UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Characterization of murine hematopoietic stem cells with high self-renewal activity Kent, David Geoffrey 2009

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Notice for Google Chrome users:
If you are having trouble viewing or searching the PDF with Google Chrome, please download it here instead.

Item Metadata


24-ubc_2009_spring_kent_david.pdf [ 16.5MB ]
JSON: 24-1.0067106.json
JSON-LD: 24-1.0067106-ld.json
RDF/XML (Pretty): 24-1.0067106-rdf.xml
RDF/JSON: 24-1.0067106-rdf.json
Turtle: 24-1.0067106-turtle.txt
N-Triples: 24-1.0067106-rdf-ntriples.txt
Original Record: 24-1.0067106-source.json
Full Text

Full Text

   CHARACTERIZATION OF MURINE HEMATOPOIETIC STEM CELLS WITH HIGH SELF-RENEWAL ACTIVITY  by DAVID GEOFFREY KENT B.Sc. (Hons), University of Western Ontario, 2003  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY   in   THE FACULTY OF GRADUATE STUDIES  (Genetics)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  April 2, 2009 © David Geoffrey Kent, 2009  ii Abstract  Hematopoietic stem cells (HSCs) produce all blood cell types required throughout life. They are identified by their ability to sustain the production of at least 1% of the mature white blood cells for 4 or more months, as demonstrated in limiting dilution or single-cell transplants. Recently, methods for obtaining suspensions of highly purified HSCs from mouse bone marrow have been developed.  This has made possible the design of experiments to address: (i) the nature and extent of their biological heterogeneity, (ii) whether maintenance of durable in vivo reconstituting activity is regulated separately from HSC survival and proliferative activity, and (iii) whether differences in gene expression distinguish HSCs with durable as compared to finite in vivo self-renewal potential.  Assessment of the different types of donor-derived blood cells produced in ~100 mice transplanted with a single HSC (or a 4-day in vitro-derived clone) allowed identification of 4 subtypes, only 2 of which could propagate continuing blood formation in secondary and even tertiary recipients.  To facilitate the investigation of HSC subtypes with durable self-renewal potential (as compared to the other two subtypes with large, but finite, self-renewal potential), I devised a strategy that achieves their simultaneous, but separate, isolation from each other prior to transplantation.   From time course experiments that compared the effects of altered extrinsic cytokine stimulation on different HSC activities, I showed that low Steel factor concentrations can rapidly (within 16 hours) extinguish their in vivo regenerative ability without affecting their immediate subsequent survival or mitogenesis in vitro.  Finally, from comparative gene expression analyses I identified 3 genes (Vwf, Rhob, and Pld3) that are consistently expressed at higher levels in HSCs with durable self-renewal potential than in several closely related cell types with less extensive or already extinct self-renewal potential.  Together, these findings provide strong support for a model of HSC regulation that includes a degree of separation in the mechanisms that control HSC self-renewal from those  iii influencing their survival, mitogenesis, and lineage commitment probabilities.  Further investigations of this model using the tools and molecules herein identified should facilitate improvements in ex vivo HSC expansion and in understanding leukemogenesis.   iv Table of Contents  Abstract ........................................................................................................................................ ii  Table of Contents ....................................................................................................................... iv  List of Tables ............................................................................................................................. vii  List of Figures ........................................................................................................................... viii  List of Abbreviations .................................................................................................................. x  Acknowledgements ................................................................................................................... xii  Dedication ................................................................................................................................. xiii  Co-Authorship Statement ....................................................................................................... xiv  Chapter 1 – Introduction............................................................................................................ 1 1.1 – Concept of tissue stem cells and their regulation ............................................. 1 1.2 – Overview of the blood forming system and its hierarchical organization ..... 2 1.3 – Developmental origin of the blood forming system ......................................... 5 1.4 – Heterogeneity in the differentiation patterns of individual HSCs.................. 6 1.5 – Regulation of HSC Numbers.............................................................................. 7 1.5.1 – General principles ................................................................................... 7 1.5.2 – Cell cycle .................................................................................................. 8 1.5.3– Apoptosis ................................................................................................... 9 1.6 – Extrinsic regulation of HSCs ........................................................................... 10 1.6.1 – HSC niches ............................................................................................. 10 1.6.2 – Molecular mediators ............................................................................. 11 1.7 – Intrinsic regulators of HSC self-renewal ........................................................ 18 1.7.1 – The JAK/STAT pathway ...................................................................... 19 1.7.2 – Polycomb transcription factors ........................................................... 19 1.7.3 – Cell cycle regulators .............................................................................. 20 1.8 – Methodologies for analyzing HSC transcriptomes ........................................ 21 1.9 – Thesis objectives ................................................................................................ 24  Chapter 2 – Materials and Methods........................................................................................ 34 2.1 – Mice .................................................................................................................... 34 2.2 – Isolation of subsets of FL and adult BM cells................................................. 34 2.3 – Analysis of transplanted mice .......................................................................... 37 2.4 – Cell cultures ....................................................................................................... 38 2.5 – Statistical analysis ............................................................................................. 39 2.6 – Quantitative real-time PCR analysis ............................................................... 39 2.7 – Construction and sequencing of LongSAGE libraries .................................. 40  Chapter 3 – Heterogeneity of HSC programs and their Resolution by Improved Purification methods ...................................................................................... 44 3.1 – Introduction ....................................................................................................... 44  v 3.2 – Results ................................................................................................................ 46  3.2.1 – Identification of subtypes of murine HSCs with differing self- renewal programs ............................................................................................. 46  3.2.2 – Isolation of different HSC subtypes using EPCR as a substitute phenotypic marker for Ho efflux ability ......................................................... 48  3.2.3 – Staining for EPCR in combination with CD48 and CD150 allows high and low self-renewal HSCs to be separately purified ........................... 49  3.2.4 – The E-SLAM phenotype is useful as a strategy for isolating highly purified suspensions of HSCs from reconstituted animals ................ 51 3.3 – Discussion .......................................................................................................... 52   Chapter 4 – Steel Factor Blocks Rapid Hematopoietic Stem Cell Differentiation and Leads to Predominantly Asymmetric Divisions .......................................... 66 4.1 – Introduction ....................................................................................................... 66 4.2 – Results ................................................................................................................ 67  4.2.1 – Different SF concentrations alter maintenance of HSC activity ...... 67  4.2.2 – SF concentration can rapidly alter the defining properties of HSCs without affecting their viability or cell cycle progression ................... 68  4.2.3 – Most HSC self-renewal divisions stimulated by SF and IL-11 in vitro are asymmetric ......................................................................................... 69  4.2.4 – Potential intrinsic molecular mediators of the ability of SF to sustain the stem cell state of HSCs in vitro ..................................................... 70 4.3 – Discussion .......................................................................................................... 70   Chapter 5 – Comparative transcriptome analysis of purified HSCs from Highly Purified Murine Fetal Liver and Adult Bone Marrow HSCs .................... 79 5.1 – Introduction ....................................................................................................... 79 5.2 – Results ................................................................................................................ 80  5.2.1 – Construction and characteristics of LongSAGE libraries prepared from highly purified FL and adult BM HSCs ............................... 80  5.2.2 – A gene expression signature for FL and adult BM HSCs ................. 81  5.2.3 – Identification of a subset of genes whose lower expression is associated with “nearest neighbours” of high self-renewal HSCs ................ 82 5.3 – Discussion .......................................................................................................... 83  Chapter 6 – Discussion and Future Directions..................................................................... 113 6.1 – Major contributions ........................................................................................ 113                6.2 – Implications and future directions ................................................................ 116 6.2.1 – Opportunities for direct and high-resolution analyses of HSC heterogeneity afforded by simpler and more selective isolation strategies .......................................................................................................... 116 6.2.2 – Exogenous regulation of HSC self-renewal ...................................... 120 6.2.3 – Molecular mechanisms regulating different HSC self-renewal states ..................................................................................................... 122 6.2.4 – New mediators of HSC regulation ..................................................... 123 6.3 – Concluding comments .................................................................................... 124   vi References ................................................................................................................................ 127 Appendix .................................................................................................................................. 147     vii List of Tables   Table 1.1 – Regulators of HSCs in the Stem Cell Niche ........................................................... 26  Table 1.2 – Genes Shown to Regulate HSC Self-Renewal ........................................................ 27  Table 2.1 – List of primers used in Chapters 4 and 5 ................................................................. 42  Table 4.1 – HSC yields are reduced in cultures containing a low concentration of SF ............. 74  Table 5.1 – Tags over-represented in the adult BM HSC library vs. the FL HSC library ......... 87  Table 5.2 – Tags over-represented in the FL HSC library vs. the adult BM HSC library ....... 104    viii List of Figures   Figure 1.1 – In vivo transplantation assay to detect HSCs ......................................................... 28  Figure 1.2 – Hierarchical model of hematopoiesis .................................................................... 29  Figure 1.3 – SF signalling and its role in HSCs ......................................................................... 30  Figure 1.4 – Key regulators of HSCs ......................................................................................... 31  Figure 1.5 – Polycomb complexes induce epigenetic silencing ................................................ 32  Figure 1.6 – Possible outcomes following the division of an HSC ........................................... 33  Figure 2.1 – cDNA amplification protocol for PCR-serial analysis of gene expression (PCR- SAGE) library generation ................................................................................... 43  Figure 3.1 – WBC outputs in recipients of single HSCs or their clonal progeny generated  in vitro .............................................................................................................. 54  Figure 3.2 – Identification of HSC subtypes in ternary plots of their lineage-specific contributions at 16 weeks post-transplant ........................................................ 56  Figure 3.3 – Rapid alteration of HSC distributions in vitro ....................................................... 57  Figure 3.4 – Clonal propagation of repopulation patterns in secondary and tertiary  recipients ............................................................................................................. 58  Figure 3.5 – CD45midRho-EPCR+ cells are almost exclusively SP ............................................ 60  Figure 3.6 – Approximately half of all CD45midRho-EPCR+ cells are HSCs and these  segregate into the same distribution of subtypes as CD45midlin-Rho-SP HSCs .. 61  Figure 3.7 – All 4 patterns of HSC differentiation are observed in the recipients of single CD45midRho-EPCR+ cells ................................................................................... 62  Figure 3.8 – CD45+EPCR+CD48-CD150+ (E-SLAM) cells from E14.5 FL cells and adult  BM are highly enriched for HSCs ...................................................................... 63  Figure 3.9 – CD150 expression divides the CD45+EPCR+CD48- adult BM cell population  into fractions differentially enriched in HSCs with high and low self-renewal properties............................................................................................................. 64  Figure 3.10 – CD45+EPCR+CD48-CD150+ (E-SLAM) is a surrogate marker for HSCs with  high self-renewal and isolates HSCs from reconstituted animals at high purity 65  Figure 4.1 – Kinetics of division of CD45midlin-Rho-SP cells cultured in different SF concentrations ..................................................................................................... 75  ix  Figure 4.2 – Time course of changes in HSC activity under different concentrations of SF .... 76  Figure 4.3 – Asymmetry of HSC expansion and maintenance divisions stimulated by 20  ng/mL IL-11 plus either 10 ng/mL or 300 ng/mL SF ......................................... 77  Figure 4.4 – Bmi1, Ezh2 and Lnk transcripts are downregulated with loss of HSC activity ..... 78  Figure 5.1 – LongSAGE libraries prepared from HSC-enriched fractions of E14.5 FL and  adult BM cells ................................................................................................... 107  Figure 5.2 – Prnp, Gata3, and Bmi1 transcripts are differentially expressed by E-SLAM  and CD45+EPCR+CD48-CD150- adult BM cells .............................................. 108  Figure 5.3 – Elevated Vwf, Rhob, and Pld3 expression is consistently associated with high  self-renewal activity in HSCs ........................................................................... 109  Figure 5.4 – Q-RT-PCR analyses of transcript levels of selected genes in various FL and  adult BM cell populations as indicated ............................................................. 110  Figure 5.5 – Q-RT-PCR analyses of transcript levels of selected genes in various adult  BM cell populations as indicated ...................................................................... 111  Figure 5.6 – Q-RT-PCR analyses of transcript levels of selected genes in cytokine  stimulated adult BM HSCs ............................................................................... 112  Figure 6.1 – A model detailing the relationship between the different HSC subtypes ............ 126  x List of Abbreviations   AGM  Aorta gonad mesonephros APC  Allophycocyanine ATRA  All-trans retinoic acid BM  Bone marrow CFC  Colony forming cell CFU-C  Colony forming unit-cell CFU-S  Colony forming unit-spleen CLP  Common lymphoid progenitor CMP  Common myeloid progenitor CRU  Competitive repopulating unit E  Embryonic day FBS  Fetal bovine serum FITC  Fluorescein isothiocyanate FL  Fetal liver Flt3L  Fms-like tyrosine kinase 3 ligand G-CSF  Granulocyte-colony stimulating factor GFP  Green fluorescence protein GM  Granulocytes/monocytes GM-CSF Granulocyte/macrophage-colony stimulating factor HF  HBSS plus 2% fetal bovine serum Ho  Hoechst 33342 HSC  Hematopoietic stem cell IGF  Insulin-like growth factor IL  Interleukin KSL  cKit+Sca1+Lin- LIF  Leukemia inhibitory factor Lin  Lineage markers M-CSF  Macrophage-colony stimulating factor MHC  Major histocompatibility complex PBS  Phosphate buffered saline PE  Phycoerythrin  xi PI  Propidium iodide Q-RT-PCR Quantitative reverse transcription PCR RAR  Retinoic acid receptor RB  Retinoblastoma RBC  Red blood cell Rho  Rhodamine 123 SA  Streptavidin SAGE  Serial analysis of gene expression SF  Steel factor SFM  Serum free medium SP  Side population STRC  Short-term reconstituting cell TGF-β  Transforming growth factor beta TNF  Tumour necrosis factor TPO  Thrombopoietin W41  C57Bl/6JW41/W41 WBC  White blood cell  xii Acknowledgements To Connie, I could not have asked for a more supportive or challenging supervisor.  You provided the perfect balance of motivation and freedom and had the uncanny ability to always know when I needed boosting up or knocking down.  You taught me much more than science (though the encylclopedic knowledge was useful!) and I truly value your dedication to training.  To Jamie, Kelly, and Marco for all of your guidance, criticism, and inspiring discussion. To Keith Humphries and Allen Eaves, for being wonderful mentors, even without official roles, your academic contributions and encouragement have been extremely valuable.  To Brad, for teaching an annoying newbie all the tricks of the trade at ridiculous hours of the morning and night and for being a scientific and personal role model of enormous proportion. To the others with whom I worked closely on research projects, Kai, Mike C., Claudia, Stefan, Michelle, Sanja, Florian, and Maura for keeping the work environment positive and being willing and able to buckle down and get some great work done during busy times.  To Mike O, Peter, Yun, John, Afshin, Maisam, and Mel for your special brands of thinking and your contributions to the many other things that go on outside of lab work. To the highly motivated and talented group of co-op and research students – Lindsay, Shannon, Jay, Elaine, and Heidi – who I was fortunate to supervise in some capacity, the work and energy that you gave to the lab group was amazing.  I hope that you all took great memories and experience from here and go on to enormous success in your futures. To the many friends and colleagues that have made the Terry Fox Lab and the BCCA a thoroughly enjoyable place to work: specifically the Martini’s, OJ’s, Bean So Good, and “outdoorsy” folks.  You have all given the lab a wonderful sense of camaraderie; I can only hope to work with such a great group in the future.  To past and present GrasPods executive members, this place is pretty special and it is because people like you are willing to donate your time to making it so.  Keep it up.  To Erika and Beth and the huge number of volunteers and collaborators involved in the UBC Let’s Talk Science Partnership Program, for making my time at UBC about far more than lab research.  To Janet, Chad, and Brian for putting your faith in us to build something big, I know that you will continue to give such support to the next generation of students.  To UWO professors Burr Atkinson and Tony Percival-Smith for teaching me that Genetics (and Biology for that matter) was much more about problem solving than swallowing text books.  To my brother Eddy and sister-in-law Terri, for your choice of cities over the years, for your support, company, good judgment, and for bringing nephew number one, Felix, into our lives.  To my mom, Eileen, for your version of pre-Kindergarten and your unwavering support for me throughout life, even though I have not always deserved it. To my dad, Ed, for just the right amount of pressure to perform at school and for distracting me during stressful times with talk of how well hockey players with (sometimes questionable) ties to Newfoundland were doing.  To Lindsay, without whom I would be a complete train wreck, for teaching me more about myself than I could ever learn on my own, for supporting me over the PhD years (especially this last one) and for getting me out into the wilderness of BC much more frequently than I would have otherwise.  xiii                        To Lindsay, For being you, and loving me for being me  xiv Co-Authorship Statement   Chapter 3: This article draws on two major bodies of work – the first of which I worked jointly with Brad Dykstra (a PhD Candidate in the Eaves lab) and the second of which was primarily conducted by me.  The work in the first section (HSC subtype identification, Figures 3.1 - 3.4) was initiated by Brad Dykstra in 2002 and was completed in 2006.  The second section (Improved purification and prospective isolation of HSCs with high self-renewal activity, Figures 3.5-3.10) began in 2005 and was completed in 2008. HSC subtype identification - The work presented was designed by Brad Dykstra with intellectual input from Connie Eaves and me.  Transplants of single cells and in vitro clones were performed by Brad Dykstra and me. Assistance with peripheral blood sampling, staining, and FACS analysis, was provided by Melisa Hamilton, Lindsay McCaffrey, and Kristin Lyons. Brad Dykstra performed the in-depth data analysis and generated the figures. The resulting manuscript was prepared by Brad Dykstra, Connie Eaves, and me. Improved purification and prospective isolation of HSCs with high self-renewal activity – The work presented was designed primarily by me with intellectual input from Brad Dykstra, Claudia Benz, Maura Gasparetto, and Connie Eaves.  Transplants of bone marrow HSCs were performed by me and transplants of fetal liver HSCs were performed by Claudia Benz. Assistance with peripheral blood sampling, staining, and FACS analysis, was provided by Shannon Russell, Jay Cheyne, Elaine Ma, and Heidi Mader.  The E-SLAM staining strategy was jointly discovered by Maura Gasparetto and myself.  I generated the figures and tables that appeared in the resulting manuscript which were prepared by me with input from Brad Dykstra and Connie Eaves.  Chapter 4: The work presented in this chapter took place between 2003 and 2007.  I designed the experiments with significant input from Brad Dykstra and Connie Eaves. Transplants of single cells and in vitro clones were performed by Brad Dykstra and me. Together with Brad Dykstra, I designed the cell doublet splitting technique.  I optimized the RNA isolation strategy designed for small cell numbers.  Assistance with peripheral blood sampling, staining, FACS analysis, RNA isolation, and QPCR was provided by Jay Cheyne and Elaine Ma.  xv I generated the figures and tables and prepared an initial draft of the manuscript. Brad Dykstra, Connie Eaves and I were involved in all other aspects of manuscript preparation.  Chapter 5:  The work presented in this chapter was the result of the simultaneous development of multiple different technologies and discoveries that took place from 2003 through to 2008.  Yun Zhao and Afshin Raouf in our lab, together with the help of the Michael Smith Genome Sciences Centre, were able to devise and validate a strategy that modifies the Clontech SMART amplification system to make Serial Analysis of Gene Expression libraries from limiting amounts of input RNA (10 ng). I was involved in the bioinformatic analyses to validate this strategy’s accuracy when compared to non-amplified material.  Using this strategy, in collaboration with Brad Dykstra and Michelle Bowie, I collected HSCs from adult bone marrow and fetal liver.  I amplified the collected material with assistance from Yun Zhao and the two libraries were constructed and analysed at the Genome Sciences Centre by Yongjun Zhao, Allen Delaney, and Martin Hirst. The candidate gene selection, isolation and culture of HSCs and progenitor cells, and follow-up QPCR assays were designed and performed jointly by Michael Copley and myself. Assistance with RNA Isolation and QPCR was provided by Jay Cheyne and Elaine Ma.  I performed the data analysis and generated the figures. The resulting manuscript was primarily prepared by me, with significant input from Connie Eaves.  1 1. Introduction     1.1   Concept of tissue stem cells and their regulation  The fundamental definition of a stem cell is a cell that has the competence to produce the specialized cells of a particular tissue but also possesses a mechanism to maintain this competence for an indefinite period.  In order for stem cells to sustain their numbers and hence provide for the variable lifetime needs for specialized cell production, there must be mechanisms for regulating whether stem cells retain their differentiation potential or whether they begin to activate its expression.  The establishment of competence for particular differentiation programs is presumably mediated by a combination of genetic and epigenetic mechanisms.  The regulation of whether and how that competence is sustained (or not) is often referred to as the “self- renewal” process that is viewed as the cardinal feature of stem cells.  This process and its regulation underlie the ability of stem cells to remain as the lifetime source of the specialized cells of the tissue throughout development as well as under conditions of variable demand. In model systems, stem cells have been studied at purity and in great detail.  This has allowed many molecules and pathways to be described as necessary or sufficient for stem cell maintenance or differentiation.  For example, studies in Drosophila melanogaster have been particularly useful in generating concrete evidence of a localized “niche” that provides positive support for germ stem cells (see Section 1.3) and plays a role in the asymmetric partitioning of molecules within these cells that dictate their subsequent fates. The first formal indication for the existence of a stem cell in the hematopoietic system was provided by the seminal experiments of Till and McCulloch1.  They showed that small collections of cells appeared on the spleens of transplanted myeloablated mice upon injection of  2 small numbers of bone marrow (BM) cells and that the number of these collections of cells was proportional to the number of BM cells originally transplanted. They also introduced the important principle of assigning functional names to cells that could only be detected retrospectively by functional read-outs (hence the term colony-forming unit-spleen, abbreviated as CFU-S and later the term, colony-forming unit-culture, abbreviated as CFU-C).  This group also established that the discrete collections of cells visible on the spleen surface were indeed clones and that, at later time points, they contained multiple lineages of myeloid cells as well as cells able to give rise to secondary spleen colonies (i.e.: the original CFU-S were multipotent and had self-renewal ability)2. Subsequent efforts to purify CFU-S culminated in a landmark paper from Spangrude et al.3 who demonstrated that this could be achieved by selecting for a subset of adult mouse BM cells that express both Thy1 and Sca1 after removal of all cells expressing markers for each of the major types of mature blood cells (so-called lineage or “lin” markers).  This advance ushered in a new era of HSC biology that began to focus on interrogating directly the properties of very primitive subsets of multipotent cells, more akin to the experiments that had previously been limited to simpler model organisms.  Interestingly, as detailed below, these eventually showed that most CFU-S are downstream of a more primitive hematopoietic cell type that has much more extensive self-renewal potential4-7, although the original concept of stem cell self-renewal has remained largely unchanged.   1.2   Overview of the blood-forming system and its hierarchical organization  The hematopoietic system is responsible for producing all of the various types of specialized blood cells in numbers required throughout life.  These specialized blood cells  3 comprise those of the lymphoid lineages, which include B-cells, T-cells, and natural killer cells, as well as a diversity of myeloid cell types, including erythrocytes, monocytes, dendritic cells, neutrophilic, eosinophilic and basophilic granulocytes, mast cells, and megakaryocytes that generate platelets.  Most of the mature forms of these cells cannot proliferate and also have short lifespans (a few days or weeks).  Thus, in order for the required numbers of mature blood cells to be maintained, new ones must be continuously generated. The first indication of a common origin of different blood cell types was provided by morphological8 and cytogenetic9 studies of what are now recognized as clonal myeloproliferative diseases in humans.  This concept was later experimentally validated by the characterization of CFU-S as a population of cells with multi-lineage differentiation potential and their origin from a cell not detectable as CFU-S but that had lymphoid as well as myeloid reconstituting activity2. Later, genetic tracking analyses confirmed the ability of single hematopoietic cells from normal murine and human donors to establish chimerism in the blood-forming system of transplanted recipients for periods of months to years10-13.  In some of these latter studies, the ability of the original cell to produce progeny with extensive multi-lineage regenerative potential was also documented.  Together, these observations established the existence of HSCs in mice and humans.  Subsequent experiments focused on the development of a limiting dilution approach for quantifying HSCs14,15.  This led to the adoption of a second operational term, competitive repopulating units (CRUs) to define murine HSCs as those cells that are able to regenerate at least 1% of the white blood cells, including both lymphoid and myeloid lineages for a minimum of 4 months (Figure 1.1)16-21. Much evidence indicates that the differentiation of HSCs is achieved throughout adult life by a complex multi-step differentiation process - one that originates in a rare population of cells individually capable of generating all (or most) of the differentiated blood cell types (shown schematically for the murine system in Figure 1.2).  In order for this population of cells to be  4 sustained in adequate numbers, a process must exist which ensures that their numbers are maintained throughout life. This means that, on average, when HSCs divide, at least one daughter cell must retain the same latent developmental properties to offset losses due to death or differentiation (reviewed in Bryder et al.22).  Equally important for the regulation of blood production is the differentiation process which allows the step-wise and regulated progression of cells from HSCs to multipotent progenitors, to oligopotent progenitors, to unipotent progenitors leading finally to the execution of terminal differentiation programs that generate the different types of specialized mature blood cells.  Experiments that have given strength to this hierarchical model have provided evidence of distinct and separable cell types that are derivative of HSCs and display the range of potentialities characteristic of the generally accepted sequential branching model shown in Figure 1.2.  Importantly, this includes evidence of a hierarchy within rare cells that are not fully committed to a single lineage and even extends into the compartment of cells that display no lineage restriction at all in their differentiation potential.  Examples of these primitive subsets include the Lin-IL7R+Thy1-Sca1-Kitlo common lymphoid progenitors (CLPs) that both in vitro and in vivo display an ability to give rise to large numbers of exclusively lymphoid cells but only for a short period of time23, the Lin-Kit+Sca1-(KSL)IL7Rα-FcγRloCD34+ common myeloid progenitors (CMPs) that display the complementary repertoire (i.e., transient output of only myeloid cells)24, and KSLFlt3+ multipotent cells capable of making both lymphoid and myeloid lineages but only for 8 weeks following transplantation (hence their designation as short term (ST)-HSCs)7,25.      5 1.3   Developmental origin of the blood forming system  During development, two independent waves of hematopoiesis are readily distinguished. The first is called primitive and the second definitive.  Current evidence suggests that both derive from mesodermal cells that differentiate into cells with endothelial features and/or potential, although this remains controversial.  Primitive hematopoiesis creates the immediately necessary red blood cells (RBCs) and a few macrophages first seen in mice around embryonic (E) day 7.5 in the yolk sac blood islands26.  Embryonic RBCs are unique in that they remain nucleated and express embryonic hemoglobin.  A few days later, definitive hematopoiesis is initiated independently in multiple sites that include the aorta-gonad-mesonephros (AGM) region27,28 and the placenta29,30.  This process is associated with the first appearance of transplantable HSCs. Circulation is established around E10 which is thought to allow the cells from the sites of origin of HSCs to enter the developing liver and spleen. Just before birth, hematopoietic cells also migrate to the BM.  The BM then becomes the primary site of blood cell production after birth (reviewed in Orkin et al.26).  Importantly, a number of key properties of HSCs have been documented to change markedly between fetal life and adulthood18.  Fetal HSCs are actively cycling as compared to their primarily quiescent adult counterparts and fetal HSCs also display faster regenerative kinetics and a greater average output of granulocytes and macrophages after their transplantation into myeloablated hosts.  Fetal and adult HSCs also have distinct gene expression signatures and distinct processes of lineage restriction and differentiation kinetics.       6 1.4   Heterogeneity in the differentiation patterns of individual HSCs  Studies of the clonal outputs of individual HSCs with longterm in vivo repopulating activity have revealed wide variability in the absolute and relative numbers of the different types of mature cells they generate.  This heterogeneous behavior has brought into focus the uncertainties of describing HSCs and their properties by the regenerative activity they display in bulk assays.  Such retrospective approaches are necessarily limited by the fact that they cannot discriminate behavioral differences caused by variations in the types or sequence of extrinsic cues received by the original cells (or their progeny) or the role of co-transplanted cells of other types versus pre-existing intrinsic heterogeneity and/or the contribution of intrinsic stochastic events.  Resolution of these issues requires experiments that can track all the clonal progeny produced by many HSCs over extensive periods and preferably in the absence of other cell types or even other HSCs. The HSC compartment of fetal and young adult mice is one example where a compartment of cells that meet the same defining criteria (as CRUs) display different differentiation properties as well as different self-renewal activities when transplanted into irradiated recipients.  Unfortunately, the combination of phenotypic markers historically used to obtain these cells at very high purities cannot yet be assumed to measure, or even detect, cells with the same properties in uncharacterized cell suspensions.  This is because many of the markers in question show variable expression on HSCs according to the activation status of the HSCs and may also be variably expressed on non-HSCs31-33.  The identification of molecular markers that stably associate with self-renewing HSCs independent of their cycling status or differentiation program should help to elucidate the mechanism that allows for long-term maintenance of HSC activity.  7 Tracking the clonal progeny of single adult BM HSCs (or their in vitro progeny) through 2 or 3 serial transplants has revealed their possession of specific lineage preferences that can be propagated over many self-renewal divisions in vivo.  However, these differentiation programs can also change rapidly, both in vivo (e.g., at 3 weeks after birth in mice) and under certain culture conditions18,21,34.  Taken together, these findings support a new model of HSC development in which the mechanisms that control their lineage preferences and self- maintenance have distinct, although possibly overlapping, elements with the previously unrecognized possibility that lineage preferences may be established before, rather than after, self-renewal potential is lost.   1.5  Regulation of HSC numbers  1.5.1  General principles  The number of HSCs maintained in an organism is thought to be regulated by a number of factors either intrinsic or extrinsic to the stem cell35-38.  This can occur in a number of ways, including changes mediated by both external and internal factors that control their cell cycle, apoptotic pathways, or their self-renewal ability.  Molecules intrinsic to the cell that govern HSC fates are discussed in Section 1.7. Many model systems have documented extrinsic mechanisms of stem cell regulation that are both necessary and sufficient for controlling their key properties.  Perhaps the best studied are those operative in the neuroblast and germ stem cell niches of Drosophila 36,39,40. Demonstration of the importance of a single factor is exemplified by studies of decapentaplegic (dpp) in Drosophila germ stem cells.  In these niche cells, genetic loss of dpp function has been  8 shown to cause a depletion of germline stem cells. Conversely, Flp-induced mitotic recombination experiments indicate that the heat shock protein-induced production of germline tumours (in which many cells resemble germline stem cells) is mediated by receptors/transducers of a dpp signal (i.e.: Mothers against dpp [Mad] and punt)40,41. One of the major reasons that model organisms like Drosophila have been so powerful for delineating mechanism(s) of stem cell self-renewal control is their ability to enable the measurement of responses of single cells to pure populations of supporting cells.  It is for this reason that the prospective isolation of highly purified HSCs has been so hotly pursued as it gives great power to gene expression and protein localization studies, and also allows for determination of direct effects of various molecules (cytokines, drugs, etc) on the cells of interest.   1.5.2  Cell cycle  One of the simplest ways to alter the rate of expansion/contraction of a cell population is to alter the proportion of the cells that are proliferating.  Measurements of HSC numbers during development have shown that they expand, consistent with the expectation that this would be required to accommodate the needs of the growing organism.  A number of groups have demonstrated that the HSCs found in the fetal liver (FL) at E14.5 are actively in cycle42,43 whereas the vast majority (>90%) of those in the adult BM are generally in the G0 (quiescent) phase of the cell cycle44.  During this more stable phase, where mature blood cells are being destroyed and renewed at an impressively large yet relatively constant pace, questions surrounding the activation of cells within the HSC compartment have generated much debate. Do HSCs sit dormant in G0 until the body requires activation of one or many HSCs and the  9 remaining HSCs refill the compartment with self-renewal expansion divisions (a clonal succession model)45? or do HSCs continually enter and exit the cell cycle as suggested by the BrDU labelling experiments of Bradford et al. 46 and Cheshier et al.44 which indicated that >99% of the KSLThy1+ BM cells entered the cell cycle at least once every 2 months? Two recent papers47,48 have utilized a histone 2B (H2B)-green fluorescent protein (GFP) fusion protein for the tracking of cell divisions in populations of long term HSCs.  These newer studies now suggested that the most primitive HSCs divide, on average, only once every 145 days (i.e.: only a few times over the course of the entire lifespan of a mouse)47.  Elucidation of the mechanism(s) that regulate the proliferative activity of HSCs in vivo is critical to understanding the pressures for control at later stages and has attracted the attention of mathematical modelers and stem cell biologists alike.  These models and questions can only be addressed with the recent advances that allow highly purified HSCs to be studied independent of their immediate downstream progenitor cell populations.  Some cell cycle regulators with specific roles in HSC self-renewal are described below in Section 1.7.3.   1.5.3 Apoptosis  Apoptosis is a form of programmed cell death that results in loss of membrane integrity, cell shrinkage, and DNA fragmentation and it is an essential process during development and homeostasis49.  A large body of evidence supports apoptosis as a major player in the regulation of mature blood cell numbers50,51, especially in the regulation of T-cell production during which a few thymocytes differentiate but most die.  Specifically, thymocytes that bind with low affinity to Major Histocompatibility Complex (MHC) class I or MHC class II differentiate into cytotoxic T cells or helper T cells, respectively, while those that bind with high affinity to self-MHC  10 ligands undergo apoptosis52.  Investigations of the role of apoptosis in regulating HSC numbers has been initiated but is less well developed.  Most information has come from studies of HSCs generated in a Bcl-2 transgenic mouse that overexpresses Bcl-2 under the control of the H2Kb promoter53,54.  These mice show increased HSC activity both in vitro and in vivo relative to control mice.   1.6  Extrinsic regulation of HSCs  1.6.1  HSC niches  The influence of external cues on the fate of stem cells is thought to be mediated largely by localized interactions that reflect the existence of specialized molecular microenvironments referred to as stem cell niches.  The concept of localized as opposed to humoral control of HSC activity dates back to historical findings that intravenously injected cell suspensions of normal BM cannot cure the anemia of Sl/Sld mice, whereas grafts of tissue fragments lacking hematopoietic cells can55.  Subsequent observations by Lord et al.56 showed that the majority of CFU-S within the BM are concentrated in the peripheral areas as opposed to the central marrow cavity.  In 1978, Schofield57 introduced the term “niche” to highlight the idea of specialized sites of HSC (CFU-S) support and regulation. Although this idea has since gained much interest, the anatomical location and cellular make-up of HSC niches remain subjects of debate.  Nevertheless, there appears to be a consensus that in the BM the vast majority of HSCs reside close to the bone like the closely related CFU-S population.  Using a Y chromosome-specific probe to identify male HSCs (cells that excluded Hoechst 33342 [Ho] and Rhodamine 123 [Rho]), Nilsson et al. showed that these cells migrate to  11 the endosteal surface of the bone following intravenous transplantation58.  Similarly, TIE2- positive KSL cells were found to be located in close contact with osteoblasts at the endosteal surface of the BM of transplanted mice59.  However, recent studies using a combination of markers that are more selective for HSCs (i.e.: a Lin-CD150+CD48-CD41+ phenotype) indicate that HSCs are more commonly found at the surface of the sinusoidal endothelium19 which has recently also been supported by live animal in vivo imaging studies using two-photon microscopy60.   1.6.2  Molecular mediators  The niche concept has also stimulated much research into the cells and molecules that promote HSC self-renewal.  Feeder cells from many different sources have been found to have such activity and these include stromal cells derived from the AGM61, urogenital ridge62, FL62, brain endothelium63, BM64, and osteoblasts59,65-67.  From these and other studies, many molecules that can influence HSC activity have been identified as summarized in Table 1.1 (adapted from Kiel et al.68).  In order to determine accurately the effect that various molecules have on HSC self- renewal, it is most powerful to ask these questions on single cells and in a defined medium where the factors can be assessed on an individual basis for their direct impact on HSC maintenance (self-renewal).  Use of defined media will also be essential for future ex vivo expansion of HSCs for clinical applications.  Many growth factors have been identified as having roles in regulating specific stages of hematopoiesis.  Most of these studies identified effects on populations where the precise cellular mechanisms were not discriminated.  Others have identified effects on cell survival and/or  12 proliferation.  Only in a few instances have effects on lineage selection been conclusively demonstrated, as in the cases of Granulocyte-Colony Stimulating Factor (G-CSF), Macrophage (M)-CSF, GM-CSF, Interleukin (IL)-5, and Leukemia Inhibitory Factor (LIF)69. Importantly, none of these also include effects on the self-renewal mechanism operative in HSCs with long term in vivo regenerative activity31,70. Elucidating the role of soluble extrinsic factors on HSC self-renewal requires the use of sufficiently pure HSC populations that the effects seen can be definitively attributed to effects on HSCs.  Counteracting the supportive and stimulating effects of positive influences are numerous studies that point to the existence of molecular interactions that can have a direct negative impact on HSC functions (e.g.: Transforming Growth Factor-β  [TGF-β]71, Tumour Necrosis Factor [TNF]72, and inappropriately high concentrations of IL-1 or IL-373, or IL-6 or IL-1174).  In addition, there is an extensive literature indicating that HSCs express cell surface components like CD3475, CD4476, VLA477 and VLA578 that enable them to interact with “fixed” molecules in the extracellular matrix or adjacent cells (reviewed in Chan et al.79).  The following section summarizes some selected examples of studies that have been undertaken to address the issue of how extrinsic factors can modulate expansion of HSC populations in vitro and illustrates how little definitive information there is as yet on this subject.  Steel Factor (SF) - SF (also known as Stem Cell Factor, Mast Cell Growth Factor, and/or KIT-ligand) is a transmembrane growth factor encoded by the Sl gene.  SF binds to and activates a type III transmembrane receptor tyrosine kinase called KIT (also referred to as CD117, see Figure 1.3).  KIT contains a split intracellular kinase domain and is encoded by a transcriptional unit found at the W locus.  Both SF and its receptor can be expressed as different isoforms with different activities and can be cleaved proteolytically to yield soluble forms with similar binding affinity80,81.  13 Even before the products encoded by the W and Sl loci were known to represent a receptor-ligand pair, studies of the defects caused by mutations at both loci had pointed to their involvement in HSC regulation.  For example, both fetal and adult hematopoietic tissues from mice carrying mutations within the kinase domain of Kit (e.g., see Figure 1.3) show reduced CFU-S/HSC activity82.  Mice with a W41/W41 genotype are of particular interest because they are viable and fertile (in contrast to those with more severe W-mutations)83, but still have significantly reduced HSCs numbers (10 to 20-fold).  As a result, sublethally irradiated adult W41/W41 mice can be used as hosts to detect transplanted (wild-type) HSCs with the same sensitivity as lethally irradiated wild-type hosts given a minimal radioprotective transplant42,84. In contrast, Sl-mutant mice, which have deletions in the SF genomic sequence85, have a defect in the microenvironmental niche that supports the regenerative activity of CFU-S/HSCs55. HSCs from all stages of development express the same levels of the KIT receptor on the cell surface regardless of their cycling status or position in the cell cycle43,86-88.  In vitro, the ability of different concentrations of soluble SF to modulate HSC self-renewal divisions directly has been demonstrated using highly purified starting populations and subsequent in vivo readouts of retained or lost HSC activity17,89,90.  Moreover, these effects on HSC self-renewal can be elicited even in the absence of changes in HSC viability or cell cycle progression.  These experiments have further shown that the self-renewal responses of fetal and adult murine HSCs to soluble SF in serum-free suspension cultures are both steeply SF concentration-dependent above and below an optimum level but their specific sensitivities to SF are markedly different. Fetal HSCs are 6-fold more sensitive to SF than their adult counterparts with maximum maintenance of fetal HSC activity in medium containing 50 ng/ml of SF (only) as compared to the 300 ng/ml of SF (+ 20 ng/ml IL-11) required to achieve a similar result with adult HSCs87. The different SF sensitivity displayed by fetal and adult HSCs is likely due to differences in how KIT-activated signals are transmitted to downstream intracellular targets in these cells since both  14 express similar levels of KIT and, under their respective optimal conditions of SF stimulation, they show no differences in apoptosis and divide with the same cell cycle times18. Figure 1.3 summarizes the downstream signaling pathways likely to influence HSC self- renewal responses.  SF binding induces receptor homodimerization and auto-cross- phosphorylation of tyrosine residues in the cytoplasmic domain which then serve as docking sites for various SH2 domain-containing signalling intermediates91.  Activation of KIT also leads to the recruitment and activation of adjacent kinases including JAK292, TEC93, and MATK94, the tyrosine phosphatases SHP-1 and SHP-295, phospholipase C, and the p85 subunit of phosphatidylinositol 3-kinase (PI3-K)96.  The activated KIT receptor complex is then recruited transiently to cell surface lipid rafts where the p110 catalytic subunit of PI3-K is located97.  This allows a functional PI3-K holoenzyme to assemble leading to the subsequent activation of cytosolic PDK1 and AKT/PKB.  This is accompanied by a reduction in PTEN levels (a negative regulator of the PI3-K pathway) in the rafts thus reinforcing the activation of the PI3-K pathway and multiple downstream events including inactivation of the forkhead transcription factor (FOXO3)98 and activation of the MAPK pathway99.  SF-mediated activation of the JAK2 leads, in turn, to the activation of STAT 1, 3, and 5 which then form dimers and translocate to the nucleus to alter the transcription of specific target genes100-102.  Some of these signaling elements and their ultimate transcriptional targets appear to participate in the regulation of HSC amplification although, in many cases, it has not yet been possible to discriminate between effects on HSC viability or mitogenesis as compared to independent effects on their self-renewal control.  Gp130 - Unpaired is the Drosophila homolog for gp130 and is critical in the male germ stem cell niche as a stimulator of the JAK/STAT pathway and it is made by the cap cells which surround the germ stem cells, a location central to maintaining their stem cell function103.  In  15 mice, lack of Gp130 causes major hematological disorders104 and multiple lines of evidence indicate that cytokines that signal through gp130 can affect HSC self-renewal activity, particularly in combination with Steel factor (SF) and FMS-like tyrosine kinase-3 ligand (Flt3L)105-107.  For example, a number of different investigators have cultured adult mouse BM cells in a feeder-free medium containing SF, Flt3L, IL-6, and IL-11 in varying combinations and concentrations for 7-21 days and have found that either maintenance or moderate expansion of the HSC compartment could be achieved over this period, which was inhibited by the further addition of IL-1, IL-3, or TNF70,72,107-110. Audet et al. then showed that while SF and Flt3L together were substantially mitogenic for HSCs, stimulation of the gp130 pathway was further required to optimize HSC self- renewal74.  Additionally, they showed that this response was limited to a narrow window of effective concentrations of gp130 stimulation74.  In a subsequent study, a multi-factorial design was utilized to investigate the combined effects of multiple cytokines on HSC self-renewal and proliferation90.  The modelling component of this study produced from the collected biological data was subsequently found to be predictive of cytokine combinations that are optimally stimulatory for expanding HSC and progenitor numbers in 10-14 day cultures90.  The model also predicted the observed ability of SF and Flt3L to substitute to some extent for one another and the inhibitory effects of excessive exposure to both in combination.  In addition, these studies showed that SF and IL-11 on their own could sustain input HSCs numbers for a period of 10 days90.  Subsequent validation of this prediction was provided by the experiments of Uchida et al. who cultured individual HSCs in 300 ng/mL SF and 20 ng/mL IL-11 with or without 1 ng/mL Flt3L and showed maintenance of transplantable HSC activity in the first division progeny17.  Thrombopoietin (TPO) – The receptor for TPO is MPL and in studies of mice where one gene is deleted111,112, each was found to be necessary for the generation of normally-sized HSC  16 compartments in mice.  A positive action of TPO on HSC expansion has also been demonstrated in 7-day serum-free, feeder-free cultures113.  However, TPO alone sustains HSC numbers without inducing their proliferation114, suggesting that this factor may be unique in promoting HSC survival and maintenance of the stem cell state without affecting HSC mitogenesis.  All Trans-Retinoic Acid (ATRA) - ATRA is a Vitamin A derivative that acts as an agonist on the RA receptor (RAR).  ATRA was first noted to have an ability to stimulate the generation of progenitors with in vitro colony forming cell (CFC) activity as well as CFU-S in vivo115.  Subsequent studies showed that when added to SF, FLT3L, IL-6, and IL-11 in 7-day to 14-day serum-containing cultures of KSL cells, HSC maintenance was slightly improved relative to control cultures without added ATRA and this effect was blocked in the presence of AGN 193109 (an RAR antagonist)115.  In a later study, it was shown that ATRA-treated HSCs from RARγ−null mice were unable to repopulate animals in contrast to ATRA-treated HSCs from RARα−null mice which behaved like wild type HSCs116.  Wingless (WNT) – The Wnt family of genes are homologs of Drosophila wingless (wg) which is a well-characterized segment polarity gene.  Additionally, wg has been implicated in the maintenance of somatic stem cells in the fly117.  In 2003, 2 groups obtained evidence that WNT proteins may have a role in stimulating HSC population expansion.  One group reported that 100 ng/mL of purified WNT3A was potently mitogenic and promoted HSC self-renewal in 6-day cultures containing serum and limiting concentrations of SF118.  However, the transplantation assays used to quantify changes in HSC numbers were only taken out to 6 weeks, which is insufficient to ascribe effects on cells with long term reconstituting ability.  The second group extended this finding using HSCs transduced with a constitutively active β-catenin construct and an 11-week in vivo assay to provide evidence of expansion of HSC numbers in prior 7-day  17 cultures119.  However, even interpretation of these experiments was compromised by the fact that they were performed using Bcl-2 transgenic mice, and it has recently been reported that these findings may not be generally applicable120.  Notch Ligands – Notch is another evolutionarily conserved pathway that has been implicated as having a role in HSC biology.  Overexpression of Notch ligands in vitro has been shown to expand HSC and progenitor numbers and activity121,122.  Additionally, overexpression of the downstream target Hes1 had a similar effect123.  Recently however, it has been shown that the Notch pathway is not essential for HSC generation or self-renewal as normal HSC numbers and potency were shown to be retained when this pathway was inhibited, either by forced expression of a dominant-negative form of Mastermind-like1 (a potent inhibitor of Notch- mediated transcriptional activation) or genetic inactivation of CSL/RBPJ, a DNA-binding factor required for canonical Notch signaling124.  Insulin-related factors – Insulin signalling is essential to the viability and growth of many cells and is an essential component of most defined serum substitutes125.  Insulin-like growth factor2 (IGF2) has its own specific, but non-signalling, receptor and can bind to the insulin receptor INSR126.  IGF2 was identified as a candidate stimulator of fetal HSCs from a global gene expression comparison of supportive and non-supportive feeder cells127.  Subsequent experiments indicated that when combined with serum and SF, IL-6, and Flt3L, a 2-fold net expansion of fetal HSC number could be obtained127.  More recently, the addition of IGF Binding Factor (BF) 2 has also been attributed such activity128.  However, Bowie et al., using a similar approach but a defined insulin-containing serum substitute instead of serum, was unable to confirm these findings87.  Rather, the results they obtained revealed fetal HSCs to be much  18 more sensitive to SF activation than adult HSCs.  Thus the precise role of IGF2 signalling in HSC self-renewal remains poorly defined.  In summary, reproducibly significant (>10-fold) expansion in vitro of rigorously defined long term repopulating HSCs has not been achieved in the absence of genetic manipulation of the responding HSCs themselves.  Furthermore, the dynamics of change in HSC competence mediated by altered actions of a single growth factor have not been described.  Thus, it was not clear whether the extent to which an HSC is stimulated by a single growth factor in vitro could, on its own, dictate the maintenance or loss of self-renewal activity.   1.7  Intrinsic regulators of HSC self-renewal   The molecular regulation of HSC self-renewal is a complex and dynamic process that has been shown through a large number of studies to involve impressive networks of transcription factors, signaling pathways, and regulators of chromatin structure (see summary in Table 1.2). Although the precise role of any of these molecules and the manner with which they interact with each other remains unresolved, some exciting trends have emerged highlighting the roles of canonical signaling pathways, polycomb genes, and cell cycle regulators (reviewed in Zon129, Figure 1.4).  Some examples particularly relevant to the body of work presented later in this thesis are highlighted below.  1.7.1  The JAK/STAT pathway  Not surprisingly, many pathways activated by growth factors have been identified as having a role in HSC self-renewal.  Noted above are those related to mediating effects of SF,  19 ligands that activate Gp130, TPO, and IGF2.  All of these activate STAT3 and/or 5.  In the mouse, this activation of both STAT3 and STAT5A appears to be important as shown by studies of HSCs transduced to express a dominant-negative version of STAT3130 and cells from Stat5a-/- mice131 or human CD34+ cells with RNAi-suppressed STAT5132,133.  Similarly, transduction of primitive hematopoietic cells with constitutively active forms of STAT3134 or STAT5A134,135 enhanced HSC self-renewal divisions under certain conditions and, in the case of STAT5A, led to a myeloproliferative syndrome in vivo.  However, levels of STAT3 appear to be non-limiting in HSCs since overexpression of the native form did not alter the amplification of HSC numbers in vivo130 and levels of STAT3 mRNA are found to be significantly higher (~2-fold) in proliferating adult HSCs than in their fetal counterparts87.   1.7.2  Polycomb transcription factors  Polycomb family members are extremely well conserved and form 2 major complexes (PRC1 and PRC2) that have been well-studied as regulators of gene transcription by controlling the levels of open chromatin in specific areas of the genome136,137.  PRC2 elements (encoded by Suz12, Ezh2, and Eed) initiate this process by methylating the lysine 27 residue and this is followed by PRC1 elements (variably comprised of the products of the Bmi1, Phc1, Pcgf2, Ring1 genes) where it further compacts chromatin or interferes with transcription (see Figure 1.5)137.  In the mouse model, Bmi1, Phc1 (Rae28), Ezh2, and Pcgf2 (Mel18) have all been implicated in regulating HSC self-renewal activity either positively (Bmi1138,139, Rae28 140, and Ezh2141 or negatively (Mel18)142.  Mel18 is of additional interest here because it can inhibit the activity of cyclin D2 by direct physical interaction in the nucleus143.  20 Polycomb family members have also been shown to be upstream regulators of homeobox genes.  This is of significant interest to understanding HSC self-renewal as forced overexpression of HOXB4 was one of the first strategies found to enable large (~40 fold) net expansions of HSCs numbers to be achieved in 14-day cultures without inducing leukemia144.  Remarkably, subsequent studies with several novel HOX-fusion proteins have shown such non-leukemogenic expansions of HSC populations can be further increased in the same time frame another several hundred-fold145.  Interestingly, both Mel18 and Ezh2 transcripts are expressed at much higher levels (~10-fold) in quiescent adult as compared to proliferating fetal HSCs whereas Bmi-1 transcript levels are similar in both18.   1.7.3  Cell cycle regulators  Expression of the D-type cyclins is induced by mitogenic cytokines and their expression allows the formation of complexes with partner cyclin-dependent kinases leading to entry into S- phase146.  In mice, loss of all 3 D-type cyclins severely impairs the expansion of HSC numbers in the FL and post-transplant in adults although both of these effects are likely due to an inability of the cells to transmit a mitogenic signal rather than a direct effect on the HSC self-renewal mechanism itself147.  p21, p16, and p18 are 3 of several cyclin-dependent kinase inhibitors with well-established roles in regulating the progression of cells through specific phases of the cell cycle146.  All 3 of these have also been implicated as regulators of HSC self-renewal either directly or indirectly.  Cells from adult p21-/- mice have reduced numbers of myeloid progenitors148.  They also have markedly reduced numbers of CFU-S and HSC activity and this appears to be caused by their failure to respond to signals that normally induce HSC quiescence149, which occurs when mice reach 4 weeks of age43.  In contrast, p16150 and p18151  21 deficiencies each endow HSCs with improved longterm repopulating and self-renewal activity and the latter can partially offset the negative consequence of a p21 deficiency in HSCs152. Interestingly, p18 mRNA is present at significantly lower (~10-fold) levels in fetal as compared to proliferating adult HSCs even after the cells have been stimulated to proliferate by SF in vitro87, a finding consistent with a role of p18 in mediating the observed differences between fetal and adult self-renewal activities in vivo.  Other key components of the cell cycle machinery are the retinoblastoma (RB) family of proteins (RB, p107, and p130) and the E2F transcription factors, which RB represses (reviewed in153).  Inactivation of RB results in profound myeloproliferation and mobilization of HSCs to extramedullary sites154.  Most recently, it has been shown that conditional knockout of all 3 RB family members also leads to a myeloproliferation and increased apoptosis of lymphoid progenitors.  The BM HSCs are then no longer quiescent and they are also rendered less competitive in transplantation compared to wild type HSCs.  These findings suggest that loss of RB may lead to a premature exhaustion of the HSC compartment in vivo.   1.8  Methodologies for analyzing HSC transcriptomes  Many platforms are currently used for gene expression analysis to detect changes in the transcriptome of cells undergoing particular developmental changes.  Three of the most powerful techniques are: Serial Analysis of Gene Expression (SAGE); oligonucleotide arrays; and quantitative real-time reverse transcription-PCR (Q-RT-PCR).  SAGE provides a snapshot of the transcriptome via direct sequencing of short 14 or 21-mer (LongSAGE) RNA segments.  Three principles are inherent to SAGE methodology: 1) the tags generated can uniquely identify a useful proportion of transcripts, with LongSAGE giving greater specificity and frequency of  22 unique tag-to-gene assignments.  2) Tags can be linked in tandem for cloning and sequencing.  3) The number of times a tag is represented in the library is linearly related to the level of expression of the corresponding transcript in the cells being analyzed.  Because SAGE does not depend on a pre-defined set of transcripts, it can measure changes in expression of transcripts that have not been previously identified and can also serve as a platform for gene discovery155,156. One major limitation, however, is that the original SAGE method required ~10 µg of sample RNA making amplification of cDNA a necessity for small cell numbers. Oligonucleotide arrays (e.g.: Affymetrix) are designed to make a comparison of differential transcript levels in 2 samples.  The expression of thousands of genes are concurrently monitored and compared between samples with a read-out of up- or down-regulated transcripts in relation to a reference.  Oligonucleotide arrays have a greater number of probe sets and have been suggested to be more accurate than 2-colour spotted cDNA arrays due to internal controls and the recent release of calibration data by Affymetrix157.  Specifically, Affymetrix chips contain 11 to 25 pairs of oligonucleotide probes for each target RNA in which one of the pair has a mutated base in the middle to control for stray signals.  Using the differences between the intensities of the pairs, software judges the reliability of each set and calculates a quantitative and qualitative measurement158.  A limitation of these arrays, however, is that they are not useful for gene discovery and they require at least 1-2 µg of sample RNA which, again, requires amplification when only small numbers of cells are available.  Whole genome oligonucleotide arrays are also available and have been suggested as an unbiased way of assessing gene expression because transcripts are not pre-selected to be on the chip. Q-RT-PCR has been considered to be the most accurate method for measuring the particular transcript levels in cells.  Based on PCR technology and quantification using a DNA binding fluorescent dye (typically SYBR Green), this method is a very powerful tool for comparing the level of expression of transcripts in different samples159,160.  Typically, a Q-RT-  23 PCR experiment relies on a relative measure of abundance by comparing the test signal to a single or a set of housekeeping genes (like Actb or Gapdh).  As with oligonucleotide arrays, Q- RT-PCR is not useful for gene discovery and also suffers from not being as high-throughput as the other methods described above. The major issue that faces biologists trying to perform high throughput gene expression analyses of HSCs is the low amount of sample RNA available.  These cells are very rare and RNA from pure populations in a reasonably sized experiment would fall far short of the necessary amount for most conventional SAGE and microarray protocols.  Efforts to overcome this barrier are summarized below: • A global RT-PCR procedure has been developed that amplifies RNA as much as 3 x 1011, making it useful for the amplification of picogram amounts of RNA.  This method is exponential (thereby quick and efficient) and is purported to preserve abundance relationships between replicates161. • SAGE-Lite is a modification of conventional SAGE that allows the user to reduce the amount of input RNA to as little as 50 ng.  Because the amplification is PCR based, biases can be introduced if the number of cycles is not optimal162. • In vitro transcription has been employed for the amplification of DNA for a number of years.  Groups have begun to apply the technique to RNA and one group has demonstrated a Pearson correlation value of 0.91 between 2 samples amplified from 200 pg of starting material163.  When applied to RNA, it has been demonstrated that the T7 based linear amplification introduces no systematic bias between amplified samples.  However, when an amplified sample was compared to a non-amplified sample, differences in expression of some genes were observed164. Currently, no published data exists for SAGE libraries built from highly purified (>10%) HSCs.  (SAGE libraries do exist for CD34+CD38-Lin- human hematopoietic cells from cord  24 blood, adult bone marrow and mobilized peripheral blood165 and fetal liver166; however, the actual HSC content of these populations is estimated at <1%).  Microarray data, on the other hand, has emerged from the profiling of more highly HSC-enriched populations of murine HSCs19,167-174.   1.9  Thesis Objectives  As summarized above, much evidence indicates that the competence of HSCs can either be activated or sustained in a latent state, which is controlled by a mechanism that involves a complex integration of extracellular cues and intracellular components.  However, whether and how this “self-renewal machinery” is connected to the pathways that control the proliferative (or viable) state of HSC remains poorly understood.  Historically, it has been assumed that they are tightly interwoven and a particular set of molecules determines whether a given HSC will execute a self-renewal expansion division vs. a symmetric maintenance division vs. a symmetric depletion division (Figure 1.6).  On the other hand, it is also possible that stem cell competency is maintained, at least in part by mechanisms that are independent of the process that actually makes the cells divide.  Exploration of this question requires access to populations of HSCs that are of such homogeneity and purity that definitive conclusions about their self-renewal responses and gene expression profiles can be generated from bulk populations.  Investigations of these questions served as the starting point for this thesis. Chapter 3 begins with a presentation of work performed jointly by myself and another PhD student, Brad Dykstra, that examined the heterogeneity present within the HSC compartment defined historically by the CRU assay both in terms of their individual differentiation and/or self-renewal activities revealed from analyses of a large number of  25 transplants of single cells or their in vitro-derived clones.  Evidence of heterogeneity in differentiation potential had been previously suggested175-178, but the extent to which it reflected intrinsic differences179 in the HSCs themselves versus their exposure to different factors180,181 versus stochastic events that alter their potential182-184 was not clear.  Our work provided strong evidence of functionally distinct subsets of HSCs with extensive (durable) vs. no further self- renewal activity (rather than a continuum).  These findings led me to seek new ways of separating these cells from each other so that their properties could then be studied in more depth and using more direct approaches. Based on the studies of Audet et al.74,90, I hypothesized that modulation of SF concentrations alone could alter the stem cell status of HSCs and hence influence the frequency of their executing a self-renewal division.  This required designing an experiment that would allow the rate of entry into division and the rate of change in HSC status to be monitored independently at the single cell level in vitro.  The design and execution of such studies are presented in Chapter 4. I then hypothesized that there might be additional, as yet unidentified intracellular components that are essential to maintaining a durable self-renewal state in HSCs.  To investigate this possibility, I exploited a variety of approaches that included the methods and findings described in Chapters 3 and 4 to compare their gene expression profiles with multiple closely related cell types.  These studies are presented in Chapter 5.      26 Table 1.1 - Regulators of HSCs in the Stem Cell Niche (adapted from Kiel et al.68)  Factor Genetic Evidence for Regulation of HSCs   Angiopoietin  Combined loss of Tie2 (the receptor for angiopoietin) as well as Tie1, leads to defects in postnatal HSCs185; angiopoietin appears to promote the maintenance of quiescent HSCs59  Ca2+ ions  Deletion of the Ca2+-sensing receptor leads to reduced bone-marrow cellularity and HSC content with increased progenitor-cell mobilization into the circulation and spleen186 CXCL12  Mice deficient in the chemokine CXCL12 or its receptor CXCR4 show disrupted colonization of the bone marrow, whereas conditional deletion of CXCR4 in adult mice leads to reductions in HSC numbers in the bone marrow and reduced HSC activity upon transplantation187,188,188,189 SHH  Patched (the SHH receptor) heterozygous HSCs have reduced long-term reconstituting activity, suggesting that a member of the SHH family of ligands can negatively regulate HSC self-renewal, at least when the pathway is over-activated190 Osteopontin  The matrix glycoprotein osteopontin is expressed at the endosteum by bone- lining cells and negatively regulates HSC numbers; osteopontin-deficient mice have moderately increased HSC numbers in the marrow191,192 SCF  Mice with mutations in SCF (Sl/Sld, Steel dickie mutants) or in its receptor KIT (W/Wv, dominant spotting mutants) have fewer HSCs and exhibit less HSC function193,194 Thrombopoietin  Thrombopoietin is synthesized in the liver, kidney, bone-marrow stroma and by osteoblasts and may be transported into the bone marrow through the blood195-197 mice deficient in thrombopoietin or the thrombopoietin receptor c-Mpl have profound reductions in HSC numbers195,198-200   27 Table 1.2 - Genes Shown to Regulate HSC Self-Renewal  Factor Effect on HSCs or Hematopoiesis Apc Bmi1 Cdkn1a (p21) Cdkn2c (p18) Cdkn2a (p16) Gfi1 Hoxb4 Kit Mef Mel18 Notch1 Phc1 (Rae28) Rarg Stat3 Stat5a  Tel/Etv Tie1 and Tie2 Wnt3a  Conditional inactivation increases apoptosis, decreases entry into cell cycle201 Deletion enhances HSC symmetric divisions138,139 Absence of p21 increases HSC cycling and causes stem cell exhaustion149 Overexpression increases self-renewal divisions152 Overexpression increases self-renewal divisions150 Deletion results in a reduced HSC competitive repopulating ability202 Overexpression causes expansion of HSCs144 Deletion results in a cell intrinsic defect in the CFU-S compartment203 Deletion maintains quiescence of HSCs204 Deletion negatively regulates the proliferation of HSCs142 Activation causes expansion of HSC205 Overexpression enhances HSC self-renewal140 Knockout animals show reduced numbers of HSCs116 Dominant negative Stat3 suppresses HSCs, overexpression increases HSCs130,134 Overexpression promotes HSC self-renewal in vitro135, knockout reduces self- renewal131 Deletion results in a complete depletion of bone marrow, HSC specific effect206 Chimeric mice show that these receptors are critical for adult HSC maintenance185 Overexpression results in proliferation and expansion of HSCs119,207       Figur Test c transp irradi the m determ multi  e 1.1 – In v ells are asse lanted into ated recipie any types o ined to hav ple lineages ivo transpla ssed for HS a genetically nt (to compr f white bloo e been pres  of the hema ntation ass C function  distinguish omise the h d cells at va ent in the or topoietic sy  28 ay to detec in a retrospe able (in this ost blood ce rious period iginal test c stem out to t HSCs (fro ctive transp  case by the lls) and assa s post transp ell populatio 4 months po m Kent et a lantation ass  CD45 surfa yed for thei lantation.  H n if they ca st-transplan l.208) ay where ce ce marker) r ability to p SCs are typ n produce th t. lls are roduce ically e   abilit    Figur HSCs down The H arrow y to produce e 1.2 – Hie  are placed stream linea SC is the o  at the top.  the many ty rarchical m atop the hie ges of the h nly cell in th  pes of whit odel of hem rarchy of he ematopoieti e hierarchy 29 e blood cell                           atopoiesis matopoiesis c system wi  with longte s at various (adapted fro  and have th th both mye rm self-rene periods post m Bryder et e ability to g loid and lym wal activity   al.209) ive rise to a phoid elem  indicated by ll of the ents.  the  30  Figure 1.3 – SF signalling and its role in HSCs (from Kent et al.37) Schematic representation of key signalling events activated in primitive hematopoietic cells exposed to SF (here shown as two membrane-bound molecules bound to a dimerized receptor complex). Blue arrows, pathway-promoting activities; red stop lines, inhibiting activities.  Figur A sch each intera the in  e 1.4 – Key ematic depi other.  Arrow ctions.  Ext side of the c  regulators cting some k s indicate p rinsic regula ell.  of HSCs (a ey regulato ositive inte tors appear  31 dapted from rs of HSCs ractions and on the outsi  Zon129) and how the  lines with b de of the cel y are though ars indicate l and intrins t to interact  repressive ic regulator   with s are in    Figur al.210) The n methy transc chrom e 1.5 – Poly  ucleosome lates lysine ription and atin compa comb com is first boun  27 on histo ubiquitylati ction via rec plexes indu d by a PRC2 ne H3.  The on of lysine ruitment of 32 ce epigenet  complex w  PRC1 comp  119 of histo  DNA methy  ic silencing hich recruit lex plays a ne H2A, wh ltransferase (adapted fro s a PRC1 co major role i ile the PRC s (DNMTs m Sparman mplex and n inhibiting 2 complex i in the schem n et nduces atic).  Figur There one o gives anoth e 1.6 Possib  are 3 possi f the 3 depic  rise to 2 HS er non-HSC le outcome ble outcome ted division Cs 2) a mai  and 3) a de s following s for an HS  outcomes: ntenance div pletion divis 33  the divisio C – to not di  1) a self-ren ision where ion where o n of an HSC vide, to die, ewal expan  one HSC g ne HSC giv   or to under sion divisio ives rise to es rise to 2 n  go a division n where one one HSC an on-HSCs.  with  HSC d  34 2.  Materials and Methods   2.1  Mice  BM donors were 8 to 12 week-old C57Bl/6J-CD45.1 or CD45.2 mice.  FLs were obtained from E14.5 fetuses derived from timed matings of the same strains.  All transplant recipients were Cd45-congenic C57Bl/6J-W41/W41 (W41/W41) mice previously given a sublethal dose of irradiation (360 cGy X-rays at 350 cGy per minute).  Mice were bred and maintained in microisolator cages and provided with sterile food, water and bedding.  Animal procedures were carried out in accordance with the Canadian Council on Animal Care with specific project and protocol approval from the University of British Columbia Animal Care Committee.   2.2   Isolation of subsets of FL and adult BM cells  Suspensions of BM cells were flushed from the femurs and tibias of adult (8-12 week- old) B6 donors into 1 mL of 2% (v/v) fetal bovine serum (FBS) supplemented-Hank’s Balanced Salt Solution (collectively called HF) using a 21 gauge needle and the cells then depleted of RBCs by a 10-minute incubation on ice in the presence of NH4Cl. To isolate the CD45midlin-Rho-side population (SP) fraction, the BM cells were first suspended at 1-2.5x106 cells/mL in serum-free medium (SFM = Iscove's modified Dulbecco's medium supplemented with 10 mg/mL bovine serum albumin, 10 µg/mL insulin, and 200 µg/mL transferrin, 100 units/mL penicillin, 100 µg/mL streptomycin, all from STEMCELL Technologies, and 10−4 M β-mercaptoethanol [Sigma Chemicals, St. Louis, MO, USA]).  The  35 cell suspension was warmed for 15 minutes at 37°C, after which 0.1 µg/mL Rho (Molecular Probes Inc., Eugene, OR, USA) was added to the cells in SFM and the suspension incubated for an additional 30 minutes at 37°C, followed by washing in cold HF and centrifugation.  Cells were resuspended at 1-2.5x106 cells/mL in SFM. The cells were then incubated with 0.1 µg/ml of Ho (Molecular Probes) for 90 minutes at 37°C. Cells were then washed, resuspended at 107 cells/ml in ice-cold HF plus 5% rat serum (Sigma) and 3 µg/ml of a Fc receptor blocking antibody (2.4G2)211 (blocking reagent) for 10 minutes followed by monoclonal antibody staining for 30 minutes on ice.  Antibodies used for sorting were biotinylated anti-Mac1, anti-Gr1, anti- B220, anti-Ly1, and anti-Ter119 (all from STEMCELL Technologies), and allophycocyanin (APC)-conjugated anti-CD45 (from Becton Dickenson (BD), San Jose, CA, USA)).  Cells were then washed, resuspended at 107 cells/ml in ice-cold HF and incubated for 15 minutes on ice with Streptavidin-phycoerythrin (SA-PE, BD), then washed once with HF and resuspended in HF plus 2 µl/ml propidium iodide (PI, Sigma) for sorting. To isolate the CD45midRho-EPCR+ fraction, the cells were prepared as above with the following two changes:  1) The Ho stain was not performed and the cells were directly resuspended in HF following the Rho stain, 2) The lineage marker SA-PE stains were not performed and were replaced with a PE-conjugated anti-EPCR antibody (STEMCELL Technologies). To isolate the CD45+EPCR+CD48-CD150+ (E-SLAM) and/or CD45+EPCR+CD48- CD150- fractions, the freshly obtained BM cells were first stained for 30 minutes with fluorescein-isothiocyanate (FITC)-conjugated anti-CD45, PE-conjugated anti-EPCR (STEMCELL Technologies), biotin-conjugated or PE-Cyanin7-conjugated anti-CD150 (BioLegend, San Diego, CA, USA), and APC-conjugated anti-CD48 (BioLegend).  When biotin conjugated anti-CD150 was used, cells were secondarily stained with SA-PE-Texas Red (BD).  36 FLs were suspended in HF by forcing the tissue through a sieve and then through a 40 µm filter.  Erythroid precursors were depleted by immunomagnetic removal of biotin-conjugated anti-Ter119-labelled cells using EasySep reagents (STEMCELL Technologies) as recommended by the manufacturer.  The unlabeled fraction of cells was then centrifuged and suspended at 107- 108 cells/mL of Hank’s containing blocking reagent described above.  E-SLAM cells were then isolated using the same antibody stain described above for BM cells. Lin-CD43+Mac1+Sca1+ E14.5 FL cells were prepared by staining Ter119-depleted cells with biotinylated anti-Gr1, anti-B220, and anti-Ly1 (all of which were prepared in the Terry Fox Laboratory), and Ter119 (from BD), and PE-labelled anti-Sca-1 (BD), FITC-conjugated anti- CD43 and APC-conjugated anti-Mac1 (all from BD).  Cells were then washed with HF, centrifuged, resuspended at 107-108 cells/mL of HF and incubated for an additional 15 minutes on ice with SA-PE-TexasRed.  Cells were washed again in HF and then resuspended in HF plus 2 µg/ml PI (Sigma). To isolate lin- populations from BM or FL cells, the cells were stained for 30 minutes with biotin-conjugated anti-Ly1, anti-Gr1, anti-CD5, and anti-B220 (STEMCELL Technologies), washed, resuspended in HF, stained for 15 minutes with SA-PE (BD), washed and suspended in HF containing DAPI to mark dead cells (Sigma). All cell sorting was performed using either a FACSVantage (BD), FACSDiVa (BD), FACSAria (BD) or Influx Cell Sorter (Cytopeia, Seattle, WA, USA).  For CD45+EPCR+CD48- CD150+ (E-SLAM) and/or CD45+EPCR+CD48-CD150- FL or adult BM sorts, cells were first sorted at a high rate (10,000-15,000 cells per second) using an EPCR+CD48- gate that captured approximately 0.5% of all the viable cells and were then re-sorted at a slower rate (1-200 cells/second) to improve the purity.  When single cells were required, the single cell deposition unit of the sorter was used to place these individually into the wells of round-bottom 96-well  37 plates, each well having been preloaded with 100-200 µL SFM.  Each well was then visually inspected to identify those that contained only one viable cell.   2.3  Analysis of transplanted mice  All transplants were injected intravenously into irradiated mice via the tail vein. For single cell injections, each cell was sorted into 100-200 µL SFM in an individual well of a 96- well plate and the plate was centrifuged at ~180 g for 5 minutes to bring the cells to the bottom of each well without damaging them.  Each well was examined using a standard inverted microscope and the wells were confirmed to have one and only one cell present.  For each well, a single use 28 G1/2 insulin syringe filled with ~300 µL phosphate buffered saline (PBS) and no air bubbles was used to gently push approximately 50 µL of the 300 µL into the well to disturb the cell from the bottom of the well.  The syringe was then used to remove almost all of the liquid from the well which was gently dispensed back into the well.  Finally, all of the liquid was aspirated into the syringe and the entire volume was injected into the tail vein of an irradiated mouse that had been exposed to an infra-red heat lamp for ~ 2-3 minutes to dilate the vein prior to injection.  For secondary or tertiary transplantations, BM was harvested from selected repopulated primary recipients of single HSCs, and the cell content equivalent of one femur (~10% of the total BM) was injected into each of 2 secondary sublethally irradiated W41/W41 recipients. Peripheral blood samples were collected from the tail vein of mice 8, 16 and 24 weeks post-transplant.  RBCs were lysed with NH4CL for 10 minutes on ice and the WBCs stained with antibodies for both donor and recipient CD45 allotypes (using anti-CD45.1-APC and anti- CD45.2-FITC antibodies) as well as anti-Ly6g-PE/anti-Mac1-PE for myeloid (GM) cells, anti-  38 B220-PE for B-cells, and anti-CD5-PE for T-cells (CD45.2-FITC purified and conjugated in the Terry Fox Laboratory; CD45.1-APC from eBiosciences, San Diego CA; all other antibodies from BD).  All double negative or double positive CD45.1 and CD45.2 events were excluded from further analysis.  To calculate repopulation levels, the contributions of the donor CD45 allotype to the populations of circulating GM, B, T and total WBCs were calculated.  Recipients with >1% donor-derived white blood cells (WBCs) at 16 and/or 24 weeks post-transplant were considered to be repopulated with HSCs.  α (myeloid-biased), β (balanced lympho-myeloid), γ (lymphoid-biased and still multi-lineage at 4 months), and δ (lymphoid-biased but no longer multi-lineage at 4 months) subtypes of HSCs were discriminated by calculating the relative ratios of the donor contributions to the GM versus B plus T lineages measured at 4 months post transplant as follows: The α and β clusters were defined, respectively, by donor-derived GM:(B + T) ratios of ≥2 and 0.25 to 2.  Mice that had donor-derived GM:(B + T) ratios of <0.25 were further subdivided into 2 clusters according to whether there was a continuing ≥1% donor contribution to the myeloid lineage as well as to both lineages of lymphoid cells at 16 weeks (γ- type), or whether they contributed exclusively to the lymphoid lineages at this time (δ-type)21.   2.4  Cell cultures  Sixteen-hour, 4-day, and 10-day cultures of E-SLAM or CD45midlin-Rho-SP cells were incubated in SFM plus 20 ng/mL IL-11 (Genetics Institute, Cambridge, MA, USA) and either 1, 10, or 300 ng/mL SF (STEMCELL Technologies).    39 2.5   Statistical Analysis  L-Calc software (STEMCELL Technologies) was used to quantify the number of HSCs present by limiting dilution analysis of pooled 10-day clones.  This calculation is based on Poisson statistics which predicts that one HSC per animal was present on average when 37% of the animals read out negatively.  In Table 4.1, the range defined by ± SEM is shown in brackets underneath the calculated frequency of HSCs.  Fisher’s Exact test (available in the open source statistics package R [www.r-project.org]) was used to determine whether or not the frequency of HSCs calculated in individual 8-hour, 16-hour and 1- to 2-day doublet cells, and 4-day clones was significantly different from the input frequency of HSCs. DiscoverySpace software version 4.01212, which utilizes Audic Claverie statistics213, was used to identify tags that were over- or under-represented in a comparison of the LongSAGE libraries.  Q-RT-PCR data was collected from 3-6 biological replicates and each sample was assigned a δ-ct value with respect to the levels of Gapdh transcripts present in the same sample. The SEM of the resulting data was then calculated and plotted and significant differences (p<0.05) were established using the Students t-test.   2.6   Quantitative real-time PCR analysis  A PicoPure kit (Arcturus Bioscience, Mountain View, CA) was used to extract RNA from cells harvested from cultures initiated 16 hours previously with 70 to 200 CD45midRho-EPCR+ adult mouse BM cells placed in 200 µL of SFM containing 20 ng/mL IL-11 and either 1, 10 or 300 ng/mL SF.  The extracted RNA was reverse transcribed into cDNA using the SuperScript III First-Strand Synthesis System for RT-PCR (Invitrogen, Burlington, ON, Canada) and then Q-RT-  40 PCR analyses were performed using Power SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA).  The primers used in this thesis are listed in Table 2.1.   2.7  Construction and sequencing of LongSAGE libraries  Five ng RNA was collected for cDNA synthesis and then amplified by PCR to generate 200 ng214 and then LongSAGE libraries constructed.  In order to enable useful LongSAGE libraries to be made from small amounts of RNA (<10 ng), I first helped to evaluate the applicability of the SMART technology developed by Clontech (catalog number 635000; Clontech, Mountain View, CA, http://www.clontech.com).  This technology is used in the SAGELite protocol214, but for the libraries to be made here, 2 further modifications were introduced.  The first was to change the cDNA amplification primer to contain a biotin molecule and the second was to change the template switching primer by introducing an AscI restriction endonuclease site into it.  These steps allow the isolation of a final product in which the cDNAs are biotinylated only on the 5’ end which is a requirement for generating SAGE libraries (Figure 2.1).  The ability of this method to be applied to very small (10 ng) of RNA and allow the generation of representative libraries was first established using aliquots of a large pool of human embryonic stem cell RNA and then on extracts of HSC/progenitor-enriched CD34+ cells isolated from normal human cord blood215.  In brief, the test RNA used here was first reverse transcribed and the first strand cDNA was then purified with a NucleoSpin column and amplified using an Advantage II PCR Kit (BD) in combination with an AscI template switching primer and a modified PCR primer that contained a biotin molecule at its 5’ end.  The biotinylated 5’ ends of the amplified cDNAs were then removed by digestion of the initial amplified product with AscI (New England BioLabs, Beverly, MA, USA).  The cDNA was purified on a Chroma-Spin 200  41 Column (BD) and its concentration determined using a spectrophotometer (GeneQuant Pro, Biochrom, Cambridge, UK).  The amplified cDNA was then processed according to the standard LongSAGE protocol modified in BCCA Genome Sciences Centre using the I-SAGE Long kit (Invitrogen, Carlsbad, CA, USA) and described in detail in Khattra et al.215.  Following analysis of data quality from a first 384-well sequencing plate, each library was sequenced to a sampling depth of 44,506 (adult BM) and 200,319 (FL) raw tags (GEO Series accession number GSE13243, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13243).  42 Table 2.1 – List of primers used in Chapters 4 and 5 Gene  GenBank # Forward Primer  Reverse Primer  Gapdh  NM_008084  AACTTTGGCATTGTGGAAGG  ATGCAGGGATGATGTTCTGG Stat3 NM_213659 GGCACCTTGGATTGAGAGTC ACTCTTGCAGGAATCGGCTA MEF NM_019680 TCTGTGGATGAGGAGGTTCC GGGTGCTGGAGAAGAACTCA ATM NM_007499 GCAGAGTGTCTGAGGGTTTGT AACTTCCAGCAACCTTCACC Gata2 NM_008090 TGACTATGGCAGCAGTCTCTTC ACACACTCCCGGCCTTCT Lyl1 NM_008535.2 GACCCTTCAGCATCTTCCCTAACA AGCCACCTTCTGGGGTTGGT G3bp1 NM_013716.2 GGGAAGCCAGCAGATGCAGT ATCCACGTGGCGGATCTTG Eif1a NM_010120.3 CCGCTGCGTTTTGGTCACTA TCGGTTCTGGCCTGGTTCTC Tubb5 NM_011655.3 CAGCTGGACCGAATCTCTGTGT GGACCTGAGCGAACGGAGTC Hmga2 NM_010441.1 GGTGCCACAGAAGCGAGGAC GGGCTCACAGGTTGGCTCTT Psap NM_011179.2 ACTGTGGGGCCGTGAAGC GTCGCAAGGAAGGGATTTCG Prnp NM_011170.1 TCCAATTTAGGAGAGCCAAGCA GCCGACATCAGTCCACATAGTCA Pld3 NM_0111161.1 GCTGAGGAACCGGAAGCTGT GGGAAAGGGGTGGTCCTGAG Rhob NM_007483.2 GGGGCACGCAGAGTGGTT GCAACAGTAGTGGCTTGCTGGTT Vwf NM_011708.3 GGCGAGGATGGAGTTCGACA TGACAGGGCTGATGGTCTGG Car3 NM_007606.3 TGGCTAAGGAGTGGGGCTAC GTCCCCTTTGGCAATTGGAT Plp1 NM_011123.2 TCAGTCTATTGCCTTCCCTAGCAA GCATTCCATGGGAGAACACCA Hdac3 NM_010411 TCAACGTGGGTGATGACTGC GCAGAGATGCGCCTGTGTA Chd4 NM_145979 GCTGCCAGAGATCCCAAACG TTGCCCTTAAGAGCTGGACAA Cul4a NM_146207 GGAGAACATTTGACAGCAATTCTACA GTGAGGTCGGGCACCCTGT Trim27 NM_009054 GAAGAGACGGCGGGCACA GCTGCTCAAACTCCCAGACAA Fus NM_139149 CACTGGTTGCATTCATTTCTCCA CCAGTGGAGGTGGTGGAGGT Cebpa NM_007678 CCAGTCAGACCAGAAAGCTGA CCACAAAGCCCAGAAACCTA Mlx NM_011550 TGTGTCTTCAGCTGGATTGAGGA GGACACCGATCACAATCTCTCG Smarcc1 NM_009211 TGGGAGAGCCCGGACACG TTGGTAGGAGCATCTGCATGAAC Smarcc2 NM_198160 TCTTCAGCCGAAGCCTCCAC CCCTTCTCAGGGAAGTTCAGCA Cdkn1a NM_007669 GTACTTCCTCTGCCCTGCTG TCTGCGCTTGGAGTGATAGA 1200009F10Rik NM_026166 GAAAAACAATACCGGTTACTGCAAA CCACGAGAGCTTCACATTCCTG Ezh2 NM_007971.1 CGCTCTTCTGTCGACGATGTTTT GTTGGGTGTTGCATGGAAGG Gata3 NM_008091.2 GGTATCCTCCGACCCACCAC CCAGCCAGGGCAGAGATCC Bmi1 NM_007552.3 AAACCAGACCACTCCTGAACA TCTTCTTCTCTTCATCTCATTTTTGA Sh2b3 NM_008507.3 CAACACACACAAGGCTGTCA CCTGTGCACAAGAACTACATCTG Rae28 NM_001042623 CGCACATCATTGAAGGCTTTGTT TTCTTTCAGGAACTGAGAACATCC Cdkn2c Gfi1 HoxA9 Meis1 Runx1  NM_007671 NM_010278.2 NM_010456.2 NM_010789.2 NM_009821 GAACTGCGCTGCAGGTTAT CGAGATGTGCGGCAAGACC GTTCCAGCGTCTGGTGTTTT GCACAGGTGACGATGATGAC AAGACCCTGCCCATCGCTTT TCAAATTGGGATTAGCACCTC ACAGTCAAAGCTGCGTTCCT ACAATGCCGAGAATGAGA AGGGTGTGTTAGATGCTGGAA TGCCATGACGGTGACCAGAG               43   Figure 2.1 - cDNA amplification protocol for PCR-serial analysis of gene expression (PCR- SAGE) library generation Incorporation of a template switching primer containing an AscI sequence allows an end-to-end amplification of the first-strand cDNA using a single biotinylated oligonucleotide primer and then subsequent removal of the 3' biotin via AscI digestion. The 5' end of the double-stranded cDNA is then available for capture on streptavidin-coated beads for SAGE library construction.      44 3. Heterogeneity of HSC Programs and Their Resolution by Improved Purification Methods   3.1  Introduction  As reviewed in Chapter 1, much evidence indicates that throughout adult life, the bone marrow maintains a rare population of HSCs extensive with self-renewal ability.  The most specific and reliable methods for identifying HSCs have historically made use of retrospective functional assays that detect the ability of HSCs to produce mature blood cells for sufficient periods of time in vivo to discriminate them from cells able to produce the same spectrum of mature cells but for only relatively short periods.  Over the years, a variety of strategies have been utilized to distinguish donor-derived cells in the recipient mice.  These include DNA-based detection of sex-mismatched transplants by Southern blot216, PCR or FISH analysis217, electrophoretic detection of different glucose isomerase isoforms218 or hemoglobin allotypes219, and more recently, flow cytometric detection of a cell surface alloantigen (CD45)3 or the product of a reporter transgene like GFP220.  A major advantage of the latter strategies is the ease with which they can be combined with flow cytometric identification of different mature blood cell types, thus allowing the differentiation potential of the injected cells to be tracked with considerable precision and sensitivity. Nevertheless, there is still considerable controversy as to the probability, durability, and molecular basis of the observed heterogeneity in self-renewal behaviour of individually tracked HSCs and hence their specific and fundamental definition.  Empirically, an association of different phenotypes with the subsequent durability of the regenerative behaviour they display in  45 irradiated recipients has led to the identification of a 4 to 6 month period of sustained repopulation as demarcating the difference between the repopulating activity of the most primitive HSCs and various types of derivative cells with transient, albeit extensive, repopulating activity (see Figure 1.2 in Chapter 1). During the last decade, various methods have been developed for isolating populations of cells from suspensions of adult mouse bone marrow that are at least 20% pure HSCs16,17,19,25,168,221-225 as defined by a repopulating activity that lasts for at least 4 to 6 months. However, many of these methods rely on the use of markers that change according to the activation/cycling status of HSCs226-230.  Therefore, most purification strategies are applicable only for steady-state BM in which the majority of adult HSCs are quiescent44,46,231. Consequently, these methods are often not useful for the direct enumeration of HSCs that have been biologically or genetically manipulated.  Therefore, enumeration of HSCs has to still rely on functional endpoints of their activity in vivo.  The demonstration that the highly discriminating CD150+CD48- phenotype of HSCs found in adult BM19 (like the absence of most lineage markers and the expression of Sca1) extends to HSCs in cytokine-mobilized, regenerating and fetal populations of hematopoietic cells20 was thus a welcome advance. Although the specificity of this phenotype for HSCs manipulated in vitro remains to be examined, these studies suggest that more direct readouts for these cells will eventually be found. Our group has been investigating the extent of HSC self-renewal heterogeneity by analyzing their clonal patterns of differentiation and self-renewal.  In a series of ~100 mice repopulated by single CD45midlin-Rho-SP cells (~30% pure HSCs) or their 4-day in vitro clones, we were able to identify 4 distinct subtypes of HSCs based on their relative lineage contributions.  To determine whether these programs were random expressions of multiple optional states, or more stably perpetuated in a clonal fashion, we then performed secondary and tertiary transplants of the cells regenerated in the BM of the primary hosts 6-8 months after their  46 initial injection.  The results showed a remarkable and unexpected stability of the differentiation patterns seen in the primary recipients and, more relevant to the studies in this thesis, a demarcation of retained or lost self-renewal ability amongst the 4 HSC subtypes.  Two of the 4 subtypes were able to regenerate sufficient HSCs so that, after 6 months post-transplant, these progeny HSCs could be detected in a standard CRU assay in secondary recipients (in which the total cellular contents of 2 femurs from the primary hosts were assessed).  Moreover, most of the primary clones produced in vivo from either of these 2 subtypes displayed extensive high self- renewal activity in these assays.  In contrast, none of the primary hosts of the other 2 original HSC subtypes had any detectable HSCs in such assays.  To facilitate further studies of the “high- self-renewal HSCs”, separate from those with more limited self-renewal activity, I undertook a series of experiments to determine if and how these subtypes of HSC might be differentially purified.   3.2  Results  3.2.1  Identification of subtypes of murine HSCs with differing self-renewal programs  To examine the WBC outputs over time of a large number of single HSCs, 352 mice were injected with a single CD45midlin-Rho-SP cell or a 4-day clone derived in vitro from such cells in the presence of 100 ng/mL SF and 20 ng/mL IL-11.  Figure 3.1 summarizes the results obtained from the 93 mice in this group in which the contribution to the total WBC count at 16 weeks post-transplant was at least 1%.  Although extensive heterogeneity was seen in the absolute outputs of both lymphoid and myeloid elements over time, analysis of the ratio of the relative contributions of the donor-derived lymphoid (B + T) and myeloid (GM) cells to the total  47 compartments of each of these populations revealed 3 statistically distinct contributions to the total output of mature circulating WBCs (Figure 3.2 and for additional details see Dykstra et al.21).  We arbitrarily named the HSCs that contributed relatively poorly to the lymphoid WBCs seen 16 weeks post-transplant α  HSCs.  Those that gave a relatively balanced contribution to both lymphoid and myeloid WBCs at 16 weeks post-transplant we named β HSCs.  The remaining group in which the relative contribution to the myeloid WBCs after 16 weeks was reduced, we split further into those that were still producing a detectable (>1%) contribution of myeloid WBCs, which we called γ HSCs, and those that were not, which we called δ HCSs. Interestingly, when the initial cells to be transplanted were first cultured as single cells for 4 or 10 days prior to transplant (in 300 ng/mL SF and 20 ng/mL IL-11), the proportion of α and β subtypes decreased and the proportion of  γ and δ subtypes detected increased (Figure 3.3). However, a different and unexpected result was obtained when we assessed the HSC activity of the cells that were produced in the BM of the primary mice over a period of 6-8 months.  Analysis of the outputs of the WBCs produced over the following 4-6 months in secondary mice transplanted with these cells showed that only the initial α and β subtypes of HSCs produced progeny HSCs.  Remarkably, the WBC outputs obtained from these regenerated HSCs demonstrated a remarkable fidelity to the lineage pattern characteristic of the original HSC injected into the primary mouse.  Similar results were obtained when BM cells from the secondary mice were assayed 6-8 months later for evidence of continuing donor-derived hematopoietic activity in tertiary hosts (Figure 3.4).  In addition, the frequency of original α and β HSCs that were capable of producing progeny HSCs through this serial transplant protocol was remarkably high (91% after one cycle and 70% after the second cycle), in contrast to the absence of serial transplantability of the 6-8-month progeny of the other 2 HSC subtypes.  These  48 observations, suggest that both the α and β HSC subtypes share a common mechanism that allows them to display a durable self-renewal activity when they are stimulated to divide in vivo. However, there also exist “HSC”-like cells (the γ and δ subtypes) that can produce multi-lineage clones of mature WBCs for up to 4 months in vivo and hence can display an extensive operational self-renewal ability, but one that appears qualitatively different in its finite longevity and association with different differentiation patterns.  Accordingly, I have chosen to refer to the first type of HSCs as “high-self-renewal HSCs” and the latter as “low self-renewal” HSCs.   3.2.2  Isolation of different HSC subtypes using EPCR as a substitute phenotypic marker for Ho efflux ability  The Ho staining protocol used to obtain the CD45midlin-Rho-SP cells is cumbersome and associated with some toxicity232 and studies by others suggested it might be replaced by selecting for cells expressing very high levels (top 0.1% of total mouse BM cells) of EPCR223.  To evaluate this possibility, I co-stained the CD45midlin-Rho-SP fraction of C57Bl/6 BM cells with EPCR to determine their phenotypic overlap and found that >75% of the CD45midRho-EPCR+ cells were contained within the SP fraction (Figure 3.5).  To determine the HSC frequency in the CD45midRho-EPCR+ population, I then transplanted 27 sub-lethally irradiated W41/W41 mice each with a single CD45-congenic cell of this phenotype in a total of 3 experiments and then measured their contribution to the B, T, and GM WBCs present in the blood from 8 to 24 weeks later (Figure 3.6A-B).  The clones derived from 18 (66%) of these single-cell transplants contributed at least 1% of the total circulating WBCs at one or more time points during the 6 months of follow-up.  Of these 18 clones, 13 (48% of the original 27) were clearly multi-lineage at some time point and reached an overall level of >1% of all the WBCs at 4 months post-  49 transplant Figure 3.6C-D.  The 4 types of repopulation patterns observed previously (i.e., α = myeloid-biased, β = balanced lympho-myeloid, γ = lymphoid-biased and still multi-lineage at 4 months and δ = lymphoid-biased but no longer multi-lineage at 4 months, Figure 3.1) were also seen in the mice injected with single CD45midRho-EPCR+ cells.  These patterns are illustrated in Figure 3.7 where the data are shown both as clonal contributions to all 3 lineages combined (Figure 3.7A-D) and also as proportional contributions to each of the 3 lineages monitored (Figure 3.7E-H).  Importantly, the frequency of each of the 4 subtypes within the CD45midRho- EPCR+ fraction was similar to that previously described for single CD45midlin-Rho-SP cells (Figure 3.6E-F).   3.2.3  Staining for EPCR in combination with CD48 and CD150 allows high and low self- renewal HSCs to be separately purified  Current strategies for obtaining murine HSCs at high purities from both FL and adult BM exploit a combination of features (e.g., lin-Kit+Sca1+3,233 and CD150+CD48−19) that distinguish these cells from their more mature derivatives.  However, to obtain high HSC purities, additional elements are required and these typically differ to accommodate the differing phenotypic characteristics of fetal and adult HSCs18,43,230 caused by their different cycling status18,43.  In preliminary studies, I found that a high expression of EPCR, a powerful discriminator of adult BM HSCs223,234 was stable on HSCs that had been proliferating in vitro for 5 to 7 days (data not shown).  This finding suggested that selection of EPCR positivity in combination with a CD48- CD150+ phenotype might allow fetal and adult HSCs to be purified using a simple identical protocol.  Representative FACS profiles of the CD45+EPCR+CD48-CD150+ (hereafter referred to  50 as E-SLAM) cells thus obtained from both E14.5 FL and adult BM are shown in Figures 3.8 and 3.9. The repopulation results obtained when mice were transplanted with a single E-SLAM cell from E14.5 FL (n = 49, 3 independent experiments) or adult BM (n = 62, 4 independent experiments) are also shown in Figure 3.9.  In the experiments with E-SLAM FL cells, a HSC purity of 24% (50% high self-renewal HSCs, β only, data not shown) was measured (Figure 3.8A) with no additional cells identified as having any repopulating activity for 8 weeks or more. Since all FL HSCs are proliferating and only those in the G1 phase of the cell cycle are detectable by conventional transplantation strategies44,235, a demonstrated FL HSC purity of 24% (12% high self-renewal HSCs) can be estimated to represent an actual FL HSC purity of ~48% (24% high self-renewal HSCs), assuming G1 occupies ~50% of the total cell cycle. The adult BM E-SLAM population was found to be 56% pure HSCs (Figure 3.8B) of which >75% are high self-renewing HSCs (α and β).  Thus the absolute purity of high self- renewal HSCs in the E-SLAM fraction of adult BM is 43% (Figure 3.9B).  This value is modestly increased from previously reported for other powerful HSC isolation strategies (e.g.: CD45midlin-Rho-SP cells17,21).  I found another 2% of the adult BM E-SLAM population to be STRCs, defined here as cells that generated clones containing >1% of the circulating WBC population between 4 and 8 weeks post-transplant but not later.  The remainder did not have repopulating activity detectable at or beyond 8 weeks post-transplant.  Thus, isolation of E- SLAM cells offers a simple method for obtaining high-self renewal HSCs at high purities from both fetal and adult sources.   Because of the apparent depletion of low self-renewal HSCs from the CD150+ fraction of CD45+EPCR+CD48- adult BM cells, I examined the matching CD150- subset for HSC activity. Analysis of 28 mice (2 independent experiments) transplanted with single cells of this CD150- subset (see Figure 3.9A) showed that 39% of these cells also had HSC repopulating activity but  51 these were predominantly of the low self-renewal subtypes (γ and δ, Figure 3.9Β).  Thus, within the total CD45+EPCR+CD48- population, ~90% of the high self-renewal HSCs were in the CD150+ subset at a purity of 43%, and ~50% of the low self-renewal HSCs were in the corresponding CD150- subset at a purity of 32%.  These results indicate that increasing expression of CD150 distinguishes adult BM HSCs with low and high self-renewal activity and this parameter can be exploited for the differential isolation of these 2 biologically distinct cell types at suitable purities for direct characterization studies (as described in Chapter 5).   3.2.4  The E-SLAM phenotype is useful as a strategy for isolating highly purified suspensions of HSCs from reconstituted animals  Next, I examined the HSC content of the E-SLAM population produced in reconstituted primary mice to determine if a similar purity of HSCs would be isolated and hence allow the E- SLAM phenotype to serve as a surrogate measure of the regenerated HSCs.  Analysis of the donor-type E-SLAM content of the BM cells from primary mice reconstituted 32 weeks previously with either a single α, β, or γ HSC revealed that the levels of BM chimerism were highest in the α− and β−reconstituted mice (50% and 60%, respectively) compared to the γ−reconstituted mice (<5%) (Figures 3.10A-B) and this was inversely correlated to the level of chimerism in the blood, which was highest in the β− and γ−reconstituted mice (70% and 50%, respectively) compared to the α−reconstituted mice (20%).  Furthermore, when I transplanted single donor-derived E-SLAM cells from the α− or β−reconstituted mice into secondary recipients, I found the frequency of HSCs in the regenerated E-SLAM population to be 26%  52 (n=33) (Figure 3.10B-C), i.e., only slightly lower than in the original E-SLAM population present in the young adult BM.   3.3  Discussion  HSCs remain one of the best models for studying stem cell self-renewal in the adult mouse and their isolation at purity is critical to the types of studies that can address questions about the mechanism behind self-renewal.  Using one such purification method for isolating HSCs at a frequency of ~1/3, we document significant heterogeneity in the cell population that gives rise to 1% of total white blood cells with multi-lineage reconstitution 4-6 months following transplantation.  While heterogeneity in the biological behaviour of individual HSC has been well-documented in numerous other studies177,178,236,237, this current study allowed us to prospectively isolate HSCs with heterogeneous potentials.  Based on the patterns of WBC output obtained, 4 distinct subtypes of HSC could be identified, only 2 of which could regenerate robust and durable hematopoiesis upon transplantation into secondary and tertiary mice. Detailed characterization of the clonal differentiation patterns displayed by the CD45midRho-EPCR+ cells in irradiated recipients revealed the same 4 subtypes of HSCs (α, β, γ, and δ) previously identified in similar experiments in which the progeny of individually transplanted CD45midlin-Rho-SP cells were analyzed.  Moreover, these 4 HSC subtypes were present in the same proportions within the CD45midlin-Rho-SP or CD45midRho-EPCR+ populations of cells. These results indicate that the CD45midlin-Rho-SP and CD45midRho-EPCR+ fractions of normal adult mouse BM are highly overlapping populations.  They also provide further evidence that the quiescent HSCs present in normal adult mouse BM are heterogeneous with respect to the differentiation programs they exhibit on transplantation into irradiated hosts.  53 The differentiation programs displayed by HSCs also appear to be an intrinsic component, as the E-SLAM strategy described in these experiments prospectively isolate HSCs with high self- renewal activity from those with low self-renewal activity. When HSCs are stimulated to exit quiescence, they rapidly lose the ability to efflux Rho228, a phenotypic lability that extends to many markers used to purify quiescent adult HSCs (e.g., CD34, MAC1, AA4.1, CD38, and the ability to efflux Ho)227,228,238-241. Interestingly, in these experiments, we have found that the EPCR+ phenotype exhibited by HSCs is stable regardless of their activation/cycling status in 5 and 7 day cultures. Thus, high EPCR expression on HSCs may more closely resemble the recently reported stable expression of the SLAM family antigen (CD150) on HSCs20.  Additionally, the E-SLAM sorting strategy appears to not only discriminate the relative contribution to the HSC compartment from repopulated mice of different HSC subtypes, but it also isolates HSCs at high purity (>20% as measured by single- cell transplantation).  A stable phenotype for HSCs is highly desirable as it could potentially be used as a surrogate marker in functional screens for molecular and cellular manipulations of HSCs.  More work is clearly required to validate the stability of this strategy for HSC isolation in additional settings such as HSC cell culture in vitro and during HSC mobilization to peripheral blood in vivo.  These caveats aside, the E-SLAM strategy offers an attractive method for comparing the differences in molecular program of HSCs and studying the process of self renewal with a level of detail not previously possible. .     54  Figure 3.1 - WBC outputs in recipients of single HSCs or their clonal progeny generated in vitro A)  Donor contributions to the total circulating WBCs for each of the 93 reconstituted mice shown individually. B)  Variations in the donor contributions to the total circulating WBCs at 16 weeks post- transplant of all 4 HSC subtypes.  Each point represents an individual mouse.  Horizontal bars indicate mean values.  55 C)  Distinct patterns of WBC reconstitution by each of the 4 HSC subtypes.  Values are the mean ±SEM of all mice in each HSC group as defined in the text. D) and E) Examples of individual mice repopulated with freshly isolated HSCs (D), or HSCs from 4-day clones generated in vitro (E).  Top panels: Colored areas represent donor WBC of GM (red), B-cell (blue) and T-cell (yellow) lineages as a percentage of all WBCs over time post- transplant.  Data are stacked such that the sum of the individual contributions to each lineage by donor cells represents the total donor contribution to all WBCs. Bottom panels: For each time point, the separate donor contributions to the GM (red), B-cell (blue) and T-cell (yellow) lineages are shown as bars, and the percentage donor contribution to the total WBCs is shown as a grey area. F)  Distinct patterns of donor contributions to the GM (red), B-cell (blue) and T-cell (black/yellow) lineages over time are shown.  Values are the mean ±SEM of data from all mice in each HSC group (n=93).   56   Figure 3.2 - Identification of HSC subtypes in ternary plots of their lineage-specific contributions at 16 weeks post-transplant A)  Comparison of the ratio of donor clone contributions to the GM (up), B-lineage (lower left) and T-lineage (lower right) WBCs.  The graph can be divided into 3 sections based on specific myeloid to lymphoid contribution ratios: High GM:(B+T) = ratio ≥ 2:1; low GM:(B+T) = ratio ≤ 1:4; balanced GM:(B+T) = ratio between 1:4 and 2:1. B)  Subdivision of LTRCs according to the ratio of their contributions to the myeloid and lymphoid lineages at 16 weeks post-transplant.  α-LTRCs display a high GM:(B+T) contribution (blue squares), β-LTRCs a balanced GM:(B+T) contribution (pink circles), γ-LTRCs a low GM:(B+T) contribution (green triangles), δ-LTRCs contribute B-cells and/or T-cells but no (<1%) GM cells at 16 weeks (yellow diamonds).  57  Figure 3.3 - Rapid alteration of HSC distributions in vitro A)  The distribution of α-, β-, γ-, or δ-HSCs identified in freshly isolated CD45midlin-Rho-SP BM cells. B)  The distribution of α-, β-, γ-, or δ-HSCs identified in 4-day clones generated in vitro from freshly isolated CD45midlin-Rho-SP BM cells. C)  The distribution of α-, β-, γ-, or δ-HSCs identified in subdivided 10-day clones generated in vitro from freshly isolated CD45midlin-Rho-SP BM cells. Eight clones were subdivided into halves or thirds and those fractions were injected into a total of 21 recipients.  58  Figure 3.4 - Clonal propagation of repopulation patterns in secondary and tertiary recipients A)  Summary of the repopulation patterns seen in pairs of secondary and tertiary recipients transplanted with the progeny of each of the 4 HSC subtypes. B)  Five examples of serial transplants originating from each of the 4 HSC types are shown. Bars represent the percent donor contribution to the GM (red), B-cell (blue) and T-cell (yellow)  59 lineages at 16 weeks post-transplant in primary, secondary and tertiary recipients (as indicated). Negative recipients (<1% donor WBCs at 16 weeks post-transplant) are indicated with an asterisk. nd = not done. † indicates the recipient mouse died before 16 weeks post-transplant.  60   Figure 3.5 – CD45midRho-EPCR+ cells are almost exclusively SP A)  The upper 0.1% of the EPCR+ cells are CD45mid. B)  EPCR+CD45+ cells plotted against Rho. C), D), and E) Subdivision into 3 clusters (Rho-, Rhomid and, Rhohigh).  When further examined by dual wavelength analysis of their Ho content, the degree of Rho staining appears to correlate with the level of Ho staining, as can be seen by the proportion of each group that falls within the indicated SP fraction.  A B C D E  61   Figure 3.6 - Approximately half of all CD45midRho-EPCR+ cells are HSCs and these segregate into the same distribution of subtypes as CD45midlin-Rho-SP HSCs A) Rho- cells appear in the left gate and were defined by cells unstained with Rho. B) Rho- cells plotted on a CD45 vs. EPCR plot. The majority of the remaining EPCR+ cells are CD45mid and comprise a distinct population that represents only 0.11% of the Rho- fraction for a total of 0.005% of the total adult mouse bone marrow cells. C) When 3 independent transplantation experiments were performed and the results were pooled, the frequency of HSCs was approximately 50%. D) Representative FACS plots for a repopulated mouse transplanted 16 weeks earlier with a single CD45midRho-EPCR+ cell showing donor derived contribution to GM, B, and T cells in the peripheral blood. E) and F) By comparing the ratio of donor-derived B, T, and GM cells in the peripheral blood at 16 weeks, mice were determined to have been repopulated by one of the 4 previously defined HSC subtypes.21  The pie charts in show the percentage of each subtype that is represented in each HSC population.   Experiment       Frequency of HSC         Total D  62   Figure 3.7 - All 4 patterns of HSC differentiation are observed in the recipients of single CD45midRho-EPCR+ cells A), B), C), and D) Examples of individual mice repopulated with freshly isolated cells where coloured areas represent donor WBCs of GM (red), B-cell (blue) and T-cell (yellow) lineages as a percentage of all WBCs over time post-transplant.  Data are stacked such that the sum of the individual contributions to each lineage by donor cells represents the total donor contribution to all WBCs. E), F), G), and H) Separate donor contributions to the individual GM (red), B-cell (blue) and T- cell (yellow) lineages and are shown as bars.  The percentage donor contribution to the total WBCs is shown as a grey area behind the bars.     63   Figure 3.8 - CD45+EPCR+CD48-CD150+ (E-SLAM) cells from E14.5 FL cells and adult BM are highly enriched for HSCs Representative profiles of viable cells after being stained with antibodies to CD45-FITC, EPCR- PE, CD48-APC, and one of CD150-biotin/SA-PE-TexasRed or CD150-PECy7 from E14.5 FL (A) and adult mouse BM (B).  The E-SLAM fraction of cells represents ~0.02% of Ter119- depleted FL cells and ~0.004% of the adult BM population.  The HSC purities in these suspensions were determined from monitoring mice injected with single E-SLAM cells.  Plots were generated using FlowJo software from TreeStar.  64   Figure 3.9 - CD150 expression divides the CD45+EPCR+CD48- adult BM cell population into fractions differentially enriched in HSCs with high and low self-renewal properties A) Gates used to subdivide CD45+EPCR+CD48- adult BM cells into CD150+ and CD150- fractions as generated by FlowJo with single cell transplantation frequencies of each population immediately below that population. B) Distribution of different types of repopulating cells according to their self-renewal capacity (pie chart on the left) or differentiation (diff’n) programs displayed (bar chart on the right) from analyses of 62 mice transplanted with single E-SLAM cells (top) and 28 mice transplanted with single CD45+EPCR+CD48-CD150- cells (bottom).    65  Figure 3.10 – CD45+EPCR+CD48-CD150+ (E-SLAM) is a surrogate marker for HSCs with high self-renewal and isolates HSCs from reconstituted animals at high purity A)  Peripheral blood and bone marrow chimerism for primary animals transplanted with a single α, β, or γ HSC. B)  Frequency and relative donor contribution of E-SLAM cells from α, β, or γ HSC repopulated mice. C)  HSC frequency of the E-SLAM population isolated from α− or β−reconstituted mice as detected by 10 cell and single cell transplantation experiments into recipient mice. A B  66 4. Exposure to High Concentrations of Steel Factor in Combination with IL-11 Can Block the Otherwise Rapid Differentiation of Adult HSCs In Vitro   4.1  Introduction  The development of methods to isolate highly purified HSC populations16,17,19,221 has permitted extensive analyses of their individual in vivo differentiation and self-renewal activities in serial transplantation experiments initiated with single HSCs17,21,242-244.  These experiments have revealed that some HSCs have self-renewal ability in vivo that is strongly and consistently associated with the display of either a balanced lympho-myeloid differentiation ability or a highly skewed generation of myeloid progeny, at least in the HSCs present in the BM of young adult mice21. Intense interest in understanding the mechanisms that control HSC self-renewal has led to the identification of multiple genes that intrinsically regulate HSC properties.  As summarized in Chapter 1, these include regulators of the cell cycle, such as Cdkn1a (p21)149 and Cdkn2c (p18)151, and members of the transcriptional control machinery, such as HoxA9,245 HoxB4,144 Phc1 (Rae28) 140 , Bmi1138, Ezh2141, Gfi1246, Gata2167, and Gata3247, Etv6206, Pcgf2 (Mel18) 142 , Mcl1248, Meis1245, and Runx1167.  In addition, growth factor receptors like GP13074 and KIT87 and their downstream signaling intermediates, including STAT3134, STAT5135, PTEN249, and LNK244, have been shown to mediate the ability of HSCs to execute self-renewal divisions. These findings reinforce data suggesting that multiple external cues, including SF250, TPO113,198, TGF-β251,  Flt3-L252 and factors like IL-6 and IL-1190,253 that signal through GP130 can modulate HSC self-renewal, proliferation, and viability independently.  Nevertheless, only a few  67 studies17,114 have provided definitive evidence of the directed extrinsic alteration of HSC self- renewal since this requires clonal analysis of highly purified HSCs stimulated under conditions where differences in cell death cannot account for changes in HSC recoveries. Thus, both the intrinsic heterogeneity of the HSC compartment itself and the mechanisms that regulate the behaviour individual HSCs may display appear to be more complex than initially anticipated.  To investigate how these 2 issues may be interrelated, I examined the timing and magnitude of changes in HSC activity that occur over a 4-day period in cultures initiated with a single cell maintained under different conditions of SF stimulation plus a constant dose of IL-11 (20 ng/mL).  The highest SF concentration chosen (300 ng/mL) was one predicted to optimize HSCs self-renewal under these conditions and the others (10 and 1 ng/mL) were predicted to not affect either the viability or the initial mitogenic response of the cells37.   4.2  Results  4.2.1   Different SF concentrations alter maintenance of HSC activity  In a first series of experiments, a total of 100 single cells were cultured for 10 days in either 10 ng/mL or 300 ng/mL SF (plus 20 ng/mL IL-11).  At this time, there was no obvious difference in the frequency or distribution of clone sizes generated under the 2 different conditions.  However, when the cells from each set of cultures were pooled and assayed using a limiting dilution (CRU) transplant protocol to determine the overall number of HSCs produced during the 10 day culture period, the cultures containing 300 ng/mL SF showed maintenance of the input number of HSCs, whereas the cultures containing 10 ng/mL SF showed that the yield of HSCs numbers was 13-fold lower (Table 4.1).  68 4.2.2   SF concentration can rapidly alter the defining properties of HSCs without affecting their viability or cell cycle progression  To determine how quickly exposure to different concentrations of SF might alter the ability of HSCs to sustain their stem cell properties and the relationship of such effects to their viability and mitogenic responses, single CD45midlin-Rho-SP or CD45midRho-EPCR+ cells were cultured individually for defined periods in SFM supplemented with 20 ng/mL IL-11 and 1, 10 or 300 ng/mL of SF and then visually examined every 4 to 6 hours to determine if and when any cells died and the timing of any divisions that took place based on the first appearance of 2 and then 3 or 4 cells.  A cumulative plot of the data obtained from 130 such single-cell cultures (3 independent experiments) is shown in Figure 4.1.  In the cultures containing 300 ng/mL SF, no divisions occurred prior to 22 hours of incubation, but >90% of the original cells completed a first mitosis within the following 20 hours (i.e., between 22 and 42 hours after the cells were placed at 37oC).  The division kinetics of the cells incubated in the 10 ng/mL SF condition were indistinguishable from those displayed by the cells incubated in the 300 ng/mL SF condition and no cell death was observed in any of the 114 wells containing cells maintained under either of these 2 conditions.  Cultures containing 1 ng/mL SF showed a slightly delayed entry into the first and second division.  Dead cells first became evident in these latter cultures after the second division and 35% to 40% of the clones were no longer viable after 4 days of culture. We then compared the frequency of clones that retain HSC activity during the first 4 days in culture when maintained in 300 ng/mL vs. 10 ng/mL SF (plus 20 ng/mL IL-11).  For these experiments, another 160 single-cell cultures were initiated.  Then 8, 16, or 96 hours later, each single cell, or the clone it had generated, was harvested individually and transplanted into an irradiated mouse to determine whether one or more HSCs were present.  As shown in Figure 4.2, the proportion of cells still detectable as HSCs remained unchanged for the first 16 hours in the  69 cultures containing 300 ng/mL SF and, even after 4 days, the frequency of clones containing at least one HSC was still 50% of the frequency of HSCs in the original suspension.  In the cultures containing 10 ng/mL SF, the number of HSCs also did not change during the first 8 hours of incubation (Fishers Exact Test, n=17, p=1.0) but, within the next 8 hours, their numbers decreased to one-third of the input value (Fishers Exact Test, n=24, p=0.10) and remained significantly reduced thereafter (Fishers Exact Test, n=43, p=0.009).  These findings raise the intriguing possibility that changes in SF stimulation can directly and very rapidly regulate the functional integrity of HSCs in vitro while they are still in a quiescent state, without affecting their immediate viability or the timing of their subsequent proliferative response.   4.2.3  Most HSC self-renewal divisions stimulated by SF and IL-11 in vitro are asymmetric  We then investigated the type of repopulating cells generated from the first division of 21 CD45midlin-Rho-SP cells maintained in 20 ng/mL IL-11 plus either 300 ng/mL SF (n=15) or 10 ng/mL SF (n=6) SF.  Single-cell cultures were visually monitored to determine the timing of the first division and then, between 4 and 8 hours later, the 2 daughter cells were harvested, separated, and each transplanted into a separate irradiated recipient.  Assessment of the repopulation patterns obtained showed that 5 of the 15 progeny pairs generated under the high SF condition contained daughter HSCs (i.e.: maintenance of the starting frequency of 1 in 3), whereas none of the 6 pairs generated under the 10 ng/mL SF condition showed HSC activity, again indicative of a significant (Fishers Exact Test, p=.048) rapid reduction in HSCs under this condition (Figure 4.3A).  Interestingly, even in the presence of 300 ng/mL SF, both progeny were HSCs in only 2 cases and were then not of the same differentiation subtype (i.e.: they did  70 not produce a similar ration of lymphoid:myeloid progeny in transplantation assays).  In the other 3 positive pairs, only one of the 2 progeny was an HSC (Figure 4.3B).  An example of the 4-month repopulation data obtained from one of the 2 pairs where both progeny were HSCs is shown in Figure 4.3C.  Taken together, these results demonstrate the highly preferential execution of asymmetric divisions by HSCs in vitro under the conditions examined.   4.2.4   Potential intrinsic molecular mediators of the ability of SF to sustain the stem cell state of HSCs in vitro  To determine whether this loss of HSC functional activity might be correlated with differences in the expression of critical genes associated with HSC self-renewal control, we set up parallel bulk cultures of CD45midRho-EPCR+ cells using the same conditions of 20 ng/mL IL- 11 plus 1, 10, or 300 ng/mL SF and then analyzed the RNA extracted from them 16 hours later by Q-RT-PCR.  No significant differences were seen in the levels of transcripts for Gata2, Gata3, Gfi1, Hoxa9, Meis1 or Runx1 in cells incubated in any of the different concentrations of SF tested.  However, transcript levels for both Bmi-1 and Ezh2, 2 members of the group of repressive Polycomb transcription factor genes were significantly higher in the cultures containing 300 ng/mL SF (Figure 4.4).  A similar finding was also noted for Lnk, a gene encoding a negative regulator of receptor tyrosine kinase receptor signaling.  4.3    Discussion  Recent experiments utilizing single-cell transplants have provided evidence of heterogeneity within the rare subset of quiescent adult mouse BM cells that produce mature  71 blood cells for extended periods of time (>4 months) in irradiated recipients.  This heterogeneity is manifested as a marked skewing (or not) in favour of either granulopoietic or lymphoid differentiation in vivo that is faithfully transmitted to derivative repopulating cells21.  This finding raises the important notion that in HSCs, self-renewal, cell cycle entry and progression, and lineage restriction are independent processes that are regulated by mechanisms with at least some distinct features. To further investigate the prevalence of heterogeneity among the HSCs present in adult mouse bone marrow, we performed a series of single cell transplants using a population that was isolated via a simpler, but similarly powerful, procedure (using only anti-CD45 and anti-EPCR antibodies in combination with Rho staining).  We were thus able to use the CD45midlin-Rho-SP and CD45midRho-EPCR+ purification strategies interchangeably to determine the proportion of HSCs that would execute at least 2 self-renewal divisions when cultured under “optimal” cytokine conditions in vitro (300 ng/mL SF plus 20 ng/mL IL-11)17,90.  Visual monitoring of clone development in vitro showed that every input cell completed at least 2 divisions within 4 days.  Functional assessment of 4–day clones showed that the frequency of clones containing at least one HSC was about half the frequency of HSCs in the original population.  In fact, this would likely be an underestimate because any HSCs in S/G2/M would not have been detected.43,235  Thus, continuous exposure to a high concentration of SF in combination with IL- 11 appears sufficient to allow many input HSCs to execute multiple self-renewal divisions over a 4–day period. To address this question more directly, I analyzed the individual first division G1 progeny of 15 input cells cultured under the same conditions.  The results showed that one or both of the members of 5 of these progeny pairs (30%) was an HSC - again, a similar proportion to the frequency of HSCs in the starting cells.  However, characterization of the types and levels of WBCs produced in vivo by each of the 2 cells in these 5 progeny pairs showed that they all  72 appeared to be the product of asymmetric divisions; i.e., 3 pairs contained only one HSC and the other 2 pairs contained 2 HSCs but each member of the pair was a different subtype.  These findings are consistent with a more rapid loss in vitro of the HSC subtypes that retain extensive self-renewal activity in vivo21 and a stochastic distribution of self-renewal events amongst individual multi-potent cells proliferating in vitro254.  At the same time they appear inconsistent with the reported symmetry of the first 2 divisions of CD34-KSL cells in vitro255 and of the clonally amplified HSCs seen after 10 days in vitro21.  Clearly, additional experiments will be required to determine more precisely when and how symmetry is established when HSCs are stimulated under different conditions in vitro. Our experiments also provide new information about the effects of exposing HSCs and/or their clonal derivatives in vitro to different SF concentrations.  For this comparison, single cells from the same HSC-enriched populations were incubated in IL-11 plus a level of SF (1 or 10 ng/mL) that was predicted to give a markedly decreased output of HSCs, as suggested by previous results using 10-day cultures of less purified bone marrow cells.90  Assessment of the cells cultured in the 10 ng/mL SF condition confirmed the predicted loss of HSC activity within 10 days.  More detailed time course studies further revealed that the loss of HSC activity induced by inadequate SF stimulation did not become manifest until after 8 hours but was evident within the ensuing 8 hours.  From the subsequent kinetics of division seen, it can be readily inferred that most of the cells would not have exited G0 until after the first 16 hours of incubation.  Thus, loss of HSC function likely occurred in most affected cells before they had entered the cell cycle. Interestingly, these effects also occurred in the absence of any evidence of effects on their immediate viability or mitogenic responses.  Previous evidence of a similarly rapid induction of differentiation in the absence of proliferation by pluripotent hematopoietic cells was noted many years ago in studies of the FDCP-mix(bcl-2) cell line model256.  The findings presented here now show that this is also a property of normal adult HSCs.  73 The ability of HSCs to undergo such abrupt changes in their function raises intriguing questions about the nature of the molecular events involved and provides a novel experimental system for the further analysis of this process.  Here we performed an initial survey of a small number of transcripts associated with HSC integrity.  Strikingly, even this early data set revealed a significant rapid and specific reduction in transcripts for Bmi1 and Ezh2 that accompanied the biological changes in HSC function apparent within 16 hours of incubation under low SF conditions.  Both Bmi1 and Ezh2 are of interest because they have been strongly implicated as regulators of the adult HSC self-renewal program138,139,141.  Our findings also extend those demonstrating that HSCs are detectable amongst one or both of the first division progeny of Lnk-/- cells incubated in cultures containing 50 ng/mL SF244,257.  Since LNK is a negative regulator of SF-activated kit signalling257, deletion of Lnk might be expected to enhance HSC output in cultures containing a concentration of SF that is suboptimal for wild-type HSCs.  Curiously, we found that Lnk transcripts were lower in cells maintained in the lower SF conditions.  This result suggests that our current picture of how HSC self-renewal is controlled by known regulators may be incomplete, including the predicted consequence of reduced Lnk transcripts.  Accordingly, it will be important in future studies to evaluate multiple elements of the self-renewal machinery, as well as measuring changes at the level of the encoded proteins and their activity. In summary, this study provides further support for a model of HSC control in which there are elements regulating self-renewal activity that are different from those controlling lineage restriction, quiescence, or survival.  The rapidity with which HSCs can be induced to differentiate under defined signalling conditions now provides a novel framework for delineating in molecular terms precisely how these elements achieve the biological readouts used to define HSC function.   74 Table 4.1  HSC yields are reduced in cultures containing a low concentration of SF          a.   Each dose of transplanted cells was sampled from a large pool of 10-day clones generated in either 300 ng/mL or 10 ng/mL SF in combination with 20 ng/mL IL-11.  The cell doses are expressed as “starting equivalents” (day zero = ~30 HSCs).  Since each experiment was initiated with 100 starting cells, a cell dose of 7 represents 7% of all the cells from the pooled clones.  b. L-Calc software (STEMCELL Technologies) was used to calculate the mean frequency of HSCs in the pooled 10-day clones from limiting dilution transplant results.  The starting HSC frequency (3/10 = 30%) was determined from single cell transplants of freshly isolated CD45midlin–Rho–SP cells.     1/5 0/5 0/3 5/5 3/8 0/6 No. of positive mice/ No. of mice tested  2 (0.8 to 6) 27 (19 to 39) No. of HSCs detected after 10 days (±SEM)b  7 2 0.7     10 ng/mL SF + 20 ng/mL IL-11 7 2 0.7    300 ng/mL SF + 20 ng/mL IL-11  Dose of cells injecteda  Cytokine condition  Figur conce 130 c indiv to 6 h divisi could SF.  A estim secon  e 4.1 - Kin ntrations ells (n = 56 idually into ours to dete on when a s  be seen.  T  Lowess sp ated based o d divisions etics of divi for 300 ng/m 96-well plat rmine their econd cell c here was <1 line curve w n the marke under each c sion of CD4 L, n = 58 f es, visually kinetics of d ould be obs % cell death as generate d values in ondition. 75 5midlin-Rho or 10ng/mL confirmed t ivision.  A c erved in the  when the c d in GraphP the time cou -SP cells cu  and n = 16 o be single c ell was scor well and a s ells were cu ad Prism (V rse and is sh ltured in di for 1 ng/mL ells and the ed as havin econd divis ltured in eith ersion 4.03) own for eac fferent SF ) were depo n observed e g undergone ion when a t er 10 or 30  using 248 v h of the firs  sited very 4  a first hird cell 0 ng/mL alues t and  Figur Singl ng/m perce for ea startin SP or (p<0. e 4.2 - Tim e cells or th L IL-11 plus ntage of pos ch condition g HSC con  CD45midRh 05) from the e course of eir clonal pr  either 300 itive transpl  and time p tent as deter o-EPCR+ ce  input HSC changes in ogeny were ng/mL (blue ants (numbe oint assesse mined by si lls.  The ast  frequency. 76  HSC activi injected foll ) or 10 ng/m r of positiv d.  The strai ngle cell tra erisk indicat ty under di owing 8, 16 L (red) SF. e mice as a p ght line acro nsplants of f es values th fferent conc  or 96 hours   Each data roportion o ss the graph reshly isola at are signif  entrations  of culture i point repres f the total an  represents ted CD45mid icantly diffe of SF n 20 ents the alyzed) the lin-Rho- rent  Figur ng/m A) Si when were divisi B) Th cells C) FA from e 4.3 - Asy L IL-11 plu ngle cell cul  a first divis separated an on type sho e distributio repopulated CS plots fo one separate mmetry of H s either 10 tures of CD ion took pla d each of th wn.  SR = se n of HSC s  an irradiate r a pair of r d daughter SC expan ng/mL or 3 45midlin-Rho ce.  Betwee e 2 cells inj lf-renewal, ubtypes is d d recipient. epopulated m pair. 77 sion and ma 00 ng/mL S -SP cells w n 4 and 8 ho ected into a SF = Steel F etailed in th  ice transpl intenance F ere monitore urs followin separate rec actor. e cases wher anted 16 we divisions sti d every 4 h g the first m ipient with t e at least on eks earlier w mulated by ours to deter itosis, doub he resulting e of the 2 d ith individu   20 mine lets  aughter al cells  Figur Q-RT initia bars) not d exper from e 4.4 – Bm -PCR analy ted with CD , 10 ng/mL ( etected.  Va iments, with a single exp i1, Ezh2 and ses of transc 45midRho-EP red bars), or lues shown a  each measu eriment.  Lnk trans ript levels i CR+ cells a  1 ng/mL S re the mean rement der 78 cripts are d n extracts of nd maintain F (brown ba  ± SEM of v ived from tr ownregulat  cells harve ed in 20 ng/ rs).  All valu alues obtai iplicate assa ed with los sted from 16 mL IL-11 p es normaliz ned in 2-3 in ys.  Data wi  s of HSC ac -hour cultu lus 300 ng/m ed to Gapdh dependent thout error b  tivity res L (blue ; ND = ars are  79 5. New Candidate Regulators of Hematopoietic Stem Cells with High Self- renewal Activity   5.1 Introduction  An output of at least 1% of all the WBCs for a period of at least 4 months has thus been generally adopted as the minimal criteria for the specific and sensitive enumeration of HSCs transplanted into congenic irradiated mice258.  This definition has also been widely assumed to capture a unique and homogeneous population of HSCs with similar self-renewal potential. However, a precise and widely accepted definition of what this means molecularly, or even biologically, at the single cell level is less well defined and remains a subject of intense interest and investigation38.  This situation is due, in part, to the heterogeneity in differentiation behaviour and clone maintenance that is encountered when the numbers and types of cells produced by individual hematopoietic repopulating cells are monitored over time176,254,259,260.  It is now clear that some of this heterogeneity is predetermined - as demonstrated by a consistent association of shorter term WBC outputs with a distinguishing phenotype of the cells initially transplanted (e.g.: CD49b+ and CD34+) when these are taken from the BM of adult mice261,262. More recently, we and others have provided evidence that even amongst cells with longer term repopulating activity, there is predetermined heterogeneity in HSC differentiation and self- renewal potential21,236,243,263.  For example, from analyses of a large number of single-cell transplants, we have resolved 2 subtypes of adult BM HSCs that can be discriminated by their lymphopoietic ability but share a relatively high myelopoietic ability and a pervasive high self- renewal capability that persists through 3 cycles of clonal expansion in vivo21.  In contrast, 2  80 other subtypes that share a robust lymphopoietic ability but more transient myelopoietic activity failed to generate detectable HSCs after 6 months of clonal expansion in primary recipients, suggesting their possession of a self-renewal mechanism that was destined to be extinguished after a finite, albeit large number of divisions.  Importantly, we found that these high and low self-renewal HSC subtypes were both EPCR+CD48- but could be separated to some extent on the basis of their high and low expression of CD150, respectively.  Similar evidence of HSCs with different regenerative activity and in vivo turnover rates has recently been reported by others47,48. To gain further insights into regulators that may be of major importance to the maintenance of an unlimited self-renewal state, I applied a comparative gene expression approach to multiple populations that are variably enriched in high HSCs.  The cells analyzed were purified from both FL and adult BM and extracts of these were analyzed for differences in transcript levels using a combination of a global strategy (LongSAGE) and a more specific strategy (Q-RT-PCR analysis) of a group of genes identified from the LongSAGE data and from the literature.   5.2 Results  5.2.1 Construction and characteristics of LongSAGE libraries prepared from highly purified FL and adult BM HSCs  Ten thousand lin-CD43+Mac1+Sca1+ E14.5 FL cells and 3,700 CD45midlin-Rho-SP adult BM cells were isolated and used to prepare LongSAGE libraries that were then sequenced to a depth of ~160,000 and ~36,000 tags, respectively.  In previous studies carried out by our lab at the same time as these samples were isolated, HSC purities of 20% (assuming half of the HSCs  81 are undetectable because they are in the S/G2/M phases of the cell cycle43and 30% in these populations, respectively, were measured.  Further details of the library characteristics are summarized in Figure 5.1A and given on line (GEO Series accession number GSE13243, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13243). Tag frequencies for many genes previously reported as having a role in fetal and/or adult HSCs were present at expected relative levels (Figure 5.1B).  The tag profile for the FL library showed a large degree of overlap with published lists generated from other proliferating (or activated) HSC-enriched populations.  For example, I found tags for 36 of the 50 most upregulated transcripts in the activated HSC population identified by Venezia et al. 264 to be present in the E14.5 FL HSC library. Figure 5.1C shows a quantitative display of the overall pattern of significantly differentially expressed genes between the 2 libraries.  All tags found to be significantly over- represented in the adult BM library are listed in Table 5.1 and those significantly over- represented in the FL library are listed in Table 5.2.  When these lists of differentially represented tags were surveyed for their Gene Ontology assignments (www.geneontology.org), the “mitotic cell cycle”, “protein kinase activity” and “ATP-binding” categories were over- represented in the FL library and the “chemotaxis” and “cell surface and receptor-linked signal transduction” categories were over-represented in the adult BM library (Figure 5.1D). These libraries thus provide a new resource for global transcriptome analyses and comparisons of fetal and adult HSC programs.       82 5.2.2  A gene expression signature for FL and adult BM HSCs  I used the PCR SAGE libraries and the literature as a starting point to identify 27 candidate genes whose expression was anticipated might be specifically up-regulated in high self-renewal HSCs.  The 27 genes selected were: Rhob, Hmga2, Trim27, Mef, Pld3, Gata2, Cdkn2c, Vwf, Atm, Cdkn1a, Lyl1, Car3, Plp1, Smarcc1, Cul4a, Stat3, G3bp1, Chd4, Eif1a, Cebpa, Smarcc2, Fus, Psap, Tubb5, Mlx, Hdac3, and Rik1200009F10.  As a preliminary test of this hypothesis, the transcript levels of these 27 genes were compared in E14.5 FL and adult BM E-SLAM cells with their corresponding lin- fractions (in which high self-renewal HSCs would be expected to constitute <1% of the population.  The results showed that 9 of the 27 genes were consistently expressed at higher levels in the E-SLAM cell fractions (Chd4, Pld3, Lyl1, Psap, Stat3, Vwf, Rhob, Smarcc2 and Hmga2, Figure 5.2A-B).   5.2.3 Identification of a subset of genes whose lower expression is associated with “nearest neighbours” of high self-renewal HSCs  I then asked whether the biological differences in self-renewal activity between E-SLAM and the more closely related CD45-EPCR+CD48-CD150- adult BM cells (described in Chapter 3) are associated with differences in expression of genes previously implicated in the regulation of HSC self-renewal, i.e., Prnp265, Bmi1138,139, Gata3247, Rae28140, Lnk257,266, and Ezh2141.  Figure 5.3 shows the results of a comparison of the transcript levels measured in these 2 populations of adult BM cells by Q-RT-PCR.  Transcripts for all 6 genes were consistently detected in the E- SLAM subset (selectively enriched in high self-renewal HSCs), albeit at low levels relative to Gapdh, as expected.  Moreover, transcript levels for 3 of these 6 genes (Prnp, Gata3, and Bmi1)  83 were significantly higher in the CD150+ subset (p<0.05), suggesting a possible functional role for these molecules in maintaining a high self-renewal state in HSCs. When I assayed these populations for their expression of the 9 candidate genes, there was no difference in Lyl1, Stat3, Hmga2, Psap, and Chd4 transcript levels, but the CD150+ fraction (i.e., the HSCs with high self-renewal activity) contained significantly higher levels of Smarcc2, Vwf, Rhob, and Pld3 transcripts (Figure 5.2C).  To examine the potential importance of these genes I then examined their stability in another system where HSCs rapidly lose their high self- renewal activity.  For this, I took advantage of my earlier finding (see Chapter 4) that freshly isolated adult BM HSCs remain viable and clonogenic in vitro, but show a differential retention (100% vs. 20%) of their longterm in vivo repopulating ability when exposed for 16 hours in vitro to varying concentrations of SF (from 300 ng/mL down to 1 ng/mL) in combination with 20 ng/mL IL-11.  Previous measurements showed that Bmi-1 and Ezh-2 transcript levels in such cultured HSC populations are markedly lower in the cells cultured in limiting concentrations of SF (Chapter 4).  These findings were confirmed in the new experiments described here.  In addition, the present set of experiments identified transcripts for Vwf, Rhob and Pld3 to be present at reduced levels in the cells cultured in concentrations of SF that selectively and rapidly eliminate their repopulating activity (Figure 5.2D).  Additional Q-RT-PCR data from these experiments is displayed for all comparisons in Figures 5.4, 5.5, and 5.6.   5.3  Discussion  Understanding HSC self-renewal control remains a priority in medicine as this knowledge is likely to provide insights into methods for expanding HSC populations and producing blood products in vitro in addition to identifying key pathways that are perturbed or  84 hijacked by leukemic stem cells.  Furthermore, it is possible that parts of this machinery are used by other stem cell populations to maintain their undifferentiated status.  Already, a surprisingly large number of genes have been identified from overexpression or knock-out experiments as able to influence HSC function to varying degrees in assays designed to test the ability of these cells to amplify their numbers either in vitro or in vivo.  These include genes like Bmi1139 and Cdkn1a (p21)149 whose expression appears to be required for optimal HSC self-renewal, as well as Lnk244 and Cdkn2c (p18)151, whose expression appears to suppress HSC self-renewal. However, whether these genes constitute the complete self-renewal circuitry of HSCs is unclear. It also remains a mystery as to how cells are molecularly configured to have very large but discrete differences in self-renewal capabilities that determine whether their ability to produce mature progeny will be sustained for 2-3 months or 4-8 months vs. longer periods that can exceed the lifetime of the mouse.  Indeed, evidence of a clear distinction between the latter 2 types of HSCs has only recently become available from studies that have assessed the in vivo self-renewal properties of a large number of individual HSCs at a clonal level21 and have subsequently revealed associated differences in the expression of CD150 on these cells and its association with different compartment turnover rates (Chapter 3 and47,48)  Thus, it has not been possible to implicate any of the genes thus far identified as to whether they might be particularly important in keeping HSCs in a state where the probability of executing a self-renewal division when stimulated in vivo remains high. We found that Prnp, Bmi1, and Gata3 were selectively up-regulated in the E-SLAM (high self-renewal HSC) population, consistent with their suggested roles in the maintenance of this state.  We now present evidence from pairwise comparisons of several other genes and show that 3 genes (Rhob, Pld3 and Vwf) may have similar roles given their selective but consistently elevated expression in populations that are most enriched in high-self-renewal HSCs.  85 Prion protein (Prnp) transcripts, which appeared in the LongSAGE screen as being highly upregulated in adult BM, and doubles as a positive control for our screen, has a very interesting role in HSCs.  In 2005, Zhang et al.265 showed that PRNP was expressed on adult BM HSCs both by phenotypic overlap studies and by affinity purification followed by competitive repopulation experiments.  The primary transplants of Prnp-/- BM cells were found to compete equally with wild-type cells, but the secondary and tertiary transplants of Prnp-/- cells showed a 2 to 3-fold reduction in repopulating activity when compared to wild-type HSCs.  This is in strong agreement with Prnp having a functional role in maintaining a durable self-renewal capability in HSCs265.  Rhob encodes a small GTPase which has been described to have a role in the inhibition of malignant cell growth and is the putative target of farnesyltransferase inhibitors267.  It has been shown to interact with mDia1268, which in both heterozygous and homozygous knockout animals leads to age-dependent myeloproliferative defects that include splenomegaly, a hypercellular bone marrow, and extramedullary hematopoiesis269.  Phospholipase D3, on the other hand, is a gene about which relatively little is known. Pld3, also known as Sam-9 is strongly expressed in neural tissue270 and transcripts have also been identified in T-cell lines271, T-regulatory cells and Foxp3-transduced CD25-CD4+ T-cells272. Pld3 has 30-40% homology to Pld1 and Pld2 whose products are stimulated by PIP2, G proteins, ARF and RHOA.  PLD1 is directly regulated by PKC in most mammalian cells273.  Most interesting is the strong connection between Phospholipases and Rho family members as 2 of the 3 new candidate regulators identified here are RHOB and PLD3. Absence of VWF is primarily associated with defective hemostasis and thrombosis.  Vwf knockout mice are normal at birth, but have a highly prolonged bleeding time and reduced levels of Factor VIII274.  However, a role of Vwf in the control of HSC self-renewal has not been previously indicated.  86 Interestingly, Lyl1 (an Scl family member) is a gene that remains high in the low self- renewal fraction of HSCs, which show poor maintenance of myelopoietic potential.  Recently, Capron et al.275 showed that Lyl1-/- BM cells are 1.6- to 5.7-fold less competitive than wild-type BM cells with the vast majority of the long-term impairment being attributable to poor B- and T- cell production.  Furthermore, overexpression of Lyl1 has been clearly implicated in B and T-cell lymphoma with 30% of Lyl1 transgenic mice developing malignant lymphoma276. In summary, we have now shown that HSCs with longterm multi-lineage potential in vivo, but markedly different self-renewal properties, can be prospectively isolated as separate, highly purified cell types and found to display unique gene expression signatures.  These findings strongly support the hypothesis that HSCs self-renewal activity is not gradually lost with successive divisions but is maintained in a state where differentiation is indefinitely postponed until an initiation event occurs, which may bring on a termination of self-renewal divisions more or less rapidly according to the signals the cell receives even when it is quiescent. The generation of whole transcriptome LongSAGE data should provide a useful resource for many future studies and the identification of 3 genes not previously associated with HSC self- renewal activity offers an exciting approach to further deciphering the molecular machinery of HSC self-renewal.    87 Table 5.1 Tags over-represented in the adult BM HSC library vs. the FL HSC library FL FL HSC BM BM HSC Fold  Accession Gene Name Sequence data HSC /100K HSC /100K Diff. GCTCTGGGAGTTATAAG 0 0 88 243.32 N/A NM_008293 Hsd3b1 TGCTTTATAGGCCTCAA 0 0 74 204.61 N/A NM_009062 Rgs4 AATTAAAAACATTACAA 0 0 66 182.49 N/A NM_019946 Mgst1 TATATTAAATCCCTCCT 0 0 55 152.075 N/A NM_011428 Snap25 GAGGAGTGGGATGTGCC 0 0 46 127.19 N/A NM_022422 Gng13 CCACAGAGAGGTGGTGG 0 0 41 113.365 N/A NM_016805 Hnrnpu CACTCTTCTATCACTGA 0 0 41 113.365 N/A NM_027885 Smug1 TAACTGGTGCACATTTA 0 0 41 113.365 N/A NM_027920 Mar8 GACCAGAACAGAGACGG 0 0 40 110.6 N/A NM_010861 Myl2 CAGTCTTGAGTGCCCTA 0 0 40 110.6 N/A NM_029787 Cyb5r3 GCATAAGCAATGATTCT 0 0 39 107.835 N/A NM_007471 App ATTAATTATGTATTAGT 0 0 39 107.835 N/A NM_009441 Ttc3 ACACCCGAAGAATGGAC 0 0 37 102.305 N/A NM_029934 Mboat7 TATGTATGTATGTATGC 0 0 37 102.305 N/A NM_175534 Mrgpre AACTGAGGGGTCTCTGT 0 0 35 96.775 N/A NM_011179 Psap GGCCCTTGCTCCAGCTG 0 0 35 96.775 N/A NM_026065 D10Ertd322e TTCCTTGTTAACATTTT 0 0 35 96.775 N/A NM_028262 Setd3 TTACAGAAATGCTGAAA 0 0 34 94.01 N/A NM_001042650 Dcun1d2 TTAGCAACATATTTATC 0 0 34 94.01 N/A NM_008098 Mtpn TACTATGTGGATGTGCT 0 0 34 94.01 N/A NM_021431 Nudt11 AACAACCAAGTGAAAAG 0 0 34 94.01 N/A NM_023290 Mkrn2 ATTCACACTGAAAAAAG 0 0 34 94.01 N/A NM_134255 Elovl5 TCTATAGAGTGTGCCCT 0 0 34 94.01 N/A NM_184053 Calu GGGACTGCATTGAGAGC 0 0 33 91.245 N/A NM_008219 Hbb-bh1 TAATGATTCTTTCTCAC 0 0 33 91.245 N/A NM_008409 Itm2a CTCAGTATCCCTTCCAG 0 0 33 91.245 N/A NM_008512 Lrp1 ACTGCAAACTAAAACCC 0 0 33 91.245 N/A NM_008683 Nedd8 AACTGTACAAATTTACA 0 0 32 88.48 N/A NM_007569 Btg1 GATGTGGTTTTTGTTTT 0 0 32 88.48 N/A NM_009930 Col3a1 CATAGGTATCAGGCTTG 0 0 32 88.48 N/A NM_019413 Robo1 CCCTTAGCGCAGGCTAC 0 0 32 88.48 N/A NM_021473 Akr1a4 GTAAATTGTTAAGCTGT 0 0 31 85.715 N/A NM_010917 Nid1 CATAGGCTGCTATGTGA 0 0 31 85.715 N/A NM_011135 Cnot7 TCCTTTTTGACTGTGTG 0 0 31 85.715 N/A NM_019635 Stk3 GCTGCCGCCTTCGCGCG 0 0 31 85.715 N/A NM_138748 Ppp2r4 GGTCGGCATCTTCTTAA 0 0 30 82.95 N/A NM_009269 Sptlc1 CTGGACCCGGGTCTGGA 0 0 30 82.95 N/A NM_011680 Usf2 ATGTGATAAATGTGAAA 0 0 30 82.95 N/A NM_020025 B3galt2 GGCTGAAGGTATGATAG 0 0 30 82.95 N/A NM_025837 Mpi TTTAAGATACAACATCT 0 0 30 82.95 N/A NM_146207 Cul4a GAACATTCCAGATCTGA 0 0 29 80.185 N/A NM_007431 Alpl  88 CCGCCGTGGGAGCGTGA 0 0 29 80.185 N/A NM_008635 Mtap7 GAACAGTCGACACACTT 0 0 29 80.185 N/A NM_009605 Adipoq TTTCCTACTGCCTTCCC 0 0 29 80.185 N/A NM_011550 Mlx TGCATAAGTCACAGAGA 0 0 29 80.185 N/A NM_016762 Matn2 ATAATTGAAAGCCAGCC 0 0 29 80.185 N/A NM_145962 Pank3 AGAAAGTAGATTTTCAG 0 0 28 77.42 N/A NM_001029934 Usp32 TGAAAAATGACAAATGT 0 0 28 77.42 N/A NM_001040399 Larp2 TCTGCAATTTAAATTCT 0 0 28 77.42 N/A NM_007937 Epha5 GGACTAACTACGGACTC 0 0 28 77.42 N/A NM_010064 Dync1i2 GCCTCATCCCTGCACCA 0 0 28 77.42 N/A NM_010929 Notch4 GAGTTGGGAATTAAAGA 0 0 28 77.42 N/A NM_013865 Ndrg3 CCACATCCAGTACTCAG 0 0 28 77.42 N/A NM_022721 Fzd5 CTCACAAATGTGAGAGA 0 0 28 77.42 N/A NM_025278 Gng12 TAACAGAACCACTTGAG 0 0 28 77.42 N/A NM_028343 Tmem135 TCCTGTGTCAACAACCC 0 0 27 74.655 N/A NM_007765 Crmp1 AAAACCATTGCAGGAAA 0 0 27 74.655 N/A NM_009127 Scd1 GACAGTGGAGATGAGGC 0 0 27 74.655 N/A NM_010773 Mbd2 TTTATTAAATGAATGAG 0 0 27 74.655 N/A NM_019986 Habp4 GTTTAAAATAAATCAGA 0 0 27 74.655 N/A NM_021414 Ahcyl2 CTGGTTGGAGGAAGGCA 0 0 27 74.655 N/A NM_027400 Lman1 ACAAATACGGCAATATG 0 0 27 74.655 N/A NM_030052 Cox7b2 TGCATCTGCGTTGTTCT 0 0 27 74.655 N/A NM_144875 Rab7l1 ACTATAAATACCGGGTG 0 0 27 74.655 N/A NM_199195 Bckdhb GTTGCTGTTTTAGGCCC 0 0 26 71.89 N/A NM_001114096 Smarcc2 GAATTGATGATGCTCAC 0 0 26 71.89 N/A NM_009129 Scg2 ATCCCTGAGCTGGTGCC 0 0 26 71.89 N/A NM_009995 Cyp21a1 AAGGTGAAGGAGACAAA 0 0 26 71.89 N/A NM_020494 Ddx24 ATTTAATAAAATAACTT 0 0 26 71.89 N/A NM_032008 Slmap AGAATATGTAAGAGTAA 0 0 26 71.89 N/A NM_172616 C330027C09Rik AGGTGCCTCCAAGGACA 0 0 26 71.89 N/A NM_172687 Coq3 AGGCATCTTCTGATATC 0 0 26 71.89 N/A NM_199197 1110032A13Rik TGGGGCCTCTCCTCTGA 0 0 25 69.125 N/A NM_009778 C3 CCAACGCTTTACTACTG 0 0 25 69.125 N/A NM_010233 Fn1 AAATTATTGGGAATTCC 0 0 25 69.125 N/A NM_011123 Plp1 TATTTTGTTTTGTCATA 0 0 25 69.125 N/A NM_011170 Prnp TGTATTCTGTCAGGAAT 0 0 25 69.125 N/A NM_026200 Kcnv1 CCAACACCACTATGGAG 0 0 25 69.125 N/A NM_146207 Cul4a GCTTGGTACACCTGGGG 0 0 25 69.125 N/A NM_178920 Mal2 AATTCCTTTGCTCATCT 0 0 25 69.125 N/A NR_003368 Pvt1 TGCTCAGATGAATGCTC 0 0 24 66.36 N/A NM_001107952 Zfyve9 GGGGGAGTGGAGGGCGT 0 0 24 66.36 N/A NM_010923 Nnat GGGACCAGGTATGCAAG 0 0 24 66.36 N/A NM_011485 Star CCACTCTCAGTCAACAG 0 0 24 66.36 N/A NM_019791 Maged1 GCTTGCTTACTTCGGTG 0 0 24 66.36 N/A NM_029734 2410187C16Rik TTCTATAGAAACTTTTC 0 0 24 66.36 N/A NM_153175 Gimap6  89 TTGAGTTACTACTTTGC 0 0 24 66.36 N/A NM_178362 Sorbs1 CTGCATAGCTCTTTAAA 0 0 23 63.595 N/A NM_007643 Cd36 CTTGGGTGCAATTGGTC 0 0 23 63.595 N/A NM_011164 Prl GTGAGAGGAAGCAAGCA 0 0 23 63.595 N/A NM_015784 Postn GTGAGGACACCAGCTTT 0 0 23 63.595 N/A NM_029688 Srxn1 GTGCCAACAGATTAGAA 0 0 23 63.595 N/A NM_177608 3110001I20Rik GTGCTGTGAGATTGTGG 0 0 22 60.83 N/A NM_009995 Cyp21a1 TATAATTATACGTATCA 0 0 22 60.83 N/A NM_025703 Tceal8 GACTAGCATCCCCAGTC 0 0 22 60.83 N/A NM_028292 Ppme1 AGTTGTGAAGTTTCACT 0 0 22 60.83 N/A NM_053079 Slc15a1 CCTTTAATCCTCCCACT 0 0 22 60.83 N/A NM_178619 1810026J23Rik TATATTAAAGATTTTTT 0 0 22 60.83 N/A NM_198620 Rundc3b CCCAGGCTTGGGGGAGG 0 0 21 58.065 N/A NM_009271 Src TGTGCCGGCCTCGAGAC 0 0 21 58.065 N/A NM_011485 Star GCCAGTTTTCTTCCCTC 0 0 21 58.065 N/A NM_019535 Sh3gl2 AGGGGATCTGATGCCCT 0 0 21 58.065 N/A NM_027415 Tmem70 GAACAGTACAGGACCAG 0 0 21 58.065 N/A NM_138681 Bcas3 CTGAAGTGGGATTAAAG 0 0 21 58.065 N/A NM_139063 Muted TACTGAAAGAGCATTTT 0 0 21 58.065 N/A NM_207653 Cflar AGCCCTTTTACAGTGAC 0 0 20 55.3 N/A NM_007711 Clcn3 AGGAGCAAAAACCCGTT 0 0 20 55.3 N/A NM_009266 Sephs2 TTTTACATATAAATTGC 0 0 20 55.3 N/A NM_011806 Dmtf1 CTGGGTTCGGGCCAGAC 0 0 20 55.3 N/A NM_013805 Cldn5 CTTTAAGACCTTGTTCA 0 0 20 55.3 N/A NM_020000 Med8 TTGTAAAATCCTACTGT 0 0 20 55.3 N/A NM_025565 Spc25 TTGCCTGTATGAAATTG 0 0 20 55.3 N/A NM_026456 Tceb1 TCTTCTATGCATCTACA 0 0 19 52.535 N/A NM_007743 Col1a2 GTTCAAGTGACAATAAA 0 0 19 52.535 N/A NM_010545 Cd74 CTACTTCTATCACAAGG 0 0 19 52.535 N/A NM_011739 Ywhaq CAAAATACATTTATTTG 0 0 19 52.535 N/A NM_019791 Maged1 CACTATTTATATAGACT 0 0 19 52.535 N/A NM_152816 Dnm1l GTGCTGGAGGGGCTCGG 0 0 19 52.535 N/A NM_178873 Adck2 TGACTAGCGTGACTTGT 0 0 18 49.77 N/A NM_007694 Chgb TTGTCAGGTAGTTGTAA 0 0 18 49.77 N/A NM_008615 Me1 TGAAATGGTCAAAGAAT 0 0 18 49.77 N/A NM_009138 Ccl25 ATGACAAAGAAAAAGAC 0 0 18 49.77 N/A NM_009946 Cplx2 TCCCCCTTCCCTATGGG 0 0 18 49.77 N/A NM_010131 Emx1 ATCCTGGTAATGCACTT 0 0 18 49.77 N/A NM_013494 Cpe GCAATCAGACGTCATTT 0 0 18 49.77 N/A NM_013900 Mfi2 GAAGTGAATGTGGACGT 0 0 18 49.77 N/A NM_025772 Dtnbp1 TTCACGAATGTGGCTCT 0 0 18 49.77 N/A NM_026045 Prpf18 TTTAAGGATACAAGACA 0 0 18 49.77 N/A NM_026218 Fgfr1op2 AGTATGCGCCAACACAT 0 0 18 49.77 N/A NM_026609 Leprotl1 TTTGGTTTAATAGTGTA 0 0 18 49.77 N/A NM_028059 Zfp654 GAGACACAGTTTAGTCC 0 0 18 49.77 N/A NM_133809 Kmo  90 ATAGATTTTTTATTATT 0 0 18 49.77 N/A NM_177782 BC067047 AACGAACACATACTGGA 0 0 17 47.005 N/A NM_001013379 D10627 TTATGGATCTTACCTTT 0 0 17 47.005 N/A NM_001038990 Ids CTATCCTCTCACTCTGT 0 0 17 47.005 N/A NM_001083929 Gpx3 CAAATACCTTTGATACT 0 0 17 47.005 N/A NM_001111292 Caprin1 TCTCTCTATTCATTCTA 0 0 17 47.005 N/A NM_007784 Csn1s1 CACACACAAACACACAC 0 0 17 47.005 N/A NM_008121 Gja5 CTAGAAACTTTATGACA 0 0 17 47.005 N/A NM_009242 Sparc TTTGCACCTTTCTAGTT 0 0 17 47.005 N/A NM_010217 Ctgf GTTATGTGCCAACACCC 0 0 17 47.005 N/A NM_011485 Star GGGGGAAACACCTCAAG 0 0 17 47.005 N/A NM_018747 Akap7 GTCTCTGTTGAACATTT 0 0 17 47.005 N/A NM_023565 Cse1l GAGTTGAATGGAATGCC 0 0 17 47.005 N/A NM_025976 Bfar ATATTAAACTCTTGAGA 0 0 17 47.005 N/A NM_026936 Oxa1l CAAAGTTCCCACATCTC 0 0 17 47.005 N/A NM_029017 Mrpl47 GGAACCAACATCGGGGT 0 0 17 47.005 N/A NM_030087 1500032D16Rik CACGCCTTGTTTCCCCA 0 0 17 47.005 N/A NM_175028 Adnp2 TGTGTTTGTACGTATTT 0 0 17 47.005 N/A NM_201369 N4bp2l2 GCTCAAGGAATTGTGTG 0 0 16 44.24 N/A NM_001013391 Cpsf6 CCTATTAAAAACAAAAA 0 0 16 44.24 N/A NM_007606 Car3 GGGGACTGGAGATTTTT 0 0 16 44.24 N/A NM_008560 Mc2r GATAGAGAGTTTTGGAG 0 0 16 44.24 N/A NM_008721 Npdc1 GTGTCTGATAATGAGCC 0 0 16 44.24 N/A NM_009931 Col4a1 AAGCTGGAGGAGGGCAA 0 0 16 44.24 N/A NM_018749 Eif3d ACAGTGCCCCTGCGAAG 0 0 16 44.24 N/A NM_025548 Tbcb GCTGACTCTTGCCTGCT 0 0 16 44.24 N/A NM_026481 Tppp3 AATGACCTCCACTTCAG 0 0 16 44.24 N/A NM_172624 Dpp9 GCGGGCCTTTTACTGGG 0 0 16 44.24 N/A NM_197996 Tspan15 GATGACATTCTAGTGAA 0 0 15 41.475 N/A NM_001040611 Peg10 CTATCGAGATCTGAAGG 0 0 15 41.475 N/A NM_019750 Nat6 GAGTGAAATAGATGATT 0 0 15 41.475 N/A NM_023873 Cep70 GTCACATATAGGTCACA 0 0 15 41.475 N/A NM_026697 Rab14 TAAAAGTTGTTTGTTCT 0 0 15 41.475 N/A NM_134071 Ankrd32 TTCTGTGAATCTGCCAT 0 0 15 41.475 N/A NM_145575 Cald1 CCGAAGTGTCACAACTG 0 0 15 41.475 N/A NM_146090 Zadh2 CACTGAGGTGCCTCAGC 0 0 15 41.475 N/A NM_175143 Qrich1 ATCTTGCAATGTTGGGT 0 0 14 38.71 N/A NM_001081394 0610007L01Rik GTTTTGAGAAAAGCAAA 0 0 14 38.71 N/A NM_001111314 Ngef AAGTGTCGCCGCTTTGT 0 0 14 38.71 N/A NM_008117 Gh GTGTGCCAGCACCCTGA 0 0 14 38.71 N/A NM_010840 Mthfr GGGCATTTGAGGGTGGT 0 0 14 38.71 N/A NM_019779 Cyp11a1 ATGTAATGAAAACACAC 0 0 14 38.71 N/A NM_027379 Far1 TCTTTTTGGTGCTGTGC 0 0 14 38.71 N/A NM_027995 Paqr7 CCCCGGGCCTGCCCCCC 0 0 14 38.71 N/A NM_134002 Csnk1g2 TTTGAGAGGTTTTACCA 0 0 14 38.71 N/A NM_134063 BC016423  91 ACCCAGGAGATTCCCAG 0 0 14 38.71 N/A NM_138651 Cds2 AAAATAAAAATGTTACC 0 0 14 38.71 N/A NM_172775 Plxnb1 GATGGCAAGATCAAGCT 0 0 13 35.945 N/A NM_001013366 Wdr91 GGAGCTCACGCCCCTGT 0 0 13 35.945 N/A NM_001039089 Sel1l GCTATGGCCAGTCTCTC 0 0 13 35.945 N/A NM_007752 Cp GTTTGTCAGCCCACACT 0 0 13 35.945 N/A NM_008010 Fgfr3 GCCAGTTCTTTAAAGAA 0 0 13 35.945 N/A NM_008775 Pafah1b2 GCTTCGTCCAGACAGCG 0 0 13 35.945 N/A NM_010777 Mbp TGACGTAGCCCACGGAG 0 0 13 35.945 N/A NM_019661 Ykt6 AGGAAGAATTAGGTAGT 0 0 13 35.945 N/A NM_025866 Cdca7 TGAATCCATTCACAGGA 0 0 13 35.945 N/A NM_025882 Pole4 GTTCAGCTGTGGACCTG 0 0 13 35.945 N/A NM_027269 1110034A24Rik AAGAGCTGGAGTATTTA 0 0 13 35.945 N/A NM_028177 Ndufab1 TAATTCTAATTTTAAAT 0 0 13 35.945 N/A NM_028705 Herc3 GCTCTGACTGTTGTGGA 0 0 13 35.945 N/A NM_146142 Tdrd7 GAAATACCTTTTCTAGA 0 0 13 35.945 N/A NM_172424 Med13l CACGGCTACTTCCCAGG 0 0 12 33.18 N/A NM_001081214 Pprc1 GAGACTAACAGAACCGC 0 0 12 33.18 N/A NM_007496 Zfhx3 GATACAGTCGAGCTGCT 0 0 12 33.18 N/A NM_007520 Bach1 GTGAGATCATTATGGAC 0 0 12 33.18 N/A NM_007652 Cd59a GCTTAAGTGTTGAAAAT 0 0 12 33.18 N/A NM_007874 Reep5 GACAGTAATATATTTTG 0 0 12 33.18 N/A NM_008822 Pex7 TACTAGCCTTAATACAC 0 0 12 33.18 N/A NM_009874 Cdk7 ATTTAATGAAACTGGGT 0 0 12 33.18 N/A NM_011499 Strap AATTCGCGGATGTGGTT 0 0 12 33.18 N/A NM_013697 Ttr GCTGGGTTAGCAGGCCC 0 0 12 33.18 N/A NM_026472 Mki67ip CCATTACATTAAAATTA 0 0 12 33.18 N/A NM_026487 Atad1 AACACTGGGGCTTGGAT 0 0 12 33.18 N/A NM_172961 Abat GCTTAATGTATGGACGG 0 0 12 33.18 N/A NM_175752 Chn1 AAGCAGGAGAAGCAGTG 0 0 12 33.18 N/A NM_178874 Tmcc2 TGCAGTGCCTGTGGCCT 0 0 11 30.415 N/A NM_001030025 Upp1 ACAAACTCCTTTACATA 0 0 11 30.415 N/A NM_001081430 Nat12 GATCAATGGGAGAAGGG 0 0 11 30.415 N/A NM_001113325 Gria1 ACTGCTCTCTCTCCTTC 0 0 11 30.415 N/A NM_007590 Calm3 GACCTCATTCCTCTCTG 0 0 11 30.415 N/A NM_007933 Eno3 TTTCAAGAGTGCTAAGA 0 0 11 30.415 N/A NM_007998 Fech TCACTTTTAATATTACC 0 0 11 30.415 N/A NM_009163 Sgpl1 CATACTTCAAAAGTATT 0 0 11 30.415 N/A NM_009537 Yy1 TACACAATAATTTTTTT 0 0 11 30.415 N/A NM_010258 Gata6 GTCTGGGGGGAGGCAGG 0 0 11 30.415 N/A NM_011844 Mgll ATGTCGAAGACGAGCTT 0 0 11 30.415 N/A NM_013758 Add3 TGATTTTTGTTTCTCAA 0 0 11 30.415 N/A NM_023118 Dab2 CGGTCTAGTCCAGTTTT 0 0 11 30.415 N/A NM_025451 Camk2n1 TACAGCACAGATCCTGA 0 0 11 30.415 N/A NM_025569 Mgst3 TCTTAAAAACTCAGATG 0 0 11 30.415 N/A NM_027412 Ttc9c  92 ACTGCTTGCCCTAAGCA 0 0 11 30.415 N/A NM_145569 Mat2a TGATTTGTAAATGTACC 0 0 11 30.415 N/A NM_175194 Slc25a16 TGTGGGTCTGGGAATGA 0 0 11 30.415 N/A NM_178620 Mfsd11 ATGCGGTACAGGGCATT 0 0 10 27.65 N/A NM_001001326 St5 AAAGGATGTTAACCTTT 0 0 10 27.65 N/A NM_001004190 Zfp560 GACCACAGCCTTCTAAC 0 0 10 27.65 N/A NM_001102650 Nt5c3l ATGTTGCTGGCCAGATG 0 0 10 27.65 N/A NM_007408 Adfp CCAGCTGTCAACATTCA 0 0 10 27.65 N/A NM_008640 Laptm4a GGCGCTCGTACACCCCT 0 0 10 27.65 N/A NM_011520 Sdc3 GAATATGGAACTTTGTA 0 0 10 27.65 N/A NM_145546 Gtf2b CTTATATTTAAGGCTTA 0 0 9 24.885 N/A NM_001007580 Gm784 GGGTTCTTCCACTGAAA 0 0 9 24.885 N/A NM_008212 Hadh GTTAATAAACGTCGATG 0 0 9 24.885 N/A NM_009670 Ank3 TGATTTCGAGGTCCTTG 0 0 9 24.885 N/A NM_010276 Gem GGGGGCTGTGGTGTTCC 0 0 9 24.885 N/A NM_010890 Nedd4 GGTGAGAAAACAGGCCA 0 0 9 24.885 N/A NM_023305 Ubap1 TTATTTAAAGAGGAAGA 0 0 9 24.885 N/A NM_028108 Nat13 TCTGGACTTGTCCTGAG 0 0 9 24.885 N/A NM_029929 Vps33a GGACCCGGGCCAACTTC 0 0 9 24.885 N/A NM_144942 Csad TCTACATCTCCCTCCTA 0 0 9 24.885 N/A NM_148950 Pknox2 CAGACCTCAACCCCTTG 0 0 8 22.12 N/A NM_001039089 Sel1l CTGTGTGTCAATCCTCC 0 0 8 22.12 N/A NM_001110499 Canx ATGCAGTGGCGGGATGT 0 0 8 22.12 N/A NM_009258 Spink3 CAGCGGGAGCTGGGGCC 0 0 8 22.12 N/A NM_016801 Stx1a GCACTTGAAAGTGTATT 0 0 8 22.12 N/A NM_019759 Dpt CTCACTTAGTGTAAGCT 0 0 8 22.12 N/A NM_023865 9530002B09Rik TATACTGTGATATAAAA 0 0 8 22.12 N/A NM_030750 Sgpp1 ATCCCCCTCTGGGAGAG 0 0 8 22.12 N/A NM_133934 Isy1 GATTCTACAGTGGAGGA 0 0 7 19.355 N/A NM_001029895 Ate1 CCTCCTCCAGGAATGAG 0 0 7 19.355 N/A NM_001082961 Snrpn CCTGAACTTTAAGAAAT 0 0 7 19.355 N/A NM_008083 Gap43 TAGAAGCCTAGCCTTTT 0 0 7 19.355 N/A NM_008630 Mt2 GCCTATCCAAATCTCGT 0 0 7 19.355 N/A NM_008784 Igbp1 TGTTCATCTTGTTTTAA 0 0 7 19.355 N/A NM_009930 Col3a1 GGTGACCACACCCCAAC 0 0 7 19.355 N/A NM_013459 Cfd TGAAGTAAGGAGCCTGT 0 0 7 19.355 N/A NM_013677 Surf1 TCCCATCAGTTGGAATT 0 0 7 19.355 N/A NM_020586 Herpud2 CGGAGCGACCACCTGAC 0 0 7 19.355 N/A NM_021366 Klf13 GGTAAGAATAGTCCATT 0 0 7 19.355 N/A NM_025586 Rpl15 GTGGACTCACAAGGGTG 0 0 7 19.355 N/A NM_029645 Gatc AGGCCAAGAAGTATGCT 0 0 7 19.355 N/A NM_030559 Vps16 GCACAGTATCACATCTG 0 0 7 19.355 N/A NM_080855 Zcchc14 TAATGTGAAACTCCTCC 0 0 7 19.355 N/A NM_133945 Vrk3 TAAGAGGTGCCAGTCCC 0 0 7 19.355 N/A NM_152915 Dner AACAAGAGGAAATTTTT 0 0 7 19.355 N/A NM_172664 Tlk1  93 CTCCTGTCTTGATGATA 0 0 7 19.355 N/A NM_176842 Tprkb TGTAGAAACCATTTTGG 0 0 7 19.355 N/A NM_177798 Frs2 GGTCTTCAGAGTTATAG 0 0 6 16.59 N/A NM_007984 Fscn1 TCAGAGACCCGGCCACT 0 0 6 16.59 N/A NM_008091 Gata3 TATCCTCCTGATTATTG 0 0 6 16.59 N/A NM_009418 Tpp2 GCATAGTAACTGGAAAT 0 0 6 16.59 N/A NM_009706 Arhgap5 CCTCCCCCTCCCCCAGG 0 0 6 16.59 N/A NM_013651 Sf3a2 TCCCAATTAGGGAAGAA 0 0 6 16.59 N/A NM_133818 AI597479 GAACCCAACAAGCAGAA 0 0 6 16.59 N/A NM_133953 Sf3b3 CCTCTTGAGCAGCTTTC 0 0 5 13.825 N/A NM_001081213 Ermp1 AATGACCTGGTGTCTGA 0 0 5 13.825 N/A NM_009450 Tubb2a TCTTCTCCACTTGGTAC 0 0 5 13.825 N/A NM_013842 Xbp1 TATTCTTCATAATGGAG 0 0 5 13.825 N/A NM_013918 Usp25 GAGACGGTGCTGGTCCT 0 0 5 13.825 N/A NM_022004 Fxyd6 TGACTGAGGTCAGTCAG 0 0 5 13.825 N/A NM_025291 Sra1 ACAGCAGGAGACTTTCA 0 0 5 13.825 N/A NM_026120 2410127L17Rik TTGGGAGGCAAGCATCT 0 0 5 13.825 N/A NM_026176 Pdcl TTCTCAGAACTTCTTAG 0 0 5 13.825 N/A NM_026386 Snx2 TAGGCCAGGCTGGCCTT 0 0 5 13.825 N/A NM_027222 2010001M09Rik GGAAACAGCTGAGTACT 0 0 5 13.825 N/A NM_029094 Pik3cb ACATTTACAGAGCACGG 0 0 5 13.825 N/A NM_145529 Cstf3 TTACTGCAATGTCAGTG 0 0 5 13.825 N/A NM_173369 Cyld CACAGGCCTGCAATCTG 0 0 5 13.825 N/A NM_177151 Vps13b GGCTCAGGACAAGCCCT 0 0 4 11.06 N/A NM_001001565 Chpf CTGGGCATCTTAGTTAA 0 0 4 11.06 N/A NM_001039201 Hdhd2 CAGCAACCTTGATTTAA 0 0 4 11.06 N/A NM_001081049 Mll1 TAAATACTATATCTCAG 0 0 4 11.06 N/A NM_008341 Igfbp1 CTCTTATTTTCCTTAAC 0 0 4 11.06 N/A NM_008783 Pbx1 GTGACCTGGCCTCAGGA 0 0 4 11.06 N/A NM_008963 Ptgds GATGTGTGGGGAATCCA 0 0 4 11.06 N/A NM_009533 Xrcc5 GTGGAAGAAGGTGAGGA 0 0 4 11.06 N/A NM_009702 Aqr AAAAAGTGAATATCATC 0 0 4 11.06 N/A NM_009859 Sept7 ACAGAAAAAAACAAAAC 0 0 4 11.06 N/A NM_010136 Eomes CACTAGGGGTAGCTTAG 0 0 4 11.06 N/A NM_010193 Fem1b GAAGAACCAAGTTTTTC 0 0 4 11.06 N/A NM_011767 Zfr CTCTTTCCTCCTTCCCC 0 0 4 11.06 N/A NM_021395 Hyou1 TGAAGAGGAAATAGCTG 0 0 4 11.06 N/A NM_025441 Sdccag1 CTGCCTGAAGACTCTTC 0 0 4 11.06 N/A NM_028262 Setd3 TGTAACAAATGCCAGCC 0 0 4 11.06 N/A NM_130450 Elovl6 CTGCTGCAGCCTTTTAA 0 0 4 11.06 N/A NM_145625 Eif4b TTTTAATTTTATACAAT 0 0 4 11.06 N/A NM_148926 Zfand3 AAAATTGAATAGGAAAT 0 0 4 11.06 N/A NM_173739 Galntl4 GCTTCATCTATTTGGAT 0 0 4 11.06 N/A NM_175313 A130022J15Rik TCCCAGGCCAAGGAGCT 0 0 4 11.06 N/A NM_178622 Suds3 GGCACAAGACTTGTAGT 1 0.622 54 149.31 240.08 NM_001077529 Nme2  94 GGCTTCCGCGAGGGTAC 1 0.622 54 149.31 240.08 NM_010784 Mdk GTTTTGTATATTTATTC 1 0.622 50 138.25 222.29 NM_145943 BC031781 CCACACAAGCGTTTATT 1 0.622 48 132.72 213.4 NM_021540 Rnf130 GAGATAATTTCTGGCAT 1 0.622 47 129.955 208.96 NM_152816 Dnm1l TACTGGGAGCTGTAATG 1 0.622 46 127.19 204.51 NM_007801 Ctsh ACTGGCTGGGCCTGCTG 1 0.622 46 127.19 204.51 NM_008910 Ppm1a AAGAATACAAGATAAGG 1 0.622 36 99.54 160.05 NM_001099637 Cep170 CTACCAAAACTGACTTA 1 0.622 36 99.54 160.05 NM_023248 Sbds GCATCCTGTTAAAAAAA 1 0.622 35 96.775 155.61 NM_009433 Tspyl1 TGTGGGAACCACAGCGC 1 0.622 35 96.775 155.61 NM_133716 Smap2 CAGAATGCTGTTATTCT 1 0.622 35 96.775 155.61 NM_133718 Tmem30a TCTGGAACAAGCAGTAT 1 0.622 33 91.245 146.71 NM_011956 Nubp2 TAACACCAACCCCAGTT 1 0.622 33 91.245 146.71 NM_028152 Mms19 TAAGAAACCACTAGAAG 1 0.622 32 88.48 142.27 NM_008231 Hdgf GGTGTGGCAGTGGGCAG 1 0.622 32 88.48 142.27 NM_145409 Chtf18 TCTTTTTTAGGTTGACC 1 0.622 31 85.715 137.82 NM_007516 Hnrnpd CAGCTCTGCCTCCGCAG 1 0.622 31 85.715 137.82 NM_022029 Nrgn CCCAGCTTTCTTTTCAG 1 0.622 30 82.95 133.38 NM_053102 Sep15 GAGGGGGAGCCGCTGCC 1 0.622 30 82.95 133.38 NM_139229 Cog8 CCAAGTCAGGCCTGTAG 1 0.622 30 82.95 133.38 NM_182990 Ssrp1 GTCTCTACTGCATTTTC 1 0.622 29 80.185 128.93 NM_009054 Trim27 TAAATATAAGCCTTACT 1 0.622 29 80.185 128.93 NM_009270 Sqle TGTATAAAAATAAAAAA 1 0.622 29 80.185 128.93 NM_011631 Hsp90b1 ACTGGAATGACAAAGAG 1 0.622 29 80.185 128.93 NM_025942 Ola1 CCCTACTTCATCCTTTG 2 1.244 55 152.075 122.26 NR_001592 H19 GTAGCAGTTTGGGCCTT 1 0.622 27 74.655 120.04 NM_025292 Synj2bp TGATGACCGAACCCCCA 1 0.622 27 74.655 120.04 NM_026307 Cuta GGCTTAAGTAGGAAAGT 1 0.622 26 71.89 115.59 NM_010730 Anxa1 CTATGACCTGGCTATCC 1 0.622 26 71.89 115.59 NM_011708 Vwf GCCCAGACTGGCCCAGA 1 0.622 26 71.89 115.59 NM_011743 Zfp106 CAGCTGCACCACAGCAA 1 0.622 26 71.89 115.59 NM_013671 Sod2 GCTCCTCCCACTGTGTC 1 0.622 26 71.89 115.59 NM_021493 4933428G20Rik GTTGGGAGCTGTGAGGT 1 0.622 25 69.125 111.15 NM_009305 Syp GGAGGCTTTTCCCTAAG 1 0.622 25 69.125 111.15 NM_015735 Ddb1 ATTAGTTACCCTACACT 1 0.622 25 69.125 111.15 NM_015762 Txnrd1 ACCACCAGATGCCCACC 1 0.622 25 69.125 111.15 NM_027196 Pold4 GCACTAGCTGGGTGAGT 1 0.622 24 66.36 106.7 NM_016783 Pgrmc1 TGTAGCCTCATCCCCCT 1 0.622 23 63.595 102.26 NM_007503 Fxyd2 AGACAAAGTTTAGGAAA 1 0.622 23 63.595 102.26 NM_008300 Hspa4 ATAAGGGATTGGGTTCC 1 0.622 23 63.595 102.26 NM_016752 Slc35b1 ACGCTATGGATTCCTAC 1 0.622 23 63.595 102.26 NM_178112 Ints8 GCCTCCCCTGGTTAGCA 1 0.622 22 60.83 97.81 NM_025400 Nat9 AGTATCTGATGTTTTCA 1 0.622 22 60.83 97.81 NM_025901 Polr3k GAGAACACACCTGTTAT 1 0.622 22 60.83 97.81 NM_027453 Btf3l4 CCTGATGGTAGACATCG 1 0.622 20 55.3 88.92 NM_013898 Timm8a1  95 TGACCGCCCAGTTTGGA 1 0.622 20 55.3 88.92 NM_027189 Gemin7 AATACACAAGTGTTGCC 1 0.622 20 55.3 88.92 NM_028148 Sfrs2ip CCAATCTTTGAATGTAA 1 0.622 19 52.535 84.47 NM_001110251 Hmbs AAATATACAGTGTTTGG 1 0.622 19 52.535 84.47 NM_027374 Ppil3 ACTGTAGATGAGGATAG 4 2.488 75 207.375 83.36 NM_019411 Ppp2ca AACCCCTTTGAGTCTTG 2 1.244 37 102.305 82.25 NM_010192 Fem1a ACAGCCCACCCCCCAGC 1 0.622 18 49.77 80.03 NM_009721 Atp1b1 TGCCGTTTTGAGGCTTT 1 0.622 18 49.77 80.03 NM_010360 Gstm5 CTGGGCCCAGACCTTTG 1 0.622 18 49.77 80.03 NM_011116 Pld3 GTAGTGGAGCCCTTAAA 1 0.622 18 49.77 80.03 NM_022417 Itm2c TGCACCCTGCCCTGGAG 1 0.622 18 49.77 80.03 NM_025397 Med11 CTGCGCTCTTTGTCTAC 1 0.622 18 49.77 80.03 NM_145135 Rnh1 AGTTATTTTGATTGAGA 1 0.622 17 47.005 75.58 NM_001039522 Leo1 TCAGGAAGAGCAACCGG 1 0.622 17 47.005 75.58 NM_001042408 Txnl4a TTTTTTGTGTGTCAATT 1 0.622 17 47.005 75.58 NM_016891 Ppp2r1a AAGGTTTATCATCTTGA 1 0.622 17 47.005 75.58 NM_025547 Mterfd1 ATTTGATTAGCCCCAAA 1 0.622 17 47.005 75.58 NM_025596 Prelid1 GGTCCTTGCTGATCCCT 1 0.622 17 47.005 75.58 NM_027353 Cd2bp2 TAGCTGTAACGGGGGGC 1 0.622 17 47.005 75.58 NM_144900 Atp1a1 GTGATGCGGAGCCACTG 1 0.622 17 47.005 75.58 NM_153791 Flywch1 ACTTTAATCCCAGCACT 2 1.244 33 91.245 73.36 NM_001012200 Ttll1 CATTTTCTGGCAAAATC 1 0.622 16 44.24 71.13 NM_001122737 Igf2 CCTTACCGCTGTAATGG 1 0.622 16 44.24 71.13 NM_175692 A930034L06Rik CACCAGGCTGGCCACTA 2 1.244 31 85.715 68.91 NM_144826 Utp6 GATTTCTTTGACAAAAA 1 0.622 15 41.475 66.69 NM_016697 Gpc3 TGTAACTGGTCACAAGG 1 0.622 15 41.475 66.69 NM_024457 Rap1b CACATTAACTCTTTACT 1 0.622 15 41.475 66.69 NM_028136 Dhx36 TTGGTTATTTTACCCCT 2 1.244 29 80.185 64.47 NM_010690 Lats1 GAATGTCAAGGTAGAGG 2 1.244 29 80.185 64.47 NM_018753 Ywhab AATGTTTGTAACACTGA 2 1.244 28 77.42 62.24 NM_001014995 1110013L07Rik CATTTAAAATGAGATGG 1 0.622 14 38.71 62.24 NM_028234 Prr8 AAGAAGTCATCAGTCAC 1 0.622 14 38.71 62.24 NM_133232 Pfkfb3 TTGTTAGTGCTGCAATC 4 2.488 53 146.545 58.91 NM_008618 Mdh1 ACATTCTGCAATATTTT 2 1.244 26 71.89 57.8 NM_026386 Snx2 TTTCCTTCCTCCTGTCA 1 0.622 13 35.945 57.8 NM_009516 Wee1 GAGGAGCTGAGCAGCCA 1 0.622 13 35.945 57.8 NM_026382 6530403A03Rik GTCAATTCAGAAAAGTC 3 1.866 36 99.54 53.35 NM_022309 Cbfb AATTTCTCCTGCAGGAG 2 1.244 24 66.36 53.35 NM_177298 Pisd GCGCTGGCCGCCCGTCT 1 0.622 12 33.18 53.35 NM_001081181 9430016H08Rik CACCAGTGAGCTGGCTA 1 0.622 12 33.18 53.35 NM_001107959 Atpaf1 CCTTTGGCAATTGCTCA 3 1.866 35 96.775 51.87 NM_011187 Psmb7 ACCTTTACTGTGTTAGC 2 1.244 23 63.595 51.13 NM_011638 Tfrc CTTCGGATGTCTTGGAG 3 1.866 34 94.01 50.39 NM_025287 Spop GTTTGCTGTGTGACCGA 4 2.488 45 124.425 50.02 NM_007798 Ctsb GAGGTCCTAGCCTTTCC 3 1.866 33 91.245 48.9 NM_009058 Ralgds  96 ATAGCTGGGCTTCAGTC 2 1.244 22 60.83 48.9 NM_008927 Map2k1 CTCCCCCTAGCCCAGGC 2 1.244 22 60.83 48.9 NM_145417 Rnpep TGTTTGTACATTTTTGT 1 0.622 11 30.415 48.9 NM_019835 B4galt5 TCTGCGTCCTAGCATAA 1 0.622 11 30.415 48.9 NM_021535 Smu1 ACACTGTGTGCGGTTCC 1 0.622 11 30.415 48.9 NM_023232 Diablo AAGCCACAGAACCAAGC 1 0.622 11 30.415 48.9 NM_145925 Pttg1ip CAAGTGCACTCAGCTTG 8 4.975 84 232.26 46.68 NM_026160 Map1lc3b CTACTGAACACAGGAAC 2 1.244 21 58.065 46.68 NM_177680 Ythdc1 GTGACAAAAAACCAGGG 3 1.866 31 85.715 45.94 NM_019996 Rnuxa AAAGCTCTATGTAAAGG 3 1.866 31 85.715 45.94 NM_183308 Pon2 ACCTTGCCCTCCATAGG 5 3.11 51 141.015 45.35 NM_025448 Ssr2 TGACCGAGGACATAAGG 3 1.866 30 82.95 44.46 NM_028250 Acbd6 CTATTAAATAGGTTTTT 3 1.866 30 82.95 44.46 NM_145422 D10Wsu52e TGATGTATATTAAACTT 2 1.244 20 55.3 44.46 NM_008321 Id3 GATTTTGTATGTTCCTC 2 1.244 20 55.3 44.46 NM_016755 Atp5j ACTTCAGACTCCTTATT 2 1.244 20 55.3 44.46 NM_178142 Lcorl AGCCACGGGGGCTGGCT 1 0.622 10 27.65 44.46 NM_011565 Tead2 GGAAACAGTGGTTGTTT 1 0.622 10 27.65 44.46 NM_013915 Zfp238 CCATAAAAGACCGATCC 1 0.622 10 27.65 44.46 NM_019806 Vapb TGAATAAACTACTTGAT 1 0.622 10 27.65 44.46 NM_019975 Hacl1 CAGGGTGATGGTGAAGA 3 1.866 29 80.185 42.98 NM_009536 Ywhae GGGGCTCACAACCATCT 5 3.11 48 132.72 42.68 NR_001463 Xist ATCCGGGCTTTACGAAT 2 1.244 19 52.535 42.24 NM_008845 Pip4k2a GGAGAGGGTATCCGGTT 2 1.244 19 52.535 42.24 NM_011739 Ywhaq ATTTTAATAACACTTTT 4 2.488 37 102.305 41.12 NM_027494 Zcchc8 TAACTTGTAGCTATAAA 4 2.488 36 99.54 40.01 NM_009761 Bnip3l TTATTAAAATAGTGATG 3 1.866 27 74.655 40.01 NM_011692 Vbp1 AGGCCCAGGGTGCTGAC 2 1.244 18 49.77 40.01 NM_013895 Timm13 TGAATGGCCTAGAGAAC 2 1.244 18 49.77 40.01 NM_027117 Klhdc2 GTGGCACACGCCTTTAG 1 0.622 9 24.885 40.01 NM_006989 RASA4 TGCAGAGAAAAGCCTCC 1 0.622 9 24.885 40.01 NM_007483 Rhob GTGTATGACATCACCAG 1 0.622 9 24.885 40.01 NM_026697 Rab14 CACAAGGCTACCAAGCT 1 0.622 9 24.885 40.01 NM_026752 Zfyve21 TAGCAGTATGCTCATTT 1 0.622 9 24.885 40.01 NM_146075 Lemd2 GAGACTAGCAAAATAGT 6 3.732 52 143.78 38.53 NM_019793 Tspan3 ATCACAGGTGATTCACA 3 1.866 26 71.89 38.53 NM_001108393 Zmiz1 GGAGGGGGGAACAAGTC 6 3.732 51 141.015 37.79 NM_022325 Ctsz TGCAATATTTCTTACTG 2 1.244 17 47.005 37.79 NM_001110131 Cic GCATAGAACATAGCATT 2 1.244 17 47.005 37.79 NM_153762 Rnf26 CTAACAGAATCCAGGCC 3 1.866 25 69.125 37.05 NM_153792 Traf7 AAGAAAAAGTGATGACA 3 1.866 24 66.36 35.57 NM_023735 Actr3 ATTGAGCGGCCAGAGCC 2 1.244 16 44.24 35.57 NM_019745 Pdcd10 CTCCTGTACTCCTCGGA 2 1.244 16 44.24 35.57 NM_133949 Ptov1 AAAATGTATCACGTGTT 2 1.244 16 44.24 35.57 NM_144545 Eif3j ATCTAGAGTTTGTTTTC 2 1.244 16 44.24 35.57 NM_144833 Zfp410  97 GATTAGAAGAACAAGGA 1 0.622 8 22.12 35.57 NM_001127346 Ndufaf2 AGCAGGTTTTCTTTAAG 1 0.622 8 22.12 35.57 NM_007589 Calm2 GAACCCATCAAAGTTCT 1 0.622 8 22.12 35.57 NM_019734 Asah1 TGCTGGCTGCAGGCTTC 1 0.622 8 22.12 35.57 NM_134011 Tbrg4 AGAAGGACCTCGGAGGC 4 2.488 31 85.715 34.46 NM_011400 Slc2a1 GATATCATCAACCTCTT 4 2.488 31 85.715 34.46 NM_026617 Tmbim4 TGCAGGAGCTGGCGGGC 5 3.11 38 105.07 33.79 NM_145979 Chd4 CCGTGCAGCAGAAGCCC 2 1.244 15 41.475 33.34 NM_011512 Surf4 ATAGCACAGTGGACTTT 2 1.244 15 41.475 33.34 NM_025391 Nip7 GCCTATCCAAGAGGAAA 3 1.866 22 60.83 32.6 NM_026388 Tprgl CCAGACTGATCACCGGG 3 1.866 22 60.83 32.6 NM_175287 A430005L14Rik AATGTGAGTCATTATGT 11 6.841 78 215.67 31.53 NM_018871 Ywhag CAGTTATAAAAATCAGC 4 2.488 28 77.42 31.12 NM_008410 Itm2b CCGAATATTCCAGCAGC 4 2.488 28 77.42 31.12 NM_011370 Cyfip1 GAAACGCAGAGACCAAG 3 1.866 21 58.065 31.12 NM_001037878 Tcf25 GCCCAGCCTTGAGTGGA 3 1.866 21 58.065 31.12 NM_001115132 Ncaph2 GGCAATAATGGGAGCTG 3 1.866 21 58.065 31.12 NM_010497 Idh1 TCTGTAGCCCAGTGCCC 3 1.866 21 58.065 31.12 NM_031134 Thra GTGGCTCACAAACATCT 3 1.866 21 58.065 31.12 NM_153159 Zc3h12a TGAACTGGTGTGACCAA 2 1.244 14 38.71 31.12 NM_001033379 Dcp1b CTGTATATTCAGATGGA 2 1.244 14 38.71 31.12 NM_001033634 Zyg11b ATTGCCTACGATGCCCT 1 0.622 7 19.355 31.12 NM_007414 Adprh TATACGGTTCAGAGTGA 1 0.622 7 19.355 31.12 NM_010615 Kif11 AAACAGAAGTCTGAGAT 1 0.622 7 19.355 31.12 NM_027604 Usp15 GGGGGCCCAGGTGTCCT 5 3.11 35 96.775 31.12 NM_145135 Rnh1 AGCATTGGCGGTTCGTG 4 2.488 27 74.655 30.01 NM_011650 Tsn GGGAGCGGGCAGAGTTG 7 4.353 47 129.955 29.85 NM_134101 Psmd2 CCCGGGTACAAGTGCAG 4 2.488 26 71.89 28.9 NM_011876 Twf2 TGGACTGTTTTCTGAGC 2 1.244 13 35.945 28.9 NM_008014 Ppm1g CCCTATGTTTGTGCCTT 2 1.244 13 35.945 28.9 NM_016686 Vezf1 CCCCCCGTCAGTCATCT 5 3.11 30 82.95 26.68 NM_029565 Tmem59 GTGTTTTAAAGCTAAAT 3 1.866 18 49.77 26.68 NM_009775 Tspo GTTAGAGACTAACTGGA 2 1.244 12 33.18 26.68 NM_011650 Tsn TGAGTTCCCTTTAAATA 2 1.244 12 33.18 26.68 NM_027769 Cpne3 GGTGACTGTTCTCTGTC 2 1.244 12 33.18 26.68 NM_172424 Med13l AAGAAAAAAAAAAAAAA 1 0.622 6 16.59 26.68 NM_006206 PDGFRA GCTTGACATAGAGGGTT 1 0.622 6 16.59 26.68 NM_153194 Zfp740 AGAGCAGAGAAGCAGCT 1 0.622 6 16.59 26.68 NM_172661 5830434P21Rik TGAACTTATTATGAAGG 1 0.622 6 16.59 26.68 NM_172920 Dpy19l1 TTCAAGTCTTCCAGTTA 6 3.732 34 94.01 25.19 NM_178218 Hist3h2a TATGCCCATTTTTTCAA 3 1.866 17 47.005 25.19 NM_013771 Yme1l1 AAGAGAAGGTGGCTGCA 3 1.866 17 47.005 25.19 NM_026819 Dhrs1 TGTGAATGATTTAAAAA 5 3.11 28 77.42 24.9 NM_029409 Mff CTGGGGTGCGCGCGACC 6 3.732 33 91.245 24.45 NM_174987 1810063B05Rik ATGCAACTACTAATAAA 9 5.597 49 135.485 24.21 NM_025628 Cox6b1  98 GCCCAGGTTTATTAAAG 5 3.11 27 74.655 24.01 NM_011341 Sdf4 GAGCGCAGTGAGCTGGC 5 3.11 27 74.655 24.01 NM_053193 Cpsf1 TTGATGCCATTTCCCTT 3 1.866 16 44.24 23.71 NM_010064 Dync1i2 AAATAGACATTTCCCCC 3 1.866 16 44.24 23.71 NM_020003 0610031J06Rik TCTGTCCCGCCAGGCCC 5 3.11 26 71.89 23.12 NM_016852 Wbp2 TGCCCAGGACTTACGCG 7 4.353 35 96.775 22.23 NM_019566 Rhog AATGAAATAAAGATTTG 6 3.732 30 82.95 22.23 NM_133726 St13 ATTCTTTATAAGTGTTA 4 2.488 20 55.3 22.23 NM_009861 Cdc42 GCGACAGAGGTGGCAGA 4 2.488 20 55.3 22.23 NM_194068 D12Ertd647e TTGAACACTTTATGATG 4 2.488 20 55.3 22.23 NR_001592 H19 ATGCAGACTTCAGGATG 3 1.866 15 41.475 22.23 NM_026444 Cs GATATCTGAAGCCTTGT 2 1.244 10 27.65 22.23 NM_011981 Zfp260 AAATTGGACACACCAGC 2 1.244 10 27.65 22.23 NM_016698 Rnf10 AGTTCTTTTTGGGAAAG 2 1.244 10 27.65 22.23 NM_024179 0610009O20Rik CAAGGTGAACCTGAGGG 1 0.622 5 13.825 22.23 NM_010411 Hdac3 TTGACGACTCCTCCAGA 1 0.622 5 13.825 22.23 NM_010724 Psmb8 ATATTGAAGAAAAGTGC 1 0.622 5 13.825 22.23 NM_011899 Srp54a ACCTGCTCACAGTGCTG 1 0.622 5 13.825 22.23 NM_026373 Cdk2ap2 AATAAACTCAGCATATT 1 0.622 5 13.825 22.23 NM_029271 Mrpl32 TGGAAAAAAAAAAAAAA 1 0.622 5 13.825 22.23 NM_152894 Pop1 CCCCCACCCCAACCCTT 1 0.622 5 13.825 22.23 NM_198862 Nlgn2 GCCGGAGGTTCCTGGCT 5 3.11 25 69.125 22.23 NM_001082532 Pigyl CCATTGATCAAGGGTCG 10 6.219 49 135.485 21.78 NM_025947 Dynlrb1 AAGAGAAGAGTGGGGGA 6 3.732 29 80.185 21.49 NM_001130150 Arhgef1 TAAGGAACAAATGACTA 4 2.488 19 52.535 21.12 NM_024206 Sec13 GGGCAGCTGGCACACTC 3 1.866 14 38.71 20.75 NM_133918 Emilin1 GTTAAATAAAGGGTTCT 7 4.353 32 88.48 20.32 NM_024174 Mrps23 CAGGAGCGGACTTTGCT 8 4.975 36 99.54 20.01 NM_007917 Eif4e ACAAACTTAGGAGAAAA 8 4.975 36 99.54 20.01 NM_009790 Calm1 AGGAAGTCCCAAGGTTC 4 2.488 18 49.77 20.01 NM_022994 Dap3 GGGATTTCTAGTGATGG 4 2.488 18 49.77 20.01 NM_133954 AA960436 TGTACCCAGGGGTGGCT 2 1.244 9 24.885 20.01 NM_008060 Ganab TGTGCCTGCATCTGCCC 2 1.244 9 24.885 20.01 NM_025300 Mrpl15 GAGTAATACAAACTGAA 5 3.11 22 60.83 19.56 NM_177470 Acaa2 TTGGTGAAGGAAAAAGC 23 14.304 100 276.5 19.33 NM_021278 Tmsb4x CGGGTCATATATTGGAG 6 3.732 26 71.89 19.27 NM_011185 Psmb1 TTAATGAGGTGGGTCTG 3 1.866 13 35.945 19.27 NM_009037 Rcn1 CAGCTGAAAACCCTGGG 3 1.866 13 35.945 19.27 NM_016805 Hnrnpu CATACGCTCACAAAAGA 3 1.866 13 35.945 19.27 NM_133933 Rpn1 GGGTGTCCCAGTGTATA 4 2.488 17 47.005 18.9 NM_016772 Ech1 AACCTCGCTGGGTGTTC 9 5.597 36 99.54 17.78 NM_153526 Insig1 ATCTGACTCCCTCTTCT 8 4.975 32 88.48 17.78 NM_026701 Pbld ATCGTGGCTGCTATCCA 6 3.732 24 66.36 17.78 NM_008197 H1f0 ACTTCAGCCAGATTAGC 5 3.11 20 55.3 17.78 NM_009342 Dynlt1 ATCTATTCTTGCAGTTT 5 3.11 20 55.3 17.78 NM_198304 Nup188  99 TACTCTCCTTTCACTGT 4 2.488 16 44.24 17.78 NM_009773 Bub1b ATCCGCACCCTTGCTTC 3 1.866 12 33.18 17.78 NM_007590 Calm3 GGCACACAGCTCATAGG 3 1.866 12 33.18 17.78 NM_024174 Mrps23 CGATCCCCTTCCTACCT 3 1.866 12 33.18 17.78 NM_024256 B3gat3 CCTCAGGGATCCTTGGC 3 1.866 12 33.18 17.78 NM_025895 Med28 GGTGGGACACATTAAAA 3 1.866 12 33.18 17.78 NM_026775 Tmed10 GTGGCTCACATCCATCT 2 1.244 8 22.12 17.78 NM_023045 Xpo7 GATGCTTACGGTTTACC 2 1.244 8 22.12 17.78 NM_025849 3110001D03Rik GCTACAGGTAGAACTGG 2 1.244 8 22.12 17.78 NM_028862 Rnf145 CCCTGCACAGATCTCAC 7 4.353 27 74.655 17.15 NM_019953 Cnpy2 ATCTCAAACCTAAAGGG 6 3.732 23 63.595 17.04 NM_026851 Mrpl52 TGGTTTTGGGTGTTTTT 5 3.11 19 52.535 16.89 NM_011942 Lypla2 TAATAGTAACTTGGACT 7 4.353 26 71.89 16.51 NM_007747 Cox5a CAGCGCGCCCTTCAGGA 3 1.866 11 30.415 16.3 NM_001033458 Gm1673 CTCCTGCAGCTGAATCG 3 1.866 11 30.415 16.3 NM_016903 Esd GCAAGGTCAGTGTGGAG 9 5.597 33 91.245 16.3 NM_013536 Emg1 ACCCAGGCTGGAGTAGA 10 6.219 36 99.54 16.01 NM_024219 Hsbp1 GACTGGAGACCTGGCAG 6 3.732 21 58.065 15.56 NM_001033136 1200015F23Rik TCCCTCCTTAGCCTAAG 4 2.488 14 38.71 15.56 NM_013477 Atp6v0d1 TGGACATTTGTAATATC 2 1.244 7 19.355 15.56 NM_001080926 Lrp8 ACAATATGTATCGAAAG 2 1.244 7 19.355 15.56 NM_010926 Cox4nb GACTGCTGGCCTGCTCT 2 1.244 7 19.355 15.56 NM_021356 Gab1 AATGTTAACAAGTACAG 2 1.244 7 19.355 15.56 NM_178647 Cggbp1 GCTGCTGCCAGAACTGG 2 1.244 7 19.355 15.56 NM_201364 BC055324 CTGAGCTGTGGCCAAGG 7 4.353 24 66.36 15.24 NM_009045 Rela CTCATTTCCTAAAAGAT 5 3.11 17 47.005 15.12 NM_001113564 Serbp1 CTCAACAGCAACATCAA 11 6.841 37 102.305 14.95 NM_025344 Eif3f TTTTCTGCTGGGTGGGA 7 4.353 23 63.595 14.61 NM_146036 Ahsa1 CGGATAACCAGTGGTCC 11 6.841 35 96.775 14.15 NM_011119 Pa2g4 GGGAGCGAAAACGTTAA 7 4.353 22 60.83 13.97 NM_010496 Id2 GCCTTCTCAGGCCTGGC 9 5.597 28 77.42 13.83 NM_025567 Cyc1 GCCTTTATGAGAAGAAA 29 18.036 87 240.555 13.34 NM_207634 Rps24 TTAATATTTAACTAGAG 13 8.085 39 107.835 13.34 NM_025987 Ndufa6 CTGCTGGTGGCTCTGGC 10 6.219 30 82.95 13.34 NM_010261 Rabac1 CGCCTGCAGGGTGTAGC 6 3.732 18 49.77 13.34 NM_009422 Traf2 CGCCTGTACTATGTTTG 4 2.488 12 33.18 13.34 NM_027259 Polr2i TGCTTTTTTCTGTAAAT 3 1.866 9 24.885 13.34 NM_008048 Igfbp7 GCGACAGCCACTCTCAG 3 1.866 9 24.885 13.34 NM_011293 Polr2j ATCCTCGCTGAACGGCA 3 1.866 9 24.885 13.34 NM_023260 Mrps34 GGCTATGCCAAAATTAA 3 1.866 9 24.885 13.34 NM_026313 3300001P08Rik AAGGTCTTTAATTTTTT 2 1.244 6 16.59 13.34 NM_007788 Csnk2a1 ATGGGAAACTCAGAATC 2 1.244 6 16.59 13.34 NM_025662 Pigk AGCAAAATATGGCGAAA 2 1.244 6 16.59 13.34 NM_145380 Eif3m TCTTCTTTGGTTCTGGG 10 6.219 29 80.185 12.89 NM_010227 Flna AATCCTGTGGAGCATCC 36 22.389 103 284.795 12.72 NM_012053 Rpl8  100 GAGGACTGCCACCCCTC 16 9.951 45 124.425 12.5 NM_008529 Ly6e CAATGAATTGCTAAACC 5 3.11 14 38.71 12.45 NM_001130169 Zfp207 TGCTTTTACAATAAATG 5 3.11 14 38.71 12.45 NM_019870 Ard1a TAGACCAGACCAGCTCT 9 5.597 25 69.125 12.35 NM_019802 Ggcx GCCTAGAACTATGTAGC 9 5.597 25 69.125 12.35 NM_026774 Hbxip AAGCACTGGTTTAAGCC 9 5.597 25 69.125 12.35 NM_134093 Letmd1 CAGCCAGTGTATCAGCC 13 8.085 36 99.54 12.31 NM_026155 Ssr3 GTTCTGATCCTCCTCCT 11 6.841 30 82.95 12.13 NM_001082548 Spint2 GACTGAATCTGCTTGTT 10 6.219 27 74.655 12 NM_133668 Slc25a3 GCTGCCAGGGGCAACTA 6 3.732 16 44.24 11.86 NM_009736 Bag1 ATGCTAAAAAAAAAAAA 3 1.866 8 22.12 11.86 NM_016776 Mybbp1a GGGCTTTAGATGGCGGC 3 1.866 8 22.12 11.86 NM_026374 Ilf2 TGTAATTTGTGTTCTAC 3 1.866 8 22.12 11.86 NM_211355 Smek1 CCCTTCTTCTCTCCCTT 18 11.195 47 129.955 11.61 NM_001083955 Hba-a2 TGGGTTGTCTAAAAATA 35 21.767 91 251.615 11.56 NM_009429 Tpt1 TTGGCCAGAGTGGAATC 10 6.219 26 71.89 11.56 NM_001039474 Tcerg1 AGCAAGAATTCCTAAGC 5 3.11 13 35.945 11.56 NM_007996 Fdx1 GCCGATCCTCGCGTGAG 5 3.11 13 35.945 11.56 NM_009321 Tbca GGCTGCATTCTGCTGTT 7 4.353 18 49.77 11.43 NM_178600 Vkorc1 GAGTGGATTCTCCAGGT 8 4.975 20 55.3 11.11 NM_007653 Cd63 GATACCATTAATAAAAA 4 2.488 10 27.65 11.11 NM_011327 Scp2 TGAGAGAACAAGGGATG 4 2.488 10 27.65 11.11 NM_011682 Utrn GACGTGAATGGCAAGTA 11 6.841 27 74.655 10.91 NM_021789 Trappc4 CTACCAGAGAAATGGGA 7 4.353 17 47.005 10.8 NM_026873 Ptcd2 ATGTCATCAAATGGGTG 5 3.11 12 33.18 10.67 NM_009679 Ap2m1 GCTGGAATGACTCACAC 5 3.11 12 33.18 10.67 NM_011779 Coro1c TTGTGAAATCTTTAGAG 5 3.11 12 33.18 10.67 NM_024459 Ppp3r1 CCGTGTGTTCTAATGGG 5 3.11 12 33.18 10.67 NM_027350 Nars CAATATCATTTAAGAGA 6 3.732 14 38.71 10.37 NM_001013028 AI597468 ATGTACTCGGGGGAGCT 6 3.732 14 38.71 10.37 NM_011830 Impdh2 CATATACTCCCAAGGAG 6 3.732 14 38.71 10.37 NM_172301 Ccnb1 TATGTAGGACTCACAGA 3 1.866 7 19.355 10.37 NM_025548 Tbcb GCAAAACCAGCTGGTGG 16 9.951 37 102.305 10.28 NM_009840 Cct8 GCCACACCCCGCACACG 11 6.841 25 69.125 10.1 NM_012053 Rpl8 GGACTTAACAGGTGAGG 9 5.597 20 55.3 9.88 NM_023211 Usmg5 AATTTTACAAGTGACCT 6 3.732 13 35.945 9.63 NM_011874 Psmc4 CCCCACCCCACTCCCAC 6 3.732 13 35.945 9.63 NM_175403 2410014A08Rik TTGAAAATAAACAAAAA 6 3.732 13 35.945 9.63 NM_201358 Lyrm4 CAGGACTCCGTTTCCTT 13 8.085 28 77.42 9.58 NM_009128 Scd2 AATTTTTGTTAAGCAGT 7 4.353 15 41.475 9.53 NM_019989 Sh3bgrl TGAAAAAAAAAAAAAAA 10 6.219 21 58.065 9.34 NM_183024 Raver2 CAGAGGCCGCCCATCCT 15 9.329 31 85.715 9.19 NM_178576 Cpsf4 GGCAATGTGGTGGAGGC 24 14.926 48 132.72 8.89 NM_026318 2310003F16Rik CACAGACTGTGGTTCTT 16 9.951 32 88.48 8.89 NM_026467 Rps27l TGCTGGGATGGGGTTTG 9 5.597 18 49.77 8.89 NM_011885 Mrps12  101 TTCCATTAAATGTAGTT 7 4.353 14 38.71 8.89 NM_011879 Ik CTGAATATGGAAGGCAG 7 4.353 14 38.71 8.89 NM_013543 H2-Ke6 TGACAATTTTATAAAAG 6 3.732 12 33.18 8.89 NM_012922 Casp3 GGTCACACTATGACGCC 6 3.732 12 33.18 8.89 NM_025710 Uqcrfs1 TGTTGTGTTCTTTCTTT 6 3.732 12 33.18 8.89 NM_134054 1110002B05Rik GCTTGTGACGAATGAAT 5 3.11 10 27.65 8.89 NM_011528 Taldo1 GTTTGCAGAGGCGGGTG 5 3.11 10 27.65 8.89 NM_172860 Cbfa2t2 GCGAGGAGTGACCAGTC 4 2.488 8 22.12 8.89 NM_019403 Rnf5 ATCCATATTGCAGACAC 4 2.488 8 22.12 8.89 NM_145139 Eif3eip TGATGTTTGACTGTACC 18 11.195 35 96.775 8.64 NM_011873 Dazap2 CACAGAACCAGCAGTCT 11 6.841 21 58.065 8.49 NM_009836 Cct3 TATTGTTTACCTTCAAA 9 5.597 17 47.005 8.4 NM_010817 Psmd7 CTGCACTCCTGAACTGT 7 4.353 13 35.945 8.26 NM_013908 Fbxw5 GAAGATGGAGAAATTGA 20 12.438 37 102.305 8.22 NM_010880 Ncl GCACCGAACACTGTAGA 6 3.732 11 30.415 8.15 NM_019771 Dstn TAACATACACATTTGTA 6 3.732 11 30.415 8.15 NM_028151 Skiv2l2 TCAGCCTTGTCGGTGGC 6 3.732 11 30.415 8.15 NM_153152 2410015M20Rik TATGTGGTTTGGAGGCA 16 9.951 29 80.185 8.06 NM_009121 Sat1 GATGTGGTACGGAAGGT 15 9.329 27 74.655 8 NM_011149 Ppib GTGGATTTCCACGTCAG 9 5.597 16 44.24 7.9 NM_146047 Clptm1l GATAGATAATTCAAAGC 17 10.573 30 82.95 7.85 NM_007505 Atp5a1 TGTATGTCTGGTTTTAT 17 10.573 30 82.95 7.85 NM_023431 Mum1 GATGAAGACTGCCTGTT 8 4.975 14 38.71 7.78 NM_009186 Sfrs10 AAGGCCTTCCAGAAGAT 8 4.975 14 38.71 7.78 NM_025840 Bzw2 GTACCAGGACACCACAT 8 4.975 14 38.71 7.78 NM_030083 Lsmd1 CAGAAGAAAAGCTCAGG 4 2.488 7 19.355 7.78 NM_001040435 Tacc3 TAGATTTGGGGGTTTCT 4 2.488 7 19.355 7.78 NM_009703 Araf ATTACGGTGGATGGGAA 4 2.488 7 19.355 7.78 NM_021473 Akr1a4 TATTAATAAGAGGTCAG 4 2.488 7 19.355 7.78 NM_026554 Ncbp2 CGGCTGTCGCAACTGAA 4 2.488 7 19.355 7.78 NM_026964 Ccdc124 TGGATCCTGAGAACTTC 73 45.4 127 351.155 7.73 NM_016956 Hbb-b2 CCCTTTGTCACAGAGGA 15 9.329 26 71.89 7.71 NM_011690 Vars TCTTAATGAAGTTTGAA 10 6.219 17 47.005 7.56 NM_001123037 Eif4a2 TTTGCAGATCATCTGCA 42 26.121 70 193.55 7.41 NM_023230 Ube2v1 CTCCTTGTATGGCTCTG 6 3.732 10 27.65 7.41 NM_026998 Snx6 GGGAGGCCTCAGCCACC 6 3.732 10 27.65 7.41 NM_134002 Csnk1g2 TCTGTGTGAAGGCTTTC 8 4.975 13 35.945 7.22 NM_021498 Pole3 TTTCAAGGGAGGAGGCT 8 4.975 13 35.945 7.22 NM_023168 Grina GTTCTGGGCCAACTGTG 15 9.329 24 66.36 7.11 NM_145410 Fam173a TGGGCAAAGCCGTCAAT 40 24.877 63 174.195 7 NM_026007 Eef1g AGAAGGAGGTGCTCCAG 14 8.707 22 60.83 6.99 NM_019641 Stmn1 AACTCCACCCCTGTGAG 7 4.353 11 30.415 6.99 NM_001134646 1110019J04Rik AGGCGGAGGCAGCAGGT 16 9.951 25 69.125 6.95 NM_016905 Galk1 CTGGACACTGGATCTCC 14 8.707 21 58.065 6.67 NM_029097 Atp13a2 GGTATCAGTCTGTTTTG 10 6.219 15 41.475 6.67 NM_011278 Rnf4  102 TCCCTGGCCAGCCCGGA 6 3.732 9 24.885 6.67 NM_008956 Ptbp1 CAGTTACATCTCTTTCT 6 3.732 9 24.885 6.67 NM_009761 Bnip3l GGCTTCGGTCTTTTTGA 137 85.203 196 541.94 6.36 NM_018853 Rplp1 CTAGTCTTTGTACACAA 14 8.707 20 55.3 6.35 NM_009093 Rps29 GGGAGAGATAAAGCAAC 20 12.438 28 77.42 6.22 NM_145382 BC021381 CTAGTTCGGAAGATCCA 10 6.219 14 38.71 6.22 NM_146200 Eif3c AACAATTTGGGCTCTTT 61 37.937 84 232.26 6.12 NM_011292 Rpl9 CTCGAGTTTCTTCCTGT 27 16.792 37 102.305 6.09 NM_011354 Serf2 GATTGTGAAGAATGAAC 11 6.841 15 41.475 6.06 NM_001033268 BC010304 GCCTCCTCCCAGTAAGC 17 10.573 23 63.595 6.02 NM_028659 Eif3k ACATACAATTGAGCCCC 6 3.732 8 22.12 5.93 NM_011188 Psmc2 CTAGTTTCTCCACTGGG 9 5.597 12 33.18 5.93 NM_009304 Syngr2 CAGGCCACACAAGAGCC 57 35.45 75 207.375 5.85 NM_016774 Atp5b GTGGCTCATAACCATCC 38 23.633 50 138.25 5.85 NR_003632 EG627782 CTGCACTTTTTTATTCT 11 6.841 14 38.71 5.66 NM_008568 Mcm7 TGCTGTCAGCTGGAGAC 8 4.975 10 27.65 5.56 NM_021884 Tsg101 TTTGTCAGATTTTTTCA 8 4.975 10 27.65 5.56 NM_138593 Larp7 TCAATAAAGGAATGACC 9 5.597 11 30.415 5.43 NM_025356 Ube2d3 ATGTAGTAGTGTCTTAC 14 8.707 17 47.005 5.4 NM_007516 Hnrnpd CAGCCAAACCGCAGAGC 19 11.817 23 63.595 5.38 NM_016876 Eif3g TTTTATGTTTAAATAAA 30 18.658 36 99.54 5.34 NM_172086 Rpl32 ATTGGCTTAAAGTGAAG 15 9.329 18 49.77 5.34 NM_008831 Phb TAGCAGACAGGGAGAGG 10 6.219 12 33.18 5.34 NM_026846 Zfand2b ACAACTTCCTGAGCCTC 12 7.463 14 38.71 5.19 NM_010299 Gm2a TTTGGGCCCAGATTGTC 13 8.085 15 41.475 5.13 NM_019642 Rpn2 TGGGCATCCACCCCAGC 72 44.778 83 229.495 5.13 NM_009080 Rpl26 TATTGGCTCTGCTTGGT 56 34.828 64 176.96 5.08 NM_007750 Cox8a GAACGCGACGGCTCCAG 21 13.06 24 66.36 5.08 NM_008946 Psmb6 AGTACAATGACATCAAG 14 8.707 16 44.24 5.08 NM_175190 2900010J23Rik GCTATGGTGCCTTTCTG 8 4.975 9 24.885 5 NM_011970 Psmb2 GCATCTGCCCTGCCTTG 8 4.975 9 24.885 5 NM_134138 Psmg2 GTGGCTCACAACCATTC 10 6.219 11 30.415 4.89 NM_001101478 D3Ertd254e GCACAACTTGCCTCAAA 11 6.841 12 33.18 4.85 NM_007589 Calm2 TTTCAGCAGTGTTGGCT 11 6.841 12 33.18 4.85 NM_013556 Hprt1 TCGTGGGAAAGGCTGCA 11 6.841 12 33.18 4.85 NM_181392 Gtf2h5 GATTGAGAATGCTTAGA 15 9.329 16 44.24 4.74 NM_010380 H2-D1 TGTGTGAGGACCTGCTG 17 10.573 18 49.77 4.71 NM_029663 Eef1d CAGCGCGGGAAAAGGAG 18 11.195 19 52.535 4.69 NM_001081379 Ankrd11 ATGTATGAAAGGAGCAG 18 11.195 19 52.535 4.69 NM_025509 2310008M10Rik AGATCTATACAGTCGGG 77 47.888 80 221.2 4.62 NM_011291 Rpl7 GAAGGACTAAATGGTCA 17 10.573 17 47.005 4.45 NM_025875 Rbm8a GACTGATGTCTCAGGTT 10 6.219 10 27.65 4.45 NM_013715 Cops5 CATCGCCAGTGGGCAAA 22 13.682 21 58.065 4.24 NM_009696 Apoe AAGAAACCAGAATCCTT 21 13.06 20 55.3 4.23 NM_001077529 Nme2 GAATAATAAAACTATTT 61 37.937 58 160.37 4.23 NM_031165 Hspa8  103 CAGTTGTAAATAAAAGT 16 9.951 15 41.475 4.17 NM_016792 Txnl1 AATACTTTTGTATTGCT 31 19.28 29 80.185 4.16 NM_001113564 Serbp1 TAGGGTACAGATGAGGG 13 8.085 12 33.18 4.1 NM_016843 Atxn10 AAGTTCAGAACACATTT 24 14.926 22 60.83 4.08 NR_002702 Npm3-ps1 CCAAATAAAACCTTGAA 54 33.584 49 135.485 4.03 NM_010699 Ldha TGGCTCGGTCACTTGGG 79 49.132 71 196.315 4 NM_009609 Actg1 TCGCAAGCAAACGTATC 58 36.071 51 141.015 3.91 NM_001113199 Naca GTTCTCAATTAATTTGG 54 33.584 47 129.955 3.87 NM_023871 Set ATGAACACACGGCGGAC 15 9.329 13 35.945 3.85 NM_008302 Hsp90ab1 CCTTTGAGATCATCCAC 42 26.121 36 99.54 3.81 NM_009095 Rps5 CTGTCATTTGTAATATG 22 13.682 18 49.77 3.64 NM_013663 Sfrs3 TTCTCCTCAGACCATCC 20 12.438 16 44.24 3.56 NM_019880 Mtch1 CGCTGGTTCCAGCAGAA 48 29.852 38 105.07 3.52 NM_025919 Rpl11 GTGAGCCCATTGGCCGG 45 27.986 35 96.775 3.46 NM_008302 Hsp90ab1 AATATGTGTGGGCTAAG 43 26.743 32 88.48 3.31 NM_053071 Cox6c GAAAGCAATGTCAAGTC 25 15.548 18 49.77 3.2 NM_001110233 Ngfrap1 GGCTGCAGCCAATCAGG 45 27.986 32 88.48 3.16 NM_020261 Psg23 GATTCCGTGAGGGAACA 55 34.206 38 105.07 3.07 NM_026069 Rpl37 ATGGCTCACAACCATCT 44 27.365 30 82.95 3.03 NM_001005508 Arhgap30 CCTCCATCCTTTATACT 26 16.17 17 47.005 2.91 NM_009536 Ywhae AAGACCTATGTGGAAAA 41 25.499 25 69.125 2.71 NM_001037999 Dbi ATGTGGTGTGATTCCAG 53 32.962 32 88.48 2.68 NM_011034 Prdx1 GTGGCTCATAACCATCT 45 27.986 27 74.655 2.67 NM_172773 Slc17a5 AAAACAGTGGCCGGTGG 124 77.118 69 190.785 2.47 NM_009084 Rpl37a AGAAACAAGATGACTTG 170 105.727 91 251.615 2.38 NM_011434 Sod1 GTGTAATAAGACATAAC 60 37.315 32 88.48 2.37 NM_016806 Hnrnpa2b1 TCTTTGGAACCACTTGA 45 27.986 24 66.36 2.37 NM_008617 Mdh2 CCGACGGGCGCTGACCC 53 32.962 28 77.42 2.35 NR_003278 Rn18s GGTGAGCCTGAAGCTTG 65 40.425 33 91.245 2.26 NM_011563 Prdx2 GTCTGCTGATGGCCAGA 235 146.152 111 306.915 2.1 NM_008143 Gnb2l1 TAAGTAGCAAACAGGGC 176 109.458 83 229.495 2.1 NM_008410 Itm2b GAGCGTTTTGGGTCCAG 272 169.163 124 342.86 2.03 NM_008907 Ppia TGTGCCAAGTGTGTCCG 125 77.74 50 138.25 1.78 NM_001005859 Rpl34 TGTAGTGTAATAAAGGT 207 128.738 80 221.2 1.72 NM_009098 Rps8 GGATTTGGCTTGTTTGA 389 241.927 147 406.455 1.68 NM_026020 Rplp2 GAAGCAGGACCAGTAAG 397 246.903 126 348.39 1.41 NM_007687 Cfl1   104  Table 5.2 Tags over-represented in the FL HSC library vs. the adult BM HSC library FL FL HSC BM BM HSC Fold  Accession Gene Name Sequence data HSC /100K HSC /100K Diff. TTCCTGGCATTATTTTG 103 64.05791 0 0 N/A NM_001001806 Zfp36l2 AATATGCCTTGTTCAAT 63 39.18105 0 0 N/A NM_001001806 Zfp36l2 TTCTCTTACCCTGAAAC 48 29.85223 0 0 N/A NM_001003963 Dnmt3b AGAATTTGGTGTTTGGA 75 46.64411 0 0 N/A NM_001005507 Smg7 CAGATTTAGGTGCTTTC 95 59.08254 0 0 N/A NM_001005859 Rpl34 TATCTGTCTACTTTCTC 72 44.77835 0 0 N/A NM_001008551 BC085271 GTGGTTCACAACCATCT 61 37.93721 0 0 N/A NM_001039158 Ube2j2 ATCTCTTTTCCCTTCCT 79 49.1318 0 0 N/A NM_001105843 Lsm12 TTCAATGGTGTCAAAAC 46 28.60839 0 0 N/A NM_001108324 Ranbp1 TGGAATGCAGATGGGTG 45 27.98647 0 0 N/A NM_001110499 Canx GACGCGACCATCCTCCT 175 108.8363 0 0 N/A NM_007393 Actb TTGATCATCACAAACTC 40 24.87686 0 0 N/A NM_007486 Arhgdib TACAACACTCTGTAAAT 142 88.31285 0 0 N/A NM_007624 Cbx3 GGATGGGGAGGGATACG 93 57.8387 0 0 N/A NM_007687 Cfl1 CTCACAAGGGGTTCCCA 52 32.33992 0 0 N/A NM_007968 Ewsr1 GTTGTGATTTTTTTTTT 43 26.74262 0 0 N/A NM_007968 Ewsr1 ATTTGAAATAATAAAAT 37 23.0111 0 0 N/A NM_008138 Gnai2 CCAAAGAGGTACACTGG 48 29.85223 0 0 N/A NM_008143 Gnb2l1 AGAGCTGCACAGGTGCA 50 31.09607 0 0 N/A NM_008376 Gimap1 TTTGCTACAAATTTTGG 43 26.74262 0 0 N/A NM_008388 Eif3e TAGCAATCAAATTATCC 64 39.80298 0 0 N/A NM_008391 Irf2 GAGGTACATTTCAGTTG 79 49.1318 0 0 N/A NM_008505 Lmo2 ATCCTGTTAACCGCGAC 59 36.69337 0 0 N/A NM_008535 Lyl1 TGAAATAAACTCAGTAT 157 97.64167 0 0 N/A NM_008722 Npm1 CTCGAGTCTCCAGAGTC 53 32.96184 0 0 N/A NM_008774 Pabpc1 GAGAGTAACAGGCCTGA 39 24.25494 0 0 N/A NM_009030 Rbbp4 CTTTTCAGCAACACTTC 280 174.138 0 0 N/A NM_009536 Ywhae GAATTAACATTAAACTT 130 80.84979 0 0 N/A NM_009536 Ywhae GATAATGTGCTTTGGAA 50 31.09607 0 0 N/A NM_009593 Abcg1 AGAAAGGAAGTCTGGGA 48 29.85223 0 0 N/A NM_009593 Abcg1 TTGCTGTGTGATTATCT 39 24.25494 0 0 N/A NM_009600 Macf1 CAAATCAGGCTGACCTA 45 27.98647 0 0 N/A NM_009829 Ccnd2 GCAATTGACAGTCCTAA 64 39.80298 0 0 N/A NM_010193 Fem1b ACTGTTAACAATGCATT 47 29.23031 0 0 N/A NM_010441 Hmga2 TCGGTTGCATCCCAGAG 38 23.63302 0 0 N/A NM_010485 Elavl1 CAGAATGTGCTAAGCGG 55 34.20568 0 0 N/A NM_010885 Ndufa2 TTTTTGAGTTAAGGTGC 43 26.74262 0 0 N/A NM_010891 Sept2 TTGACTGATTCTTAGAA 42 26.1207 0 0 N/A NM_010891 Sept2 GGGAAGGGGCTTCTCTG 42 26.1207 0 0 N/A NM_011117 Plec1  105 GAGGACCTGGGACTACG 99 61.57023 0 0 N/A NM_011218 Ptprs TGGGAAAGATGCACACA 38 23.63302 0 0 N/A NM_011218 Ptprs CTTCCCCGGGAGACGCG 47 29.23031 0 0 N/A NM_011434 Sod1 TACTACTTTGACTTTTG 63 39.18105 0 0 N/A NM_011480 Srebf1 TGAAGGAACAAGCTGGT 37 23.0111 0 0 N/A NM_011508 Eif1 TAAAAATTAATTTAACC 54 33.58376 0 0 N/A NM_011543 Skp1a GGGCAGAGGTGGTGACA 323 200.8806 0 0 N/A NM_011655 Tubb5 CCACCTCTCAGGCGAAG 44 27.36455 0 0 N/A NM_011664 Ubb ATCTTTCTGGCTCCACT 150 93.28822 0 0 N/A NM_011740 Ywhaz GTATGTGCCCGAGGGGT 43 26.74262 0 0 N/A NM_011969 Psma7 GACCTGAGTACCACATT 37 23.0111 0 0 N/A NM_012002 Cops6 TCAACATCTAGGCTCCA 37 23.0111 0 0 N/A NM_012023 Ppp2r5c GGCCTGCTTCTGGAAGC 59 36.69337 0 0 N/A NM_013535 Grcc10 TTTTATTTGTATTTGTA 52 32.33992 0 0 N/A NM_013716 G3bp1 GCGGCTCACCTGTCCTT 46 28.60839 0 0 N/A NM_015816 Lsm4 TGCACTTTGGGATTTTG 64 39.80298 0 0 N/A NM_016756 Cdk2 GCGAAGGCTGGAACGGG 131 81.47172 0 0 N/A NM_018796 Eef1b2 GAATCCAACTACTTCGA 120 74.63058 0 0 N/A NM_019435 Ndufb11 AAAGACTTTGTGTTAGT 75 46.64411 0 0 N/A NM_019776 Snd1 ATTTGACTGGTTTTCCT 70 43.5345 0 0 N/A NM_022410 Myh9 AAGGATGTGCCCAACTG 50 31.09607 0 0 N/A NM_023312 Ndufa13 CAGACTTGGTAAAACCC 295 183.4668 0 0 N/A NM_023595 Dut CTCACAGTGCAGACTTA 49 30.47415 0 0 N/A NM_023595 Dut GGCTGCTCTGCTCGGAG 94 58.46062 0 0 N/A NM_025573 Sfrs9 GCGTCGAGCCCAGCCCT 68 42.29066 0 0 N/A NM_025577 2810428I15Rik GCCATTGGAATGGGCAT 99 61.57023 0 0 N/A NM_025946 2010100O12Rik TGGAAGAAACTGCAGGA 130 80.84979 0 0 N/A NM_026063 2900010M23Rik TCTGAATCTGCGGTAGA 48 29.85223 0 0 N/A NM_026069 Rpl37 CAAAGACAACTCTGTGT 46 28.60839 0 0 N/A NM_026521 Zfp706 GGAGCAGAGGAGCCCGA 41 25.49878 0 0 N/A NM_026552 Arpc4 CTCAATCCCACTCTGTC 42 26.1207 0 0 N/A NM_026636 5430437P03Rik TCGCGTCGCTCACTTCA 84 52.24141 0 0 N/A NM_028291 Pan3 TAAGATTTCAATAAAAC 52 32.33992 0 0 N/A NM_028871 Hnrnpr CAGGAGTTCAAAGAAGG 39 24.25494 0 0 N/A NM_029711 Arpc2 TTGACCTCGCTAGGCCG 47 29.23031 0 0 N/A NM_029767 Rps9 GATCTCAAAGAGTAAGT 37 23.0111 0 0 N/A NM_033618 Supt16h GCAGAGACATCTTGACC 57 35.44952 0 0 N/A NM_133362 Erdr1 TAGCCTCTGGTCCTGTC 38 23.63302 0 0 N/A NM_138586 Exosc5 CGGGAGATGCTCTGAGA 91 56.59486 0 0 N/A NM_138597 Atp5o GCACAAACTACTCCTTG 60 37.31529 0 0 N/A NM_144901 Csde1 CACACAGACTTCTCCTA 97 60.32638 0 0 N/A NM_146243 Actr2 ACTGTTAAAATGATGTA 97 60.32638 0 0 N/A NM_146243 Actr2 TAACTGGAGGATGTGCT 37 23.0111 0 0 N/A NM_172736 Leng8  106 TGCAAGCATCCTCTCCA 45 27.98647 0 0 N/A NM_172746 Hirip3 TATCTTGGCACATTTCA 96 59.70446 0 0 N/A NM_177301 Hnrnpl GCCTTGGTGAAACTCCC 56 34.8276 0 0 N/A NM_181582 Eif5a ATCTCTTTGTGTAGTTC 39 24.25494 0 0 N/A NM_198609 BC003885 CTCCAGGGCAGCTGGTA 62 38.55913 0 0 N/A NM_198652 6430706D22Rik GGAATAACGCCGCCGCA 2474 1538.634 0 0 N/A NR_003278 Rn18s  Figur adult A) Su fracti B) No prese C) Sc Confi statis D) G as co e 5.1 - Lon  BM cells mmary of t ons of E14.5 rmalized nu nt.  N.D. = n atter plot of dence interv tics213. ene Ontolog mpared to th gSAGE libr he size and c  FL and adu mber of tag ot detected  individual t als of 95%, y analysis o e FL library aries prepa ontent of L lt BM. s per 105 to . ags and thei  99%, and 9 f significant  and vice ve 107 red from H ongSAGE li tal tags pres r respective 9.9% were d ly over-repr rsa (black). SC-enrich braries prep ent in each l  counts in th etermined u esented tags  ed fractions ared from H ibrary for ge e 2 LongSA sing Audic  in the adult  of E14.5 F SC-enriche nes expecte GE librarie  Claverie  BM library  L and d d to be s.  (white)  Figur and C Q-RT CD45 are th being signif  e 5.2 – Prnp D45+EPCR -PCR analy +EPCR+CD e mean ± SE  derived fro icantly diffe , Gata3, an +CD48-CD ses of transc 48-CD150- M of value m triplicate rent (p<0.0 d Bmi1 tra 150- adult ript levels i cells (light b s obtained i assays.  Res 5). 108 nscripts ar BM cells n extracts of ars).  All va n 3-6 indepe ults for Prnp e differentia  400 E-SLA lues normal ndent exper , Gata3, an  lly express M cells (da ized to Gap iments, with d Bmi1 in th ed by E-SL rk bars) or dh.  Values  each measu e 2 fraction AM shown rement s are  Figur self-r A) Q 104 li B) Q- 104 li C) & comp ng/m All v indep mean e 5.3 – Elev enewal acti -RT-PCR an n- (white ba RT-PCR an n- (white ba  D) Q-RT-P ared to CD4 l of IL-11 su alues norma endent expe s not done. ated Vwf, R vity in HSC alyses of tra rs) from FL alyses of tra rs) from adu CR analyses 5+EPCR+CD pplemented lized to Gap riments, wit hob, and P s nscript leve . nscript leve lt BM.  of transcrip 48-CD150  with 10 ng/ dh.  Values h each mea 109 ld3 express ls in extract ls in extract t levels from - cells (C, lig ml SF (D, g  shown are t surement be ion is consi s of 300-400 s of 300-400  adult BM ht bars) and rey bars) or he mean ± S ing derived stently asso  E-SLAM c  E-SLAM c E-SLAM ce  E-SLAM c  1 ng/mL SF EM of valu from triplica ciated with ells (dark b ells (dark b lls (dark bar ells cultured  (D, light ba es obtained te assays.  N   high ars) or ars) or s)  in 20 rs). in 3-6 .D.  Figur adult Trans HSCs HSCs mean deriv e 5.4 – Q-R  BM cell po cript levels  vs. lin- adu , white hatc  ± SEM of v ed from trip T-PCR an pulations a of all genes lt BM cells hed bars = l alues obtain licate assays alyses of tra s indicated assayed in t (black bars = in-).  All val ed in 2-6 in . 110 nscript lev  he original s  HSCs, wh ues were no dependent e els of select creen for ge ite bars = lin rmalized to xperiments, ed genes in nes commo -) and FL ce Gapdh.  Va  with each m various FL nly upregul lls (grey ba lues shown easuremen   and ated in rs = are the t being  Figur cell p Trans cells value triplic e 5.5 – Q-R opulations cript levels (light bars). s obtained in ate assays. T-PCR an as indicated in the adult  All values  2-6 indepe  alyses of tra  BM E-SLA were norma ndent exper 111 nscript lev M cells (dar lized to Gap iments, with els of select k bars) and dh.  Values  each measu ed genes in CD45+EPCR shown are t rement bein various adu +CD48-CD he mean ± S g derived fr lt BM 150- EM of om  Figur stimu Trans ng/m were indep e 5.6 – Q-R lated adult cripts levels L SF (dark b normalized endent expe T-PCR an  BM HSCs  in E-SLAM ars), 10 ng/ to Gapdh.  V riments, wit alyses of tra   cells cultu mL SF facto alues show h each mea 112 nscript lev red in 20 ng r (light bars n are the me surement be els of select /ml of IL-11 ) or 1 ng/mL an ± SEM o ing derived ed genes in  supplemen  SF (white f values ob from triplica cytokine ted with eith bars).  All v tained in 2-6 te assays. er 300 alues    113 6. Discussion and Future Directions   6.1  Major contributions  The work presented in this thesis is focussed on the regulation of mouse HSC self- renewal.  It has long been postulated that HSCs are unique in their possession of a self-renewal mechanism that can sustain hematopoiesis throughout life.  However, investigations of the cellular and molecular basis of this mechanism have been hindered, mostly by an inability to isolate self-renewing cells at sufficient purities to allow the discrimination of pre-determined and stochastically decided events.  Consequently, the identification and characterization of HSCs has relied historically on the detection of empirically defined levels of multi-lineage differentiation and sustained hematopoietic activity in myeloablated recipients of transplanted test cell populations.  This approach has been accompanied by considerable inconsistency in the exact definition of what is or is not an HSC with self-renewal and multilineage potential. In this thesis, I describe a series of studies that now allow discrete subsets of self- renewing cells to be isolated from the BM of adult mice.  Importantly, the features shown to distinguish these subsets suggest that a sharp demarcation exists between the ability of a primitive hematopoietic cell to self-renew indefinitely versus its variable exhaustion within a few days to 6 months (Figure 6.1).  Using the new purification methods described for isolating different subsets of primitive quiescent adult BM HSCs, I then further defined the different in vitro growth factor dependences of their viability, proliferation, and maintenance (or loss) of stem cell potential.  Finally, I exploited both of these developments to evaluate the gene expression patterns of HSCs and determine which transcripts might be differentially associated  114 with a high self-renewal state independent of the lineage preferences of the particular HSCs in which they were found. Chapter 3 builds on initial experiments that allowed the heterogeneous differentiation and self-renewal behavior displayed by ~100 individually tracked HSCs to be segregated into 4 subtypes in terms of their relative contributions to the lymphoid and myeloid WBCs for at least 16 weeks.  Two of these subtypes of HSCs were consistently found to possess lifelong self- renewal potential as determined from secondary and tertiary transplant assays and showed frequent stable propagation of the same differentiation program characteristic of the original cell. In contrast, when the same spectrum of input HSCs were placed in vitro under the best known cytokine conditions for their maintenance, there was a rapid shift toward the HSC subtypes that do not generate progeny HSCs able to repopulate secondary mice out to 6 months.  Using EPCR223 and CD15019 as positive markers and CD4819 as a negative marker, I was able to further increase the purity of HSCs obtainable (56%) with a selective enrichment of with high self-renewal HSCs.  At the same time, I identified a similarly rare sister population of cells which differed only in their lack of expression of CD150 and contained the low self-renewal HSCs subtypes at an equivalent purity (39%).  Thus, at least in quiescent adult mouse BM populations, differences in CD150 expression appear to distinguish HSCs with high (durable) self-renewal potential from those whose self-renewal potential has been destined to decline. Functional characterization of the regenerative properties of CD45+EPCR+CD48-CD150+ (E- SLAM) cells present in E14.5 FLs (where the HSCs are actively cycling) or in reconstituted mice indicated that this phenotype was also selective for these disparate, and previously difficult to purify, sources of transplantable HSCs. In Chapter 4, I showed that exposure of 130 individually monitored HSCs to different concentrations of a single growth factor (SF) could directly alter the frequency with which they would execute one or more self-renewal divisions in culture without affecting their viability or  115 their kinetics of cell division.  While 300 ng/mL of SF could maintain HSC numbers in IL-11 supplemented cultures, 10 ng/mL SF resulted in a net 13-fold decrease in HSC numbers. Remarkably, more detailed assessment of the timing of these differential responses showed that a reduction in HSC numbers could be obtained within the first 16 (but not 8) hours.  This shows that such changes can manifest themselves before HSCs complete a first mitosis and likely before even entering the cell cycle.  Furthermore, I identified Bmi1, Ezh2, and Lnk as 3 transcripts that might play a role in or at least be co-regulated by the events precipitating these rapid differential responses.  Assessment of the post-first division progeny confirmed the marked loss of transplantable HSC activity with continued maintenance of the cells under low SF conditions (>95%).  Interestingly, when separate daughter cells were cultured in a high concentration of SF, ~1/3 of the HSCs could give rise to at least 1 HSC and in 40% of these divisions, 2 daughter HSCs were created.  However, 2 daughter HSCs of the high self-renewal type were not seen in any instance suggesting that this condition promotes asymmetric HSC divisions.  Thus careful examination of the response kinetics of HSCs to variable concentrations of SF indicates that the intensity of signaling obtained from this growth factor alone can regulate the speed with which the durable self-renewal state can be lost within a few hours even though it may occur over a period of many months in vivo. Chapter 5 describes a comparative gene expression approach to identify potential regulators of the high self-renewal HSC state.  Using results from LongSAGE libraries prepared from highly purified E14.5 FL HSCs and adult BM HSCs and a survey of published data, 27 initial candidates were identified for more detailed quantitative analysis in a variety of populations using Q-RT-PCR to compare transcript levels. The expression of 9 of these were found to be consistently higher in HSC-enriched fractions compared to a variety of related fractions in which these cells were present at much lower levels.  In addition, 3 of the 9 genes  116 (Vwf, Pld3, and Rhob) were consistently associated with the most purified source of high self- renewal HSCs. Together this work identifies and prospectively isolates HSCs with durable self-renewal from a similar subset with extensive but finite self-renewal and identifies candidate genes that strongly associate with these states.  Furthermore, these studies identify extrinsic regulatory cytokine conditions where depending on the concentration of a single growth factor (SF), HSCs self-renewal is either promoted to preserve overall HSC numbers or dramatically reduced without any impact on the viability or divisional kinetics of the cells.  Importantly, though, this work also describes that these changes can be manifest even before the cell physically divides, suggesting that self-renewal can be influenced in a cell division-independent fashion.   6.2  Implications and Future Directions  6.2.1 Opportunities for direct and high-resolution analyses of HSC heterogeneity afforded by simpler and more selective isolation strategies  Since the first description of a highly purified HSC population in 1996, when Osawa et al.221 showed that 1 in 4 Lin-Sca1+Kit+CD34- adult mouse BM cells was capable of repopulating an irradiated recipient for 3 months, many refinements and variations of mouse HSC purification have been described17,19,221,277.  Some of these have involved adding more markers to the Osawa protocol (e.g.: removal of Flt3+ cells222) to enhance the purity of HSCs with longterm repopulating activity.  Others have exploited the high Ho278 and/or Rho279,280 dye exclusion activity and/or the more recently discovered EPCR+223 and SLAM (CD150+CD48-) phenotypes19 that are also selective for HSCs from adult mouse BM.  One of the most significant contributions  117 of these advances has been to enable both direct and clonal functional analyses of large numbers of individual mouse HSCs.  This has led to an appreciation of a greater heterogeneity of HSC phenotypes that are coupled to distinct differentiation and self-renewal programs than was historically anticipated.  Thus, even these purification schemes have become increasing complex and hence difficult to standardize.  Moreover, the vast majority of reports from other groups still do not yet include studies of serially analyzed single cell transplants, and hence it has not been possible to deduce their content of specific HSC subsets. The E-SLAM subset that we describe in Chapter 3 replicates the power of simple SP- based strategies but avoids the toxicity of Ho232 and also shortens the length of time that the HSCs spend outside of the host before being isolated.  More importantly, it provides the greatest selectivity for high self-renewal HSCs thus far achieved.  A second issue that has challenged the generalization of HSC purification strategies or the direct measurement of phenotypes to replace functional endpoints for HSC quantification has been the fact that the expression of many markers useful for purifying unmanipulated (quiescent) HSCs from normal adult mouse BM (e.g., CD34226, Mac1230, CD38227, PrP229, Tie2229, Ho228, MPL229, and CD105229) is not stable. Yilmaz et al. provided the first evidence that the SLAM phenotype remains selective for HSCs independent of their activation20.  The experiments in Chapter 3 confirm the data for the SLAM phenotype and identify EPCR also as a stable marker.  Thus the E-SLAM combination allows HSCs from multiple activated settings (fetal liver, cultured cells, and reconstituted animals) to be obtained at purities of >20%.  In addition, the experiments in Chapter 3 identify a very closely related phenotype (the CD150- subset of the CD45+EPCR+CD48-) that is equally rare and highly enriched in mainly low-self-renewal HSCs (constituting 39% of the population).  Moving forward, these prospectively isolated populations should prove extremely useful for studying the properties of HSCs with subtle, but potentially important molecular differences that determine whether their subsequent self-renewal potential has already been limited or not.  Indeed the work  118 presented in Chapter 4 and discussed below provides preliminary support for this prediction. One must use caution, however, as these sorting strategies may be mouse strain-specific and genes identified in one set of analyses clearly require additional validation. Excitingly, though, my experiments demonstrate that it is now technically feasible to investigate primary mouse HSCs with the same power as has previously been restricted to model systems in lower organisms or cell lines.  Reasonable numbers of HSCs can be studied at the single-cell level and novel insights can be made with respect to their underlying biology through the adaptation of other analytical tools for single-cell analyses.  These include transcriptome profiling of single cells161,165,264,281,282, immunostaining of subcellular elements of manipulated HSCs283,284, time-lapse video imaging of living single cells in vitro285,286, and in vivo60, and studies of cytokine effects on HSC self-renewal, lineage fate selection and differentiation in single-cell cultures17,87,257,287.  Thus, addressing many previously inaccessible questions concerning the process of murine HSC self-renewal is now within reach.  One of these is the capability of determining the properties of the daughter cells generated from the mitosis of individual HSCs in vitro. Manipulations of HSCs (genetic, epigenetic, extrinsic, etc) prior to division should permit identification of the key players that maintain the original stem cell state versus a state that allows some properties to be lost.  One group has recently shown by transplantation of each first division progeny pair of purified HSCs that Lnk-/- HSCs are more likely to undergo HSC expansion type divisions in vitro when compared to wild type257. The rapid advancement of high-throughput gene expression analysis technology (e.g.: microarray19,169,172,173, cDNA arrays264, single-cell cDNA amplification161, and SAGE (see Chapter 5)) is also revolutionizing our ability to analyze this aspect of HSC phenotypes. Furthermore, transcriptional networks are now being developed that show how these datasets may be interconnected.  A web-based tool has recently been developed called BloodExpress  119 (http://hscl.cimr.cam.ac.uk/bloodexpress/index.html).  This database incorporates over 250 microarray experiments from 15 different studies and allows cross-comparisons to be made to look for commonly expressed genes across the hematopoietic tree288.  For example, this approach has also led to the identification of a triad of the SCL/TAL1, GATA2, and FLI1 transcription factors with important roles in regulating HSCs through a self-reinforcing mechanism289. The application of real-time video imaging and analysis and highly sensitive gene and protein labeling/marking strategies to highly purified HSC populations likewise can now enable experiments to interrogate when and under what conditions asymmetric partitioning of molecules290 accompanies the retention or loss of HSC-specific traits285.  For example, Wu et al.290 have reported asymmetric partitioning of Notch into each daughter cell of putative HSCs. While not yet validated with follow-up in vivo readouts, this sets the stage for exciting experiments surrounding asymmetric partitioning of key self-renewal regulators.  Striking proof- of-principle experiments illustrating the power of single cell analyses have also recently been reported by Yamazaki et al.291.  These studies showed with impressive clarity that inhibition of lipid raft clustering suppressed the PI3K–Akt–FOXO pathway and induced hibernation in HSCs ex vivo, the first description involving lipid raft clustering in HSC divisional kinetics292.  The results presented in this thesis suggest the following model describing the HSC state of adult mouse BM.  These cells have an unlimited potential for sustaining a high probability of self-renewal coupled to a latent pervasive multi-lineage myeloid differentiation potential but variable propensities for lymphoid differentiation.  Once this state changes, the cell is irreversibly destined to generate a self-exhausting clone.  However, its multilineage potential may still be retained for many more cell divisions resulting in the generation of clones that may contribute a substantial fraction of the blood produced and do so for up a substantial fraction (10%-15%) of the animal’s ~2-year lifetime.  The evidence presented here to support this model is 3-fold.  First, singly transplanted HSCs exhibiting α and β differentiation programs were  120 shown to consistently possess a durable self-renewal capacity that was perpetuated through 2 serial regenerative cycles.  In contrast, HSCs exhibiting γ and δ differentiation programs showed a complete inability to regenerate detectable HSCs after 6 months.  Second, these features were shown to segregate with CD150 expression within a population of CD45+EPCR+CD48- cells, which allows their prospective isolation as distinct subsets.  Third, HSCs with durable and finite self-renewal phenotypes have distinct genetic programs.  This model is similar features to one proposed by Muller-Sieburg et al.34 who have also obtained evidence of intrinsic, but age- dependent heterogeneity in HSCs differentiation programs, but have not linked these to separate self-renewal programs.  Underlying both of these models, however, is a series of assumptions that exclude the possibility of reversibility of HSC properties in steady-state BM and hence, depending on the time/situation might be variably equipped with properties essential for their detection in vivo.  On the other hand, the finding that HSCs with finite self-renewal potential can generate robust but only transient multilineage clones when assayed in irradiated hosts poses a strong argument against the reversibility hypothesis.   6.2.2  Exogenous regulation of HSC self-renewal  Many growth factors have been identified as having a role in HSC self-renewal but the highest maintenance of HSC numbers has been speculated to be through the use of very high concentrations of SF and a factor like IL-11 that can act on HSCs to generate signalling through Gp130 (see Section 1.3.3 in Chapter 1)17,74,90.  Here I provide direct confirmation of that prediction in single cell cultures and further demonstrate that the concentration of SF alone can dramatically alter the probability of a given HSC undertaking a next self-renewal division or a symmetric differentiation division.  Furthermore, I discovered that such changes in HSC  121 potential are surprisingly rapid, i.e., they occur even before the cells enter mitosis, but not before an initial period of several hours, for an initially quiescent population.  These findings strongly suggest that changes to the molecular mechanisms that preserve HSC self-renewal activity can be activated well before cells physically partition their contents.  Furthermore, they indicate that this activation process can be triggered by changes in signalling cues from the environment that may then require several hours to become effective.  Interestingly, the data presented in Chapter 4 indicate that the so-called self-renewal divisions that HSCs undergo, even under the high SF concentration conditions, are overstated in light of the proposed model.  Most give rise to only one daughter cell high self- renewal/reconstitution pattern and even this event is rare.  This is also evidenced in the data presented in Chapter 3, where few of the HSCs detected after 4 days displayed differentiation programs associated with a high self-renewal status (i.e.: most were lymphoid-biased) and no HSCs detected after 10 days of culture showed a robust contribution to the output of myeloid cells in recipient animals.  Together, these data suggest that the best feeder free conditions are poor at sustaining durable self-renewal ability in HSCs.  Given the known ability of, as yet undefined, factors produced by stromal cells to achieve this support62,64, revisiting their mechanisms of action on defined HSC subtypes would now be warranted.  One potential hypothesis is that immobilization of growth factors is required in order to establish polarity in the HSC prior to division. As an alternative strategy to investigate mechanisms that regulate HSC self-renewal, genetic techniques have been applied to assess the consequences of overexpression or deletion of specific molecules.  Perhaps the most dramatic results of this approach have been the large expansion of HSCs that results from retroviral over-expression of Hoxb4 (40-fold)144,145 and, more recently, the nearly maximal expansion of HSCs numbers (10,000-fold) obtained using a novel fusion gene consisting of Nucleoporin98 and the homeodomain of HoxA10144,145.  122 The availability of a strategy that can prospectively isolate HSCs with durable and finite self-renewal activity as separate populations should facilitate more precise examination of the following types of questions:  Do HSCs with durable self-renewal activity divide more slowly or more quickly when stimulated with high SF and IL-11?  Does this change when supportive stromal cells are also present and, if so, how?  Is the loss of self-renewal seen within 16 hours of exposure of HSCs to a suboptimal concentration of SF irreversible?   6.2.3  Molecular mechanisms regulating different HSC self-renewal states  As discussed above, multiple lines of evidence now suggest that HSCs have pre- determined programs of self-renewal and/or differentiation potential whose regulation is likely to have distinct although linked components.  In Chapter 5, I show that HSCs with durable self- renewal activity express higher levels of several transcripts previously associated with a HSC molecular signature; i.e.: Bmi1, Prnp, and Gata3.  Bmi1 is a member of the PRC1 group of Polycomb genes and has been previously shown to play an important and non-redundant role in supporting the generation of adult populations of mouse HSCs consistent with an involvement in maintaining their self-renewal ability138,139,293.  Interestingly, BMI1 has also been found to be important in other stem cell populations, including mammary294 and neural295 tissue.  This suggests that some common mechanisms may be used to stably repress the activation of pre- established, but latent differentiation programs.  The fact that higher Prnp expression is a feature of high-self-renewal HSCs corroborates the previously reported finding that lack of PRNP (prion protein) has no effect on the generation of HSC in normal mice or their ability to regenerate WBC production in primary irradiated hosts, but can severely compromise secondary and tertiary reconstitution ability265.  While no direct role has yet been described for Gata3 in HSCs,  123 its absence has critical effects on fetal hematopoiesis247 and its overexpression has been shown to preferentially bias HSCs toward myeloid (specifically megakaryoctytic and erythroid lineages) cell outputs296.   6.2.4  New mediators of HSC regulation  Recently, much hype has centred on epigenetic regulation of stem cell properties and the role of small non-coding RNAs (called microRNAs) as regulators of transcript availability.  The relative amount of DNA compaction around particular coding regions determines whether or not the transcriptional machinery can access and transcribe RNA molecules and altered expression of many epigenetic regulators, particularly those of the Polycomb group have been shown to affect HSC biology (Chapter 1).  Recently, in mouse and human ES cells, it has been shown that methylation of lysine 3 and lysine 27 on histone H3 play a major role in whether or not developmental genes drive an ES cell to differentiate or not, thereby playing a major role in their differentiation297.  It will be interesting to see if a similar mechanism exists for HSCs and their lineage commitment.  Although such studies are likely to require further technical advances given the small numbers of purified HSCs obtainable, initial developments along these lines appear to be underway298.  MicroRNAs have already been implicated as major players in regulating stem cell divisions (reviewed in Croce et al.299), with evidence showing that mutations in dicer-1 render a stem cell unable to bypass the G1/S checkpoint of the cell cycle300.  More recently, mouse hematopoietic cells have been shown to require specific microRNAs in order to differentiate into particular lineages (reviewed in Baltimore et al.301).  MicroRNAs have also been implicated in leukemic transformation (e.g.: mir223302) and the onset of myeloproliferative disorder (e.g.:  124 mir155303) and HSCs, themselves, are currently being profiled by a number of groups to determine their expression signature. As classic chromatin regulatory complexes and microRNAs can simultaneously regulate large numbers of genes, it is attractive to posit their involvement with major developmental changes and shifts in cell states.  Interestingly, mir101 has been shown to play a role in prostate cancer by suppressing the activity of Ezh2304, another member of the Polycomb gene group. Another microRNA family that has garnered particular interest is the let-7 family of microRNAs which regulate large numbers of genes whose transcripts are up and down-regulated during development.  Specifically, let-7 has been shown to regulate Hmga2, a gene implicated in aging in the context of stem cells305,306.  Interestingly, Hmga2 is also significantly over-expressed in FL HSCs vs. BM HSCs and appears to be stem cell specific in both the FL and BM (Chapter 5).   6.3  Concluding Comments  The results and ideas presented in this thesis support the existence of a molecularly regulated mechanism that defines a state of unlimited HSC self-renewal independent of the differentiation programs expressed when the cells are released from that state or whether they are quiescent or being activated to progress through the cell cycle.  One function of such a mechanism could be to stabilize a repressed state of various chromatin configurations that would otherwise allow multiple hematopoietic differentiation programs, particularly those associated with myelopoiesis to be rapidly activated.  The recent observations that transcription factors regulating HSCs also playing a role in regulating myelopoiesis (Gata2307) and vice versa (Pu.1308,309) is an interesting linkage between myelopoiesis and HSC self-renewal.  125 A greater understanding of exactly how the self-renewal, proliferation, and lineage commitment machinery work in relation to each other will have major implications for clinical hematology.  For example, HSCs with high self-renewal and distinct lineage differentiation programs could be isolated (or manipulated) to create the cell types needed on a patient by patient basis.  Donated cells could be expanded in a fashion that would vastly decrease the strain on many current clinical transplantation programs.  Key regulatory pathways could be up or down-regulated for the production of unlimited numbers of specific blood cell types from human embryonic or induced pluripotent stem cells, and to investigate and devise better treatments for diseases thought to arise from perturbations in particular cell types.  126   Figure 6.1 – A model detailing the relationship between the different HSC subtypes The four subtype of HSCs are located in the grey box and the relational arrows are drawn based on the in vitro and serial transplantation data that strongly suggest that α- or β-HSCs can give rise to γ- and/or δ-HSCs and that α-HSCs can give rise to β-HSCs.  As serial transplants were not performed at limit dilution, it cannot be demonstrated that β –HSCs can or cannot give rise to Serial transplant and in vitro data suggest that, cells form a hierarchy that corresponds to α-HSCs    127 References   (1)  Till JE, McCulloch EA. A direct measurement of the radiation sensitivity of normal mouse bone marrow cells. Radiat Res. 1961;14:213-222.  (2)  Till JE, McCulloch EA. Hemopoietic stem cell differentiation. Biochim Biophys Acta. 1980;605:431-459.  (3)  Spangrude GJ, Heimfeld S, Weissman IL. Purification and characterization of mouse hematopoietic stem cells. Science. 1988;241:58-62.  (4)  Ploemacher RE, Brons RHC. Separation of CFU-S from primitive cells responsible for reconstitution of the bone marrow hemopoietic stem cell compartment following irradiation: Evidence for a pre-CFU-S cell. Exp Hematol. 1989;17:263-266.  (5)  Ploemacher RE, Van Der Sluijs JP, van Beurden CAJ, Baert MRM, Chan PL. Use of limiting-dilution type long-term marrow cultures in frequency analysis of marrow- repopulating and spleen colony- forming hematopoietic stem cells in the mouse. Blood. 1991;78:2527-2533.  (6)  Jones RJ, Wagner JE, Sharkis SJ, and Celano P. Separation of pluripotent hematopoietic stem cells (PHSC) from multipotential progenitors (CFU-S) [abstract]. Blood. 1989;74:114a.  (7)  Jones RJ, Wagner JE, Celano P, Zicha MS, Sharkis SJ. Separation of pluripotent haematopoietic stem cells from spleen colony-forming cells. Nature. 1990;347:188-189.  (8)  Dameshek W. Some speculations on the myeloproliferative syndromes. Blood. 1951;6:372-375.  (9)  Nowell PC, Hungerford DA. Chromosome studies on normal and leukemic human leukocytes. J Natl Cancer Inst. 1960;25:85-109.  (10)  Dick JE, Magli MC, Huszar D, Phillips RA, Bernstein A. Introduction of a selectable gene into primitive stem cells capable of long-term reconstitution of the hemopoietic system of W/Wv mice. Cell. 1985;42:71-79.  (11)  Keller G, Paige C, Gilboa E, Wagner EF. Expression of a foreign gene in myeloid and lymphoid cells derived from multipotent haematopoietic precursors. Nature. 1985;318:149-154.  (12)  Lemischka IR, Raulet DH, Mulligan RC. Developmental potential and dynamic behavior of hematopoietic stem cells. Cell. 1986;45:917-927.  (13)  Wu AM, Till JE, Siminovitch L, McCulloch EA. Cytological evidence for a relationship between normal hemotopoietic colony-forming cells and cells of the lymphoid system. J Exp Med. 1968;127:455-464.  (14)  Szilvassy SJ. The biology of hematopoietic stem cells. Arch Med Res. 2003;34:446-460.  128  (15)  Szilvassy SJ, Nicolini FE, Eaves CJ, Miller CL. Quantitation of murine and human hematopoietic stem cells by limiting-dilution analysis in competitively repopulated hosts. In: Jordon CT, Klug CA, eds. Methods in molecular medicine: hematopoietic stem cell protocols.63. New Jersey: Humana Press; 2002:167-187.  (16)  Benveniste P, Cantin C, Hyam D, Iscove NN. Hematopoietic stem cells engraft in mice with absolute efficiency. Nat Immunol. 2003;4:708-713.  (17)  Uchida N, Dykstra B, Lyons KJ, Leung FYK, Eaves CJ. Different in vivo repopulating activities of purified hematopoietic stem cells before and after being stimulated to divide in vitro with the same kinetics. Exp Hematol. 2003;31:1338-1347.  (18)  Bowie MB, Kent DG, Dykstra B et al. Identification of a new intrinsically timed developmental checkpoint that reprograms key hematopoietic stem cell properties. Proc Natl Acad Sci USA. 2007;104:5878-5882.  (19)  Kiel MJ, Yilmaz OH, Iwashita T et al. SLAM family receptors distinguish hematopoietic stem and progenitor cells and reveal endothelial niches for stem cells. Cell. 2005;121:1109-1121.  (20)  Yilmaz OH, Kiel MJ, Morrison SJ. SLAM family markers are conserved among hematopoietic stem cells from old and reconstituted mice and markedly increase their purity. Blood. 2006;107:924-930.  (21)  Dykstra B, Kent D, Bowie M et al. Long-term propagation of distinct hematopoietic differentiation programs in vivo. Cell Stem Cell. 2007;1:218-229.  (22)  Bryder D, Rossi DJ, Weissman IL. Hematopoietic stem cells: the paradigmatic tissue- specific stem cell. Am J Pathol. 2006;169:338-346.  (23)  Kondo M, Weissman IL, Akashi K. Identification of clonogenic common lymphoid progenitors in mouse bone marrow. Cell. 1997;91:661-672.  (24)  Akashi K, Traver D, Miyamoto T, Weissman IL. A clonogenic common myeloid progenitor that gives rise to all myeloid lineages. Nature. 2000;404:193-197.  (25)  Adolfsson J, Borge OJ, Bryder D et al. Upregulation of flt3 expression within the bone marrow Lin-Sca1+c-kit+ stem cell compartment is accompanied by loss of self-renewal capacity. Immunity. 2001;15:659-669.  (26)  Orkin SH, Zon LI. Hematopoiesis: an evolving paradigm for stem cell biology. Cell. 2008;132:631-644.  (27)  Cumano A, Dieterlen-Lievre F, Godin I. Lymphoid potential, probed before circulation in mouse, is restricted to caudal intraembryonic splanchnopleura. Cell. 1996;86:907-916.  (28)  Dzierzak E. Hematopoietic stem cells and their precursors: developmental diversity and lineage relationships. Immunol Rev. 2002;187:126-138.  (29)  Gekas C, Dieterlen-Lievre F, Orkin SH, Mikkola HK. The placenta is a niche for hematopoietic stem cells. Dev Cell. 2005;8:365-375.  129  (30)  Ottersbach K, Dzierzak E. The murine placenta contains hematopoietic stem cells within the vascular labyrinth region. Dev Cell. 2005;8:377-387.  (31)  Spangrude GJ, Brooks DM, Tumas DB. Long-term repopulation of irradiated mice with limiting numbers of purified hematopoietic stem cells:  in vivo expansion of stem cell phenotype but not function. Blood. 1995;85:1006-1016.  (32)  Eaves CJ, Eaves AC. Part II. Cell biology and pathobiology. Anatomy and physiology of hematopoiesis. In: Pui C-H, ed. Childhood Leukemias. Cambridge: Cambridge University Press; 2006:69-105.  (33)  Morrison SJ, Lagasse E, Weissman IL. Demonstration that thylo subsets of mouse bone marrow that express high levels of lineage markers are not significant hematopoietic progenitors. Blood. 1994;83:3480-3490.  (34)  Muller-Sieburg CE, Sieburg HB. The GOD of hematopoietic stem cells: a clonal diversity model of the stem cell compartment. Cell Cycle. 2006;5:394-398.  (35)  Orford KW, Scadden DT. Deconstructing stem cell self-renewal: genetic insights into cell-cycle regulation. Nat Rev Genet. 2008;9:115-128.  (36)  Xie T, Li L. Stem cells and their niche: an inseparable relationship. Development. 2007;134:2001-2006.  (37)  Kent D, Copley M, Benz C et al. Regulation of hematopoietic stem cells by the steel factor-KIT signaling pathway. Clin Cancer Res. 2008;14:1926-1930.  (38)  Zon LI. Intrinsic and extrinsic control of haematopoietic stem-cell self-renewal. Nature. 2008;453:306-313.  (39)  Knoblich JA. Mechanisms of asymmetric stem cell division. Cell. 2008;132:583-597.  (40)  Lin H. The stem-cell niche theory: lessons from flies. Nat Rev Genet. 2002;3:931-940.  (41)  Xie T, Spradling AC. decapentaplegic is essential for the maintenance and division of germline stem cells in the Drosophila ovary. Cell. 1998;94:251-260.  (42)  Trevisan M, Yan X-Q, Iscove NN. Cycle initiation and colony formation in culture by murine marrow cells with long-term reconstituting potential in vivo. Blood. 1996;88:4149-4158.  (43)  Bowie MB, McKnight KD, Kent DG et al. Hematopoietic stem cells proliferate until after birth and show a reversible phase-specific engraftment defect. J Clin Invest. 2006;116:2808-2816.  (44)  Cheshier SH, Morrison SJ, Liao X, Weissman IL. In vivo proliferation and cell cycle kinetics of long-term self-renewing hematopoietic stem cells. Proc Natl Acad Sci USA. 1999;96:3120-3125.  (45)  Kay HEM. How many cell-generations? Lancet. 1965;2:418-419.  130  (46)  Bradford GB, Williams B, Rossi R, Bertoncello I. Quiescence, cycling, and turnover in the primitive hematopoietic stem cell compartment. Exp Hematol. 1997;25:445-453.  (47)  Wilson A, Laurenti E, Oser G et al. Hematopoietic stem cells reversibly switch from dormancy to self-renewal during homeostasis and repair. Cell. 2008;135:1118-1129.  (48)  Foudi A, Hochedlinger K, Van Buren D et al. Analysis of histone 2B-GFP retention reveals slowly cycling hematopoietic stem cells. Nat Biotechnol. 2008.  (49)  Kerr JFR, Wyllie AH, Currie AR. Apoptosis: A basic biological phenomenon with wide- ranging implications in tissue kinetics. Br J Cancer. 1972;26:239-257.  (50)  Sentman CL, Shutter JR, Hockenbery D, Kanagawa O, Korsmeyer SJ. bcl-2 inhibits multiple forms of apoptosis but not negative selection in thymocytes. Cell. 1991;67:879- 888.  (51)  McDonnell TJ, Nunez G, Platt FM et al. Deregulated Bcl-2-immunoglobulin transgene expands a resting but responsive immunoglobulin M and D-expressing B-cell population. Mol Cell Biol. 1990;10:1901-1907.  (52)  Werlen G, Hausmann B, Naeher D, Palmer E. Signaling life and death in the thymus: timing is everything. Science. 2003;299:1859-1863.  (53)  Bauman JG, de Vries P, Pronk B, Visser JW. Purification of murine hemopoietic stem cells and committed progenitors by fluorescence activated cell sorting using wheat germ agglutinin and monoclonal antibodies. Acta Histochem Suppl. 1988;36:241-253.  (54)  Domen J, Gandy KL, Weissman IL. Systemic overexpression of BCL-2 in the hematopoietic system protects transgenic mice from the consequences of lethal irradiation. Blood. 1998;91:2272-2282.  (55)  McCulloch EA, Siminovitch L, Till JE, Russell ES, Bernstein SE. The cellular basis of the genetically determined hemopoietic defect in anaemic mice of genotype Sld/Sld. Blood. 1965;26:399-410.  (56)  Lord BI, Testa NG, Hendry JH. The relative spatial distributions of CFUs and CFUc in the normal mouse femur. Blood. 1975;46:65-72.  (57)  Schofield R. The relationship between the spleen colony-forming cell and the haemopoietic stem cell. Blood Cells. 1978;4:7-25.  (58)  Nilsson SK, Dooner MS, Tiarks CY, Weier HU, Quesenberry PJ. Potential and distribution of transplanted hematopoietic stem cells in a nonablated mouse model. Blood. 1997;89:4013-4020.  (59)  Arai F, Hirao A, Ohmura M et al. Tie2/angiopoietin-1 signaling regulates hematopoietic stem cell quiescence in the bone marrow niche. Cell. 2004;118:149-161.  (60)  Celso CL, Fleming HE, Wu JW et al. Live-animal tracking of individual haematopoietic stem/progenitor cells in their niche. Nature. 2008.  131  (61)  Taoudi S, Gonneau C, Moore K et al. Extensive hematopoietic stem cell generation in the AGM region via maturation of VE-cadherin+CD45+ pre-definitive HSCs. Cell Stem Cell. 2008;3:99-108.  (62)  Oostendorp RA, Robin C, Steinhoff C et al. Long-term maintenance of hematopoietic stem cells does not require contact with embryo-derived stromal cells in cocultures. Stem Cells. 2005;23:842-851.  (63)  Chute JP, Saini AA, Chute DJ et al. Ex vivo culture with human brain endothelial cells increases the SCID-repopulating capacity of adult human bone marrow. Blood. 2002;100:4433-4439.  (64)  Moore KA, Ema H, Lemischka IR. In vitro maintenance of highly purified, transplantable hematopoietic stem cells. Blood. 1997;89:4337-4347.  (65)  Calvi LM, Adams GB, Weibrecht KW et al. Osteoblastic cells regulate the haematopoietic stem cell niche. Nature. 2003;425:841-846.  (66)  Zhang J, Niu C, Ye L et al. Identification of the haematopoietic stem cell niche and control of the niche size. Nature. 2003;425:836-841.  (67)  Mayack SR, Wagers AJ. Osteolineage niche cells initiate hematopoietic stem cell mobilization. Blood. 2008;112:519-531.  (68)  Kiel MJ, Morrison SJ. Uncertainty in the niches that maintain haematopoietic stem cells. Nat Rev Immunol. 2008;8:290-301.  (69)  Metcalf D. Hematopoietic cytokines. Blood. 2008;111:485-491.  (70)  Rebel VI, Dragowska W, Eaves CJ, Humphries RK, Lansdorp PM. Amplification of Sca- 1+ Lin- WGA+ cells in serum- free cultures containing Steel factor, interleukin-6, and erythropoietin with maintenance of cells with long-term in vivo reconstituting potential. Blood. 1994;83:128-136.  (71)  Fortunel NO, Hatzfeld A, Hatzfeld JA. Transforming growth factor-β: pleiotropic role in the regulation of hematopoiesis. Blood. 2000;96:2022-2036.  (72)  Bryder D, Ramsfjell V, Dybedal I et al. Self-renewal of multipotent long-term repopulating hematopoietic stem cells is negatively regulated by fas and tumor necrosis factor receptor activation. J Exp Med. 2001;194:941-952.  (73)  Ogawa M, Matsunaga T. Humoral regulation of hematopoietic stem cells. Ann N Y Acad Sci. 1999;872:17-23.  (74)  Audet J, Miller CL, Rose-John S, Piret J, Eaves CJ. Distinct role of gp130 activation in promoting self-renewal divisions by mitogenically stimulated murine hematopoietic stem cells. Proc Natl Acad Sci USA. 2001;98:1757-1762.  (75)  Krause DS, Fackler MJ, Civin CI, May WS. CD34: structure, biology, and clinical utility. Blood. 1996;87:1-13.  132  (76)  Ghaffari S, Smadja-Joffe F, Oostendorp R et al. CD44 isoforms in normal and leukemic hematopoiesis. Exp Hematol. 1999;27:978-993.  (77)  Papayannopoulou T, Craddock C, Nakamoto B, Priestley GV, Wolf NS. The VLA4/VCAM-1 adhesion pathway defines contrasting mechanisms of lodgement of transplanted murine hemopoietic progenitors between bone marrow and spleen. Proc Natl Acad Sci USA. 1995;92:9647-9651.  (78)  van der Loo JC, Xiao X, McMillin D et al. VLA-5 is expressed by mouse and human long-term repopulating hematopoietic cells and mediates adhesion to extracellular matrix protein fibronectin. J Clin Invest. 1998;102:1051-1061.  (79)  Chan JY, Watt SM. Adhesion receptors on haematopoietic progenitor cells. Br J Haematol. 2001;112:541-557.  (80)  Wypych J, Bennett LG, Schwartz MG et al. Soluble kit receptor in human serum. Blood. 1995;85:66-73.  (81)  Zsebo KM, Wypych J, McNiece IK et al. Identification, purification, and biological characterization of hematopoietic stem cell factor from buffalo rat liver--conditioned medium. Cell. 1990;63:195-201.  (82)  McCulloch EA, Siminovitch L, Till JE. Spleen colony formation in anemic mice of genotype W/Wv. Science. 1964;144:844-846.  (83)  Geissler EN, McFarland EC, Russell ES. Analysis of pleiotropism at the dominant white- spotting (W) locus of the house mouse: A description of ten new W alleles. Genetics. 1981;97:337-361.  (84)  Miller CL, Eaves CJ. Expansion in vitro of adult murine hematopoietic stem cells with transplantable lympho-myeloid reconstituting ability. Proc Natl Acad Sci USA. 1997;94:13648-13653.  (85)  Huang E, Nocka K, Beier DR et al. The hematopoietic growth factor KL is encoded by the Sl locus and is the ligand of the c-kit receptor, the gene product of the W locus. Cell. 1990;63:225-233.  (86)  Ikuta K, Weissman IL. Evidence that hematopoietic stem cells express mouse c-kit but do not depend on steel factor for their generation. Proc Natl Acad Sci USA. 1992;89:1502- 1506.  (87)  Bowie MB, Kent DG, Copley MR, Eaves CJ. Steel factor responsiveness regulates the high self-renewal phenotype of fetal hematopoietic stem cells. Blood. 2007;109:5043- 5048.  (88)  Ashman LK. The biology of stem cell factor and its receptor C-kit. Int J Biochem Cell Biol. 1999;31:1037-1051.  (89)  Zandstra PW, Conneally E, Petzer AL, Piret JM, Eaves CJ. Cytokine manipulation of primitive human hematopoietic cell self-renewal. Proc Natl Acad Sci USA. 1997;94:4698-4703.  133  (90)  Audet J, Miller CL, Eaves CJ, Piret JM. Common and distinct features of cytokine effects on hematopoietic stem and progenitor cells revealed by dose response surface analysis. Biotechnol Bioeng. 2002;80:393-404.  (91)  Linnekin D. Early signaling pathways activated by c-Kit in hematopoietic cells. Int J Biochem Cell Biol. 1999;31:1053-1074.  (92)  Weiler SR, Mou S, DeBerry CS et al. JAK2 is associated with the c-kit proto-oncogene product and is phosphorylated in response to stem cell factor. Blood. 1996;87:3688-3693.  (93)  Tang B, Mano H, Yi T, Ihle JN. Tec kinase associates with c-kit and is tyrosine phosphorylated and activated following stem cell factor binding. Mol Cell Biol. 1994;14:8432-8437.  (94)  Jhun BH, Rivnay B, Price D, Avraham H. The MATK tyrosine kinase interacts in a specific and SH2-dependent manner with c-Kit. J Biol Chem. 1995;270:9661-9666.  (95)  Kozlowski M, Larose L, Lee F et al. SHP-1 binds and negatively modulates the c-Kit receptor by interaction with tyrosine 569 in the c-Kit juxtamembrane domain. Mol Cell Biol. 1998;18:2089-2099.  (96)  Linnekin D. Early signaling pathways activated by c-Kit in hematopoietic cells. Int J Biochem Cell Biol. 1999;31:1053-1074.  (97)  Jahn T, Leifheit E, Gooch S, Sindhu S, Weinberg K. Lipid rafts are required for Kit survival and proliferation signals. Blood. 2007;110:1739-1747.  (98)  Engstrom M, Karlsson R, Jonsson JI. Inactivation of the forkhead transcription factor FoxO3 is essential for PKB-mediated survival of hematopoietic progenitor cells by kit ligand. Exp Hematol. 2003;31:316-323.  (99)  Wandzioch E, Edling CE, Palmer RH, Carlsson L, Hallberg B. Activation of the MAP kinase pathway by c-Kit is PI-3 kinase dependent in hematopoietic progenitor/stem cell lines. Blood. 2004;104:51-57.  (100)  Deberry C, Mou S, Linnekin D. Stat1 associates with c-kit and is activated in response to stem cell factor. Biochem J. 1997;327 ( Pt 1):73-80.  (101)  Gotoh A, Takahira H, Mantel C et al. Steel factor induces serine phosphorylation of Stat3 in human growth factor-dependent myeloid cell lines. Blood. 1996;88:138-145.  (102)  Ryan JJ, Huang H, McReynolds LJ et al. Stem cell factor activates STAT-5 DNA binding in IL-3-derived bone marrow mast cells. Exp Hematol. 1997;25:357-362.  (103)  Kiger AA, Jones DL, Schulz C, Rogers MB, Fuller MT. Stem cell self-renewal specified by JAK-STAT activation in response to a support cell cue. Science. 2001;294:2542-2545.  (104)  Yoshida K, Taga T, Saito M et al. Targeted disruption of gp130, a common signal transducer for the interleukin 6 family of cytokines, leads to myocardial and hematological disorders. Proc Natl Acad Sci USA. 1996;93:407-411.  134  (105)  Miller CL, Eaves CJ. Expansion in vitro of adult murine hematopoietic stem cells with transplantable lympho-myeloid reconstituting ability. Proc Natl Acad Sci U S A. 1997;94:13648-13653.  (106)  Holyoake TL, Freshney MG, McNair L et al. Ex vivo expansion with stem cell factor and interleukin-11 augments both short-term recovery posttransplant and the ability to serially transplant marrow. Blood. 1996;87:4589-4595.  (107)  Yonemura Y, Ku H, Lyman SD, Ogawa M. In vitro expansion of hematopoietic progenitors and maintenance of stem cells: comparison between Flt3/Flk-2 ligand and kit ligand. Blood. 1997;89:1915-1921.  (108)  Matsunaga T, Hirayama F, Yonemura Y, Murray R, Ogawa M. Negative regulation by interleukin-3 (IL-3) of mouse early B-cell progenitors and stem cells in culture: transduction of the negative signals by βc and βIL-3 proteins of IL-3 receptor and absence of negative regulation by granulocyte-macrophage colony-stimulating factor. Blood. 1998;92:901-907.  (109)  Yonemura Y, Ku H, Hirayama F, Souza LM, Ogawa M. Interleukin 3 or interleukin 1 abrogates the reconstituting ability of hematopoietic stem cells. Proc Natl Acad Sci USA. 1996;93:4040-4044.  (110)  Traycoff CM, Cornetta K, Yoder MC, Davidson A, Srour EF. Ex vivo expansion of murine hematopoietic progenitor cells generates classes of expanded cells possessing different levels of bone marrow repopulating potential. Exp Hematol. 1996;24:299-306.  (111)  Alexander WS, Roberts AW, Nicola NA, Li R, Metcalf D. Deficiencies in progenitor cells of multiple hematopoietic lineages and defective megakaryocytopoiesis in mice lacking the thrombopoietin receptor c-Mpl. Blood. 1996;87:2162-2170.  (112)  Carver-Moore K, Broxmeyer HE, Luoh S-M et al. Low levels of erythroid and myeloid progenitors in thrombopoietin-and c-mpl - deficient mice. Blood. 1996;88:803-808.  (113)  Matsunaga T, Kato T, Miyazaki H, Ogawa M. Thrombopoietin promotes the survival of murine hematopoietic long-term reconstituting cells:  Comparison with the effects of FLT3/FLK-2 ligand and interleukin-6. Blood. 1998;92:452-461.  (114)  Ema H, Takano H, Sudo K, Nakauchi H. In vitro self-renewal division of hematopoietic stem cells. J Exp Med. 2000;192:1281-1288.  (115)  Purton LE, Bernstein ID, Collins SJ. All-trans retinoic acid enhances the long-term repopulating activity of cultured hematopoietic stem cells. Blood. 2000;95:470-477.  (116)  Purton LE, Dworkin S, Olsen GH et al. RARgamma is critical for maintaining a balance between hematopoietic stem cell self-renewal and differentiation. J Exp Med. 2006;203:1283-1293.  (117)  Song X, Xie T. Wingless signaling regulates the maintenance of ovarian somatic stem cells in Drosophila. Development. 2003;130:3259-3268.  135  (118)  Willert K, Brown JD, Danenberg E et al. Wnt proteins are lipid-modified and can act as stem cell growth factors [abstract]. Nature. 2003;423:448-452.  (119)  Reya T, Duncan AW, Ailles L et al. A role for Wnt signalling in self-renewal of haematopoietic stem cells. Nature. 2003;423:409-414.  (120)  Kirstetter P, Anderson K, Porse BT, Jacobsen SE, Nerlov C. Activation of the canonical Wnt pathway leads to loss of hematopoietic stem cell repopulation and multilineage differentiation block. Nat Immunol. 2006;7:1048-1056.  (121)  Varnum-Finney B, Purton LE, Yu M et al. The notch ligand, Jagged-1, influences the development of primitive hematopoietic precursor cells. Blood. 1998;91:4084-4091.  (122)  Karanu FN, Murdoch B, Gallacher L et al. The Notch ligand Jagged-1 represents a novel growth factor of human hematopoietic stem cells. J Exp Med. 2000;192:1365-1372.  (123)  Kunisato A, Chiba S, Nakagami-Yamaguchi E et al. HES-1 preserves purified hematopoietic stem cells ex vivo and accumulates side population cells in vivo. Blood. 2003;101:1777-1783.  (124)  Maillard I, Weng AP, Carpenter AC et al. Mastermind critically regulates Notch- mediated lymphoid cell fate decisions. Blood. 2004;104:1696-1702.  (125)  Guilbert LJ, Iscove NN. Partial replacement of serum by selenite, transferrin, albumin and lecithin in haemopoietic cell cultures. Nature. 1976;263:594-595.  (126)  Nakae J, Kido Y, Accili D. Distinct and overlapping functions of insulin and IGF-I receptors. Endocr Rev. 2001;22:818-835.  (127)  Zhang CC, Lodish HF. Insulin-like growth factor 2 expressed in a novel fetal liver cell population is a growth factor for hematopoietic stem cells. Blood. 2004;103:2513-2521.  (128)  Zhang CC, Kaba M, Iizuka S, Huynh H, Lodish HF. Angiopoietin-like 5 and IGFBP2 stimulate ex vivo expansion of human cord blood hematopoietic stem cells as assayed by NOD/SCID transplantation. Blood. 2008;111:3415-3423.  (129)  Zon LI. Intrinsic and extrinsic control of haematopoietic stem-cell self-renewal. Nature. 2008;453:306-313.  (130)  Oh I-H, Eaves CJ. Overexpression of a dominant negative form of STAT3 selectively impairs hematopoietic stem cell activity. Oncogene. 2002;21:4778-4787.  (131)  Bunting KD, Bradley HL, Hawley TS et al. Reduced lymphomyeloid repopulating activity from adult bone marrow and fetal liver of mice lacking expression of STAT5. Blood. 2002;99:479-487.  (132)  Li G, Wang Z, Zhang Y et al. STAT5 requires the N-domain to maintain hematopoietic stem cell repopulating function and appropriate lymphoid-myeloid lineage output. Exp Hematol. 2007;35:1684-1694.  136  (133)  Schepers H, van Gosliga D, Wierenga AT et al. STAT5 is required for long-term maintenance of normal and leukemic human stem/progenitor cells. Blood. 2007;110:2880-2888.  (134)  Chung Y-J, Park B-B, Kang Y-J et al. Unique effects of STAT3 on the early phase of hematopoietic stem cell regeneration. Blood. 2006;108:1208-1215.  (135)  Kato Y, Iwama A, Tadokoro Y et al. Selective activation of STAT5 unveils its role in stem cell self-renewal in normal and leukemic hematopoiesis. J Exp Med. 2005;202:169- 179.  (136)  Buszczak M, Spradling AC. Searching chromatin for stem cell identity. Cell. 2006;125:233-236.  (137)  Ringrose L, Paro R. Epigenetic regulation of cellular memory by the Polycomb and Trithorax group proteins. Annu Rev Genet. 2004;38:413-443.  (138)  Lessard J, Sauvageau G. Bmi-1 determines the proliferative capacity of normal and leukaemic stem cells. Nature. 2003;423:255-260.  (139)  Park IK, Qian D, Kiel M et al. Bmi-1 is required for maintenance of adult self-renewing haematopoietic stem cells. Nature. 2003;423:302-305.  (140)  Ohta H, Sawada A, Kim JY et al. Polycomb group gene rae28 is required for sustaining activity of hematopoietic stem cells. J Exp Med. 2002;195:759-770.  (141)  Kamminga LM, Bystrykh LV, de Boer A et al. The Polycomb group gene Ezh2 prevents hematopoietic stem cell exhaustion. Blood. 2006;107:2170-2179.  (142)  Kajiume T, Ninomiya Y, Ishihara H, Kanno R, Kanno M. Polycomb group gene mel-18 modulates the self-renewal activity and cell cycle status of hematopoietic stem cells. Exp Hematol. 2004;32:571-578.  (143)  Chun T, Rho SB, Byun HJ, Lee JY, Kong G. The polycomb group gene product Mel-18 interacts with cyclin D2 and modulates its activity. FEBS Lett. 2005;579:5275-5280.  (144)  Antonchuk J, Sauvageau G, Humphries RK. HoxB4-induced expansion of adult hematopoietic stem cells ex vivo. Cell. 2002;109:39-45.  (145)  Ohta H*, Sekulovic S*, Bakovic S et al. Near-maximal expansion of hematopoietic stem cells in culture using NUP98-HOX fusions. Exp Hematol. 2007;35:817-830.  (146)  Sherr CJ, Roberts JM. Living with or without cyclins and cyclin-dependent kinases. Genes Dev. 2004;18:2699-2711.  (147)  Kozar K, Ciemerych MA, Rebel VI et al. Mouse development and cell proliferation in the absence of D-cyclins. Cell. 2004;118:477-491.  (148)  Mantel C, Lou Z, Canfield J et al. Involvement of p21cip-1 and p27kip-1 in the molecular mechanisms of steel factor-induced proliferative synergy in vitro and of p21cip-1 in the maintenance of stem/progenitor cells in vivo. Blood. 1996;88:3710-3719.  137  (149)  Cheng T, Rodrigues N, Shen H et al. Hematopoietic stem cell quiescence maintained by p21cip1/waf1. Science. 2000;287:1804-1808.  (150)  Janzen V, Forkert R, Fleming HE et al. Stem-cell ageing modified by the cyclin- dependent kinase inhibitor p16INK4a. Nature. 2006;443:421-426.  (151)  Yuan Y, Shen H, Franklin DS, Scadden DT, Cheng T. In vivo self-renewing divisions of haematopoietic stem cells are increased in the absence of the early G1-phase inhibitor, p18INK4C. Nat Cell Biol. 2004;6:436-442.  (152)  Yu H, Yuan Y, Shen H, Cheng T. Hematopoietic stem cell exhaustion impacted by p18 INK4C and p21 Cip1/Waf1 in opposite manners. Blood. 2006;107:1200-1206.  (153)  Galderisi U, Cipollaro M, Giordano A. The retinoblastoma gene is involved in multiple aspects of stem cell biology. Oncogene. 2006;25:5250-5256.  (154)  Walkley CR, Shea JM, Sims NA, Purton LE, Orkin SH. Rb regulates interactions between hematopoietic stem cells and their bone marrow microenvironment. Cell. 2007;129:1081-1095.  (155)  Saha S, Sparks AB, Rago C et al. Using the transcriptome to annotate the genome. Nat Biotechnol. 2002;20:508-512.  (156)  Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis of gene expression. Science. 1995;270:484-487.  (157)  Naef F, Socci ND, Magnasco M. A study of accuracy and precision in oligonucleotide arrays: extracting more signal at large concentrations. Bioinformatics. 2003;19:178-184.  (158)  Butte A. The use and analysis of microarray data. Nat Rev Drug Discov. 2002;1:951-960.  (159)  Bustin SA. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol. 2000;25:169-193.  (160)  Bustin SA. Quantification of mRNA using real-time reverse transcription PCR (RT- PCR): trends and problems. J Mol Endocrinol. 2002;29:23-39.  (161)  Iscove NN, Barbara M, Gu M et al. Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA. Nat Biotechnol. 2002;20:940-943.  (162)  Peters DG, Kassam AB, Yonas H et al. Comprehensive transcript analysis in small quantities of mRNA by SAGE-lite. Nucleic Acids Res. 1999;27:e39.  (163)  Rudnicki M, Eder S, Schratzberger G et al. Reliability of t7-based mRNA linear amplification validated by gene expression analysis of human kidney cells using cDNA microarrays. Nephron Exp Nephrol. 2004;97:e86-e95.  (164)  Schneider J, Buness A, Huber W et al. Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments. BMC Genomics. 2004;5:29.  138  (165)  Georgantas RWI, Tanadve V, Malehorn M et al. Microarray and serial analysis of gene expression analyses identify known and novel transcripts overexpressed in hematopoietic stem cells. Cancer Res. 2004;64:4434-4441.  (166)  Slukvin I, Vodyanik M, Choi K-D et al. Delinition of cellular pathways of hematopoietic development from human embryonic stem cells (hESCs) [abstract].  2008.  (167)  Bruno L, Hoffmann R, McBlane F et al. Molecular signatures of self-renewal, differentiation, and lineage choice in multipotential hemopoietic progenitor cells in vitro. Mol Cell Biol. 2004;24:741-756.  (168)  Chen CZ, Li M, de Graaf D et al. Identification of endoglin as a functional marker that defines long-term repopulating hematopoietic stem cells. Proc Natl Acad Sci USA. 2002;99:15468-15473.  (169)  Ivanova NB, Dimos JT, Schaniel C et al. A stem cell molecular signature. Science. 2002;298:601-604.  (170)  Ohmine K, Ota J, Ueda M et al. Characterization of stage progression in chronic myeloid leukemia by DNA microarray with purified hematopoietic stem cells. Oncogene. 2001;20:8249-8257.  (171)  Park IK, He Y, Lin F et al. Differential gene expression profiling of adult murine hematopoietic stem cells. Blood. 2002;99:488-498.  (172)  Phillips RL, Ernst RE, Brunk B et al. The genetic program of hematopoietic stem cells. Science. 2000;288:1635-1640.  (173)  Ramalho-Santos M, Yoon S, Matsuzaki Y, Mulligan RC, Melton DA. "Stemness": transcriptional profiling of embryonic and adult stem cells. Science. 2002;298:597-600.  (174)  Terskikh AV, Easterday MC, Li L et al. From hematopoiesis to neuropoiesis: evidence of overlapping genetic programs. Proc Natl Acad Sci USA. 2001;98:7934-7939.  (175)  Siminovitch L, McCulloch EA, Till JE. The distribution of colony-forming cells among spleen colonies. J Cell Physiol. 1963;62:327-336.  (176)  Lemischka IR, Raulet DH, Mulligan RC. Developmental potential and dynamic behavior of hematopoietic stem cells. Cell. 1986;45:917-927.  (177)  Snodgrass R, Keller G. Clonal fluctuation within the haematopoietic system of mice reconstituted with retrovirus-infected stem cells. EMBO J. 1987;6:3955-3960.  (178)  Jordan CT, Lemischka IR. Clonal and systemic analysis of long-term hematopoiesis in the mouse. Genes Dev. 1990;4:220-232.  (179)  Muller-Sieburg CE, Sieburg HB. The GOD of hematopoietic stem cells: a clonal diversity model of the stem cell compartment. Cell Cycle. 2006;5:394-398.  (180)  Metcalf D. Lineage commitment and maturation in hematopoietic cells: the case for extrinsic regulation. Blood. 1998;92:345-347.  139  (181)  Moore KA, Lemischka IR. Stem cells and their niches. Science. 2006;311:1880-1885.  (182)  Till JE, McCulloch EA, Siminovitch L. A stochastic model of stem cell proliferation, based on the growth of spleen colony-forming cells. Proc Natl Acad Sci U S A. 1964;51:29-36.:29-36.  (183)  Kirkland MA. A phase space model of hemopoiesis and the concept of stem cell renewal. Exp Hematol. 2004;32:511-519.  (184)  Roeder I, Kamminga LM, Braesel K et al. Competitive clonal hematopoiesis in mouse chimeras explained by a stochastic model of stem cell organization. Blood. 2005;105:609-616.  (185)  Puri MC, Bernstein A. Requirement for the TIE family of receptor tyrosine kinases in adult but not fetal hematopoiesis. Proc Natl Acad Sci USA. 2003;100:12753-12758.  (186)  Adams GB, Chabner KT, Alley IR et al. Stem cell engraftment at the endosteal niche is specified by the calcium-sensing receptor. Nature. 2006;439:599-603.  (187)  Sugiyama T, Kohara H, Noda M, Nagasawa T. Maintenance of the hematopoietic stem cell pool by CXCL12-CXCR4 chemokine signaling in bone marrow stromal cell niches. Immunity. 2006;25:977-988.  (188)  Nagasawa T, Hirota S, Tachibana K et al. Defects of B-cell lymphopoiesis and bone- marrow myelopoiesis in mice lacking the CXC chemokine PBSF/SDF-1. Nature. 1996;635-638.  (189)  Ara T, Tokoyoda K, Sugiyama T et al. Long-term hematopoietic stem cells require stromal cell-derived factor-1 for colonizing bone marrow during ontogeny. Immunity. 2003;19:257-267.  (190)  Trowbridge JJ, Scott MP, Bhatia M. Hedgehog modulates cell cycle regulators in stem cells to control hematopoietic regeneration. Proc Natl Acad Sci U S A. 2006;103:14134- 14139.  (191)  Stier S, Ko Y, Forkert R et al. Osteopontin is a hematopoietic stem cell niche component that negatively regulates stem cell pool size. J Exp Med. 2005;201:1781-1791.  (192)  Nilsson SK, Johnston HM, Whitty GA et al. Osteopontin, a key component of the hematopoietic stem cell niche and regulator of primitive hematopoietic progenitor cells. Blood. 2005;106:1232-1239.  (193)  Barker JE. S1/S1d hematopoietic progenitors are deficient in situ. Exp Hematol. 1994;22:174-177.  (194)  McCarthy KF, Ledney GD, Mitchell R. A deficiency of hematopoietic stem cells in steel mice. Cell Tissue Kinet. 1977;10:121-126.  (195)  Yoshihara H, Arai F, Hosokawa K et al. Thrombopoietin/MPL signaling regulates hematopoietic stem cell quiescence and interation with the osteoblastic niche. Cell Stem Cell. 2007;1:685-697.  140  (196)  Guerriero A, Worford L, Holland HK et al. Thrombopoietin is synthesized by bone marrow stromal cells. Blood. 1997;90:3444-3455.  (197)  Sungaran R, Markovic B, Chong BH. Localization and regulation of thrombopoietin mRNa expression in human kidney, liver, bone marrow, and spleen using in situ hybridization. Blood. 1997;89:101-107.  (198)  Kimura S, Roberts AW, Metcalf D, Alexander WS. Hematopoietic stem cell deficiencies in mice lacking c-Mpl, the receptor for thrombopoietin. Proc Natl Acad Sci USA. 1998;95:1195-1200.  (199)  Kaushansky K. Thrombopoietin: accumulating evidence for an important biological effect on the hematopoietic stem cell. Ann N Y Acad Sci. 2003;996:39-43.  (200)  Qian H, Buza-Vidas N, Hyland CD et al. Critical role of thrombopoietin in maintaining adult quiescent hematopoietic stem cells. Cell Stem Cell. 2007;1:671-684.  (201)  Qian Z, Chen L, Fernald AA, Williams BO, Le Beau MM. A critical role for Apc in hematopoietic stem and progenitor cell survival. J Exp Med. 2008;205:2163-2175.  (202)  Zeng H, Yucel R, Kosan C, Klein-Hitpass L, Moroy T. Transcription factor Gfi1 regulates self-renewal and engraftment of hematopoietic stem cells. EMBO J. 2004;23:4116-4125.  (203)  Wright EG, Lorimore SA. Haemopoietic stem cell proliferation in the bone marrow of Sl/Sld mice. Cell Tissue Kinet. 1987;20:301-310.  (204)  Lacorazza HD, Yamada T, Liu Y et al. The transcription factor MEF/ELF4 regulates the quiescence of primitive hematopoietic cells. Cancer Cell. 2006;9:175-187.  (205)  Stier S, Cheng T, Dombkowski D, Carlesso N, Scadden DT. Notch1 activation increases hematopoietic stem cell self-renewal in vivo and favors lymphoid over myeloid lineage outcome. Blood. 2002;99:2369-2378.  (206)  Hock H, Meade E, Medeiros S et al. Tel/Etv6 is an essential and selective regulator of adult hematopoietic stem cell survival. Genes Dev. 2004;18:2336-2341.  (207)  Luis TC, Weerkamp F, Naber BA et al. Wnt3a deficiency irreversibly impairs hematopoietic stem cell self-renewal and leads to defects in progenitor cell differentiation. Blood. 2008.  (208)  Kent D, Dykstra B, Eaves C. Isolation and assessment of long-term reconstituting hematopoietic cells from adult mouse bone marrow. In: Bhatia M, Pera M, Fisher S, Patient R, Eggan K, Elefanty A, eds. Current Protocols in Stem Cell Biology. John Wiley & Sons, Inc.; 2007:4.1-4.23.  (209)  Bryder D, Rossi DJ, Weissman IL. Hematopoietic stem cells: the paradigmatic tissue- specific stem cell. Am J Pathol. 2006;169:338-346.  (210)  Sparmann A, van Lohuizen M. Polycomb silencers control cell fate, development and cancer. Nat Rev Cancer. 2006;6:846-856.  141  (211)  Unkeless JC. Characterization of a monoclonal antibody directed against mouse macrophage and lymphocyte Fc receptors. J Exp Med. 1979;150:580-596.  (212)  Robertson N, Oveisi-Fordorei M, Zuyderduyn SD et al. DiscoverySpace: an interactive data analysis application. Genome Biol. 2007;8:R6.  (213)  Audic S, Claverie JM. The significance of digital gene expression profiles. Genome Res. 1997;7:986-995.  (214)  Zhao Y, Raouf A, Kent D et al. A modified polymerase chain reaction-long serial analysis of gene expression protocol identifies novel transcripts in human CD34+ bone marrow cells . Stem Cells. 2007;25:1681-1689.  (215)  Khattra J, Delaney AD, Zhao Y et al. Large scale production of SAGE libraries from microdissected tissues, flow-sorted cells and cell lines. Genome Res. 2007;17:108-116.  (216)  Szilvassy SJ, Humphries RK, Lansdorp PM, Eaves AC, Eaves CJ. Quantitative assay for totipotent reconstituting hematopoietic stem cells by a competitive repopulation strategy. Proc Natl Acad Sci USA. 1990;87:8736-8740.  (217)  Ramshaw HS, Rao SS, Crittenden RB et al. Engraftment of bone marrow cells into normal unprepared hosts: effects of 5-fluorouracil and cell cycle status. Blood. 1995;86:924-929.  (218)  Trevisan M, Iscove N. Phenotypic analysis of murine long-term hemotopoietic reconstituting cells quantitated competitively in vivo and comparsion with more advanced colony-forming progeny. J Exp Med. 1995;181:93-103.  (219)  Harrison DE. Competitive repopulation: A new assay for long-term stem cell functional capacity. Blood. 1980;55:77-81.  (220)  Wagers AJ, Sherwood RI, Christensen JL, Weissman IL. Little evidence for developmental plasticity of adult hematopoietic stem cells. Science. 2002;297:2256- 2259.  (221)  Osawa M, Hanada KI, Hamada H, Nakauchi H. Long-term lymphohematopoietic reconstitution by a single CD34-low/negative hematopoietic stem cell. Science. 1996;273:242-245.  (222)  Christensen JL, Weissman IL. Flk-2 is a marker in hematopoietic stem cell differentiation: A simple method to isolate long-term stem cells. Proc Natl Acad Sci USA. 2001;98:14541-14546.  (223)  Balazs AB, Fabian AJ, Esmon CT, Mulligan RC. Endothelial protein C receptor (CD201) explicitly identifies hematopoietic stem cells in murine bone marrow. Blood. 2006;107:2317-2321.  (224)  Wagers AJ, Weissman IL. Differential expression of alpha2 integrin separates long-term and short-term reconstituting Lin-/loThy1.1(lo)c-kit+ Sca-1+ hematopoietic stem cells. Stem Cells. 2006;24:1087-1094.  142  (225)  Matsuzaki Y, Kinjo K, Mulligan RC, Okano H. Unexpectedly efficient homing capacity of purified murine hematopoietic stem cells. Immunity. 2004;20:87-93.  (226)  Sato T, Laver JH, Ogawa M. Reversible expression of CD34 by murine hematopoietic stem cells. Blood. 1999;94:2548-2554.  (227)  Tajima F, Deguchi T, Laver JH, Zeng H, Ogawa M. Reciprocal expression of CD38 and CD34 by adult murine hematopoietic stem cells. Blood. 2001;97:2618-2624.  (228)  Uchida N, Dykstra B, Lyons K et al. ABC transporter activities of murine hematopoietic stem cells vary according to their developmental and activation status. Blood. 2004;103:4487-4495.  (229)  Zhang CC, Lodish HF. Murine hematopoietic stem cells change their surface phenotype during ex vivo expansion. Blood. 2005;105:4314-4320.  (230)  Rebel VI, Miller CL, Thornbury GR et al. A comparison of long-term repopulating hematopoietic stem cells in fetal liver and adult bone marrow from the mouse. Exp Hematol. 1996;24:638-648.  (231)  Harrison DE, Lerner CP. Most primitive hematopoietic stem cells are stimulated to cycle rapidly after treatment with 5-fluorouracil. Blood. 1991;78:1237-1240.  (232)  Machalinski B, Wiszniewska B, Baskiewicz M et al. In vivo and in vitro studies on the toxicity of Hoechst 33342 (Ho342).  Implications for employing Ho342 for the isolation of haematopoietic stem cells. Ann Transplant. 1998;3:5-13.  (233)  Jordan CT, McKearn JP, Lemischka IR. Cellular and developmental properties of fetal hematopoietic stem cells. Cell. 1990;61:953-963.  (234)  Kent D, Dykstra B, Cheyne J, Ma E, Eaves C. Steel factor coordinately regulates the molecular signature and biologic function of hematooietic stem cells. Blood. 2008;112:560-567.  (235)  Habibian HK, Peters SO, Hsieh CC et al. The fluctuating phenotype of the lymphohematopoietic stem cell with cell cycle transit. J Exp Med. 1998;188:393-398.  (236)  Muller-Sieburg CE, Cho RH, Karlsson L, Huang JF, Sieburg HB. Myeloid-biased hematopoietic stem cells have extensive self-renewal capacity but generate diminished lymphoid progeny with impaired IL-7 responsiveness. Blood. 2004;103:4111-4118.  (237)  Lemischka IR. Clonal, in vivo behavior of the totipotent hematopoietic stem cell. Immunology. 1991;3:349-355.  (238)  Spangrude GJ, Johnson GR. Resting and activated subsets of mouse multipotent hematopoietic stem cells. Proc Natl Acad Sci USA. 1990;87:7433-7437.  (239)  Morrison SJ, Hemmati HD, Wandycz AM, Weissman IL. The purification and characterization of fetal liver hematopoietic stem cells. Proc Natl Acad Sci USA. 1995;92:10302-10306.  143  (240)  Randall TD, Weissman IL. Phenotypic and functional changes induced at the clonal level in hematopoietic stem cells after 5-fluorouracil treatment. Blood. 1997;89:3596-3606.  (241)  Orlic D, Fischer R, Nishikawa S, Nienhuis AW, Bodine DM. Purification and characterization of heterogeneous pluriopotent hematopoietic stem cell populations expressing high levels of c- kit receptor. Blood. 1993;82:762-770.  (242)  Sieburg HB, Cho RH, Dykstra B et al. The hematopoietic stem compartment consists of a limited number of discrete stem cell subsets. Blood. 2006;107:2311-2316.  (243)  Sudo K, Ema H, Morita Y, Nakauchi H. Age-associated characteristics of murine hematopoietic stem cells. J Exp Med. 2000;192:1273-1280.  (244)  Ema H, Sudo K, Seita J et al. Quantification of self-renewal capacity in single hematopoietic stem cells from normal and Lnk-deficient mice. Dev Cell. 2005;8:907-914.  (245)  Pineault N, Abramovich C, Ohta H, Humphries RK. Differential and common leukemogenic potentials of multiple NUP98-Hox fusion proteins alone or with Meis1. Mol Cell Biol. 2004;24:1907-1917.  (246)  Hock H, Hamblen MJ, Rooke HM et al. Gfi-1 restricts proliferation and preserves functional integrity of haematopoietic stem cells. Nature. 2004;431:1002-1007.  (247)  Pandolfi PP, Roth ME, Karis A et al. Targeted disruption ofthe GATA3 gene causes severe abnormalities in the nervous system and in fetal liver haematopoiesis. Nat Genet. 1995;11:40-44.  (248)  Opferman JT, Iwasaki H, Ong CC et al. Obligate role of anti-apoptotic MCL-1 in the survival of hematopoietic stem cells. Science. 2005;307:1101-1104.  (249)  Yilmaz OH, Valdez R, Theisen BK et al. Pten dependence distinguishes haematopoietic stem cells from leukaemia-initiating cells. Nature. 2006;441:475-482.  (250)  Harrison DE, Zsebo KM, Astle CM. Splenic primitive hematopoietic stem cell (PHSC) activity is enhanced by steel factor because of PHSC proliferation. Blood. 1994;83:3146- 3151.  (251)  Larsson J, Goumans MJ, Sjostrand LJ et al. Abnormal angiogenesis but intact hematopoietic potential in TGF-β type I receptor-deficient mice. EMBO J. 2001;20:1663- 1673.  (252)  Hannum C, Culpepper J, Campbell D et al. Ligand for FLT3/FLK2 receptor tyrosine kinase regulates growth of haematopoietic stem cells and is encoded by variant RNAs. Nature. 1994;368:643-648.  (253)  Hirano T, Nakajima K, Hibi M. Signaling mechanisms through gp130: a model of the cytokine system. Cytokine Growth Factor Rev. 1997;8:241-252.  (254)  Humphries RK, Eaves AC, Eaves CJ. Self-renewal of hemopoietic stem cells during mixed colony formation in vitro. Proc Natl Acad Sci USA. 1981;78:3629-3633.  144  (255)  Takano H, Ema H, Sudo K, Nakauchi H. Asymmetric division and lineage commitment at the level of hematopoietic stem cells: inference from differentiation in daughter cell and granddaughter cell pairs. J Exp Med. 2004;199:295-302.  (256)  Fairbairn LJ, Cowling GJ, Reipert BM, Dexter TM. Suppression of apoptosis allows differentiation and development of a multipotent hemopoietic cell line in the absence of added growth factors. Cell. 1993;74:823-832.  (257)  Seita J, Ema H, Ooehara J et al. Lnk negatively regulates self-renewal of hematopoietic stem cells by modifying thrombopoietin-mediated signal transduction. Proc Natl Acad Sci USA. 2007;104:2349-2354.  (258)  Purton LE, Scadden DT. Limiting factors in murine hematopoietic stem cell assays. Cell Stem Cell. 2007;1:263-270.  (259)  Dick JE, Magli MC, Huszar D, Phillips RA, Bernstein A. Introduction of a selectable gene into primitive stem cells capable of long-term reconstitution of the hemopoietic system of W/Wv mice. Cell. 1985;42:71-79.  (260)  Till JE, McCulloch EA, Siminovitch L. A stochastic model of stem cell proliferation, based on the growth of spleen colony-forming cells. Proc Natl Acad Sci USA. 1964;51:29-36.  (261)  Yang L, Bryder D, Adolfsson J et al. Identification of Lin-Sca1+kit+CD34+Flt3- short- term hematopoietic stem cells capable of rapidly reconstituting and rescuing myeloablated transplant recipients. Blood. 2005;105:2717-2723.  (262)  Wagers AJ, Weissman IL. Differential expression of α2 integrin separates long-term and short-term reconstituting Lin-/loThy1.1loc-kit+ Sca-1+ hematopoietic stem cells. Stem Cells. 2006;24:1087-1094.  (263)  Muller-Sieburg CE, Sieburg HB. Clonal diversity of the stem cell compartment. Curr Opin Hematol. 2006;13:243-248.  (264)  Venezia TA, Merchant AA, Ramos CA et al. Molecular signatures of proliferation and quiescence in hematopoietic stem cells. PLoS Biol. 2004;2:e301.  (265)  Zhang CC, Steele AD, Lindquist S, Lodish HF. Prion protein is expressed on long-term repopulating hematopoietic stem cells and is important for their self-renewal. Proc Natl Acad Sci USA. 2006;103:2184-2189.  (266)  Takaki S, Morita H, Tezuka Y, Takatsu K. Enhanced hematopoiesis by hematopoietic progenitor cells lacking intracellular adaptor protein, Lnk. J Exp Med. 2002;195:151-160.  (267)  Liu AX, Rane N, Liu JP, Prendergast GC. RhoB is dispensable for mouse development, but it modifies susceptibility to tumor formation as well as cell adhesion and growth factor signaling in transformed cells. Mol Cell Biol. 2001;21:6906-6912.  (268)  Watanabe N, Kato T, Fujita A, Ishizaki T, Narumiya S. Cooperation between mDia1 and ROCK in Rho-induced actin reorganization. Nat Cell Biol. 1999;1:136-143.  145  (269)  Peng J, Kitchen SM, West RA et al. Myeloproliferative defects following targeting of the Drf1 gene encoding the mammalian diaphanous related formin mDia1. Cancer Res. 2007;67:7565-7571.  (270)  Pedersen KM, Finsen B, Celis JE, Jensen NA. Expression of a novel murine phospholipase D homolog coincides with late neuronal development in the forebrain. J Biol Chem. 1998;273:31494-314504.  (271)  Bradshaw CD, Ella KM, Qi C et al. Effects of phorbol ester on phospholipase D and mitogen-activated protein kinase activities in T-lymphocyte cell lines. Immunol Lett. 1996;53:69-76.  (272)  Sugimoto N, Oida T, Hirota K et al. Foxp3-dependent and -independent molecules specific for CD25+CD4+ natural regulatory T cells revealed by NDA microarray analysis. Int Immunol. 2006;18:1197-1209.  (273)  Exton JH. Phospholipase D: enzymology, mechanisms of regulation, and function. Physiol Rev. 1997;77:303-320.  (274)  Denis C, Methia N, Frenette PS et al. A mouse model of severe von Willebrand disease: defects in hemostasis and thrombosis. Proc Natl Acad Sci USA. 1998;95:9524-9529.  (275)  Capron C, Lecluse Y, Kaushik AL et al. The SCL relative LYL-1 is required for fetal and adult hematopoietic stem cell function and B-cell differentiation. Blood. 2006;107:4678- 4686.  (276)  Zhong Y, Jiang L, Hiai H, Toyokuni S, Yamada Y. Overexpression of a transcription factor LYL1 induces T- and B-cell lymphoma in mice. Blood. 2007;26:6937-6947.  (277)  Morrison SJ, Weissman IL. The long-term repopulating subset of hematopoietic stem cells is deterministic and isolatable by phenotype. Immunity. 1994;1:661-673.  (278)  Goodell MA, Brose K, Paradis G, Conner AS, Mulligan RC. Isolation and functional properties of murine hematopoietic stem cells that are replicating in vivo. J Exp Med. 1996;183:1797-1806.  (279)  Li CL, Johnson GR. Rhodamine123 reveals heterogeneity within murine Lin-, Sca-1+ hemopoietic stem cells. J Exp Med. 1992;175:1443-1447.  (280)  Leemhuis T, Yoder MC, Grigsby S et al. Isolation of primitive human bone marrow hematopoietic progenitor cells using Hoechst 33342 and Rhodamine 123. Exp Hematol. 1996;24:1215-1224.  (281)  Kim I, Saunders TL, Morrison SJ. Sox17 dependence distinguishes the transcriptional regulation of fetal from adult hematopoietic stem cells. Cell. 2007;130:470-483.  (282)  Ramos CA, Bowman TA, Boles NC et al. Evidence for Diversity in Transcriptional Profiles of Single Hematopoietic Stem Cells. PLoS Genet. 2006;2.  146  (283)  Yamazaki S, Iwama A, Takayanagi S et al. Cytokine signals modulated via lipid rafts mimic niche signals and induce hibernation in hematopoietic stem cells. EMBO J. 2006;25:3515-3523.  (284)  Ema H, Morita Y, Yamazaki S et al. Adult mouse hematopoietic stem cells: purification and single-cell assays. Nat Protoc. 2006;1:2979-2987.  (285)  Dykstra B, Ramunas J, Kent D et al. High-resolution video monitoring of hematopoietic stem cells cultured in single-cell arrays identifies new features of self-renewal. Proc Natl Acad Sci USA. 2006;103:8185-8190.  (286)  Schroeder T. Tracking hematopoiesis at the single cell level. Ann N Y Acad Sci. 2005;1044:201-209.  (287)  Takano H, Ema H, Sudo K, Nakauchi H. Asymmetric division and lineage commitment at the level of hematopoietic stem cells: inference from differentiation in daughter cell and granddaughter cell pairs. J Exp Med. 2004;199:295-302.  (288)  Miranda-Saavedra D, De S, Trotter MW, Teichmann SA, Gottgens B. BloodExpress: a database of gene expression in mouse haematopoiesis. Nucleic Acids Res. 2009;37:D873-D879.  (289)  Pimanda JE, Ottersbach K, Knezevic K et al. Gata2, Fli1, and Scl form a recursively wired gene-regulatory circuit during early hematopoietic development. Proc Natl Acad Sci U S A. 2007;104:17692-17697.  (290)  Wu M, Kwon HY, Rattis F et al. Imaging hematopoietic precursor division in real time. Cell Stem Cell. 2007;1:541-554.  (291)  Yamazaki S, Iwama A, Takayanagi S et al. Cytokine signals modulated via lipid rafts mimic niche signals and induce hibernation in hematopoietic stem cells. EMBO J. 2006;25:3515-3523.  (292)  Yamazaki S, Iwama A, Takayanagi S et al. Cytokine signals modulated via lipid rafts mimic niche signals and induce hibernation in hematopoietic stem cells. EMBO J. 2006;25:3515-3523.  (293)  Iwama A, Oguro H, Negishi M et al. Enhanced self-renewal of hematopoietic stem cells mediated by the polycomb gene product Bmi-1. Immunity. 2004;21:843-851.  (294)  Liu S, Dontu G, Mantle ID et al. Hedgehog signaling and Bmi-1 regulate self-renewal of normal and malignant human mammary stem cells. Cancer Res. 2006;66:6063-6071.  (295)  Molofsky AV, Pardal R, Iwashita T et al. Bmi-1 dependence distinguishes neural stem cell self-renewal from progenitor proliferation. Nature. 2003;425:962-967.  (296)  Chen D, Zhang G. Enforced expression of the GATA-3 transcription factor affects cell fate decisions in hematopoiesis. Exp Hematol. 2001;29:971-980.  (297)  Bernstein BE, Mikkelsen TS, Xie X et al. A bivalent chromatin structure marks key developmental genes in embryonic stem cells. Cell. 2006;125:315-326.  147  (298)  Attema JL, Papathanasiou P, Forsberg EC et al. Epigenetic characterization of hematopoietic stem cell differentiation using miniChIP and bisulfite sequencing analysis. Proc Natl Acad Sci U S A. 2007;104:12371-12376.  (299)  Croce CM, Calin GA. miRNAs, cancer, and stem cell division. Cell. 2005;122:6-7.  (300)  Hatfield SD, Shcherbata HR, Fischer KA et al. Stem cell division is regulated by the microRNA pathway. Nature. 2005;435:974-978.  (301)  Baltimore D, Boldin MP, O'Connell RM, Rao DS, Taganov KD. MicroRNAs: new regulators of immune cell development and function. Nat Immunol. 2008;9:839-845.  (302)  Fazi F, Racanicchi S, Zardo G et al. Epigenetic silencing of the myelopoiesis regulator microRNA-223 by the AML1/ETO oncoprotein. Cancer Cell. 2007;12:457-466.  (303)  O'Connell RM, Rao DS, Chaudhuri AA et al. Sustained expression of microRNA-155 in hematopoietic stem cells causes a myeloproliferative disorder. J Exp Med. 2008;205:585- 594.  (304)  Varambally S, Dhanasekaran SM, Zhou M et al. The polycomb group protein EZH2 is involved in progression of prostate cancer. Nature. 2002;419:624-629.  (305)  Nishino J, Kim I, Chada K, Morrison SJ. Hmga2 promotes neural stem cell self-renewal in young but not old mice by reducing p16Ink4a and p19Arf Expression. Cell. 2008;135:227-239.  (306)  Yu F, Yao H, Zhu P et al. let-7 regulates self renewal and tumorigenicity of breast cancer cells. Cell. 2007;131:1109-1123.  (307)  Walsh JC, DeKoter RP, Lee HJ et al. Cooperative and antagonistic interplay between PU.1 and GATA-2 in the specification of myeloid cell fates. Immunity. 2002;17:665-676.  (308)  Walsh JC, DeKoter RP, Lee HJ et al. Cooperative and antagonistic interplay between PU.1 and GATA-2 in the specification of myeloid cell fates. Immunity. 2002;17:665-676.  (309)  Fukuchi Y, Ito M, Shibata F, Kitamura T, Nakajima H. Activation of CCAAT/enhancer- binding protein alpha or PU.1 in hematopoietic stem cells leads to their reduced self- renewal and proliferation. Stem Cells. 2008;26:3172-3181.  


Citation Scheme:


Citations by CSL (citeproc-js)

Usage Statistics



Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            async >
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:


Related Items