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Domains of genome-wide gene expression dysregulation in Down’s syndrome

Nature volume 508, pages 345–350 (2014)Cite this article

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A Corrigendum to this article was published on 02 December 2015

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Abstract

Trisomy 21 is the most frequent genetic cause of cognitive impairment. To assess the perturbations of gene expression in trisomy 21, and to eliminate the noise of genomic variability, we studied the transcriptome of fetal fibroblasts from a pair of monozygotic twins discordant for trisomy 21. Here we show that the differential expression between the twins is organized in domains along all chromosomes that are either upregulated or downregulated. These gene expression dysregulation domains (GEDDs) can be defined by the expression level of their gene content, and are well conserved in induced pluripotent stem cells derived from the twins’ fibroblasts. Comparison of the transcriptome of the Ts65Dn mouse model of Down’s syndrome and normal littermate mouse fibroblasts also showed GEDDs along the mouse chromosomes that were syntenic in human. The GEDDs correlate with the lamina-associated (LADs) and replication domains of mammalian cells. The overall position of LADs was not altered in trisomic cells; however, the H3K4me3 profile of the trisomic fibroblasts was modified and accurately followed the GEDD pattern. These results indicate that the nuclear compartments of trisomic cells undergo modifications of the chromatin environment influencing the overall transcriptome, and that GEDDs may therefore contribute to some trisomy 21 phenotypes.

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Figure 1: Gene expression fold change is organized in chromosomal domains.
Figure 2: Weakly and highly expressed genes contribute differently to the domains.
Figure 3: GEDDs are conserved in iPS cells.
Figure 4: GEDDs are conserved in Ts65Dn mouse model for Down’s syndrome.
Figure 5: Correlation with LADs.
Figure 6: Correlation with replication time domains and H3K4me3 mark.

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Gene Expression Omnibus

Data deposits

All sequencing data have been deposited in the Gene Expression Omnibus (GEO) data repository under accession number GSE55426.

Change history

  • 02 December 2015

    Nature 508, 345–350 (2014); doi:10.1038/nature13200 Owing to a labelling error in the input files, one of the two replicate data sets used for Fig. 5d and e and Supplementary Fig. 6d of this Article was incorrect. We have now repeated the analysis with a correct, independent replicate experiment. This confirms our previous conclusion that there are no detectable differences in nuclear lamina interactions between the normal and trisomy 21 twin cells.

References

  1. Antonarakis, S. E., Lyle, R., Dermitzakis, E. T., Reymond, A. & Deutsch, S. Chromosome 21 and down syndrome: from genomics to pathophysiology. Nature Rev. Genet. 5, 725–738 (2004)

    Article  CAS  PubMed  Google Scholar 

  2. Korenberg, J. R. et al. Down syndrome phenotypes: the consequences of chromosomal imbalance. Proc. Natl Acad. Sci. USA 91, 4997–5001 (1994)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  3. Pritchard, M. A. & Kola, I. The “gene dosage effect” hypothesis versus the “amplified developmental instability” hypothesis in Down syndrome. J. Neural Transm. Suppl. 57, 293–303 (1999)

    CAS  PubMed  Google Scholar 

  4. Lyle, R. et al. Genotype-phenotype correlations in Down syndrome identified by array CGH in 30 cases of partial trisomy and partial monosomy chromosome 21. Eur. J. Hum. Genet. 17, 454–466 (2009)

    Article  CAS  PubMed  Google Scholar 

  5. Shapiro, B. L. Down syndrome–a disruption of homeostasis. Am. J. Med. Genet. 14, 241–269 (1983)

    Article  CAS  PubMed  Google Scholar 

  6. Letourneau, A. & Antonarakis, S. E. Genomic determinants in the phenotypic variability of Down syndrome. Prog. Brain Res. 197, 15–28 (2012)

    Article  CAS  PubMed  Google Scholar 

  7. Davisson, M. T. et al. Segmental trisomy as a mouse model for Down syndrome. Prog. Clin. Biol. Res. 384, 117–133 (1993)

    CAS  PubMed  Google Scholar 

  8. Reeves, R. H. et al. A mouse model for Down syndrome exhibits learning and behaviour deficits. Nature Genet. 11, 177–184 (1995)

    Article  CAS  PubMed  Google Scholar 

  9. Chrast, R. et al. Mice trisomic for a bacterial artificial chromosome with the single-minded 2 gene (Sim2) show phenotypes similar to some of those present in the partial trisomy 16 mouse models of Down syndrome. Hum. Mol. Genet. 9, 1853–1864 (2000)

    Article  CAS  PubMed  Google Scholar 

  10. Ahn, K. J. et al. DYRK1A BAC transgenic mice show altered synaptic plasticity with learning and memory defects. Neurobiol. Dis. 22, 463–472 (2006)

    Article  CAS  PubMed  Google Scholar 

  11. Costa, V. et al. Massive-scale RNA-Seq analysis of non ribosomal transcriptome in human trisomy 21. PLoS ONE 6, e18493 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Esposito, G. et al. Genomic and functional profiling of human Down syndrome neural progenitors implicates S100B and aquaporin 4 in cell injury. Hum. Mol. Genet. 17, 440–457 (2008)

    Article  CAS  PubMed  Google Scholar 

  13. Lockstone, H. E. et al. Gene expression profiling in the adult Down syndrome brain. Genomics 90, 647–660 (2007)

    Article  CAS  PubMed  Google Scholar 

  14. Sommer, C. A., Pavarino-Bertelli, E. C., Goloni-Bertollo, E. M. & Henrique-Silva, F. Identification of dysregulated genes in lymphocytes from children with Down syndrome. Genome 51, 19–29 (2008)

    Article  CAS  PubMed  Google Scholar 

  15. Prandini, P. et al. Natural gene-expression variation in Down syndrome modulates the outcome of gene-dosage imbalance. Am. J. Hum. Genet. 81, 252–263 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Deutsch, S. et al. Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes. Hum. Mol. Genet. 14, 3741–3749 (2005)

    Article  CAS  PubMed  Google Scholar 

  17. Dahoun, S. et al. Monozygotic twins discordant for trisomy 21 and maternal 21q inheritance: a complex series of events. Am. J. Med. Genet. A. 146A, 2086–2093 (2008)

    Article  CAS  PubMed  Google Scholar 

  18. Marco-Sola, S., Sammeth, M., Guigo, R. & Ribeca, P. The GEM mapper: fast, accurate and versatile alignment by filtration. Nature Methods 9, 1185–1188 (2012)

    Article  CAS  PubMed  Google Scholar 

  19. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010)

    Article  CAS  PubMed  Google Scholar 

  20. Huang da, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4, 44–57 (2009)

    Article  PubMed  CAS  Google Scholar 

  21. Ram, G. & Chinen, J. Infections and immunodeficiency in Down syndrome. Clin. Exp. Immunol. 164, 9–16 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Caron, H. et al. The human transcriptome map: clustering of highly expressed genes in chromosomal domains. Science 291, 1289–1292 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  23. Gierman, H. J. et al. Domain-wide regulation of gene expression in the human genome. Genome Res. 17, 1286–1295 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hibaoui, Y. et al. Modelling and rescuing neurodevelopmental defect of Down syndrome using induced pluripotent stem cells from monozygotic twins discordant for trisomy 21. EMBO Mol. Med. 6, 259–277 (2014)

    Article  CAS  PubMed  Google Scholar 

  25. Duchon, A. et al. Identification of the translocation breakpoints in the Ts65Dn and Ts1Cje mouse lines: relevance for modeling Down syndrome. Mamm. Genome 22, 674–684 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lappalainen, T. et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506–511 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  27. Guelen, L. et al. Domain organization of human chromosomes revealed by mapping of nuclear lamina interactions. Nature 453, 948–951 (2008)

    Article  ADS  CAS  PubMed  Google Scholar 

  28. Peric-Hupkes, D. et al. Molecular maps of the reorganization of genome-nuclear lamina interactions during differentiation. Mol. Cell 38, 603–613 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zullo, J. M. et al. DNA sequence-dependent compartmentalization and silencing of chromatin at the nuclear lamina. Cell 149, 1474–1487 (2012)

    Article  CAS  PubMed  Google Scholar 

  30. Akhtar, A. & Gasser, S. M. The nuclear envelope and transcriptional control. Nature Rev. Genet. 8, 507–517 (2007)

    Article  CAS  PubMed  Google Scholar 

  31. Vogel, M. J., Peric-Hupkes, D. & van Steensel, B. Detection of in vivo protein-DNA interactions using DamID in mammalian cells. Nature Protocols 2, 1467–1478 (2007)

    Article  CAS  PubMed  Google Scholar 

  32. Hansen, R. S. et al. Sequencing newly replicated DNA reveals widespread plasticity in human replication timing. Proc. Natl Acad. Sci. USA 107, 139–144 (2010)

    Article  ADS  CAS  PubMed  Google Scholar 

  33. Gilbert, D. M. Replication timing and transcriptional control: beyond cause and effect. Curr. Opin. Cell Biol. 14, 377–383 (2002)

    Article  CAS  PubMed  Google Scholar 

  34. Hiratani, I. et al. Global reorganization of replication domains during embryonic stem cell differentiation. PLoS Biol. 6, e245 (2008)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Pope, B. D. et al. Replication-timing boundaries facilitate cell-type and species-specific regulation of a rearranged human chromosome in mouse. Hum. Mol. Genet. 21, 4162–4170 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Gu, H. et al. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nature Protocols 6, 468–481 (2011)

    Article  CAS  PubMed  Google Scholar 

  37. Barski, A. et al. High-resolution profiling of histone methylations in the human genome. Cell 129, 823–837 (2007)

    Article  CAS  PubMed  Google Scholar 

  38. Thurman, R. E. et al. The accessible chromatin landscape of the human genome. Nature 489, 75–82 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genet. 43, 491–498 (2011)

    Article  CAS  PubMed  Google Scholar 

  40. Singh, M. P., Wijeratne, S. S. & Zempleni, J. Biotinylation of lysine 16 in histone H4 contributes toward nucleosome condensation. Arch. Biochem. Biophys. 529, 105–111 (2013)

    Article  CAS  PubMed  Google Scholar 

  41. Pestinger, V., Wijeratne, S. S., Rodriguez-Melendez, R. & Zempleni, J. Novel histone biotinylation marks are enriched in repeat regions and participate in repression of transcriptionally competent genes. J. Nutr. Biochem. 22, 328–333 (2011)

    Article  CAS  PubMed  Google Scholar 

  42. Narang, M. A., Dumas, R., Ayer, L. M. & Gravel, R. A. Reduced histone biotinylation in multiple carboxylase deficiency patients: a nuclear role for holocarboxylase synthetase. Hum. Mol. Genet. 13, 15–23 (2004)

    Article  CAS  PubMed  Google Scholar 

  43. Postnikov, Y. & Bustin, M. Regulation of chromatin structure and function by HMGN proteins. Biochim. Biophys. Acta 1799, 62–68 (2010)

    Article  CAS  PubMed  Google Scholar 

  44. Zhu, N. & Hansen, U. Transcriptional regulation by HMGN proteins. Biochim. Biophys. Acta 1799, 74–79 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Canzonetta, C. et al. DYRK1A-dosage imbalance perturbs NRSF/REST levels, deregulating pluripotency and embryonic stem cell fate in Down syndrome. Am. J. Hum. Genet. 83, 388–400 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Huang, H., Rambaldi, I., Daniels, E. & Featherstone, M. Expression of the Wdr9 gene and protein products during mouse development. Dev. Dyn. 227, 608–614 (2003)

    Article  CAS  PubMed  Google Scholar 

  47. Bakshi, R. et al. The human SWI/SNF complex associates with RUNX1 to control transcription of hematopoietic target genes. J. Cell. Physiol. 225, 569–576 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Contestabile, A. et al. Cell cycle alteration and decreased cell proliferation in the hippocampal dentate gyrus and in the neocortical germinal matrix of fetuses with Down syndrome and in Ts65Dn mice. Hippocampus 17, 665–678 (2007)

    Article  PubMed  Google Scholar 

  49. Williams, B. R. et al. Aneuploidy affects proliferation and spontaneous immortalization in mammalian cells. Science 322, 703–709 (2008)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. Voss, T. C. & Hager, G. L. Dynamic regulation of transcriptional states by chromatin and transcription factors. Nature Rev. Genet. 15, 69–81 (2014)

    Article  CAS  PubMed  Google Scholar 

  51. Dimas, A. S. et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science 325, 1246–1250 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  52. Takahashi, K. et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861–872 (2007)

    Article  CAS  PubMed  Google Scholar 

  53. Grad, I. et al. NANOG priming before full reprogramming may generate germ cell tumours. Eur. Cells Mat. 22, 258–274 (2011)

    Article  ADS  CAS  Google Scholar 

  54. Knowles, D. G., Roder, M., Merkel, A. & Guigo, R. Grape RNA-Seq analysis pipeline environment. Bioinformatics 29, 614–621 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Akalin, A. et al. methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol. 13, R87 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  57. John, S. et al. Genome-scale mapping of DNase I hypersensitivity. Curr. Protoc. Mol. Biol. Ch. 27, Unit 21 27. (2013)

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Acknowledgements

We thank the Swiss National Science Foundation (SNF-144082), the European Research Council (ERC-249968), AnEUploidy and BluePrint EU grants, the Lejeune, and ChildCare foundations for supporting the S.E.A. laboratory. The laboratories of R.G. were supported by Spanish MICINN (BIO2011-26205) and ERC-294653, B.v.S. by NWO-ALW-VICI, Y.He. by CNRS, INSERM, University of Strasbourg and ANR-10-INBS-07, J.A.S. by NIH U54HG007010, and A.F. by Genico and Ernest Boninchi foundation. We thank S. Dahoun and J. L. Blouin for the discordant twins sample collection.

Author information

Author notes

  1. Audrey Letourneau and Federico A. Santoni: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Genetic Medicine and Development, University of Geneva Medical School, University Hospitals of Geneva, 1211 Geneva, Switzerland,

    Audrey Letourneau, Federico A. Santoni, Ximena Bonilla, M. Reza Sailani, Marco Garieri, Konstantin Popadin, Emilie Falconnet, Maryline Gagnebin, Corinne Gehrig, Anne Vannier, Michel Guipponi, Daniel Robyr, Eugenia Migliavacca, Christelle Borel & Stylianos E. Antonarakis

  2. Center for Genomic Regulation, University Pompeu Fabra, 08003 Barcelona, Spain,

    David Gonzalez & Roderic Guigo

  3. Division of Gene Regulation, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands,

    Jop Kind & Bas van Steensel

  4. AneuPath 21, Institut de Génétique Biologie Moléculaire et Cellulaire, Translational medicine and Neuroscience program, IGBMC, ICS, PHENOMIN, CNRS, INSERM, Université de Strasbourg, UMR7104, UMR964, 1 rue Laurent Fries, 67404 Illkirch, France,

    Claire Chevalier & Yann Herault

  5. Department of Genome Sciences, University of Washington, Seattle, 98195, Washington, USA

    Robert Thurman, Richard S. Sandstrom & John A. Stamatoyannopoulos

  6. Department of Obstetrics and Gynecology, Stem Cell Research Laboratory, Geneva University Hospitals, 1211 Geneva, Switzerland,

    Youssef Hibaoui & Anis Feki

  7. FASTERIS SA, 1228 Plan-les-Ouates, Switzerland,

    Laurent Farinelli

  8. Swiss Institute of Bioinfomatics, 1211 Geneva, Switzerland,

    Eugenia Migliavacca

  9. DOE Joint Genome Institute, Walnut Creek, 94598, California, USA

    Samuel Deutsch

  10. iGE3 Institute of Genetics and Genomics of Geneva, 1211 Geneva, Switzerland,

    Stylianos E. Antonarakis

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  1. Audrey Letourneau
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Contributions

The project was coordinated by S.E.A. A.L. coordinated/undertook the main laboratory work. F.A.S. coordinated/undertook the main bioinformatics/statistical analyses. X.B. performed ChIP-seq experiments. M.R.S. performed DNA methylation, A.L., F.A.S., M.G., R.G. and D.G. processed NGS data. J.K. and B.v.S. performed DamID experiments. C.C. and Y.He. maintained the mouse colony and contributed mouse samples. R.T., R.S.S. and J.A.S. performed DNase experiments; Y.Hi. and A.F. derived the iPS cells; and K.P., D.R. R.G. and E.M. performed additional statistical analyses. E.F., M.G., C.G., A.V., M.G., L.F., C.B. and S.D. assisted with wet lab experiments and contributed to performing NGS experiments. The main findings were interpreted by S.E.A., A.L. and F.A.S., who also wrote the manuscript. All authors made comments on the manuscript.

Corresponding author

Correspondence to Stylianos E. Antonarakis.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Figures

This file contains Supplementary Figures 1-12. (PDF 8032 kb)

Supplementary Table 1

Differential expression analysis results as given by EdgeR. For each gene, the table gives gene coordinates, Ensembl gene ID, gene category, gene symbol, log2 gene expression fold change (T1DS/T2N, all replicates), log2 counts-per-million (logCPM), p-value and false discovery rate (FDR). (XLSX 4151 kb)

Supplementary Table 2

List of GEDDs identified in the twins’ fibroblasts (Rep0). Table gives the domain ID, the names and coordinates of the first genes at the left and right borders of each GEDD, the number of genes included in the domain and the median log2 fold change within the domain. GEDDs were obtained with a smoothing bandwidth of 3%. (XLSX 38 kb)

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Letourneau, A., Santoni, F., Bonilla, X. et al. Domains of genome-wide gene expression dysregulation in Down’s syndrome. Nature 508, 345–350 (2014). https://doi.org/10.1038/nature13200

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