.org/10.1038/nrg3354
  37. Stadler, M.B., Murr, R., Burger, L., Ivanek, R., Lienert, F., Scholer, A., van Nimwegen, E., Wirbelauer, C., Oakeley, E.J., Gaidatzis, D., et al. (2011). DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480, 490-495.
  38. Swamy, M., Pathak, S., Grzes, K.M., Damerow, S., Sinclair, L.V., van Aalten, D.M., and Cantrell, D.A. (2016). Glucose and glutamine fuel protein O-GlcNAcylation to control T cell self-renewal and malignancy. Nat. Immunol. 17, 712-720. https://doi.org/10.1038/ni.3439
  39. Team, R.C. (2013). R: A language and environment for statistical computing.
  40. Trapnell, C., Pachter, L., and Salzberg, S.L. (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105-1111. https://doi.org/10.1093/bioinformatics/btp120
  41. Tsagaratou, A., Aijo, T., Lio, C.W., Yue, X., Huang, Y., Jacobsen, S.E., Lahdesmaki, H., and Rao, A. (2014). Dissecting the dynamic changes of 5-hydroxymethylcytosine in T-cell development and differentiation. P. Nat. Acad. Sci. USA 111, E3306-3315. https://doi.org/10.1073/pnas.1412327111
  42. Villani, A.C., Satija, R., Reynolds, G., Sarkizova, S., Shekhar, K., Fletcher, J., Griesbeck, M., Butler, A., Zheng, S., Lazo, S., et al. (2017). Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356.
  43. von Boehmer, H., Teh, H.S., and Kisielow, P. (1989). The thymus selects the useful, neglects the useless and destroys the harmful. Immunol. Today 10, 57-61. https://doi.org/10.1016/0167-5699(89)90307-1
  44. Wang, E.T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S.F., Schroth, G.P., and Burge, C.B. (2008). Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476. https://doi.org/10.1038/nature07509
  45. Wilson, C.B., Makar, K.W., Shnyreva, M., and Fitzpatrick, D.R. (2005). DNA methylation and the expanding epigenetics of T cell lineage commitment. Semin. Immunol. 17, 105-119. https://doi.org/10.1016/j.smim.2005.01.005
  46. Yu, M., Hon, G.C., Szulwach, K.E., Song, C.X., Zhang, L., Kim, A., Li, X., Dai, Q., Shen, Y., Park, B., et al. (2012). Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 149, 1368-1380. https://doi.org/10.1016/j.cell.2012.04.027
  47. Yui, M.A., and Rothenberg, E.V. (2014). Developmental gene networks: a triathlon on the course to T cell identity. Nat. Rev. Immunol. 14, 529-545. https://doi.org/10.1038/nri3702
  48. Zhang, J.A., Mortazavi, A., Williams, B.A., Wold, B.J., and Rothenberg, E.V. (2012). Dynamic transformations of genome-wide epigenetic marking and transcriptional control establish T cell identity. Cell 149, 467-482. https://doi.org/10.1016/j.cell.2012.01.056
  49. Zhao, M., Wang, J., Liao, W., Li, D., Li, M., Wu, H., Zhang, Y., Gershwin, M.E., and Lu, Q. (2016). Increased 5- hydroxymethylcytosine in CD4(+) T cells in systemic lupus erythematosus. J. Autoimmun. 69, 64-73. https://doi.org/10.1016/j.jaut.2016.03.001