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Scientifica
Volume 2012 (2012), Article ID 437956, 11 pages
http://dx.doi.org/10.6064/2012/437956
Review Article

Genome-Scale Technology Driven Advances to Research into Normal and Malignant Haematopoiesis

Department of Haematology, Cambridge Institute for Medical Research, Cambridge University and Wellcome Trust and MRC Stem Cell Institute, Hills Road, Cambridge CB2 0XY, UK

Received 30 September 2012; Accepted 16 December 2012

Academic Editors: J. L. Badano, F. Chiarini, J. Kennell, T. Te Kronnie, H.-Y. Wang, and G. Zafarana

Copyright © 2012 Berthold Göttgens. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. Bryder, D. J. Rossi, and I. L. Weissman, “Hematopoietic stem cells: the paradigmatic tissue-specific stem cell,” American Journal of Pathology, vol. 169, no. 2, pp. 338–346, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. D. Miranda-Saavedra and B. Göttgens, “Transcriptional regulatory networks in haematopoiesis,” Current Opinion in Genetics and Development, vol. 18, no. 6, pp. 530–535, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. S. H. Orkin and L. I. Zon, “Hematopoiesis: an evolving paradigm for stem cell biology,” Cell, vol. 132, no. 4, pp. 631–644, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. J. E. Pimanda and G. Berthold, “Gene regulatory networks governing haematopoietic stem cell development and identity,” International Journal of Developmental Biology, vol. 54, no. 6-7, pp. 1201–1211, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. N. K. Wilson, F. J. Calero-Nieto, R. Ferreira, and B. Göttgens, “Transcriptional regulation of haematopoietic transcription factors,” Stem Cell Research & Therapy, vol. 2, no. 1, article 6, 2011. View at Google Scholar
  6. M. Osawa, K. I. Hanada, H. Hamada, and H. Nakauchi, “Long-term lymphohematopoietic reconstitution by a single CD34- low/negative hematopoietic stem cell,” Science, vol. 273, no. 5272, pp. 242–245, 1996. View at Google Scholar · View at Scopus
  7. D. G. Tenen, “Disruption of differentiation in human cancer: AML shows the way,” Nature Reviews Cancer, vol. 3, no. 2, pp. 89–101, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. F. Rosenbauer and D. G. Tenen, “Transcription factors in myeloid development: balancing differentiation with transformation,” Nature Reviews Immunology, vol. 7, no. 2, pp. 105–117, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. D. G. Tenen, R. Hromas, J. D. Licht, and D. E. Zhang, “Transcription factors, normal myeloid development, and leukemia,” Blood, vol. 90, no. 2, pp. 489–519, 1997. View at Google Scholar · View at Scopus
  10. S. Koschmieder, F. Rosenbauer, U. Steidl, B. M. Owens, and D. G. Tenen, “Role of transcription factors C/EBPα and PU.1 in normal hematopoiesis and leukemia,” International Journal of Hematology, vol. 81, no. 5, pp. 368–377, 2005. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Shima and I. Kitabayashi, “Deregulated transcription factors in leukemia,” International Journal of Hematology, vol. 94, no. 2, pp. 134–141, 2011. View at Google Scholar
  12. E. S. Lander, L. M. Linton, B. Birren, et al., “Initial sequencing and analysis of the human genome,” Nature, vol. 409, no. 6822, pp. 860–921, 2001. View at Google Scholar
  13. J. C. Venter, M. D. Adams, E. W. Myers, et al., “The sequence of the human genome,” Science, vol. 291, no. 5507, pp. 1304–1351, 2001. View at Google Scholar
  14. K. Basso, A. A. Margolin, G. Stolovitzky, U. Klein, R. Dalla-Favera, and A. Califano, “Reverse engineering of regulatory networks in human B cells,” Nature Genetics, vol. 37, no. 4, pp. 382–390, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. L. Agnelli, M. Forcato, F. Ferrari, et al., “The reconstruction of transcriptional networks reveals critical genes with implications for clinical outcome of multiple myeloma,” Clinical Cancer Research, vol. 17, no. 23, pp. 7402–7412, 2011. View at Google Scholar
  16. J. D. Allen, Y. Xie, M. Chen, L. Girard, and G. Xiao, “Comparing statistical methods for constructing large scale gene networks,” PLoS One, vol. 7, no. 1, article e29348, 2012. View at Google Scholar
  17. G. Altay and F. Emmert-Streib, “Inferring the conservative causal core of gene regulatory networks,” BMC Systems Biology, vol. 4, article 132, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. K. Basso, M. Saito, P. Sumazin et al., “Integrated biochemical and computational approach identifies BCL6 direct target genes controlling multiple pathways in normal germinal center B cells,” Blood, vol. 115, no. 5, pp. 975–984, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Cadeiras, M. von Bayern, A. Sinha et al., “Drawing networks of rejection—a systems biological approach to the identification of candidate genes in heart transplantation,” Journal of Cellular and Molecular Medicine, vol. 15, no. 4, pp. 949–956, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. M. Grimaldi, R. Visintainer, and G. Jurman, “RegnANN: reverse engineering gene networks using artificial neural networks,” PLoS One, vol. 6, no. 12, article e28646, 2011. View at Google Scholar
  21. R. Mahdi, A. S. Madduri, G. Wang et al., “Empirical Bayes conditional independence graphs for regulatory network recovery,” Bioinformatics, vol. 28, no. 15, pp. 2029–2036, 2012. View at Google Scholar
  22. A. A. Margolin, I. Nemenman, K. Basso et al., “ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context,” BMC Bioinformatics, vol. 7, supplement 1, article S7, 2006. View at Publisher · View at Google Scholar · View at Scopus
  23. A. A. Margolin, K. Wang, W. K. Lim, M. Kustagi, I. Nemenman, and A. Califano, “Reverse engineering cellular networks,” Nature Protocols, vol. 1, no. 2, pp. 662–671, 2006. View at Publisher · View at Google Scholar · View at Scopus
  24. P. E. Meyer, K. Kontos, F. Lafitte, and G. Bontempi, “Information-theoretic inference of large transcriptional regulatory networks,” Eurasip Journal on Bioinformatics and Systems Biology, vol. 2007, Article ID 79879, 2007. View at Publisher · View at Google Scholar · View at Scopus
  25. N. Novershtern, A. Subramanian, L. N. Lawton et al., “Densely interconnected transcriptional circuits control cell states in human hematopoiesis,” Cell, vol. 144, no. 2, pp. 296–309, 2011. View at Publisher · View at Google Scholar · View at Scopus
  26. N. A. Watkins, A. Gusnanto, B. De Bono et al., “A HaemAtlas: characterizing gene expression in differentiated human blood cells,” Blood, vol. 113, no. 19, pp. e1–e9, 2009. View at Publisher · View at Google Scholar · View at Scopus
  27. S. M. Chambers, N. C. Boles, K. Y. K. Lin et al., “Hematopoietic fingerprints: an expression database of stem cells and their progeny,” Cell Stem Cell, vol. 1, no. 5, pp. 578–591, 2007. View at Publisher · View at Google Scholar · View at Scopus
  28. D. Miranda-Saavedra, S. De, M. W. Trotter, S. A. Teichmann, and B. Göttgens, “BloodExpress: a database of gene expression in mouse haematopoiesis,” Nucleic Acids Research, vol. 37, no. 1, pp. D873–D879, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. J. Seita, D. Sahoo, D. J. Rossi et al., “Gene expression commons: an open platform for absolute gene expression profiling,” PLoS One, vol. 7, no. 7, article e40321, 2012. View at Google Scholar
  30. F. O. Bagger, N. Rapin, K. Theilgaard-Mönch, et al., “HemaExplorer: a Web server for easy and fast visualization of gene expression in normal and malignant hematopoiesis,” Blood, vol. 119, no. 26, pp. 6394–6395, 2012. View at Google Scholar
  31. A. A. Alizadeh, M. B. Elsen, R. E. Davis et al., “Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling,” Nature, vol. 403, no. 6769, pp. 503–511, 2000. View at Publisher · View at Google Scholar · View at Scopus
  32. A. Andersson, C. Ritz, D. Lindgren et al., “Microarray-based classification of a consecutive series of 121 childhood acute leukemias: prediction of leukemic and genetic subtype as well as of minimal residual disease status,” Leukemia, vol. 21, no. 6, pp. 1198–1203, 2007. View at Publisher · View at Google Scholar · View at Scopus
  33. B. V. Balgobind, M. M. van den Heuvel-Eibrink, R. X. De Menezes et al., “Evaluation of gene expression signatures predictive of cytogenetic and molecular subtypes of pediatric acute myeloid leukemia,” Haematologica, vol. 96, no. 2, pp. 221–230, 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. A. Barski, S. Cuddapah, K. Cui et al., “High-resolution profiling of histone methylations in the human genome,” Cell, vol. 129, no. 4, pp. 823–837, 2007. View at Publisher · View at Google Scholar · View at Scopus
  35. K. M. Bernt, N. Zhu, A. U. Sinha et al., “MLL-rearranged leukemia is dependent on aberrant H3K79 methylation by DOT1L,” Cancer Cell, vol. 20, no. 1, pp. 66–78, 2011. View at Publisher · View at Google Scholar · View at Scopus
  36. M. Camós, J. Esteve, P. Jares et al., “Gene expression profiling of acute myeloid leukemia with translocation t(8;16)(p11;p13) and MYST3-CREBBP rearrangement reveals a distinctive signature with a specific pattern of HOX gene expression,” Cancer Research, vol. 66, no. 14, pp. 6947–6954, 2006. View at Publisher · View at Google Scholar · View at Scopus
  37. E. Chen, P. A. Beer, A. L. Godfrey et al., “Distinct clinical phenotypes associated with JAK2V617F reflect differential STAT1 signaling,” Cancer Cell, vol. 18, no. 5, pp. 524–535, 2010. View at Publisher · View at Google Scholar · View at Scopus
  38. E. Coustan-Smith, C. G. Mullighan, M. Onciu et al., “Early T-cell precursor leukaemia: a subtype of very high-risk acute lymphoblastic leukaemia,” The Lancet Oncology, vol. 10, no. 2, pp. 147–156, 2009. View at Publisher · View at Google Scholar · View at Scopus
  39. N. C. Gutiérrez, R. López-Pérez, J. M. Hernández, et al., “Gene expression profile reveals deregulation of genes with relevant functions in the different subclasses of acute myeloid leukemia,” Leukemia, vol. 19, no. 3, pp. 402–409, 2005. View at Google Scholar
  40. I. Homminga, R. Pieters, A. W. Langerak et al., “Integrated transcript and genome analyses reveal NKX2-1 and MEF2C as potential oncogenes in T cell acute lymphoblastic leukemia,” Cancer Cell, vol. 19, no. 4, pp. 484–497, 2011. View at Publisher · View at Google Scholar · View at Scopus
  41. L. Huang, K. Zhou, Y. Yang et al., “FLT3-ITD-associated gene-expression signatures in NPM1-mutated cytogenetically normal acute myeloid leukemia,” International Journal of Hematology, vol. 96, no. 2, pp. 234–240, 2012. View at Google Scholar
  42. A. Kohlmann, C. Schoch, S. Schnittger et al., “Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients,” Leukemia, vol. 18, no. 1, pp. 63–71, 2004. View at Publisher · View at Google Scholar · View at Scopus
  43. Z. Li, W. Zhang, M. Wu et al., “Gene expression-based classification and regulatory networks of pediatric acute lymphoblastic leukemia,” Blood, vol. 114, no. 20, pp. 4486–4493, 2009. View at Publisher · View at Google Scholar · View at Scopus
  44. J. Nordlund, A. Kiialainen, O. Karlberg, et al., “Digital gene expression profiling of primary acute lymphoblastic leukemia cells,” Leukemia, vol. 26, no. 6, pp. 1218–1227, 2012. View at Google Scholar
  45. I. Oschlies, W. Klapper, M. Zimmermann et al., “Diffuse large B-cell lymphoma in pediatric patients belongs predominantly to the germinal-center type B-cell lymphomas: a clinicopathologic analysis of cases included in the German BFM (Berlin-Frankfurt-Münster) Multicenter Trial,” Blood, vol. 107, no. 10, pp. 4047–4052, 2006. View at Publisher · View at Google Scholar · View at Scopus
  46. A. Rosenwald, A. A. Alizadeh, G. Widhopf et al., “Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia,” Journal of Experimental Medicine, vol. 194, no. 11, pp. 1639–1647, 2001. View at Publisher · View at Google Scholar · View at Scopus
  47. M. E. Ross, X. Zhou, G. Song et al., “Classification of pediatric acute lymphoblastic leukemia by gene expression profiling,” Blood, vol. 102, no. 8, pp. 2951–2959, 2003. View at Publisher · View at Google Scholar · View at Scopus
  48. C. Schoch, W. Kern, A. Kohlmann, W. Hiddemann, S. Schnittger, and T. Haferlach, “Acute myeloid leukemia with a complex aberrant karyotype is a distinct biological entity characterized by genomic imbalances and a specific gene expression profile,” Genes Chromosomes and Cancer, vol. 43, no. 3, pp. 227–238, 2005. View at Publisher · View at Google Scholar · View at Scopus
  49. F. P. G. Silva, S. M. A. Swagemakers, C. Erpelinck-Verschueren et al., “Gene expression profiling of minimally differentiated acute myeloid leukemia: M0 is a distinct entity subdivided by RUNX1 mutation status,” Blood, vol. 114, no. 14, pp. 3001–3007, 2009. View at Publisher · View at Google Scholar · View at Scopus
  50. C. Curtis, S. P. Shah, S. F. Chin, et al., “The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups,” Nature, vol. 486, no. 7403, pp. 346–352, 2012. View at Google Scholar
  51. F. J. Calero-Nieto, A. D. Wood, N. K. Wilson, S. Kinston, J. R. Landry, and B. Göttgens, “Transcriptional regulation of Elf-1: locus-wide analysis reveals four distinct promoters, a tissue-specific enhancer, control by PU.1 and the importance of Elf-1 downregulation for erythroid maturation,” Nucleic Acids Research, vol. 38, no. 19, pp. 6363–6374, 2010. View at Publisher · View at Google Scholar · View at Scopus
  52. R. K. Hyde, Y. Kamikubo, S. Anderson et al., “Cbfb/Runx1 repression-independent blockage of differentiation and accumulation of Csf2rb-expressing cells by Cbfb-MYH11,” Blood, vol. 115, no. 7, pp. 1433–1443, 2010. View at Publisher · View at Google Scholar · View at Scopus
  53. M. R. Kantorovitz, M. Kazemian, S. Kinston et al., “Motif-blind, genome-wide discovery of cis-regulatory modules in Drosophila and mouse,” Developmental Cell, vol. 17, no. 4, pp. 568–579, 2009. View at Publisher · View at Google Scholar · View at Scopus
  54. W. W. Pang, E. A. Price, D. Sahoo et al., “Human bone marrow hematopoietic stem cells are increased in frequency and myeloid-biased with age,” Proceedings of the National Academy of Sciences of USA, vol. 108, no. 50, article 20012-7, 2011. View at Google Scholar
  55. X. Wang, M. B. Werneck, B. G. Wilson, et al., “TCR-dependent transformation of mature memory phenotype T cells in mice,” The Journal of Clinical Investigation, vol. 121, no. 10, pp. 3834–3845, 2011. View at Google Scholar
  56. Y. Benita, Z. Cao, C. Giallourakis, C. Li, A. Gardet, and R. J. Xavier, “Gene enrichment profiles reveal T-cell development, differentiation, and lineage-specific transcription factors including ZBTB25 as a novel NF-AT repressor,” Blood, vol. 115, no. 26, pp. 5376–5384, 2010. View at Publisher · View at Google Scholar · View at Scopus
  57. D. Laifenfeld, A. Gilchrist, D. Drubin et al., “The role of hypoxia in 2-butoxyethanol-Induced hemangiosarcoma,” Toxicological Sciences, vol. 113, no. 1, pp. 254–266, 2009. View at Publisher · View at Google Scholar · View at Scopus
  58. K. S. Poland, D. L. Shardy, M. Azim et al., “Overexpression of ZNF342 by juxtaposition with MPO promoter/enhancer in the novel translocation t(17;19)(q23;q13.32) in pediatric acute myeloid leukemia and analysis of ZNF342 expression in leukemia,” Genes Chromosomes and Cancer, vol. 48, no. 6, pp. 480–489, 2009. View at Publisher · View at Google Scholar · View at Scopus
  59. A. Gerrits, B. Dykstra, M. Otten, L. Bystrykh, and G. de Haan, “Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny,” Immunogenetics, vol. 60, no. 8, pp. 411–422, 2008. View at Publisher · View at Google Scholar · View at Scopus
  60. R. Qayyum, B. M. Snively, E. Ziv, et al., “A meta-analysis and genome-wide association study of platelet count and mean platelet volume in african americans,” PLOS Genetics, vol. 8, no. 3, Article ID e1002491, 2012. View at Google Scholar
  61. S. Sivapalaratnam, H. Basart, N. A. Watkins, et al., “Monocyte gene expression signature of patients with early onset coronary artery disease,” PLoS One, vol. 7, no. 2, article e32166, 2012. View at Google Scholar
  62. M. Rotival, T. Zeller, P. S. Wild, et al., “Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans,” PLOS Genetics, vol. 7, no. 12, Article ID e1002367, 2011. View at Google Scholar
  63. R. S. Fehrmann, R. C. Jansen, J. H. Veldink, et al., “Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA,” PLOS Genetics, vol. 7, no. 8, Article ID e1002197, 2011. View at Google Scholar
  64. A. H. Goodall, P. Burns, I. Salles et al., “Transcription profiling in human platelets reveals LRRFIP1 as a novel protein regulating platelet function,” Blood, vol. 116, no. 22, pp. 4646–4656, 2010. View at Publisher · View at Google Scholar · View at Scopus
  65. S. K. Ganesh, N. A. Zakai, F. J. A. Van Rooij et al., “Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium,” Nature Genetics, vol. 41, no. 11, pp. 1191–1198, 2009. View at Publisher · View at Google Scholar · View at Scopus
  66. D. Wang, A. Rendon, W. Ouwehand, and L. Wernisch, “Transcription factor co-localization patterns affect human cell type-specific gene expression,” BMC Genomics, vol. 13, article 263, 2012. View at Google Scholar
  67. T. Suzuki, M. Nakano-Ikegaya, H. Yabukami-Okuda, et al., “Reconstruction of monocyte transcriptional regulatory network accompanies monocytic functions in human fibroblasts,” PLoS One, vol. 7, no. 3, article e33474, 2012. View at Google Scholar
  68. S. N. Wontakal, X. Guo, C. Smith et al., “A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation,” Proceedings of the National Academy of Sciences of USA, vol. 109, no. 10, pp. 3832–3837, 2012. View at Google Scholar
  69. J. Zhang, L. Ding, L. Holmfeldt, et al., “The genetic basis of early T-cell precursor acute lymphoblastic leukaemia,” Nature, vol. 481, no. 7380, pp. 157–163, 2012. View at Google Scholar
  70. K. Hebestreit, S. Gröttrup, D. Emden et al., “Leukemia gene atlas—a public platform for integrative exploration of genome-wide molecular data,” PLoS One, vol. 7, no. 6, article e39148, 2012. View at Google Scholar
  71. M. Adli, J. Zhu, and B. E. Bernstein, “Genome-wide chromatin maps derived from limited numbers of hematopoietic progenitors,” Nature Methods, vol. 7, no. 8, pp. 615–618, 2010. View at Publisher · View at Google Scholar · View at Scopus
  72. N. Bonadies, S. D. Foster, W. I. Chan, et al., “Genome-wide analysis of transcriptional reprogramming in mouse models of acute myeloid leukaemia,” PLoS One, vol. 6, no. 1, article e16330, 2011. View at Google Scholar
  73. Y. Cheng, W. Wu, S. A. Kumar et al., “Erythroid GATA1 function revealed by genome-wide analysis of transcription factor occupancy, histone modifications, and mRNA expression,” Genome Research, vol. 19, no. 12, pp. 2172–2184, 2009. View at Publisher · View at Google Scholar · View at Scopus
  74. M. A. Dawson, A. J. Bannister, B. Göttgens et al., “JAK2 phosphorylates histone H3Y41 and excludes HP1α from chromatin,” Nature, vol. 461, no. 7265, pp. 819–822, 2009. View at Publisher · View at Google Scholar · View at Scopus
  75. Y. He, Y. Yu, Y. Zhang et al., “Genome-wide bovine H3K27me3 modifications and the regulatory effects on genes expressions in peripheral blood lymphocytes,” PLoS One, vol. 7, no. 6, article e39094, 2012. View at Google Scholar
  76. P. C. Hollenhorst, K. J. Chandler, R. L. Poulsen, W. E. Johnson, N. A. Speck, and B. J. Graves, “DNA specificity determinants associate with distinct transcription factor functions,” PLoS Genetics, vol. 5, no. 12, Article ID e1000778, 2009. View at Publisher · View at Google Scholar · View at Scopus
  77. S. Saeed, C. Logie, K. J. Francoijs, et al., “Chromatin accessibility, p300 and histone acetylation define PML-RARα and AML1-ETO binding sites in acute myeloid leukemia,” Blood, vol. 120, no. 15, pp. 3058–3068, 2012. View at Google Scholar
  78. M. R. Tijssen, A. Cvejic, A. Joshi et al., “Genome-wide analysis of simultaneous GATA1/2, RUNX1, FLI1, and SCL binding in megakaryocytes identifies hematopoietic regulators,” Developmental Cell, vol. 20, no. 5, pp. 597–609, 2011. View at Publisher · View at Google Scholar · View at Scopus
  79. J. A. Zhang, A. Mortazavi, B. A. Williams, B. J. Wold, and E. V. Rothenberg, “Dynamic transformations of genome-wide epigenetic marking and transcriptional control establish T cell identity,” Cell, vol. 149, no. 2, pp. 467–482, 2012. View at Google Scholar
  80. P. Wong, S. M. Hattangadi, A. W. Cheng, G. M. Frampton, R. A. Young, and H. F. Lodish, “Gene induction and repression during terminal erythropoiesis are mediated by distinct epigenetic changes,” Blood, vol. 118, no. 16, pp. e128–e138, 2011. View at Google Scholar
  81. D. Adams, L. Altucci, S. E. Antonarakis, et al., “BLUEPRINT to decode the epigenetic signature written in blood,” Nature Biotechnology, vol. 30, no. 3, pp. 224–226, 2012. View at Google Scholar
  82. C. Bock, E. Kiskinis, G. Verstappen et al., “Reference maps of human es and ips cell variation enable high-throughput characterization of pluripotent cell lines,” Cell, vol. 144, no. 3, pp. 439–452, 2011. View at Publisher · View at Google Scholar · View at Scopus
  83. C. Bock, I. Beerman, W. H. Lien et al., “DNA methylation dynamics during in vivo differentiation of blood and skin stem cells,” Molecular Cell, vol. 47, no. 4, pp. 633–647, 2012. View at Google Scholar
  84. A. Meissner, T. S. Mikkelsen, H. Gu et al., “Genome-scale DNA methylation maps of pluripotent and differentiated cells,” Nature, vol. 454, no. 7205, pp. 766–770, 2008. View at Publisher · View at Google Scholar · View at Scopus
  85. R. Lister, M. Pelizzola, R. H. Dowen et al., “Human DNA methylomes at base resolution show widespread epigenomic differences,” Nature, vol. 462, no. 7271, pp. 315–322, 2009. View at Publisher · View at Google Scholar · View at Scopus
  86. R. Lister, M. Pelizzola, Y. S. Kida et al., “Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells,” Nature, vol. 471, no. 7336, pp. 68–73, 2011. View at Publisher · View at Google Scholar · View at Scopus
  87. E. Hodges, A. Molaro, C. O. Dos Santos, et al., “Directional DNA methylation changes and complex intermediate states accompany lineage specificity in the adult hematopoietic compartment,” Molecular Cell, vol. 44, no. 1, pp. 17–28, 2011. View at Google Scholar
  88. A. Hogart, J. Lichtenberg, S. S. Ajay, et al., “Genome-wide DNA methylation profiles in hematopoietic stem and progenitor cells reveal overrepresentation of ETS transcription factor binding sites,” Genome Research, vol. 22, no. 8, pp. 1407–1418, 2012. View at Google Scholar
  89. P. A. Beer, F. Delhommeau, J. P. LeCouédic et al., “Two routes to leukemic transformation after a JAK2 mutation-positive myeloproliferative neoplasm,” Blood, vol. 115, no. 14, pp. 2891–2900, 2010. View at Publisher · View at Google Scholar · View at Scopus
  90. W. C. Chou, S. C. Chou, C. Y. Liu, et al., “TET2 mutation is an unfavorable prognostic factor in acute myeloid leukemia patients with intermediate-risk cytogenetics,” Blood, vol. 118, no. 14, pp. 3803–3810, 2011. View at Google Scholar
  91. F. Delhommeau, S. Dupont, V. Della Valle et al., “Mutation in TET2 in myeloid cancers,” The New England Journal of Medicine, vol. 360, no. 22, pp. 2289–2301, 2009. View at Publisher · View at Google Scholar · View at Scopus
  92. A. Tefferi, K. H. Lim, O. Abdel-Wahab, et al., “Detection of mutant TET2 in myeloid malignancies other than myeloproliferative neoplasms: CMML, MDS, MDS/MPN and AML,” Leukemia, vol. 23, no. 7, pp. 1343–1345, 2009. View at Google Scholar
  93. M. E. Figueroa, O. Abdel-Wahab, C. Lu et al., “Leukemic IDH1 and IDH2 mutations result in a hypermethylation phenotype, disrupt TET2 function, and impair hematopoietic differentiation,” Cancer Cell, vol. 18, no. 6, pp. 553–567, 2010. View at Publisher · View at Google Scholar · View at Scopus
  94. L. Holmfeldt and C. G. Mullighan, “The role of TET2 in hematologic neoplasms,” Cancer Cell, vol. 20, no. 1, pp. 1–2, 2011. View at Publisher · View at Google Scholar · View at Scopus
  95. A. M. Jankowska, H. Makishima, R. V. Tiu, et al., “Mutational spectrum analysis of chronic myelomonocytic leukemia includes genes associated with epigenetic regulation: UTX, EZH2, and DNMT3A,” Blood, vol. 118, no. 14, pp. 3932–3941, 2011. View at Google Scholar
  96. M. Ko, Y. Huang, A. M. Jankowska et al., “Impaired hydroxylation of 5-methylcytosine in myeloid cancers with mutant TET2,” Nature, vol. 468, no. 7325, pp. 839–843, 2010. View at Publisher · View at Google Scholar · View at Scopus
  97. M. Ko, H. S. Bandukwala, J. An, et al., “Ten-Eleven-Translocation 2 (TET2) negatively regulates homeostasis and differentiation of hematopoietic stem cells in mice,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 35, pp. 14566–14571, 2011. View at Google Scholar
  98. O. Kosmider, V. Gelsi-Boyer, M. Ciudad et al., “TET2 gene mutation is a frequent and adverse event in chronic myelomonocytic leukemia,” Haematologica, vol. 94, no. 12, pp. 1676–1681, 2009. View at Publisher · View at Google Scholar · View at Scopus
  99. S. M. C. Langemeijer, J. H. Jansen, J. Hooijer et al., “TET2 mutations in childhood leukemia,” Leukemia, vol. 25, no. 1, pp. 189–192, 2011. View at Publisher · View at Google Scholar · View at Scopus
  100. C. G. Mullighan, “TET2 mutations in myelodysplasia and myeloid malignancies,” Nature Genetics, vol. 41, no. 7, pp. 766–767, 2009. View at Publisher · View at Google Scholar · View at Scopus
  101. C. Saint-Martin, G. Leroy, F. Delhommeau et al., “Analysis of the ten-eleven translocation 2 (TET2) gene in familial myeloproliferative neoplasms,” Blood, vol. 114, no. 8, pp. 1628–1632, 2009. View at Publisher · View at Google Scholar · View at Scopus
  102. A. H. Shih, O. Abdel-Wahab, J. P. Patel, and R. L. Levine, “The role of mutations in epigenetic regulators in myeloid malignancies,” Nature Reviews Cancer, vol. 12, no. 9, pp. 599–612, 2012. View at Google Scholar
  103. S. Weissmann, T. Alpermann, V. Grossmann, et al., “Landscape of TET2 mutations in acute myeloid leukemia,” Leukemia, vol. 26, no. 5, pp. 934–942, 2012. View at Google Scholar
  104. G. Ficz, M. R. Branco, S. Seisenberger et al., “Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation,” Nature, vol. 473, no. 7347, pp. 398–404, 2011. View at Publisher · View at Google Scholar · View at Scopus
  105. S. Ito, A. C. Dalessio, O. V. Taranova, K. Hong, L. C. Sowers, and Y. Zhang, “Role of tet proteins in 5mC to 5hmC conversion, ES-cell self-renewal and inner cell mass specification,” Nature, vol. 466, no. 7310, pp. 1129–1133, 2010. View at Publisher · View at Google Scholar · View at Scopus
  106. K. P. Koh, A. Yabuuchi, S. Rao et al., “Tet1 and Tet2 regulate 5-hydroxymethylcytosine production and cell lineage specification in mouse embryonic stem cells,” Cell Stem Cell, vol. 8, no. 2, pp. 200–213, 2011. View at Publisher · View at Google Scholar · View at Scopus
  107. A. A. Sérandour, S. Avner, F. Oger, et al., “Dynamic hydroxymethylation of deoxyribonucleic acid marks differentiationassociated enhancers,” Nucleic Acids Research, vol. 40, no. 17, pp. 8255–8265, 2012. View at Google Scholar
  108. H. Wu, A. C. D'Alessio, S. Ito et al., “Genome-wide analysis of 5-hydroxymethylcytosine distribution reveals its dual function in transcriptional regulation in mouse embryonic stem cells,” Genes and Development, vol. 25, no. 7, pp. 679–684, 2011. View at Publisher · View at Google Scholar · View at Scopus
  109. H. Wu and Y. Zhang, “Tet1 and 5-hydroxymethylation: a genome-wide view in mouse embryonic stem cells,” Cell Cycle, vol. 10, no. 15, pp. 2428–2436, 2011. View at Publisher · View at Google Scholar · View at Scopus
  110. Y. Xu, F. Wu, L. Tan et al., “Genome-wide regulation of 5hmC, 5mC, and gene expression by Tet1 hydroxylase in mouse embryonic stem cells,” Molecular Cell, vol. 42, no. 4, pp. 451–464, 2011. View at Publisher · View at Google Scholar · View at Scopus
  111. D. S. Johnson, A. Mortazavi, R. M. Myers, and B. Wold, “Genome-wide mapping of in vivo protein-DNA interactions,” Science, vol. 316, no. 5830, pp. 1497–1502, 2007. View at Publisher · View at Google Scholar · View at Scopus
  112. T. Fujiwara, H. O'Geen, S. Keles et al., “Discovering hematopoietic mechanisms through genome-wide analysis of GATA factor chromatin occupancy,” Molecular Cell, vol. 36, no. 4, pp. 667–681, 2009. View at Publisher · View at Google Scholar · View at Scopus
  113. R. Hannah, A. Joshi, N. K. Wilson, S. Kinston, and B. Göttgens, “A compendium of genome-wide hematopoietic transcription factor maps supports the identification of gene regulatory control mechanisms,” Experimental Hematology, vol. 39, no. 5, pp. 531–541, 2011. View at Google Scholar
  114. M. T. Kassouf, J. R. Hughes, S. Taylor et al., “Genome-wide identification of TAL1's functional targets: Insights into its mechanisms of action in primary erythroid cells,” Genome Research, vol. 20, no. 8, pp. 1064–1083, 2010. View at Publisher · View at Google Scholar · View at Scopus
  115. L. Li, R. Jothi, K. Cui et al., “Nuclear adaptor Ldb1 regulates a transcriptional program essential for the maintenance of hematopoietic stem cells,” Nature Immunology, vol. 12, no. 2, pp. 129–136, 2011. View at Publisher · View at Google Scholar · View at Scopus
  116. C. G. Palii, C. Perez-Iratxeta, Z. Yao et al., “Differential genomic targeting of the transcription factor TAL1 in alternate haematopoietic lineages,” EMBO Journal, vol. 30, no. 3, pp. 494–509, 2011. View at Publisher · View at Google Scholar · View at Scopus
  117. N. K. Wilson, D. Miranda-Saavedra, S. Kinston et al., “The transcriptional program controlled by the stem cell leukemia gene Scl /Tal1 during early embryonic hematopoietic development,” Blood, vol. 113, no. 22, pp. 5456–5465, 2009. View at Publisher · View at Google Scholar · View at Scopus
  118. N. K. Wilson, S. D. Foster, X. Wang et al., “Combinatorial transcriptional control in blood stem/progenitor cells: genome-wide analysis of ten major transcriptional regulators,” Cell Stem Cell, vol. 7, no. 4, pp. 532–544, 2010. View at Publisher · View at Google Scholar · View at Scopus
  119. M. Garber, N. Yosef, A. Goren, et al., “A high-throughput chromatin immunoprecipitation approach reveals principles of dynamic gene regulation in mammals,” Molecular Cell, vol. 47, no. 5, pp. 810–822, 2012. View at Google Scholar
  120. A. M. Pilon, S. S. Ajay, S. A. Kumar, et al., “Genome-wide ChIP-Seq reveals a dramatic shift in the binding of the transcription factor erythroid Kruppel-like factor during erythrocyte differentiation,” Blood, vol. 118, no. 17, pp. e139–e148, 2011. View at Google Scholar
  121. S. N. Wontakal, X. Guo, B. Will et al., “A large gene network in immature Erythroid cells is controlled by the myeloid and B cell transcriptional regulator PU.1,” PLoS Genetics, vol. 7, no. 6, Article ID e1001392, 2011. View at Publisher · View at Google Scholar · View at Scopus
  122. L. Durant, W. T. Watford, H. L. Ramos et al., “Diverse targets of the transcription factor STAT3 contribute to T cell pathogenicity and homeostasis,” Immunity, vol. 32, no. 5, pp. 605–615, 2010. View at Publisher · View at Google Scholar · View at Scopus
  123. H. Kwon, D. Thierry-Mieg, J. Thierry-Mieg et al., “Analysis of interleukin-21-induced Prdm1 gene regulation reveals functional cooperation of STAT3 and IRF4 transcription factors,” Immunity, vol. 31, no. 6, pp. 941–952, 2009. View at Publisher · View at Google Scholar · View at Scopus
  124. A. Ptasinska, S. A. Assi, D. Mannari, et al., “Depletion of RUNX1/ETO in t(8,21) AML cells leads to genome-wide changes in chromatin structure and transcription factor binding,” Leukemia, vol. 26, no. 8, pp. 1829–1841, 2012. View at Google Scholar
  125. J. H. A. Martens, A. B. Brinkman, F. Simmer et al., “PML-RARα/RXR alters the epigenetic landscape in acute promyelocytic leukemia,” Cancer Cell, vol. 17, no. 2, pp. 173–185, 2010. View at Publisher · View at Google Scholar · View at Scopus
  126. H. Wang, J. Zou, B. Zhao, et al., “Genome-wide analysis reveals conserved and divergent features of Notch1/RBPJ binding in human and murine T-lymphoblastic leukemia cells,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 36, pp. 14908–14913, 2011. View at Google Scholar
  127. I. Aifantis, E. Raetz, and S. Buonamici, “Molecular pathogenesis of T-cell leukaemia and lymphoma,” Nature Reviews Immunology, vol. 8, no. 5, pp. 380–390, 2008. View at Publisher · View at Google Scholar · View at Scopus
  128. N. Soranzo, T. D. Spector, M. Mangino et al., “A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium,” Nature Genetics, vol. 41, no. 11, pp. 1182–1190, 2009. View at Publisher · View at Google Scholar · View at Scopus
  129. M. A. Nalls, D. J. Couper, T. Tanaka, et al., “Multiple loci are associated with white blood cell phenotypes,” PLOS Genetics, vol. 7, no. 6, Article ID e1002113, 2011. View at Google Scholar
  130. C. Gieger, A. Radhakrishnan, A. Cvejic, et al., “New gene functions in megakaryopoiesis and platelet formation,” Nature, vol. 480, no. 7376, pp. 201–208, 2011. View at Google Scholar
  131. P. A. Greif, A. Dufour, N. P. Konstandin, et al., “GATA2 zinc finger 1 mutations associated with biallelic CEBPA mutations define a unique genetic entity of acute myeloid leukemia,” Blood, vol. 120, no. 2, pp. 395–403, 2012. View at Google Scholar
  132. H. L. Koskela, S. Eldfors, P. Ellonen, et al., “Somatic STAT3 mutations in large granular lymphocytic leukemia,” The New England Journal of Medicine, vol. 366, no. 20, pp. 1905–1913, 2012. View at Google Scholar
  133. V. Quesada, L. Conde, N. Villamor, et al., “Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia,” Nature Genetics, vol. 44, no. 1, pp. 47–52, 2012. View at Google Scholar
  134. L. Wang, M. S. Lawrence, Y. Wan, et al., “SF3B1 and other novel cancer genes in chronic lymphocytic leukemia,” The New England Journal of Medicine, vol. 365, no. 26, pp. 2497–2506, 2011. View at Google Scholar
  135. V. Grossmann, E. Tiacci, A. B. Holmes, et al., “Whole-exome sequencing identifies somatic mutations of BCOR in acute myeloid leukemia with normal karyotype,” Blood, vol. 118, no. 23, pp. 6153–6163, 2011. View at Google Scholar
  136. K. Yoshida, M. Sanada, Y. Shiraishi, et al., “Frequent pathway mutations of splicing machinery in myelodysplasia,” Nature, vol. 478, no. 7367, pp. 64–69, 2011. View at Google Scholar
  137. X. J. Yan, J. Xu, Z. H. Gu et al., “Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia,” Nature Genetics, vol. 43, no. 4, pp. 309–317, 2011. View at Publisher · View at Google Scholar · View at Scopus
  138. R. E. Dickinson, H. Griffin, V. Bigley, et al., “Exome sequencing identifies GATA-2 mutation as the cause of dendritic cell, monocyte, B and NK lymphoid deficiency,” Blood, vol. 118, no. 10, pp. 2656–2658, 2011. View at Google Scholar
  139. E. Tiacci, V. Trifonov, G. Schiavoni, et al., “BRAF mutations in hairy-cell leukemia,” The New England Journal of Medicine, vol. 364, no. 24, pp. 2305–2315, 2011. View at Google Scholar
  140. B. A. Walker, C. P. Wardell, L. Melchor, et al., “Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4,14) and t(11,14) myeloma,” Blood, vol. 120, no. 5, pp. 1077–1086, 2012. View at Google Scholar
  141. M. J. Walter, D. Shen, L. Ding, et al., “Clonal architecture of secondary acute myeloid leukemia,” The New England Journal of Medicine, vol. 366, no. 12, pp. 1090–1098, 2012. View at Google Scholar
  142. D. C. Link, L. G. Schuettpelz, D. Shen et al., “Identification of a novel TP53 cancer susceptibility mutation through whole-genome sequencing of a patient with therapy-related AML,” Journal of the American Medical Association, vol. 305, no. 15, pp. 1568–1576, 2011. View at Publisher · View at Google Scholar · View at Scopus
  143. L. D. Wartman, D. E. Larson, Z. Xiang, et al., “Sequencing a mouse acute promyelocytic leukemia genome reveals genetic events relevant for disease progression,” The Journal of Clinical Investigation, vol. 121, no. 4, pp. 1445–1455, 2011. View at Google Scholar
  144. J. B. Egan, C. X. Shi, W. Tembe, et al., “Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides,” Blood, vol. 120, no. 5, pp. 1060–1066, 2012. View at Google Scholar
  145. X. S. Puente, M. Pinyol, V. Quesada, et al., “Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia,” Nature, vol. 475, no. 7354, pp. 101–105, 2011. View at Google Scholar
  146. M. A. Chapman, M. S. Lawrence, J. J. Keats, et al., “Initial genome sequencing and analysis of multiple myeloma,” Nature, vol. 471, no. 7339, pp. 467–472, 2011. View at Google Scholar
  147. J. S. Welch, T. J. Ley, D. C. Link, et al., “The origin and evolution of mutations in acute myeloid leukemia,” Cell, vol. 150, no. 2, pp. 264–278, 2012. View at Google Scholar
  148. Y. Hou, L. Song, P. Zhu, et al., “Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm,” Cell, vol. 148, no. 5, pp. 873–885, 2012. View at Google Scholar
  149. J. P. Glotzbach, M. Januszyk, I. N. Vial et al., “An information theoretic, microfluidic-based single cell analysis permits identification of subpopulations among putatively homogeneous stem cells,” PLoS ONE, vol. 6, no. 6, article e21211, 2011. View at Publisher · View at Google Scholar · View at Scopus
  150. A. Raj and A. van Oudenaarden, “Nature, nurture, or chance: stochastic gene expression and its consequences,” Cell, vol. 135, no. 2, pp. 216–226, 2008. View at Publisher · View at Google Scholar · View at Scopus
  151. S. Itzkovitz, A. Lyubimova, I. C. Blat et al., “Single-molecule transcript counting of stem-cell markers in the mouse intestine,” Nature Cell Biology, vol. 14, no. 1, pp. 106–114, 2012. View at Google Scholar
  152. L. Warren, D. Bryder, I. L. Weissman, and S. R. Quake, “Transcription factor profiling in individual hematopoietic progenitors by digital RT-PCR,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 47, pp. 17807–17812, 2006. View at Publisher · View at Google Scholar · View at Scopus
  153. F. Tang, C. Barbacioru, E. Nordman et al., “Deterministic and stochastic allele specific gene expression in single mouse blastomeres,” PLoS ONE, vol. 6, no. 6, article e21208, 2011. View at Publisher · View at Google Scholar · View at Scopus
  154. F. Tang, K. Lao, and M. A. Surani, “Development and applications of single-cell transcriptome analysis,” Nature Methods, vol. 8, supplement 4, pp. S6–S11, 2011. View at Publisher · View at Google Scholar · View at Scopus
  155. X. Xu, Y. Hou, X. Yin, et al., “Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor,” Cell, vol. 148, no. 5, pp. 886–895, 2012. View at Google Scholar
  156. C. Hou and V. G. Corces, “Throwing transcription for a loop: expression of the genome in the 3D nucleus,” Chromosoma, vol. 121, no. 2, pp. 107–116, 2012. View at Google Scholar
  157. A. Sanyal, D. Baù, M. A. Martí-Renom, and J. Dekker, “Chromatin globules: a common motif of higher order chromosome structure?” Current Opinion in Cell Biology, vol. 23, no. 3, pp. 325–331, 2011. View at Publisher · View at Google Scholar · View at Scopus
  158. L. B. Edelman and P. Fraser, “Transcription factories: genetic programming in three dimensions,” Current Opinion in Genetics & Development, vol. 22, no. 2, pp. 110–114, 2012. View at Google Scholar
  159. J. M. Belton, R. P. McCord, J. H. Gibcus, N. Naumova, Y. Zhan, and J. Dekker, “Hi-C: a comprehensive technique to capture the conformation of genomes,” Methods, vol. 58, no. 3, pp. 268–276, 2012. View at Google Scholar
  160. E. Lieberman-Aiden, N. L. Van Berkum, L. Williams et al., “Comprehensive mapping of long-range interactions reveals folding principles of the human genome,” Science, vol. 326, no. 5950, pp. 289–293, 2009. View at Publisher · View at Google Scholar · View at Scopus
  161. J. Zhang, H. M. Poh, S. Q. Peh, et al., “ChIA-PET analysis of transcriptional chromatin interactions,” Methods, vol. 58, no. 3, pp. 289–299, 2012. View at Google Scholar
  162. G. Li, X. Ruan, R. K. Auerbach, et al., “Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation,” Cell, vol. 148, pp. 184–298, 2012. View at Google Scholar
  163. G. Li, M. J. Fullwood, H. Xu et al., “ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing,” Genome Biology, vol. 11, no. 2, article R22, 2010. View at Publisher · View at Google Scholar · View at Scopus
  164. A. Melnikov, A. Murugan, X. Zhang, et al., “Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay,” Nature Biotechnology, vol. 30, no. 3, pp. 271–277, 2012. View at Google Scholar
  165. V. M. Bedell, Y. Wang, J. M. Campbell, et al., “In vivo genome editing using a high-efficiency TALEN system,” Nature, vol. 491, no. 7422, pp. 114–118, 2012. View at Google Scholar
  166. K. Yusa, S. T. Rashid, H. Strick-Marchand, et al., “Targeted gene correction of α1-antitrypsin deficiency in induced pluripotent stem cells,” Nature, vol. 478, no. 7369, pp. 391–394, 2011. View at Google Scholar