Skip to main content
SpringerLink
Log in

Deeply Dissecting Stemness: Making Sense to Non-Coding RNAs in Stem Cells

  • Published:
Stem Cell Reviews and Reports Aims and scope Submit manuscript

Abstract

Adult stem cells are an important source for the regeneration of damaged body parts. Unlike fish and amphibians, the regeneration capacity of human tissues is rather limited. Therefore, one might ask for reasons that led to the loss of regenerative capacity during evolution. Although intensive efforts have been made, we still cannot answer this question definitively. Recent advances in so-called “-omics” (e.g. transcriptomics, proteomics) technologies allowed researchers to obtain detailed views of both mRNA and protein expression levels at different time points during regeneration and tissue repair. It is now possible to make a series of snap shots to characterize stem cell activities at various stages. Recent findings have revealed an enormous plasticity of different cell types reaffirming the landscape model of cell differentiation. Apparently, differentiation of stem cells into a certain lineage is not a fixed process but rather a delicate balance, in which different signaling pathways are involved. To understand this balance, it is utmost importance to profile and catalog changes that occur during the differentiation process of stem cells both at mRNA and protein levels. In this review, we survey the impact of expression profiling on stem cell research with a particular emphasis on non-coding RNAs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Smith, A. (2006). A glossary for stem-cell biology. Nature, 441, 1060–1061.

    Article  CAS  Google Scholar 

  2. Takahashi, K., & Yamanaka, S. (2006). Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 126(4), 663–676.

    Article  PubMed  CAS  Google Scholar 

  3. Velculescu, V. E., Zhang, L., Vogelstein, B., & Kinzler, K. W. (1995). Serial analysis of gene expression. Science, 270(5235), 484–487.

    Article  PubMed  CAS  Google Scholar 

  4. Mardis, E. R. (2008). The impact of next-generation sequencing technology on genetics. Trends in Genetics, 24(3), 133–141.

    Article  PubMed  CAS  Google Scholar 

  5. Quackenbush, J. (2002). Microarray data normalization and transformation. Nature Genetics, 32(Suppl), 496–501.

    Article  PubMed  CAS  Google Scholar 

  6. Uchida, S., Nishida, Y., Satou, K., Muta, S., Tashiro, K., & Kuhara, S. (2005). Detection and normalization of biases present in spotted cDNA microarray data: a composite method addressing dye, intensity-dependent, spatially-dependent, and print-order biases. DNA Research, 12(1), 1–7.

    Article  PubMed  CAS  Google Scholar 

  7. MAQC Consortium, Shi, L., Reid, L., et al. (2006). The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nature Biotechnology, 24(9), 1151–1161.

    Article  PubMed  CAS  Google Scholar 

  8. Imbeaud, S., & Auffray, C. (2005). ‘The 39 steps’ in gene expression profiling: Critical issues and proposed best practices for microarray experiments. Drug Discovery Today, 10(17), 1175–1182.

    Article  PubMed  CAS  Google Scholar 

  9. Curtis, R. K., Oresic, M., & Vidal-Puig, A. (2005). Pathways to the analysis of microarray data. Trends in Biotechnology, 23(8), 429–435.

    Article  PubMed  CAS  Google Scholar 

  10. Durinck, S. (2008). Pre-processing of microarray data and analysis of differential expression. Methods in Molecular Biology, 452, 89–110.

    Article  PubMed  CAS  Google Scholar 

  11. Zhang, Y., Szustakowski, J., & Schinke, M. (2009). Bioinformatics analysis of microarray data. Methods in Molecular Biology, 573, 259–284.

    Article  PubMed  CAS  Google Scholar 

  12. Reimers, M. (2010). Making informed choices about microarray data analysis. PLoS Computational Biology, 6(5), e1000786.

    Article  PubMed  CAS  Google Scholar 

  13. Boon, K., Osorio, E. C., Greenhut, S. F., et al. (2002). An anatomy of normal and malignant gene expression. Proceedings of the National Academy of Sciences of the United States of America, 99(17), 11287–11292.

    Article  PubMed  CAS  Google Scholar 

  14. Wang, S. M. (2007). Understanding SAGE data. Trends in Genetics, 23(1), 42–50.

    Article  PubMed  CAS  Google Scholar 

  15. Gowda, M., Jantasuriyarat, C., Dean, R. A., & Wang, G. L. (2004). Robust-LongSAGE (RL-SAGE): A substantially improved LongSAGE method for gene discovery and transcriptome analysis. Plant Physiology, 134(3), 890–897.

    Article  PubMed  CAS  Google Scholar 

  16. Matsumura, H., Ito, A., Saitoh, H., et al. (2005). SuperSAGE. Cellular Microbiology, 7(1), 11–18.

    Article  PubMed  CAS  Google Scholar 

  17. Blencowe, B. J., Ahmad, S., & Lee, L. J. (2009). Current-generation high-throughput sequencing: Deepening insights into mammalian transcriptomes. Genes & Development, 23(12), 1379–1386.

    Article  CAS  Google Scholar 

  18. Wang, Z., Gerstein, M., & Snyder, M. (2009). RNA-Seq: A revolutionary tool for transcriptomics. Nature Review Genetics, 10(1), 57–63.

    Article  CAS  Google Scholar 

  19. Metzker, M. L. (2010). Sequencing technologies—the next generation. Nature Review Genetics, 11(1), 31–46.

    Article  CAS  Google Scholar 

  20. Wang, E. T., Sandberg, R., Luo, S., et al. (2008). Alternative isoform regulation in human tissue transcriptomes. Nature, 456(7221), 470–476.

    Article  PubMed  CAS  Google Scholar 

  21. Lu, C., Meyers, B. C., & Green, P. J. (2007). Construction of small RNA cDNA libraries for deep sequencing. Methods, 43(2), 110–117.

    Article  PubMed  CAS  Google Scholar 

  22. Hafner, M., Landgraf, P., Ludwig, J., et al. (2008). Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing. Methods, 44(1), 3–12.

    Article  PubMed  CAS  Google Scholar 

  23. Friedländer, M. R., Chen, W., Adamidi, C., et al. (2008). Discovering microRNAs from deep sequencing data using miRDeep. Nature Biotechnology, 26(4), 407–415.

    Article  PubMed  CAS  Google Scholar 

  24. Taft, R. J., Glazov, E. A., Cloonan, N., et al. (2009). Tiny RNAs associated with transcription start sites in animals. Nature Genetics, 41(5), 572–578.

    Article  PubMed  CAS  Google Scholar 

  25. Affymetrix ENCODE Transcriptome Project; Cold Spring Harbor Laboratory ENCODE Transcriptome Project. (2009). Post-transcriptional processing generates a diversity of 5′-modified long and short RNAs. Nature, 457(7232), 1028–1032.

    Article  CAS  Google Scholar 

  26. Johnson, D. S., Mortazavi, A., Myers, R. M., & Wold, B. (2007). Genome-wide mapping of in vivo protein-DNA interactions. Science, 316(5830), 1497–1502.

    Article  PubMed  CAS  Google Scholar 

  27. Horak, C. E., Mahajan, M. C., Luscombe, N. M., Gerstein, M., Weissman, S. M., & Snyder, M. (2002). GATA-1 binding sites mapped in the beta-globin locus by using mammalian chIp-chip analysis. Proceedings of the National Academy of Sciences of the United States of America, 99(5), 2924–2929.

    Article  PubMed  CAS  Google Scholar 

  28. May, C., Brosseron, F., Chartowski, P., et al. (2011). Instruments and methods in proteomics. Methods in Molecular Biology, 696, 3–26.

    Article  PubMed  CAS  Google Scholar 

  29. Rabilloud, T., Chevallet, M., Luche, S., & Lelong, C. (2010). Two-dimensional gel electrophoresis in proteomics: Past, present and future. Journal of Proteomics, 73(11), 2064–2077.

    Article  PubMed  CAS  Google Scholar 

  30. Valledor, L., & Jorrín, J. (2011). Back to the basics: Maximizing the information obtained by quantitative two dimensional gel electrophoresis analyses by an appropriate experimental design and statistical analyses. Journal of Proteomics, 74(1), 1–18.

    Article  PubMed  CAS  Google Scholar 

  31. Unwin, R. D., Gaskell, S. J., Evans, C. A., & Whetton, A. D. (2003). The potential for proteomic definition of stem cell populations. Experimental Hematology, 31(12), 1147–1159.

    Article  PubMed  CAS  Google Scholar 

  32. Unwin, R. D., Smith, D. L., Blinco, D., et al. (2006). Quantitative proteomics reveals posttranslational control as a regulatory factor in primary hematopoietic stem cells. Blood, 107(12), 4687–4694.

    Article  PubMed  CAS  Google Scholar 

  33. Skalnikova, H., Halada, P., Vodicka, P., Motlik, J., Rehulka, P., Hørning, O., et al. (2007). A proteomic approach to studying the differentiation of neural stem cells. Proteomics, 7(11), 1825–1838.

    Article  PubMed  CAS  Google Scholar 

  34. Zvonic, S., Lefevre, M., Kilroy, G., et al. (2007). Secretome of primary cultures of human adipose-derived stem cells: modulation of serpins by adipogenesis. Molecular & Cellular Proteomics, 6(1), 18–28.

    Article  CAS  Google Scholar 

  35. Baharvand, H., Fathi, A., Gourabi, H., Mollamohammadi, S., & Salekdeh, G. H. (2008). Identification of mouse embryonic stem cell-associated proteins. Journal of Proteome Research, 7(1), 412–423.

    Article  PubMed  CAS  Google Scholar 

  36. Yocum, A. K., Gratsch, T. E., Leff, N., et al. (2008). Coupled global and targeted proteomics of human embryonic stem cells during induced differentiation. Molecular & Cellular Proteomics, 7(4), 750–767.

    Article  CAS  Google Scholar 

  37. Dormeyer, W., van Hoof, D., Braam, S. R., et al. (2008). Plasma membrane proteomics of human embryonic stem cells and human embryonal carcinoma cells. Journal of Proteome Research, 7(7), 2936–2951.

    Article  PubMed  CAS  Google Scholar 

  38. Sarojini, H., Estrada, R., Lu, H., et al. (2008). PEDF from mouse mesenchymal stem cell secretome attracts fibroblasts. Journal of Cellular Biochemistry, 104(5), 1793–1802.

    Article  PubMed  CAS  Google Scholar 

  39. Sze, S. K., de Kleijn, D. P., Lai, R. C., et al. (2007). Elucidating the secretion proteome of human embryonic stem cell-derived mesenchymal stem cells. Molecular & Cellular Proteomics, 6(10), 1680–1689.

    Article  CAS  Google Scholar 

  40. Cutillas, P. R., & Timms, J. F. (2010). Approaches and applications of quantitative LC-MS for proteomics and activitomics. Methods in Molecular Biology, 658, 3–17.

    Article  PubMed  CAS  Google Scholar 

  41. Timms, J. F., & Cutillas, P. R. (2010). Overview of quantitative LC-MS techniques for proteomics and activitomics. Methods in Molecular Biology, 658, 19–45.

    Article  PubMed  CAS  Google Scholar 

  42. He, J., Liu, Y., Zhu, T. S., et al. (2011). Glycoproteomic analysis of glioblastoma stem cell differentiation. Journal of Proteome Research, 10(1), 330–338.

    Article  PubMed  CAS  Google Scholar 

  43. Li, J., Cui, Z., Zhao, S., & Sidman, R. L. (2007). Unique glycerophospholipid signature in retinal stem cells correlates with enzymatic functions of diverse long-chain acyl-CoA synthetases. Stem Cells, 25(11), 2864–2873.

    Article  PubMed  CAS  Google Scholar 

  44. Yanes, O., Clark, J., Wong, D. M., et al. (2010). Metabolic oxidation regulates embryonic stem cell differentiation. Nature Chemical Biology, 6(6), 411–417.

    Article  PubMed  CAS  Google Scholar 

  45. Li, Q. R., Xing, X. B., Chen, T. T., et al. (2011). Large scale phosphoproteome profiles comprehensive features of mouse embryonic stem cells. Molecular & Cellular Proteomics, 10(4), M110.001750.

    Article  CAS  Google Scholar 

  46. Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993). The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell, 75(5), 843–854.

    Article  PubMed  CAS  Google Scholar 

  47. Carninci, P. (2010). RNA dust: Where are the genes? DNA Research, 17(2), 51–59.

    Article  PubMed  CAS  Google Scholar 

  48. Ponting, C. P., Oliver, P. L., & Reik, W. (2009). Evolution and functions of long noncoding RNAs. Cell, 136(4), 629–641.

    Article  PubMed  CAS  Google Scholar 

  49. Katayama, S., Tomaru, Y., Kasukawa, T., et al. (2005). Antisense transcription in the mammalian transcriptome. Science, 309(5740), 1564–1566.

    Article  PubMed  Google Scholar 

  50. Carninci, P., Kasukawa, T., Katayama, S., et al. (2005). The transcriptional landscape of the mammalian genome. Science, 309(5740), 1559–1563.

    Article  PubMed  CAS  Google Scholar 

  51. Wilusz, J. E., Sunwoo, H., & Spector, D. L. (2009). Long noncoding RNAs: Functional surprises from the RNA world. Genes & Development, 23(13), 1494–1504.

    Article  CAS  Google Scholar 

  52. Ivey, K. N., & Srivastava, D. (2010). MicroRNAs as regulators of differentiation and cell fate decisions. Cell Stem Cell, 7(1), 36–41.

    Article  PubMed  CAS  Google Scholar 

  53. Martinez, N. J., & Gregory, R. I. (2010). MicroRNA gene regulatory pathways in the establishment and maintenance of ESC identity. Cell Stem Cell, 7(1), 31–35.

    Article  PubMed  CAS  Google Scholar 

  54. Murashov, A. K. (2010). A brief introduction to RNAi and microRNAs in stem cells. Methods in Molecular Biology, 650, 15–25.

    Article  PubMed  CAS  Google Scholar 

  55. Guttman, M., Amit, I., Garber, M., et al. (2009). Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature, 458(7235), 223–227.

    Article  PubMed  CAS  Google Scholar 

  56. Guttman, M., Garber, M., Levin, J. Z., et al. (2010). Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nature Biotechnology, 28(5), 503–510.

    Article  PubMed  CAS  Google Scholar 

  57. Mercer, T. R., Qureshi, I. A., Gokhan, S., et al. (2010). Long noncoding RNAs in neuronal-glial fate specification and oligodendrocyte lineage maturation. BMC Neuroscience, 11, 14.

    Article  PubMed  CAS  Google Scholar 

  58. Sheik Mohamed, J., Gaughwin, P. M., Lim, B., Robson, P., & Lipovich, L. (2010). Conserved long noncoding RNAs transcriptionally regulated by Oct4 and Nanog modulate pluripotency in mouse embryonic stem cells. RNA, 16(2), 324–337.

    Article  PubMed  CAS  Google Scholar 

  59. Loewer, S., Cabili, M. N., Guttman, M., et al. (2010). Large intergenic non-coding RNA-RoR modulates reprogramming of human induced pluripotent stem cells. Nature Genetics, 42(12), 1113–1117.

    Article  PubMed  CAS  Google Scholar 

  60. Fox, A. H., Lam, Y. W., Leung, A. K., et al. (2002). Paraspeckles: a novel nuclear domain. Current Biology, 12(1), 13–25.

    Article  PubMed  CAS  Google Scholar 

  61. Chen, L. L., & Carmichael, G. G. (2009). Altered nuclear retention of mRNAs containing inverted repeats in human embryonic stem cells: functional role of a nuclear noncoding RNA. Molecular Cell, 35(4), 467–478.

    Article  PubMed  CAS  Google Scholar 

  62. Clemson, C. M., Hutchinson, J. N., Sara, S. A., et al. (2009). An architectural role for a nuclear noncoding RNA: NEAT1 RNA is essential for the structure of paraspeckles. Molecular Cell, 33(6), 717–726.

    Article  PubMed  CAS  Google Scholar 

  63. Sasaki, Y. T., Ideue, T., Sano, M., Mituyama, T., & Hirose, T. (2009). MENepsilon/beta noncoding RNAs are essential for structural integrity of nuclear paraspeckles. Proceedings of the National Academy of Sciences of the United States of America, 106(8), 2525–2530.

    Article  PubMed  CAS  Google Scholar 

  64. Souquere, S., Beauclair, G., Harper, F., Fox, A., & Pierron, G. (2010). Highly ordered spatial organization of the structural long noncoding NEAT1 RNAs within paraspeckle nuclear bodies. Molecular Biology of the Cell, 21(22), 4020–4027.

    Article  PubMed  CAS  Google Scholar 

  65. Mao, Y. S., Sunwoo, H., Zhang, B., & Spector, D. L. (2011). Direct visualization of the co-transcriptional assembly of a nuclear body by noncoding RNAs. Nature Cell Biology, 13(1), 95–101.

    Article  PubMed  CAS  Google Scholar 

  66. Sunwoo, H., Dinger, M. E., Wilusz, J. E., Amaral, P. P., Mattick, J. S., & Spector, D. L. (2009). MEN epsilon/beta nuclear-retained non-coding RNAs are up-regulated upon muscle differentiation and are essential components of paraspeckles. Genome Research, 19(3), 347–359.

    Article  PubMed  CAS  Google Scholar 

  67. Nakagawa, S., Naganuma, T., Shioi, G., & Hirose, T. (2011). Paraspeckles are subpopulation-specific nuclear bodies that are not essential in mice. The Journal of Cell Biology, 193(1), 31–39.

    Article  PubMed  CAS  Google Scholar 

  68. Tripathi, V., Ellis, J. D., Shen, Z., et al. (2010). The nuclear-retained noncoding RNA MALAT1 regulates alternative splicing by modulating SR splicing factor phosphorylation. Molecular Cell, 39(6), 925–938.

    Article  PubMed  CAS  Google Scholar 

  69. Nagano, T., Mitchell, J. A., Sanz, L. A., et al. (2008). The Air noncoding RNA epigenetically silences transcription by targeting G9a to chromatin. Science, 322(5908), 1717–1720.

    Article  PubMed  CAS  Google Scholar 

  70. Rinn, J. L., Kertesz, M., Wang, J. K., et al. (2007). Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell, 129(7), 1311–1323.

    Article  PubMed  CAS  Google Scholar 

  71. Pandey, R. R., Mondal, T., Mohammad, F., et al. (2008). Kcnq1ot1 antisense noncoding RNA mediates lineage-specific transcriptional silencing through chromatin-level regulation. Molecular Cell, 32(2), 232–246.

    Article  PubMed  CAS  Google Scholar 

  72. Tsai, M. C., Manor, O., Wan, Y., et al. (2010). Long noncoding RNA as modular scaffold of histone modification complexes. Science, 329(5992), 689–693.

    Article  PubMed  CAS  Google Scholar 

  73. Harrow, J., Denoeud, F., Frankish, A., et al. (2006). GENCODE: Producing a reference annotation for ENCODE. Genome Biology, 7(Suppl 1), S4.1–9.

    Article  Google Scholar 

  74. Washietl, S., Pedersen, J. S., Korbel, J. O., et al. (2007). Structured RNAs in the ENCODE selected regions of the human genome. Genome Research, 17(6), 852–864.

    Article  PubMed  CAS  Google Scholar 

  75. Borel, C., Gagnebin, M., Gehrig, C., et al. (2008). Mapping of small RNAs in the human ENCODE regions. American Journal of Human Genetics, 82(4), 971–981.

    Article  PubMed  CAS  Google Scholar 

  76. Ørom, U. A., Derrien, T., Beringer, M., et al. (2010). Long noncoding RNAs with enhancer-like function in human cells. Cell, 143(1), 46–58.

    Article  PubMed  CAS  Google Scholar 

  77. Hipp, J. A., Hipp, J. D., Atala, A., & Soker, S. (2010). Functional genomics: New insights into the ‘function’ of low levels of gene expression in stem cells. Current Genomics, 11(5), 354–358.

    Article  PubMed  CAS  Google Scholar 

  78. Trapnell, C., Williams, B. A., Pertea, G., et al. (2010). Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology, 28(5), 511–515.

    Article  PubMed  CAS  Google Scholar 

  79. Khalil, A. M., Guttman, M., Huarte, M., et al. (2009). Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proceedings of the National Academy of Sciences of the United States of America, 106(28), 11667–11672.

    Article  PubMed  CAS  Google Scholar 

  80. Sarma, K., Levasseur, P., Aristarkhov, A., & Lee, J. T. (2010). Locked nucleic acids (LNAs) reveal sequence requirements and kinetics of Xist RNA localization to the X chromosome. Proceedings of the National Academy of Sciences of the United States of America, 107(51), 22196–22201.

    Article  PubMed  CAS  Google Scholar 

  81. Mei, Y., Goldberg, M., & Anderson, D. (2007). The development of high-throughput screening approaches for stem cell engineering. Current Opinion in Chemical Biology, 11(4), 388–393.

    Article  PubMed  CAS  Google Scholar 

  82. Ali, N., Karlsson, C., Aspling, M., et al. (2009). Forward RNAi screens in primary human hematopoietic stem/progenitor cells. Blood, 113(16), 3690–3695.

    Article  PubMed  CAS  Google Scholar 

  83. Zhao, Y., & Ding, S. (2007). A high-throughput siRNA library screen identifies osteogenic suppressors in human mesenchymal stem cells. Proceedings of the National Academy of Sciences of the United States of America, 104(23), 9673–9678.

    Article  PubMed  CAS  Google Scholar 

  84. Uchida, S., Schneider, A., Wiesnet, M., et al. (2009). An integrated approach for the systematic identification and characterization of heart-enriched genes with unknown functions. BMC Genomics, 10, 100.

    Article  PubMed  CAS  Google Scholar 

  85. Wheeler, D. L., Church, D. M., Federhen, S., et al. (2003). Database resources of the national center for biotechnology. Nucleic Acids Research, 31(1), 28–33.

    Article  PubMed  CAS  Google Scholar 

  86. Gellert, P., Uchida, S., & Braun, T. (2009). Exon array analyzer: A web interface for Affymetrix exon array analysis. Bioinformatics, 25(24), 3323–3324.

    Article  PubMed  CAS  Google Scholar 

  87. Gellert, P., Jenniches, K., Braun, T., & Uchida, S. (2010). C-It: A knowledge database for tissue-enriched genes. Bioinformatics, 26(18), 2328–2333.

    Article  PubMed  CAS  Google Scholar 

  88. Mituyama, T., Yamada, K., Hattori, E., et al. (2009). The functional RNA database 3.0: Databases to support mining and annotation of functional RNAs. Nucleic Acids Research, 37(Database issue), D89–D92.

    Article  PubMed  CAS  Google Scholar 

  89. Krzyzanowski, P. M., & Andrade-Navarro, M. A. (2007). Identification of novel stem cell markers using gap analysis of gene expression data. Genome Biology, 8(9), R193.

    Article  PubMed  CAS  Google Scholar 

  90. Tang, F., Barbacioru, C., Wang, Y., et al. (2009). mRNA-Seq whole-transcriptome analysis of a single cell. Nature Methods, 6(5), 377–382.

    Article  PubMed  CAS  Google Scholar 

  91. Kurimoto, K., Yabuta, Y., Ohinata, Y., et al. (2006). An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis. Nucleic Acids Research, 34(5), e42.

    Article  PubMed  CAS  Google Scholar 

  92. Kamme, F., Zhu, J., Luo, L., et al. (2004). Single-cell laser-capture microdissection and RNA amplification. Methods in Molecular Medicine, 99, 215–223.

    PubMed  CAS  Google Scholar 

  93. http://stemcells.nih.gov/info/scireport/appendixe. Accessed 22 December 2010.

  94. http://www.abcam.com/index.html?pageconfig=resource&rid=10088&pid=10039. Accessed 22 December 2010.

  95. http://www.ambion.com/stemcells/PDFs/markers.pdf. Accessed 22 December 2010.

  96. http://www.biolegend.com/index.php?page=pfeatured&id=17. Accessed 22 December 2010.

  97. http://www.cellsignal.com/pathways/stem_cell.html. Accessed 22 December 2010.

  98. http://www.ebioscience.com/media/pdf/literature/stem-cell-poster.pdf. Accessed 19 June 2011.

  99. http://www.genscript.com/stem_cell_antibodies.html. Accessed 22 December 2010.

  100. http://www.novusbio.com/research-areas/stem-cell-markers.html. Accessed 22 December 2010.

  101. http://www.rndsystems.com/mini_review_detail_objectname_MR03_StemCellMarkers.aspx. Accessed 22 December 2010.

  102. http://www.sigmaaldrich.com/life-science/cell-biology/cell-biology-products.html?TablePage=19923656. Accessed 22 December 2010.

  103. Ahn, S. M., Goode, R. J., & Simpson, R. J. (2008). Stem cell markers: Insights from membrane proteomics? Proteomics, 8(23–24), 4946–4957.

    Article  PubMed  CAS  Google Scholar 

  104. Graumann, J., Hubner, N. C., Kim, J. B., et al. (2008). Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins. Molecular & Cellular Proteomics, 7(4), 672–683.

    Article  CAS  Google Scholar 

  105. Fathi, A., Pakzad, M., Taei, A., et al. (2009). Comparative proteome and transcriptome analyses of embryonic stem cells during embryoid body-based differentiation. Proteomics, 9(21), 4859–4870.

    Article  PubMed  CAS  Google Scholar 

  106. Dihazi, H., Dihazi, G. H., Nolte, J., et al. (2009). Multipotent adult germline stem cells and embryonic stem cells: Comparative proteomic approach. Journal of Proteome Research, 8(12), 5497–5510.

    Article  PubMed  CAS  Google Scholar 

  107. Roche, S., Delorme, B., Oostendorp, R. A., et al. (2009). Comparative proteomic analysis of human mesenchymal and embryonic stem cells: towards the definition of a mesenchymal stem cell proteomic signature. Proteomics, 9(2), 223–232.

    Article  PubMed  CAS  Google Scholar 

  108. Osman, A. M., van Dartel, D. A., Zwart, E., Blokland, M., Pennings, J. L., & Piersma, A. H. (2010). Proteome profiling of mouse embryonic stem cells to define markers for cell differentiation and embryotoxicity. Reproductive Toxicology, 30(2), 322–332.

    Article  PubMed  CAS  Google Scholar 

  109. Gonzalez, R., Jennings, L. L., Knuth, M., et al. (2010). Screening the mammalian extracellular proteome for regulators of embryonic human stem cell pluripotency. Proceedings of the National Academy of Sciences of the United States of America, 107(8), 3552–3557.

    Article  PubMed  CAS  Google Scholar 

  110. Gundry, R. L., Tchernyshyov, I., Sheng, S., et al. (2010). Expanding the mouse embryonic stem cell proteome: Combining three proteomic approaches. Proteomics, 10(14), 2728–2732.

    Article  PubMed  CAS  Google Scholar 

  111. Collier, T. S., Sarkar, P., Rao, B., & Muddiman, D. C. (2010). Quantitative top-down proteomics of SILAC labeled human embryonic stem cells. Journal of the American Society for Mass Spectrometry, 21(6), 879–889.

    Article  PubMed  CAS  Google Scholar 

  112. Uhlén, M., Björling, E., Agaton, C., et al. (2005). A human protein atlas for normal and cancer tissues based on antibody proteomics. Molecular & Cellular Proteomics, 4(12), 1920–1932.

    Article  CAS  Google Scholar 

  113. Uhlen, M., Oksvold, P., Fagerberg, L., et al. (2010). Towards a knowledge-based human protein atlas. Nature Biotechnology, 28(12), 1248–1250.

    Article  PubMed  CAS  Google Scholar 

  114. Aranda, P., Agirre, X., Ballestar, E., et al. (2009). Epigenetic signatures associated with different levels of differentiation potential in human stem cells. PloS One, 4(11), e7809.

    Article  PubMed  CAS  Google Scholar 

  115. Ratajczak, M. Z., Kucia, M., Ratajczak, J., & Zuba-Surma, E. K. (2009). A multi-instrumental approach to identify and purify very small embryonic like stem cells (VSELs) from adult tissues. Micron, 40(3), 386–393.

    Article  PubMed  CAS  Google Scholar 

  116. Shin, D. M., Zuba-Surma, E. K., Wu, W., et al. (2009). Novel epigenetic mechanisms that control pluripotency and quiescence of adult bone marrow-derived Oct4(+) very small embryonic-like stem cells. Leukemia, 23(11), 2042–2051.

    Article  PubMed  CAS  Google Scholar 

  117. Shin, D. M., Liu, R., Klich, I., Ratajczak, J., Kucia, M., & Ratajczak, M. Z. (2010). Molecular characterization of isolated from murine adult tissues very small embryonic/epiblast like stem cells (VSELs). Molecules and Cells, 29(6), 533–538.

    Article  PubMed  CAS  Google Scholar 

  118. Guenther, M. G., Frampton, G. M., Soldner, F., et al. (2010). Chromatin structure and gene expression programs of human embryonic and induced pluripotent stem cells. Cell Stem Cell, 7(2), 249–257.

    Article  PubMed  CAS  Google Scholar 

  119. Kim, K., Doi, A., Wen, B., et al. (2010). Epigenetic memory in induced pluripotent stem cells. Nature, 467(7313), 285–290.

    Article  PubMed  CAS  Google Scholar 

  120. Polo, J. M., Liu, S., Figueroa, M. E., et al. (2010). Cell type of origin influences the molecular and functional properties of mouse induced pluripotent stem cells. Nature Biotechnology, 28(8), 848–855.

    Article  PubMed  CAS  Google Scholar 

  121. Newman, A. M., & Cooper, J. B. (2010). Lab-specific gene expression signatures in pluripotent stem cells. Cell Stem Cell, 7(2), 258–262.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

We thank the members of our laboratory (Katharina Jenniches, Piera De Gaspari, Mizue Teranishi and David John) for their help and support. We also thank Dr. Petra Uchida and Dr. Toutai Mituyama for their valuable advice and comments. This work was supported by a start-up-grant of the Excellence Cluster Cardio-Pulmonary System (ECCPS) (to SU), and by the Max-Planck-Society, the DFG (Br1416), the Kerckhoff-Foundation, and the Excellence Initiative “Cardiopulmonary System” (to TB).

Conflict of Interest

The authors declare no potential conflicts of interest.

Author information

Authors and Affiliations

  1. Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany

    Shizuka Uchida, Pascal Gellert & Thomas Braun

Authors
  1. Shizuka Uchida
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pascal Gellert
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thomas Braun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Shizuka Uchida or Thomas Braun.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Uchida, S., Gellert, P. & Braun, T. Deeply Dissecting Stemness: Making Sense to Non-Coding RNAs in Stem Cells. Stem Cell Rev and Rep 8, 78–86 (2012). https://doi.org/10.1007/s12015-011-9294-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12015-011-9294-y

Keywords

Search

Navigation