Transient modified-RNA based elevated expression of FLI-1 to augment hematopoietic stem and progenitor cell expansion

Abstract

The present disclosure is directed to a method of activation and expansion of adult non-activated hematopoietic stem and progenitor cells (HSPCs). The present disclosure reveals that Fli-1 activity is essential during regenerative hematopoiesis. Fli-1 directs activation programs while manipulating cellular sensory and output machineries, enabling HSPCs co-adoptability with a stimulated vascular niche. Applying FLI-1 transient modified-mRNA transduction into lethargic adult human mobilized HSPCs, enables their niche-mediated expansion and superior engraftment capacities. The present disclosure provides a population of regenerated and expanded adult hematopoietic stem and progenitor cells (HSPCs). The present disclosure also provides methods of treating a subject in need of activated and expanded adult HSPCs by administering the regenerated and expanded HSPCs to the subject.

Description

TRANSIENT MODIFIED-RNA BASED ELEVATED EXPRESSION OF FLI-1 TO AUGMENT HEMATOPOIETIC STEM AND PROGENITOR CELL EXPANSION CROSS REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of priority from U.S. Provisional Application No. 63 / 452,472, filed on March 16, 2023, the entire content of which is incorporated herein by reference. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was supported and partially funded by the following grants and agencies: NIH grants R35HL150809 and U01AI138329 (SR and TI), NYSTEM grant NY-STEM- C32596GG (RS), and NIH grants RC2DK114777 and K08HL140143 (BH). The government has certain rights in this invention. INCORPORATION BY REFERENCE OF SEQUENCE LISTING

[0003] The Sequence Listing in an XML format, named as 40995WO_10278_02_PC_SequenceListing of 68 KB, created on March 14, 2024, and submitted to the United States Patent and Trademark Office via Patent Center, is incorporated herein by reference. BACKGROUND

[0004] Transition between activation and quiescence programs in hematopoietic stem and progenitor cells (HSPCs) is perceived to be governed intrinsically and by microenvironmental co-adaptation. However, HSPC programs dictating both transition and adaptability, remain poorly defined. The molecular hubs that coordinate sensing and communication of stem cells with their interactive niche cells to define between multiple stem cell fates, remain unknown. Uncovering these hubs and their defined roles may assist translational efforts to manipulate hematopoietic stem and progenitor cell fate for immune regenerative medical resolutions.

[0005] To sustain hematopoiesis, to continuously produce immune blood cells throughout adulthood, HSCs possess a preset molecular epigenetic program that firmly maintains adevelopmentally predefined path, even under various stress-induced conditions (Guo, P., et al, Nat Cell Biol 24, 99-111,2022) (Yu, V.W.C., et al, Cell 168, 944-945, 2017) (Venkatraman, A., et al, Nature 500, 345-349, 2013). Nevertheless, the multicellular HSC niche landscape, with its distinct and heterogeneous arsenal of cellular stromal components, provides differential instructive cues, essential for maintenance and regeneration of balanced hematopoiesis (Itkin, T., et al, Nature 532, 323-328, 2016) (Ding, L., Nature 481, 457-462, 2012) (Ding, L. & Morrison, Nature 495, 231-235, 2013) (Baccin, C., et al, Nat Cell Biol 22, 38-48, 2020) (Tikhonova, A.N., et al, Nature 569, 222-228, 2019) even from hematopoietic progeny (Sarkaria, S.M., Bioessays 40(2018) or from distant organs such as the liver (Gao, L., Elife 10(2021). These cues arriving from various types of niche cells include soluble chemokines, cytokines, angiokines, and membrane bound ligands (Man, Y., Front Cell Dev Biol 9, 621214, 2021). As part of this crosstalk between an HSPC to its niche cells, HSPCs themselves were shown to secrete and present signaling molecules modulating niche cells in the neighboring microenvironment (Chen, Q., et al, Cell Stem Cell 25, 768-783 e766, 2019) (Zhou, B.O., Elife 4, e05521, 2015). Thus, there must be an adaptive two-way crosstalk between HSCs and their dynamic microenvironment augmenting and fine-tuning steady state and stress-induced production of immune blood cells while maintaining the HSC pool (Baryawno, N., Cell Stem Cell 20, 590-592, 2017), lending credence to an undefined intrinsic HSPC transcriptional-mechanism regulating this crosstalk. Notably, the molecular hubs that coordinate sensing and communication of stem cells with their interactive niche cells to define between multiple stem cell fates, remain unknown. Uncovering these hubs and their defined roles may assist translational efforts to manipulate hematopoietic stem cell fate for immune regenerative medical resolutions. SUMMARY

[0006] The present disclosure reveals that Friend of Leukemia Integration-1 (FLI-1) activity is essential for hematopoietic stem and progenitor cells (HSPCs) during regenerative hematopoiesis. Using the methodology of modified-RNA based transient over-expression of transcription factors, the present disclosure identifies activation factors expressed in active but not dormant / non-activated HSPCs, e.g., the FLI-1 gene and additional downstream genes. These activation factors are able to stir quiescent / non-activated HSPCs and achieve superior HSPC activation and expansion ex-vivo for multiple therapeutic purposes.

[0007] One aspect of the present disclosure is directed to a method of activation and expansion of adult non-activated hematopoietic stem and progenitor cells (HSPCs), comprising elevating the expression of the transcription factor Friend of Leukemia Integration-1 (FLI-1) transiently in adult non-activated HSPCs to obtain an expanded pool of activated HSPCs, wherein the transient expression of FLI-1 is achieved by introducing a FLI-1 modified-mRNA into the adult non- activated HSPCs.

[0008] In some embodiments, the FLI-1 modified-mRNA is a modified-mRNA of a human FLI. In some embodiments, a human FLI mRNA is a wild type human FLI mRNA, e.g., any of SEQ ID NOS: 2-5. In some embodiments, the FLI-1 modified-mRNA has an open reading frame of an mRNA as set forth in SEQ ID NOS: 2-5. In some embodiments, the FLI-1 modified-mRNA has an open reading frame as set forth in SEQ ID NO: 1. In some embodiments, a human FLI mRNA is a mutant human FLI mRNA that maintains the DNA binding activity of a wild type human FLI mRNA.

[0009] In some embodiments, a modified-mRNA used in the method disclosed herein is a modified-mRNA of a human FLI homolog, e.g., a human ERG (e.g., as set forth in any of SEQ ID NOS: 6-15). In some embodiments, the modified-mRNA has an open reading frame of an mRNA as set forth in SEQ ID NOS: 6-15.

[0010] In some embodiments, the hematopoietic stem and progenitor cells (HSPCs) are human HSPCs. In some embodiments, the human HSPCs are adult human bone marrow-derived mobilized peripheral blood (mPB) hematopoietic stem progenitor cells (HSPCs).

[0011] In some embodiments, said elevating the expression of FLI-1 transiently activates adult non-activated human HSPCs without the risk of leukemic transformation.

[0012] In some embodiments, the method further comprises, after elevating the expression of FLI-1transiently in adult non-activated human HSPCs, coculturing the HSPCs with a regenerative vascular niche platform to expand the HSPCs, or with any other culture conditions allowing human HSPC expansion.

[0013] In some embodiments, the fold of expansion of the FLI-1 activated HSPCs is enhanced by at least 2 fold, at least 3 fold, at least 4 fold, at least 5 fold, or at least 10 fold as compared to the non-activated HSPCs without elevating the expression of FLI-1 transiently.

[0014] In some embodiments, the adult non-activated human HSPCs are obtained from a donor suffering from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), a co-morbidity including diabetes, from a poorly mobilizing donor, or for gene therapy purposes that requires introduction of a correct gene to replace a mutated one in blood related disorders.

[0015] In some embodiments, the blood related disorder comprises thalassemia or immunodeficiencies.

[0016] Another aspect of the disclosure is directed to a population of regenerated and expanded adult hematopoietic stem and progenitor cells (HSPCs) generated by a method as described above.

[0017] In some embodiments, the population of regenerated and expanded adult HSPCs are capable of engraftment and full reconstitution in a recipient.

[0018] In some embodiments, the population of regenerated and expanded adult HSPCs are capable of reconstitution in the peripheral blood, the spleen and the bone marrow of the recipient.

[0019] In some embodiments, the capability of reconstitution of the population of regenerated and expanded adult HSPCs is enhanced by at least 5-7-fold, as compared to the adult non- activated HSPCs without elevating the expression of FLI-1 transiently.

[0020] Another aspect of the disclosure is directed to a method of treating a subject in need of activated and expanded adult HSPCs, comprising obtaining hematopoietic stem cells (HSPCs) from the subject or a compatible donor, elevating the expression of Friend of Leukemia Integration-1 (FLI-1) transiently in the obtained HSPCs to obtain regenerated and expanded pool of HSPCs, and administering the regenerated and expanded HSPCs to the subject.

[0021] In some embodiments, the subject is in a need for an expanded pool of HSPCs, or suffers from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), or a co- morbidity including diabetes, β-thalassemia, or sickle cell disease that requires an expanded pool of genetically modified HSPCs for transplant. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Patent and Trademark Office upon request and payment of the necessary fee.

[0023] FIGS. 1a-h. Deep analysis of perivascular HSPCs reveals unique motif activity signatures per transitional state. (a) Weighted nearest neighbor (WNN) UMAP with hematopoietic stem and progenitor cell type annotation for hematopoietic stem cell (HSC),multi-potent progenitor (MPP), megakaryocyte progenitor (MkP), and erythrocyte progenitor (EryP) sub-cluster representation. (b) Engrafting LTR-HSC transcriptional signature (from Rodriguez-Fraiticelli et al. 2020) assigned on a WNN UMAP space. (c) Heatmap representation of differential transcriptional nuclei output from distinct HSPC sub-clusters by averaged Z-score, with selected genes presented. (d) Heatmap representation of differential ChromVAR motif activity in distinct HSPC sub-clusters by averaged Z-score, with selected TF motifs presented. (e) WNN UMAP of single nuclei from selected HSC and MPP sub-clusters without the MkP and EryP sub-clusters (upper panel). Engrafting LTR-HSC transcriptional signature (from Rodriguez-Fraiticelli et al. 2020) assigned on a WNN UMAP space for HSC and MPP clusters (lower panel). (f) WNN UMAP projection of HSC / MPP re-clustering with cell identity annotation. (g) Dot plot of ChromVAR motif activity of selected motifs in each HSC / MPP sub- cluster. Colors and sizes of dots indicate the level of motif activity by Z-score and percent of cells displaying the activity for the indicated motif, respectively, in each HSC / MPP sub-cluster. (h) Violin-plots displaying chromVAR motif activity score for selected motifs per HSC sub- clusters HSC1 (blue) and HSC2 (red). Wilcoxon Rank Sum Test was used to determine p- Values.

[0024] FIGS. 2a-f. Fli-1 counterbalances niche-dependent HSPC regenerative activation versus conservative quiescence programs. (a) BM LSK HSPCs were sorted and introduced into a serum free co-culture condition with or without a vascular niche. Frequency of LSK HSPCs was determined by flow cytometry and fold expansion was calculated, relatively to initial number of seeded cells. Two-way ANOVA multiple comparisons was used; n=6 BM donor mice per genotype, each point represents an average of 3 technical replicates. (b) Gene ontology (GO) categories of biological pathways enrichment for differentially expressed genes in RNA-seq analyses of Fli-1ROSAΔvs. WT HSPCs. Positively enrichment scored processes are enriched in Fli-1ROSAΔHSPCs while negatively enrichment scored processes are enriched in WT HSPCs. (c) Transcription factor binding site motif enrichment analysis for upregulated ATAC- and H3K27ac ChIP-seq peak sites in Fli-1ROSAΔvs. WT HSPCs. (d) Volcano plot of differential BINDetect motif footprinting in Fli-1ROSAΔvs. WT HSPCs. Blue and red colors are for labeling of footprinting enriched in WT HSPCs (Blue) and in Fli-1ROSAΔHSPCs (Red), above the set thresholds for the binding score and for the p-Value. (e) BETA activating / repressive function prediction analysis of the Fli-1 (left panel) and Spi1 (right panel) binding data sets from in vitroexpanded HSPCs and expression data sets from Fli-1ROSAΔvs. WT HSPCs, identifying upregulated (red) and downregulated (purple) genes. The dashed line indicates the non- differentially expressed genes as background. (f) ABC plots displaying Spi1 genomic loci with predicted active enhancer-gene connections with their relative ABC PowerLaw score. Red arcs on the right for WT and purple arcs on the left for Fli-1ROSAΔ. Brown colored blocks represent genes and predicted active enhancers. The bi-directional enhancer “hot spot” was noted left to Spi1 genomic transcriptional start site (TSS).

[0025] FIGS. 3a-f. Fli-1 simultaneously poises regenerative activation programs via VEGF- A / Notch pathways crosstalk. (a) Volcano plot of differentially expressed genes in Fli-1ROSAΔvs. WT HSPCs. Thresholds were set at |LogFC|>0.5 for x-axis and at FDR<0.05 for y-axis. Green and red color labeling is for genes with FDR<0.05 and green and yellow color labeling is for genes with |LogFC|>0.5. Genes belonging to the Notch signaling pathway and Vegfa are annotated to their localization on the heatmap. (b) Heatmaps for KEGG database extracted Notch / VEGF-A pathways elements across RNA-seq replicates of Fli-1ROSAΔand WT HSPCs. Scale bar and coloring represent the Z-score scaled by gene for Log counts per 106normalized by library size (trimmed mean of M-values). (c) WT and Fli-1ROSAΔBM HSPCs were isolated and expanded. Harvested HSPCs were stained and analyzed by flow cytometry to determine frequency of Notch1 expressing LSK HSPCs. Representative Notch1 histogram plots gated from LSK HSPCs. Unpaired two tailed t-test was used; n=6 tissue donor mice per genotype, each point represents an average of 3-4 technical replicates. (d) WT and Fli-1ROSAΔwere bred with transgenic Notch reporter eGFP (TNR-eGFP) mice, to evaluate changes in downstream Notch signaling. BM LSK HSPCs were isolated and sorted from TNR-eGFP / WT or Fli-1ROSAΔmice and expanded in co-cultures with a vascular niche layer. Frequency of LSK HSPCs positive for Notch signaling (eGFP+) as determined by flow cytometry at the end point of co- cultures. Representative flow histograms display TNR-eGFP signaling in WT (upper, blue) and Fli-1ROSAΔ(lower, red) LSK HSPCs. Unpaired two tailed t-test was used; n=9 (WT) and n=7 (Fli-1ROSAΔ). (e) IGV peaks plots for the genomic loci of Notch1, displaying peaks calling analyses for WT and Fli-1ROSAΔRNA-seq, ATAC-seq, ATAC-seq-“Footprinting”, Fli1-ChIP- seq, and Spi1-ChIP-seq. Yellow masking highlights regions displaying ATAC, “footprinting”, and Fli-1 + Spi1 TF binding activities. Opposing correlation was noted between ATAC to “footprinting” activities, among WT and Fli-1ROSAΔsamples, for these regions, preferentially forthe ones with stronger Spi1 binding activity. (f) IGV peaks plots for the genomic loci of Notch pathway elements and downstream targets, displaying peaks calling analyses for Fli1 and Spi1 ChIP-seqs.

[0026] FIGS. 4a-l. Enforcing Notch1 activation in Fli-1 deficient HSPCs restores regenerative expansion capacities and stem cell functionality. WT, Fli-1ROSAΔ, Fli-1ROSAΔwith conditionally inducible Notch1 internal component overexpression transgene (Fli-1ROSAΔN1-ICiOE), and N1- ICiOEBM LSK HSPCs were isolated and expanded. Harvested cells were analyzed by flow cytometry and / or flow sorted for LSK HSPCs which were competitively co-transplanted with congenic SJL total BM cells into lethally irradiated congenic SJL recipient mice (panel h). (a) Representative images of co-cultures at the end point before harvest. Yellow arrows indicate megakaryocytes. Expansion of round hematopoietic cells were noted in Fli-1ROSAΔN1-ICiOEco- cultures without any appearance of megakaryocytes. Bar = 100 µM. (b) Frequency of LSK HSPCs was determined by flow cytometry and fold expansion was calculated. One-way ANOVA multiple comparisons was used; n=4 BM donor mice per genotype, with 2 technical replicates per donor. (c-g) WT, Fli-1ROSAΔ, Fli-1ROSAΔwith conditionally inducible Notch1 internal component overexpression transgene (Fli-1ROSAΔN1-ICiOE), and N1-ICiOEBM LSK HSPCs were isolated and expanded. After 48 hours of expansion in co-culture, cells were harvested and hematopoietic LSK HSPCs were sorted and applied for single cell RNA-seq analysis; n=4 per genotype “pooled” together. (c) Dimensionality reduction by UMAP of single cell transcriptomes from co-cultured and sorted LSK HSPCs. (d) Dot plot for the E-SLAM HSC markers EPCR, CD34, and CD150 per cluster identity. Dot plot size indicates percent expression in cluster and color intensity indicates average expression score. (e) Distribution of clusters 7 and 15 in UMAP for HSC identified populations among LSK HSPC clusters based on Garnette and the Dot plot from panel (d). (f) Dot plot for cell cycle scores (S phase and G2 / M phases) per cluster identity. Dot plot size indicates percent expression in cluster and color intensity indicates average expression score. (g) Cell cycle status classification in UMAP for clusters 7 and 15: WT (upper left UMAP), Fli-1ROSAΔ(lower left UMAP), Fli1ROSAΔN1-ICiOE(upper right UMAP), and N1-ICiOE(lower right UMAP). (h) Frequency of donor derived chimerism indicating engraftment levels as determined by flow cytometry. One-way ANOVA multiple comparisons was used; n=8 recipient mice per genotype. (i-l) BM cells were harvested, 16 weeks post engraftment of WT and “rescued” Fli-1ROSAΔN1-ICiOElong term repopulatingHSCs and pooled from n=4 recipient mice (from 4 different donors) per genotype. CD45.2+ / Lin- cells were flow sorted and applied for single cell RNA-seq analysis. (HSC: hematopoietic stem cells, MPP: multi-potent progenitors, LPP: lymphoid-primed progenitors, MEP: megakaryocyte / erythroid progenitors). (i) Dimensionality reduction by UMAP of single cell transcriptomes from donor-derived lineage-negative BM samples (CD45.2+ / Lin-) following transplantation of WT or Fli1ROSAΔN1-ICiOELSK HSPC. (j) Cell type classification of hematopoietic sub-populations using Garnette: WT (left panel) and Fli1ROSAΔN1-ICiOE(right panel) samples in UMAP, and distribution of cell types between samples (bar plot). (k) Distribution of WT and Fli1ROSAΔN1-ICiOEsample cells in UMAP among populations classified as multi-lineage stem / progenitor cell types (HSC, MPP, or LPP) using Garnette, and distribution of cell types between samples (bar plot). (l) Heatmaps of gene-set scores for the subset of multi- lineage stem and progenitor cell types (HSC, MPP, LPP) in UMAP (left panels), and violin plots of gene-set scores between samples (WT vs Fli1ROSAΔN1-ICiOE) (right panels), for HSC molecular overlap signature genes (from Wilson et al.2015) and engrafting long term HSC signature genes (from Rodriguez-Fraiticelli et al.2020). Gene-set scores in violin plots are shown only for the subset of cells classified as HSC cell type. Wilcoxon Rank Sum Test was used to determine p-Values.

[0027] FIGS. 5a-g. Transcriptional comparison distinguishes distinct activation / quiescence states for neonatal and adult HSPCs. (a-e) Sorted CD45+ / CD34+HSPC from cord blood (CB) and adult mobilized peripheral blood (mPB) sources, were co-cultured on top of a vascular niche for 48h to encourage HSPC activation. Next, cells were harvested and CD45+ / CD34+HSPC were sorted and applied for single cell RNA-seq analysis. (a, b) Dimensionality reduction by UMAP of single cell transcriptomes from co-cultured and sorted CD45+ / CD34+HSPC, displaying cell distribution by CB and mPB source (a), and cluster identity split to sources (b). (c) Bar plot displaying compositional analysis of cluster identity per source. Relative differences in cell proportions and statistical significance for each cluster between CB and mPB were calculated using a permutation test (n=1,000). (d) Dimensionality reduction by UMAP of single cell transcriptomes from co-cultured and sorted CD45+ / CD34+HSPC, displaying single cell cycle phase. (e) Dot plot for cell cycle scores (S phase and G2 / M phases) per cellular source (CB or mPB), for total cells in analysis (left panel) and for HSC\MPP cluster (right panel). Dot plot size indicates percent expression in cluster and color intensity indicates average expressionscore. (f) To highly enrich for HSCs, the mononuclear fraction from CB (n=3) and mPB (n=4) sources was isolated, labeled, and sorted for CD45+ / CD34+ / CD38- / CD45RA- / CD90+ / CD49f+. Sorted cells were lysed and processed for RNAseq analysis. GSEA analysis plots for HSC activation signatures (left panels) and for HSC quiescence signatures (right panels) acquired from Venezia et al., 2004 (upper panels) and from Roy et al., 2021 (lower panels), showing a positive enrichment for the activation signatures in CB HSCs and positive enrichment for quiescence signatures in mPB HSCs. (g) UMAP projections of the single cell ATAC-seq enrichment analysis for sorted HSPCs of all 10 signatures identified in Takayama et al., 2021. Colors indicate the degree of enrichment in each cell (blue, depleted; red, enriched). Scale bar indicates enrichment Z-score. Enrichment for activated HSPCs (upper panel) and quiescent HSPCs (lower panel) signatures defined in in Takayama et al., 2021., as calculated by chromVAR. Enrichment for called peaks from the FLI-1 HSPC ChIP-seq (Fli-1 signature) dataset (Beck et al., 2013) overlayed on single cell ATAC-seq HSPC dataset (Takayama et al., 2021), as analyzed by chromVAR.

[0028] FIGS. 6a-i. Activation of adult human mobilized HSPC via transient overexpression of FLI-1. Sorted human CD34+HSPCs from cord blood (CB) or mobilized peripheral blood (mPB) sources were transduced by electroporation with FLI-1 modified-RNA molecules (2 µg FLI-1 modRNA per 105cells) and expanded for 1 week on top of E4orf1 vascular niche cells in a sub- optimal ratio of 1:3 (HSPCs:ECs). Next, expansion co-cultures were analyzed and transplanted into immunodeficient NSG KitW41 mice without myeloablative preconditioning. (a) Fold expansion of CB derived hematopoietic subtypes after 1 week in co-culture following transduction with FLI-1 (red) or control (blue) modified-RNA. Unpaired two tailed t-test was used; n = 4 CB donors. Each mark represents the averaged triplicate (n = 3 technical repeats) per donor. (b) Fold expansion of mPB derived hematopoietic subtypes after 1 week in co-culture following transduction with FLI-1 (red) or control (blue) modified-RNA. Unpaired two tailed t- test was used; n = 4 mPB donors. Each mark represents the averaged triplicate (n = 3 technical repeats) per donor. (c) Representative flow dot plots of mPB HSPC analysis post 1 week of expansion in co-culture following transduction with FLI-1 or control modified-RNA. The population of CD34+\CD38negHSPCs is colored in red. (d) Time kinetics plot for internal levels of FLI-1 protein in CD34+HSPCs, as measured by flow cytometry. Time 0 was done immediately after thawing CD34+HSPCs. Multiple unpaired two tailed t-test was used; n = 3mPB donors. Each mark represents the averaged samples from 3 donors with triplicate repeats (n = 3 technical repeats) per donor. (e) Frequency of cycling human CD34+HSPC as determined by flow cytometry at day 4 post transduction with FLI-1 (red) or control (blue) modified-RNA. Unpaired two tailed t-test was used; n = 3 mPB donors (2 independent experiments). Each mark represents the averaged triplicate (n = 3 technical repeats) per donor. (f) Human CD45 chimerism analysis in peripheral blood (PB), spleen, and bone marrow (BM) of NSG KitW41 mice. Tissues were harvested and analyzed by flow cytometry 16 weeks post transplantation. Unpaired two tailed t-test was used; n = 6 mPB donors. (g) Frequency of BM engrafted human HSPCs as determined by flow cytometry 16 weeks post transplantation. Unpaired two tailed t- test was used; n = 6 mPB donors. (h) Representative flow dot plots for BM engrafted human CD34+and CD34+\CD38negHSPCs acquired 20 weeks post transplantation. Unpaired two tailed t-test was used; n = 6 mPB donors. (i) Total BM from primary NSG KitW41 recipient mice was transplanted into secondary NSG KitW41 recipient mice without myeloablative preconditioning. Human CD45 chimerism in the BM of recipient mice was determined by flow cytometry 20 weeks post secondary transplantation. Unpaired two tailed t-test was used; n = 6 mPB donors

[0029] FIGS. 7a-h. Intersecting transcriptional and chromatin accessibility data reveals HSPC sensory and cytokine production deficiencies in the absence of Fli-1. (a) Intersection dot plot of RNA-seq and ATAC-seq in Fli-1ROSAΔvs. WT HSPCs. Each dot represents the transcriptional and chromatic accessibility statuses per gene. For gene labeling of few selected dots, thresholds FDR<0.05 for both RNA- and ATAC-seq, |LogFC|>2.5 for RNA-seq, |LogFC|>0.75 for ATAC- seq, and |Distance to TSS| < 500 parameters were set. (b) Gene ontology (GO) categories of biological processes enrichment for significantly downregulated genes in both RNA- and ATAC- seq analyses of Fli-1ROSAΔvs. WT HSPCs (lower left quadrant in panel a). Significance by FDR value is indicated. (c, d) Heatmaps for selected HSC extra-sensory quiescence (c) and activation (d) elements across RNA-seq replicates of Fli-1ROSAΔand WT HSPCs. Scale bar and coloring represent the Z-score scaled by gene for Log counts per 106normalized by library size (trimmed mean of M-values). (e) Frequency of double positive HSPCs for the activation receptors Lifr and Csfr1 in co-culture as determined by flow cytometry on day 4 post 4-OHT induction. Unpaired two tailed t-test was used; n=5 per WT or Fli-1ROSAΔ. (f) Representative flow cytometry dot plots of Lifr+ / Csfr1+double positive HSPCs in WT (upper panel) and Fli-1ROSAΔ(lower panel) co-cultures. (g, h,) Mean fluorescent intensity expression of stem markers CD150(g) and EPCR (h) on LSK HSPCs in co-culture as determined by flow cytometry on day 4 post 4-OHT induction. Unpaired two tailed t-test was used; n=5 per WT or Fli-1ROSAΔ.

[0030] FIGS. 8a-i. Restoring Notch1 signaling in Fli-1 deficient HSPCs rescues their expansion capacities. (a) Frequency of Notch1+BM LSK and SLAM LSK HSPC from WT and Fli-1ROSAΔchimeric mice, 7 days post tamoxifen induction. Unpaired two tailed t-test was used; n=5 per WT or Fli-1ROSAΔ. (b, c) WT and Fli-1ROSAΔBM HSPCs were isolated and expanded. (b) Harvested HSPCs were stained and analyzed by flow cytometry to determine frequency of Vegfa expressing LSK HSPCs. Unpaired two tailed t-test was used; n=5 tissue donor mice per genotype, each point represents an average of 3-4 technical replicates. (c) Representative Vegfa histogram plots gated from LSK HSPCs. (d) Frequency of Vegfa+BM LSK and SLAM LSK HSPC from WT and Fli-1ROSAΔchimeric mice, 7 days post tamoxifen induction. Unpaired two tailed t-test was used; n=5 per WT or Fli-1ROSAΔ. (e) IGV peaks plot for the genomic loci of Vegfa, displaying peaks calling analyses for Fli1-ChIP-seq and Spi1-ChIP-seq. (f) Representative flow dot plots for WT, Fli-1ROSAΔ, Fli-1ROSAΔN1-ICiOE, and N1-ICiOEHSPCs post expansion in co-culture with a vascular niche, gated from CD45+ / Lin- cells. It was noted that Notch1 overexpression increased LSK frequency yet was not able to restore the high c-Kit population observed in WT or N1-ICiOELSK HSPCs. (g) Frequency of hematopoietic cells was determined by flow cytometry, number of cells was determined out of total MNC counts, and fold expansion was calculated. One-way ANOVA multiple comparisons was used; n=4 BM donor mice per genotype, with 2 technical replicates per donor. (h) HSPC frequency as determined by flow cytometry. One-way ANOVA multiple comparisons was used; n=4 BM donor mice per genotype, with 2 technical replicates per donor. (i) Proposed model for Fli-1 endorsed HSPC activation via Notch / Vegfa pathways mediated crosstalk with the vascular niche. Fli-1 in HSPCs, transcriptionally presets Notch pathway-promoting external and internal elements while also transcriptionally promoting Vegfa expression. Vegfa enlists an activation supportive vascular niche by stimulating ECs to elevate the expression of Notch ligands. Reciprocal niche-mediated activation of Notch receptors presented by HSPCs, endorse downstream Notch signaling, promoting HSPC regenerative activation and expansion.

[0031] FIGS. 9a-f. Enforcing Notch1 signaling in Fli-1 deficient HSPCs restores the active- HSC sub-population. WT, Fli-1ROSAΔ, Fli-1ROSAΔN1-ICiOEand N1-ICiOEBM LSK HSPCs were isolated and expanded in co-culture with a vascular niche. Harvested cells were analyzed byflow cytometry and / or flow sorted for LSK HSPCs which were transcriptionally analyzed by scRNA-seq. (a) BrdU was supplemented to co-culture media on day 4 post 4-OHT induction and cells were analyzed after co-cultures were terminated. Frequency of BrdU+LSK HSPC was determined by flow cytometry. One-way ANOVA multiple comparisons was used; n=5 BM donor mice per genotype, with 2 technical replicates per donor. (b, c) Cells in co-culture were analyzed after 4 days post 4-OHT induction. (b) Frequency of Cdk6+LSK HSPC was determined by flow cytometry. One-way ANOVA multiple comparisons was used; n=5 BM donor mice per genotype, with 2 technical replicates per donor. (c) Representative flow cytometry histograms for Cdk6 gated from LSK HSPCs. (d, e) Statistics for the relative differences in cell proportions in per cluster were calculated for all possible pairwise combinations for the four geneteic phenotype conditions as a permutation test (n=1,000). (d) Compositional analysis-based bar plot presentation of frequency of cells for each genetic phenotype per cluster. (e) Compositional analysis-based bar plot presentation of frequency of cells in selected HSC clusters 7 and 15 only per genetic phenotype. (f) Gene ontology (GO) categories of biological processes enrichment for differentially expressed genes in scRNA-seq analyses of HSC Cluster 15 vs. HSC Cluster 7, presented in a bar plot. Positively enrichment scored processes are enriched in HSC cluster 15 while negatively enrichment scored processes are enriched in HSC cluster 7.

[0032] FIGS. 10a-e. Transcriptional comparison distinguishes distinct activation states for neonatal and adult HSPCs. (a) Violin plot presentation of for cycle scores (S phase and G2 / M phases) per cellular source (CB or mPB), for HSPC clusters in analysis presented in Fig.5b. (b) Gene ontology (GO) categories of reactome enrichment for differentially expressed genes in scRNA-seq analyses of cells from CB or mPB source in the HSC\MPP Cluster, presented in a bar plot. Positively enrichment scored processes are enriched in CB derived HSC\MPP cells while negatively enrichment scored processes are enriched in mPB derived HSC\MPP cells. (c) Gene ontology (GO) categories of Hallmark signatures pathways enrichment for differentially expressed genes in RNA-seq analyses of sorted HSCs from CB or mPB source, presented in a bar plot. Positively enrichment scored processes are enriched in mPB HSCs while negatively enrichment scored processes are enriched in CB HSCs. (d) Harvested cells from 2 day co- cultures were stained and analyzed by flow cytometry to determine frequency of NOTCH1 expressing CD34+HSPCs. Unpaired two tailed t-test was used; n=6 donors, each pointrepresents an average of 2 technical replicates. Representative NOTCH1 flow cytometry histogram plots were gated from CD34+HSPCs. (e) Harvested cells from 2 day co-cultures were stained and analyzed by flow cytometry to determine frequency of VEGFA expressing CD34+HSPCs. Unpaired two tailed t-test was used; n=6 donors, each point represents an average of 2 technical replicates. Representative VEGFA flow cytometry histogram plots were gated from CD34+HSPCs.

[0033] FIGS. 11a-d. FLI-1-drives active hematopoiesis from a quiescent HSC state. (a) Schema of experimental design. Sorted human CD34+HSPCs from cord blood (CB) or mobilized peripheral blood (mPB) sources were transduced by electroporation with FLI-1 modified-RNA molecules (2 µg FLI-1 modRNA per 105cells) and expanded for 1 week on top of E4orf1 vascular niche cells in a sub-optimal ratio of 1:3 (HSPCs:ECs). Next, expansion co- cultures were analyzed and transplanted into immunodeficient NSG KitW41 mice without myeloablative preconditioning. (b, c) Harvested mPB cells from 4 day co-cultures, post control or FLI-1 modRNA transduction, were stained and analyzed by flow cytometry to determine frequency of NOTCH1 (b) and VEGFA (c) expressing CD34+HSPCs. Unpaired two tailed t-test was used; n=6 donors, each point represents an average of 2 technical replicates. (d) Schematic illustration of suggested model for FLI-1-driven active hematopoiesis from a quiescent HSC state. Attainment of FLI-1 transcriptional activity allows HSCs to adopt an active state. FLI-1 transcriptional activity steers HSCs out of their quiescence promoting HSPC expansion along with downstream differentiation to the essential blood cell lineages, enlarging the pool of functional HSCs capable of long-term engraftment and hematopoietic reconstitution post transplantation. Mechanistically, FLI-1 establishes the co-adoptability between an activated HSC to its supportive niche by mediating the stem cell-niche cell crosstalk and mutual sensing. DETAILED DESCRIPTION

[0034] This disclosure has probed the two-way relationship between the stem cell and its vascular niche, by unraveling a new paradigm in the physiology of adult hematopoiesis. This disclosure demonstrates that the transition from quiescence to active regenerative hematopoiesis is dependent on Fli-1 enabling HSCs to sense, relay, adapt, and to execute a niche triggered activation program. Fli-1 empowers HSPCs with the capacity to interpret the pertinent niche signals destined for the transition into a hyperactive state. Vascular ECs (endothelial cells), representing prototypical niche cells, respond to Fli-1-governed VEGF-A counter signal fromHSPCs to customize a Notch-driven niche response towards support of regenerative hematopoiesis. Thus, Fli-1 intrinsic activity in HSPCs enables the crosstalk with expansion designated niche cells, allowing to “molecularly eavesdrop” on the reciprocal activation signals sustaining hematopoietic active regeneration and post-insult immune recovery. However, as of yet, the environmental signals which arise during regenerative stress conditions to activate Fli-1 in HSCs are not well defined and should be explored in follow up studies as an additional potential method to activate quiescent HSCs for regenerative purposes.

[0035] This disclosure demonstrates methods to activate human quiescent mPB HSPCs with FLI-1 modified-RNA, and to boost their expansion on a vascular niche platform to the matching level of naturally activated human CB HSPCs. Employing modified-RNA delivery into HSPCs can be benchmarked as a clinically safe technology allowing transient protein upregulation by cells, without provoking any potential pro-leukemic transformations. Enhanced engraftment levels of FLI-1 stimulated human cultures presents a therapeutic solution for patients with insufficient numbers of transplantable mPB HSPCs. The revelations gathered from this study, in which synthetic modified-RNA technology enable transient overexpression and activation of a factor or a combination of factors, can be harnessed to steer quiescent HSCs for optimal ex vivo expansion in a pre-transplantation clinical setting, as in the cases of poorly-mobilizing donors suffering from exhausted chemotherapy / irradiated stressed BM, or co-morbidities, including diabetes (Chen, J., Blood Rev 47, 100771, 2021). Mostly, it could benefit and significantly improve therapeutical efforts of autologous based HSC gene therapy, as in the case of β- thalassemia, sickle cell, and other rare diseases, by tackling currently limiting attributes (Naldini, L. EMBO Mol Med 11, 2019). HSC release from quiescence may enhance the transduction rate of the engineered vector and may further mitigate p53-mediated clonal shrinking of gene edited HSCs (Ferrari, S., et al, Nat Biotechnol 38, 1298-1308, 2020) and to expand the pool of successfully transduced HSCs, increasing the final yield of patient-engrafted engineered HSCs.

[0036] These findings set forth the transformative notion of a co-adaptive and responsive rather than a dictating niche role. The notion of molecular hubs transcriptionally presetting cellular genetic programs, masterminding distinct immune stem and progenitor cell states, may apply globally to varieties of normal and malignant stem / progenitor and niche cell types. This may further reveal a myriad of specialized niche types designated for diverse stem / progenitor cell intrinsic transcriptional programs.

[0037] In one aspect, disclosed herein is a method of activation and expansion of adult non- activated hematopoietic stem and progenitor cells (HSPCs), comprises elevating the expression of the transcription factor Friend of Leukemia Integration-1 (FLI-1) transiently in adult non- activated HSPCs to obtain an expanded pool of activated HSPCs, wherein the transient expression of FLI-1 is achieved introducing a FLI-1 modified-mRNA into the adult non- activated HSPCs.

[0038] Adult Non-Activated CD34+ HSPCs

[0039] The terms “quiescent”, “non-activated”, and “non-proliferative”, as used herein, are synonyms.

[0040] The majority (almost all) of adult HSPCs (e.g., mPB HSPCs) are found in a non-activated (non-cycling / nonproliferating) state and thus are not prone for optimal ex-vivo expansion designed as a pre-step for therapeutic treatments, in contrast to cord blood (CB) HSPCs which are mostly activated (cycling / proliferating).

[0041] In some embodiments, the adult non-activated hematopoietic stem and progenitor cells (HSPCs) are isolated from an adult subject (donor) and not from an embryo / neonatal / newborn

[0042] In some embodiments, the hematopoietic stem and progenitor cells (HSPCs) are human HSPCs. In some embodiments, the human HSPCs are adult human HSPCs. In some embodiments, adult human HSPCs are human bone marrow-derived mobilized peripheral blood (mPB) hematopoietic stem progenitor cells (HSPCs).

[0043] In some embodiments, human HSPCs in experimental and clinical settings are isolated based on the expression of the CD34+ marker.

[0044] Adult HSPCs can be obtained peripheral blood of mobilized donor (mPB), e.g., human subjects or patients in need of activated HSPCs. mPB is subjected to ficoll separation to isolate the mononuclear fraction and then CD34+ cells can be isolated using magnetic beads conjugated to antibodies against human CD34. The isolated CD34+ cells are adult HSPCs. Adult HSPCs can be obtained also from non-mobilized peripheral blood. In addition, adult HSPCs can be obtained directly from the bone marrow by performing clinical bone marrow aspiration and marrow and blood harvest from the iliac / pelvis bone. Bags of frozen CD34+ cells can be thawed, aliquoted in smaller freezing tubes, and refrozen. Tubes can be thawed prior to use, cells can be washed, counted, and allowed to recover overnight in HSPC expansion media with human cytokines.

[0045] FLI-1 modRNA

[0046] As disclosed herein, the present method comprises elevating the expression of FLI-1 transiently in adult non-activated HSPCs to obtain an expanded pool of activated HSPCs, wherein the transient expression of FLI-1 is achieved by introducing a FLI-1 modified-mRNA into tthe adult non-activated HSPCs.

[0047] In some embodiments, the HSPCs are human adult HSPCs, and the FLI-1 modified- mRNA is a human FLI-1 modified mRNA. In some embodiments, a native (or wild type) human FLI-1 mRNA is used to make a modified mRNA. Human FLI-1 has 4 different mRNA isoforms (SEQ ID NOS: 2-5, respectively), all of which can be utilized to make modified mRNA for use in the present method. In some embodiments, the FLI-1 modified-mRNA has an open reading frame of an mRNA as set forth in SEQ ID NOS: 2-5. In some embodiments, a mutant form of human FLI-1 mRNA is utilized to make modified mRNA, e.g., EWS-FLI-1 or mutants that generate amino acid substitution or a truncated form which lacks a regulatory site for degradation of the protein, while retaining the DNA binding activity, such as those described in May et al., Mol. Cell Bio.13 (12): 7393-7398, 1993; Asano et al., Transcription, Chromatin & Epigenetics 282(48): 34672-34683, 2007; Asano et al., Mol. Cell Bio.29(7): 1882-1894, 2009. In some embodiments, a human FLI-1 mRNA homolog, e.g., a human transcription factor ERG mRNA (such as SEQ ID NOS: 6-15), is used to make modified mRNA for use in the present method. In some embodiments, a modified-mRNA has an open reading frame of an mRNA as set forth in SEQ ID NOS: 6-15.

[0048] In a specific embodiment, the open reading frame for the FLI-1 modRNA is as set forth in SEQ ID NO: 1: atggacgggactattaaggaggctctgtcggtggtgagcgacgaccagtccctctttgactcagcgtacggagcggcagcccatctcccca aggccgacatgactgcctcggggagtcctgactacgggcagccccacaagatcaaccccctcccaccacagcaggagtggatcaatcag ccagtgagggtcaacgtcaagcgggagtatgaccacatgaatggatccagggagtctccggtggactgcagcgttagcaaatgcagcaa gctggtgggcggaggcgagtccaaccccatgaactacaacagctatatggacgagaagaatggcccccctcctcccaacatgaccacca acgagaggagagtcatcgtccccgcagaccccacactgtggacacaggagcatgtgaggcaatggctggagtgggccataaaggagta cagcttgatggagatcgacacatcctttttccagaacatggatggcaaggaactgtgtaaaatgaacaaggaggacttcctccgcgccacca ccctctacaacacggaagtgctgttgtcacacctcagttacctcagggaaagttcactgctggcctataatacaacctcccacaccgaccaat cctcacgattgagtgtcaaagaagacccttcttatgactcagtcagaagaggagcttggggcaataacatgaattctggcctcaacaaaagtc ctccccttggaggggcacaaacgatcagtaagaatacagagcaacggccccagccagatccgtatcagatcctgggcccgaccagcagtcgcctagccaaccctggaagcgggcagatccagctgtggcaattcctcctggagctgctctccgacagcgccaacgccagctgtatcacc tgggaggggaccaacggggagttcaaaatgacggaccccgatgaggtggccaggcgctggggcgagcggaaaagcaagcccaacat gaattacgacaagctgagccgggccctccgttattactatgataaaaacattatgaccaaagtgcacggcaaaagatatgcttacaaatttga cttccacggcattgcccaggctctgcagccacatccgaccgagtcgtccatgtacaagtacccttctgacatctcctacatgccttcctaccat gcccaccagcagaaggtgaactttgtccctccccatccatcctccatgcctgtcacttcctccagcttctttggagccgcatcacaatactgga cctcccccacggggggaatctaccccaaccccaacgtcccccgccatcctaacacccacgtgccttcacacttaggcagctactactag (SEQ ID NO: 1).

[0049] Modified RNA including modified mRNA can be made by using known methods including those described herein below. Modified RNA can be introduced into cells using known methods, such as electroporation, lipofection, and calcium phosphate precipitation, including those described in the Examples. In some embodiments, NEON electroporation transfection system (Invitrogen) can be applied for introducing modified mRNA into HSPCs. Immediately after electroporation cells can be introduced into a co-culture with E4orf1-HUVEC niche cells with hematopoietic expansion media.

[0050] Modified RNA (modRNA)

[0051] A nucleoside is a molecule including a nitrogenous base (i.e., a nucleobase) linked to a pentose (e.g., deoxyribose or ribose) sugar. Nitrogenous bases which form nucleosides include adenine, guanine, cytosine, 5-methyl cytosine, uracil, and thymine. Suitable ribonucleosides (which comprise ribose as the pentose sugar) include, e.g., adenosine (A), guanosine (G), 5- methyluridine (m5U), uridine (U), and cytidine (C). Nucleotides are molecules including a nucleoside (e.g., a ribonucleoside) and a phosphate group. Ribonucleotides include, e.g., adenosine monophosphate, adenosine diphosphate, adenosine triphosphate, guanosine monophosphate, guanosine diphosphate, guanosine triphosphate, cytidine monophosphate, cytidine diphosphate, cytidine triphosphate, uridine monophosphate, uridine diphosphate, uridine triphosphate, and derivatives thereof.

[0052] Modified RNA, or modRNA, is a synthetic modified RNA that can be used for expression of a gene of interest. Chemical modifications to a ribonucleotide included in modRNA may stabilize an RNA molecule, blunt an immune response, or enhance transcription. Additionally, unlike delivery of protein agents directly to a cell, which can activate the immune system, the delivery of modRNA can be achieved without immune impact. For example,substitution of uridine and cytidine with pseudouridine or N1-methylpseudouridine and 5- methylcytidine, respectively, drastically reduces the immune response elicited from exogenous RNA without such substitutions. Stability and translational efficiency from an RNA molecule may also be increased by including a 3´-O-Me-m7G(5')ppp(5')G Anti Reverse Cap Analog (ARCA) at the 5′ end of the RNA molecule.

[0053] modRNA may encompass an RNA molecule with at least uridine substituted with pseudouridine. modRNA may encompass an RNA molecule with at least cytidine substituted with 5-methylcytidine. modRNA may encompass an RNA molecule including the modified nucleoside 5-methylcytidine (5mC). modRNA may encompass an RNA molecule including the modified nucleoside 2-Thiouridine-5′-Triphosphate (2-thio ψU). modRNA may encompass an RNA molecule with at least the modified nucleoside 1-Methylpseudouridine-5′-Triphosphate (1- mψU). modRNA may encompass an RNA molecule with at least the modified nucleoside N1- methyl-pseudouridine (N1mΨ) substituted for uridine. modRNA may encompass an RNA molecule wherein at least 5′ triphosphates are removed. modRNA may encompass an RNA molecule wherein at least a 3′-O-Me-m7G(5′)ppp(5′)G Anti Reverse Cap Analog (ARCA) cap or C32H43N15O24P4CleanCap Reagent AG is included in a 5′ untranslated regions of the RNA molecule.

[0054] modRNAs may be prepared by in vitro transcription. modRNA may be in vitro transcribed, e.g., from a linear DNA template using one or more reagents selected from a cap analog, guanosine triphosphate, adenosine triphosphate, cytidine triphosphate, uridine triphosphate, and derivatives thereof. A cap analog may be selected from Anti-Reverse Cap Analog (ARCA) 3′-O-Me-m7G(5′)ppp(5′)G, standard cap analog m7G(5′)ppp(5′)G, unmethylated cap analog G(5′)ppp(5′)G, methylated cap analog for A+1 sites m7G(5′)ppp(5′)A, and unmethylated cap analog for A+1 sites G(5′)ppp(5′)A. In certain examples, a cap analog is Anti-Reverse Cap Analog (ARCA) 3′-O-Me-m7G(5′)ppp(5′)G. According to some examples, modRNA may be in vitro transcribed from a plasmid template using one or more reagents selected from 3′-O-Me-m7G(5′)ppp(5′)G, guanosine triphosphate, adenosine triphosphate, cytidine triphosphate, N1-methylpseudouridine-5-triphosphate, and any one or more of the aforementioned examples of modRNA, or others, without limitation and in any combination.

[0055] Additional suitable modifications to a modRNA or mRNA molecule are well known in the art (e.g., U.S. Patent No. 8,278,036 to Kariko et al.; U.S. Patent No. 10,086,043 to Chien etal.; U.S. Patent Application Publication No.2019 / 0203226 to Zangi et al.; and U.S. Patent Application Publication No. 2018 / 0353618 to Burkhardt et al.; all of which are hereby incorporated by reference in their entirety). In some embodiments, the nucleoside that is modified in the modRNA is a uridine (U), a cytidine (C), an adenine (A), or guanine (G). The modified nucleoside can be, for example, m5C (5-methylcytidine), m6A (N6-methyladenosine), s2U (2-thiouridien), ψ (pseudouridine), or Um (2-O-methyluridine). Some exemplary chemical modifications of nucleosides in the modRNA molecule may further include, for example and without limitation, pyridine-4-one ribonucleoside, 5-aza-uridine, 2-thio-5-aza uridine, 2- thiouridine, 4-thio pseudouridine, 2-thio pseudouridine, 5-hydroxyuridine, 3-methyluridine, 5- carboxymethyl uridine, 1-carboxymethyl pseudouridine, 5-propynyl uridine, 1-propynyl pseudouridine, 5-taurinomethyluridine, 1-taurinomethyl pseudouridine, 5-taurinomethyl-2-thio uridine, 1-taurinomethyl-4-thio uridine, 5-methyl uridine, 1-methyl pseudouridine, 4-thio-1- methyl pseudouridine, 2-thio-1-methyl pseudouridine, 1-methyl-1-deaza pseudouridine, 2-thio-1- methyl-1-deaza pseudouridine, dihydrouridine, dihydropseudouridine, 2-thio dihydrouridine, 2- thio dihydropseudouridine, 2-methoxyuridine, 2-methoxy-4-thio uridine, 4-methoxy pseudouridine, 4-methoxy-2-thio pseudouridine, 5-aza cytidine, pseudoisocytidine, 3-methyl cytidine, N4-acetylcytidine, 5-formylcytidine, N4-methylcytidine, 5-hydroxymethylcytidine, 1- methyl pseudoisocytidine, pyrrolo-cytidine, pyrrolo-pseudoisocytidine, 2-thio cytidine, 2-thio-5- methyl cytidine, 4-thio pseudoisocytidine, 4-thio-1-methyl pseudoisocytidine, 4-thio-1-methyl-1- deaza pseudoisocytidine, 1-methyl-1-deaza pseudoisocytidine, zebularine, 5-aza zebularine, 5- methyl zebularine, 5-aza-2-thio zebularine, 2-thio zebularine, 2-methoxy cytidine, 2-methoxy-5- methyl cytidine, 4-methoxy pseudoisocytidine, 4-methoxy-1-methyl pseudoisocytidine, 2- aminopurine, 2,6-diaminopurine, 7-deaza adenine, 7-deaza-8-aza adenine, 7-deaza-2- aminopurine, 7-deaza-8-aza-2-aminopurine, 7-deaza-2,6-diaminopurine, 7-deaza-8-aza-2,6- diaminopurine, 1-methyladenosine, N6-methyladenosine, N6-isopentenyladenosine, N6-(cis- hydroxyisopentenyl) adenosine, 2-methylthio-N6-(cis-hydroxyisopentenyl) adenosine, N6- glycinylcarbamoyladenosine, N6-threonylcarbamoyladenosine, 2-methylthio-N6-threonyl carbamoyladenosine, N6,N6-dimethyladenosine, 7-methyladenine, 2-methylthio adenine, 2- methoxy adenine, inosine, 1-methyl inosine, wyosine, wybutosine, 7-deaza guanosine, 7-deaza- 8-aza guanosine, 6-thio guanosine, 6-thio-7-deaza guanosine, 6-thio-7-deaza-8-aza guanosine, 7- methyl guanosine, 6-thio-7-methyl guanosine, 7-methylinosine, 6-methoxy guanosine, 1-methylguanosine, N2-methylguanosine, N2,N2-dimethylguanosine, 8-oxo guanosine, 7-methyl-8- oxo guanosine, 1-methyl-6-thio guanosine, N2-methyl-6-thio guanosine, or N2,N2-dimethyl-6- thio guanosine.

[0056] In some embodiments, modifications made to the modRNA are independently selected from 5-methylcytosine, pseudouridine, and 1-methylpseudouridine.

[0057] In some embodiments, the modRNA comprises a modified uracil selected from the group consisting of pseudouridine (ψ), pyridine-4-one ribonucleoside, 5-aza uridine, 6-aza uridine, 2- thio-5-aza uridine, 2-thio uridine (s2U), 4-thio uridine (s4U), 4-thio pseudouridine, 2-thio pseudouridine, 5-hydroxy uridine (ho5U), 5-aminoallyl uridine, 5-halo uridine (e.g., 5-iodom uridine or 5-bromo uridine), 3-methyl uridine (m3U), 5-methoxy uridine (mo5U), uridine 5- oxyacetic acid (cmo5U), uridine 5-oxyacetic acid methyl ester (mcmo5U), 5-carboxymethyl uridine (cm5U), 1-carboxymethyl pseudouridine, 5-carboxyhydroxymethyl uridine (chm5U), 5- carboxyhydroxym ethyl uridine methyl ester (mchm5U), 5-methoxycarbonylmethyl uridine (mcm5U), 5-methoxycarbonylmethyl-2-thio uridine (mcm5s2U), 5-aminomethyl-2-thio uridine (nm5s2U), 5-methylaminomethyl uridine (mnm5U), 5-methylaminomethyl-2-thio uridine (mnm5s2U), 5-methylaminomethyl-2-seleno uridine (mnm5se2U), 5-carbamoylmethyl uridine (ncm5U), 5-carboxymethylaminomethyl uridine (cmnm5U), 5-carboxymethylaminomethyl-2-thio uridine (cmnm5s2U), 5-propynyl uridine, 1-propynyl pseudouridine, 5-taurinomethyl uridine (τcm5U), 1-taurinomethyl pseudouridine, 5-taurinomethyl-2-thio uridine (™5s2U), 1- taurinomethyl-4-thio pseudouridine, 5-methyl uridine (m5U, e.g., having the nucleobase deoxythymine), 1-methyl pseudouridine (m1ψ), 5-methyl-2-thio uridine (m5s2U), 1-methyl-4- thio pseudouridine (m1s4ψ), 4-thio-1-methyl pseudouridine, 3-methyl pseudouridine (m3ψ), 2- thio-1-methyl pseudouridine, 1-methyl-1-deaza pseudouridine, 2-thio-1-methyl-1-deaza pseudouridine, dihydrouridine (D), dihydropseudouridine, 5,6-dihydrouridine, 5-methyl dihydrouridine (m5D), 2-thio dihydrouridine, 2-thio dihydropseudouridine, 2-methoxy uridine, 2- methoxy-4-thio uridine, 4-methoxy pseudouridine, 4-methoxy-2-thio pseudouridine, N1-methyl pseudouridine, 3-(3-amino-3-carboxypropyl) uridine (acp3U), 1-methyl-3-(3-amino-3- carboxypropyl) pseudouridine (acp3ψ), 5-(isopentenylaminomethyl) uridine (inm5U), 5- (isopentenylaminomethyl)-2-thio uridine (inm5s2U), α-thio uridine, 2′-O-methyl uridine (Um), 5,2′-O-dimethyl uridine (m5Um), 2′-O-methyl pseudouridine (ψm), 2-thio-2′-O-methyl uridine (s2Um), 5-methoxycarbonylmethyl-2′-O-methyl uridine (mcm5Um), 5-carbamoylmethyl-2′-O-methyl uridine (ncm5Um), 5-carboxymethylaminomethyl-2′-O-methyl uridine (cmnm5Um), 3,2′- O-dimethyl uridine (m3Um), 5-(isopentenylaminomethyl)-2′-O-methyl uridine (inm5Um), 1-thio uridine, deoxythymidine, 2′-F-ara uridine, 2′-F uridine, 2′-OH-ara uridine, 5-(2- carbomethoxyvinyl) uridine, and 5-3-(1-E-propenylamino) uridine.

[0058] In some embodiments, the modRNA comprises a modified cytosine selected from the group consisting of 5-aza cytidine, 6-aza cytidine, pseudoisocytidine, 3-methyl cytidine (m3C), N4-acetyl cytidine (act), 5-formyl cytidine (f5C), N4-methyl cytidine (m4C), 5-methyl cytidine (m5C), 5-halo cytidine (e.g., 5-iodo cytidine), 5-hydroxymethyl cytidine (hm5C), 1-methyl pseudoisocytidine, pyrrolo-cytidine, pyrrolo-pseudoisocytidine, 2-thio cytidine (s2C), 2-thio-5- methyl cytidine, 4-thio pseudoisocytidine, 4-thio-1-methyl pseudoisocytidine, 4-thio-1-methyl-1- deaza pseudoisocytidine, 1-methyl-1-deaza pseudoisocytidine, zebularine, 5-aza zebularine, 5- methyl zebularine, 5-aza-2-thio zebularine, 2-thio zebularine, 2-methoxy cytidine, 2-methoxy-5- methyl cytidine, 4-methoxy pseudoisocytidine, 4-methoxy-1-methyl pseudoisocytidine, lysidine (k2C), alpha-thio cytidine, 2′-O-methyl cytidine (Cm), 5,2′-O-dimethyl cytidine (m5Cm), N4- acetyl-2′-O-methyl cytidine (ac4Cm), N4,2′-O-dimethyl cytidine (m4Cm), 5-formyl-2′-O-methyl cytidine (f5Cm), N4,N4,2′-O-trimethyl cytidine (m42Cm), 1-thio cytidine, 2′-F-ara cytidine, 2′-F cytidine, and 2′-OH-ara cytidine.

[0059] In some embodiments, the modRNA comprises a modified adenine selected from the group consisting of 2-amino purine, 2,6-diamino purine, 2-amino-6-halo purine (e.g., 2-amino-6- chloro purine), 6-halo purine (e.g., 6-chloro purine), 2-amino-6-methyl purine, 8-azido adenosine, 7-deaza adenine, 7-deaza-8-aza adenine, 7-deaza-2-amino purine, 7-deaza-8-aza-2- amino purine, 7-deaza-2,6-diamino purine, 7-deaza-8-aza-2,6-diamino purine, 1-methyl adenosine (m1A), 2-methyl adenine (m2A), N6-methyl adenosine (m6A), 2-methylthio-N6-methyl adenosine (ms2m6A), N6-isopentenyl adenosine (i6A), 2-methylthio-N6-isopentenyl adenosine (ms2i6A), N6-(cis-hydroxyisopentenyl) adenosine (io6A), 2-methylthio-N6-(cis- hydroxyisopentenyl) adenosine (ms2io6A), N6-glycinylcarbamoyl adenosine (g6A), N6- threonylcarbamoyl adenosine (t6A), N6-methyl-N6-threonylcarbamoyl adenosine (m6t6A), 2- methylthio-N6-threonylcarbamoyl adenosine (ms2g6A), N6,N6-dimethyl adenosine (m62A), N6- hydroxynorvalyIcarbamoyl adenosine (hn6A), 2-methylthio-N6-hydroxynorvalylcarbamoyl adenosine (ms2hn6A), N6-acetyl adenosine (ac6A), 7-methyl adenine, 2-methylthio adenine, 2- methoxy adenine, alpha-thio adenosine, 2′-O-methyl adenosine (Am), N6,2′-O-dimethyladenosine (m6Am) N6,N6,2′-O-trimethyl adenosine (m62Am), 1,2′-O-dimethyl adenosine (m1Am), 2′-O-ribosyl adenosine (phosphate) (Ar(p)), 2-amino-N6-methyl purine, 1-thio adenosine, 8-azido adenosine, 2′-F-ara adenosine, 2′-F adenosine, 2′-OH-ara adenosine, and N6- (19-amino-pentaoxanonadecyl) adenosine.

[0060] In some embodiments, the modRNA comprises a modified guanine selected from the group consisting of inosine (I), 1-methyl inosine (m1I), wyosine (imG), methylwyosine (mimG), 4-demethyl wyosine (imG-14), isowyosine (imG2), wybutosine (yW), peroxywybutosine (o2yW), hydroxywybutosine (OHyW), undermodified hydroxywybutosine (OHyWy), 7-deaza guanosine, queuosine (Q), epoxyqueuosine (oQ), galactosyl queuosine (galQ), mannosyl queuosine (manQ), 7-cyano-7-deaza guanosine (preQ0), 7-aminomethyl-7-deaza guanosine (preQ1), archaeosine (G+), 7-deaza-8-aza guanosine, 6-thio guanosine, 6-thio-7-deaza guanosine, 6-thio-7-deaza-8-aza guanosine, 7-methyl guanosine (m7G), 6-thio-7-methyl guanosine, 7- methyl inosine, 6-methoxy guanosine, 1-methyl guanosine (m1G), N2-methyl-guanosine (m2G), N2,N2-dimethyl guanosine (m22G), N2,7-dimethyl guanosine (m2,7G), N2, N2,7-dimethyl guanosine (m2,2,7G), 8-oxo guanosine, 7-methyl-8-oxo guanosine, 1-methio guanosine, N2-methyl-6-thio guanosine, N2,N2-dimethyl-6-thio guanosine, alpha-thio guanosine, 2′-O-methyl guanosine (Gm), N2-methyl-2′-O-methyl guanosine (m2Gm), N2,N2-dimethyl-2′-O-methyl guanosine (m22Gm), 1-methyl-2′-O-methyl guanosine (m1Gm), N2,7-dimethyl-2′-O-methyl guanosine (m2,7Gm), 2′-O-methyl inosine (1m), 1,2′-O-dimethyl inosine (m1Im), 2′-O-ribosyl guanosine (phosphate) (Gr(p)), 1-thio guanosine, O6-methyl guanosine, 2′-F-ara guanosine, and 2′-F guanosine.

[0061] modRNA may include, for example, a non-natural or modified nucleotide. The non- natural or modified nucleotide may include, for example, a backbone modification, sugar modification, or base modification. The non-natural or modified nucleotide may include, for example, a base modification. In some embodiments, the base modification is selected from the group consisting of 2-amino-6-chloropurine riboside 5′ triphosphate, 2-aminoadenosine 5′ triphosphate, 2-thiocytidine 5′ triphosphate, 2-thiouridine 5′ triphosphate, 4-thiouridine 5′ triphosphate, 5-aminoallylcytidine 5′ triphosphate, 5-aminoallyluridine 5′ triphosphate, 5- bromocytidine 5′ triphosphate, 5-bromouridine 5′ triphosphate, 5-iodocytidine 5′ triphosphate, 5- iodouridine 5′ triphosphate, 5-methylcytidine 5′ triphosphate, 5-methyluridine 5′ triphosphate, 6- azacytidine 5′ triphosphate, 6-azauridine 5′ triphosphate, 6-chloropurine riboside 5′-triphosphate,7-deazaadenosine 5′ triphosphate, 7-deazaguanosine 5′ triphosphate, 8-azaadenosine 5′ triphosphate, 8-azidoadenosine 5′ triphosphate, benzimidazole riboside 5′ triphosphate, N1- methyladenosine 5′ triphosphate, N1-methylguanosine 5′ triphosphate, N6-methyladenosine 5′ triphosphate, O6-methylguanosine 5′ triphosphate, N1-methyl-pseudouridine 5′ triphosphate, puromycin 5′-triphosphate, and xanthosine 5′ triphosphate. Thus, according to some embodiments, the modRNA comprises N1-methyl-pseudouridine 5′ triphosphate.

[0062] In some embodiments, the FLI-1 modified-mRNA is a synthetic modified-mRNA. IVT (in vitro transcription) templates can be constructed for the synthesis of modRNA. In a specific example, clean PCR products generated with plasmid templates purchased from GenScript were used as the template for mRNA. Modified RNAs (or modRNAs) were generated by transcription in vitro with a customized ribonucleoside blend of ARCA; 30-O-Me-m7G (50) ppp(50)G (Trilink Biotechnologies); GTP; ATP; CTP ( Life Technologies) and N1- methylpseudouridine-50-triphosphate (Trilink Biotech-nologies). The mRNA was purified with the MEGA clear kit (Life Technologies) according to the manufacturer’s instructions or using Amicon Ultra-4 Centrifugal Filter Unit 4 mL,10 kDa (Millipore Sigma) and treated with Antarctic Phosphatase (NEB). It was then re-purified with the MEGA clear kit. The mRNA was quantified using a Nano Drop spectrometer (Thermo Scientific), precipitated with ethanol and ammonium acetate, and re-suspended in10 mM Tris-HCl and 1 mM EDTA.

[0063] Other Features of the Present Method

[0064] In some embodiments, the transient elevated expression of FLI-1 activates adult non- activated human HSPCs without the risk of leukemic transformation.

[0065] In some embodiments, after elevating the expression of FLI-1transiently in adult non- activated human HSPCs, the HSPCs are cocultured with a regenerative vascular niche platform to expand the HSPCs, or with any other culture conditions allowing human HSPC expansion.

[0066] Hematopoietic stem and progenitor cells (HSPCs) are uniquely capable of self-renewal and provision of all of the mature elements of the blood and immune system throughout the lifetime of an individual. HSPC self-renewal is regulated by both intrinsic mechanisms and extrinsic signals mediated via specialized microenvironments or ‘niches’ wherein HSPCs reside.

[0067] Hematopoietic stem and progenitor cells (HSPCs) are notoriously difficult to maintain and grow in culture. Many such cells must be grown with “feeder cells”. For example, feederlayers comprising primary endothelial cells can be used to support the growth of hematopoietic stem and progenitor cells. However, these feeder layers of primary endothelial cells generally require the presence of serum or growth factors for long-term maintenance. Many stem cells cannot tolerate the presence of serum or certain growth factors. Human vascular endothelial umbilical cord (HUVEC) derived cells transduced with the Adenovirus peptide E4ORF1 are described in U.S. Patent No. 8,465,732 to Shahin Rafii et al., which is hereby incorporated by reference in its entirety. E4ORF1 transduced HUVEC-derived cells are one type of support providing cells that can be cultured in serum free conditions which support human stem and progenitor cell expansion in vitro. These cells provide signaling cues which stimulate regenerative like conditions promoting expansions of HSPCs in vitro.

[0068] In some embodiments, the fold of expansion of the FLI-1 activated HSPCs is enhanced by at least 2 fold, at least 3 fold, at least 4 fold, at least 5 fold, at least 6 fold, at least 7 fold, at least 8 fold, at least 9 fold, or at least 10 fold as compared to the non-activated HSPCs without elevating the expression of FLI-1 transiently.

[0069] In some embodiments, the adult non-activated human HSPCs are obtained from a donor suffering from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), a co- morbidity including diabetes, from a poorly mobilizing donor, or for gene therapy purposes that requires introduction of a correct gene to replace a mutated one in blood related disorders (e.g., thalassemia, immunodeficiencies, etc.). Regenerated Adult HSPCs

[0070] Another aspect of this disclosure is directed to a population of regenerated and expanded adult hematopoietic stem and progenitor cells (HSPCs) generated by the method as disclosed above.

[0071] In some embodiments, the population of regenerated and expanded adult HSPCs are capable of engraftment and full reconstitution in a recipient.

[0072] In some embodiments, the population of regenerated and expanded adult HSPCs are capable of reconstitution in the peripheral blood, the spleen and the bone marrow of the recipient.

[0073] In some embodiments, the population of regenerated and expanded adult HSPCs, where the capability of reconstitution of the HSPCs is enhanced by at least 5-7 fold, as compared to the adult non- activated HSPCs without elevating the expression of FLI-1 transiently.

[0074] Another aspect of this disclosure is directed to a method of treating a subject in need of activated and expanded adult HSPCs, which comprises: obtaining hematopoietic stem cells (HSPCs) from the subject or a compatible donor, elevating the expression of Friend of Leukemia Integration-1 (FLI-1) transiently in the obtained HSPCs to obtain regenerated and expanded pool of HSPCs, and administering the regenerated and expanded HSPCs to the subject.

[0075] In some embodiments, the subject is in a need for an expanded pool of HSPCs, or suffers from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), or a co- morbidity including diabetes, β-thalassemia, or sickle cell disease that requires an expanded pool of genetically modified HSPCs for transplant. EXAMPLES

[0076] The present description is further illustrated by the following examples, which should not be construed as limiting in any way. The contents of all cited references (including literature references, issued patents, and published patent applications as cited throughout this application) are hereby expressly incorporated by reference. Example 1: In depth interrogation of dynamic HSPC states reveals absence of Fli-1 transcriptional activity in non-active quiescent HSCs.

[0077] In search of transcriptional hubs coordinating the HSC-niche adaptability and crosstalk, comprehensively probed a murine perivascular niche residing population of bone marrow (BM) HSPCs, highly enriched for long term repopulating (LTR) HSCs (Kiel, M.J., et al, Cell 121, 1109-1121, 2005) phenotypically marked as CD150+ / CD48negative / Lineagenegative / Sca-1+ / c-Kit+(SLAM LSK HSPCs) was comprehensively probed. This population of sorted cells was subjected to combined multimodal single nuclei RNA- and ATAC-seq (snRNA / ATAC-seq) analysis to define transcriptional output and chromatin accessibility states. Annotating cell identity for clusters over weighted nearest neighbor (WNN) uniform manifold approximation and projection (UMAP) analysis, clusters for hematopoietic stem cells (HSC), hematopoietic multi-potent progenitors (MPP), progenitors for platelet producing megakaryocytes (MkP) and for erythrocytes (EryP) were identified, confirming a previous report for SLAM LSK HSPCs (Oguro, H., et al, Cell Stem Cell 13, 102-116, 2013) (FIG.1a). To transcriptionally authorize the location and identity of HSC derived nuclei over our WNN UMAP, an HSC transcriptional signature recently defined for engraftable LTR-HSCs was applied, achieved with application ofbarcoding-based single cell lineage tracing (Rodriguez-Fraticelli, A.E., et al, Nature 583, 585- 589, 2020). Notably, although confirming the HSC cluster identity, two distinct centers with the highest Kernel densities were observed (FIG.1b), suggesting two distinguished sub-populations in the HSC cluster. Differential nuclear RNA transcriptome analysis confirmed the identity of each cluster with known gene markers for each HSPC sub-type (FIG. 1c). Differential motif activity based on chromatin accessibility analysis further exhibited transcription factor (TF) activity of known HSC factors, in the HSC cluster, among numerous other unique TFs for each cluster that were not defined yet for their role in hematopoiesis (FIG.1d).

[0078] To further uncover additional HSC and MPP sub-clustering potential, only the HSC and MPP single nuclei were re-clustered following exclusion of MkP and EryP clusters, and reapplied HSC transcriptional signature to confirm localization of HSC sub-clusters (FIG.1e). New HSC / MPP clustering WNN UMAP analysis exhibited two HSC clusters (HSC1 and HSC2), which corelate with the two density centers harboring the highest HSC signature score. Two MPP clusters (MPP1 and MPP2), and an HSC-MPP mixed cluster with low HSC signature score, were further identified (FIG.1f). Examining differential transcriptome expression and motif activity in HSC / MPP sub-clusters, uppermost activity of Spi family TFs in the late MPP2 cluster was noted but no activity in the HSC clusters (FIG. 1g). This finding supports the notion that Spi activity in HSCs may be restricted to stress-induced regenerative conditions18, but not during steady state. The earlier MPP1 cluster was defined by GATA TF family activity, while the transitioning HSC-MPP cluster was predominantly defined by the accessibility of Nfi family of TFs (FIG.1g). Comparing the gene ontology (GO) enrichment results analysis for biological processes and motif activity for the distinct HSC clusters, it was noted that the HSC1 cluster exhibited an active proliferative signature with activity of self-renewal associated TFs, including Rbpj19 and Stat3 / 520,21 (FIGS.1g, h,). While cluster HSC2 represents the metabolically non- active population of HSCs with active TF motifs maintaining murine stem cell quiescence such as Ctcf22 and Hlf23, additionally it displayed enrichment for negative regulation of multiple active cellular processes (FIGS. 1g, h). Examining the top enriched active motifs portraying each HSC / MPP subclusters, the unique lack of activity of the hemato-vascular TFs Erg and Fli-1 in the quiescent and non-active HSC2 cluster versus the other clusters was noted (FIGS.1g, h).

[0079] It has been recently found that expression of Erg and Fli-1 in endothelial cells, is essential to uphold vascular transcriptional physiological programs, and thus hypothesized that they mayperform similarly for activated HSCs24. While the role of Erg in regulation of HSC activity and balancing between self-renewal to differentiation was established (Loughran, S.J., et al, Nat Immunol 9, 810-819, 2008), (Knudsen, K.J., et al, Genes Dev 29, 1915-1929, 2015) the role of Fli-1 (Friend Leukemia integration-1) (Li, Y., et al, Oncogene 34, 2022-2031, 2015) is poorly characterized in HSC fate regulation.

[0080] Global embryonic Fli-1 deficiency results in fetal lethality attributed to vascular leakiness, and adult hematopoietic inducible Fli-1 genetic deletion impairs development and maturation of some hematopoietic myeloid lineages, affecting also the numbers of and skewing between myeloid progenitors (Spyropoulos, D.D., et al, Mol Cell Biol 20, 5643-5652, 2000) (Starck, J., et al, Blood 116, 4795-4805, 2010) and directs megakaryocyte cell fate specification (Palii, C.G., et al, Cell Stem Cell 24, 812-820 e815, 2019). Additionally, Fli-1 regulates lymphocyte progeny by restricting formation of memory NK cells31 and by restraining effector T cell lineage differentiation (Chen, Z., et al, Cell 184, 1262-1280 e1222, 2021). Nonetheless, the physiological role of the Fli-1 TF in modulating active versus quiescent states of adult immune stem cells was never defined. Example 2: Adult hematopoietic Fli-1 deficiency induces thrombocytopenia and impairs HSC immune regenerative capabilities.

[0081] To formally determine the role of Fli-1 in adult HSCs and its role in the regulation of adult hematopoiesis, Fli-1 deletion in adult mice was genetically induced. Global and hematopoietic specific Fli-1 deficiency in mice resulted in rapid mortality due to severe thrombocytopenia.

[0082] Further examining HSPC status in the BM, failure of committed progenitors to form megakaryocytic colonies was observed, whereas the BM displayed a typical myeloid progenitor “stress response” as evidenced by enhanced numbers of both granulocyte-macrophage colonies and phenotypically defined Lineagenegative / Sca-1+ / c-Kit+(LSK) HSPCs. By contrast, a decrease in the number of the more primitive and stem cell enriched SLAM LSK HSPCs was noted. This potential stem cell impairment was further corroborated by the finding that HSCs within the Fli- 1ROSAΔLSK cells, failed to engraft following transplantation. Thus, Fli-1 deficiency manifests HSC stress-response, repopulation, and engraftment defects.

[0083] To exclude niche homing defects of Fli-1ROSAΔLSK HSPCs, HSPC BM trafficking capacity was examined by intravital microscopy 24 hours following transplantation into normalwild-type irradiated mice. It was noted that while a small subset of Fli-1ROSAΔHSPCs (19%) were wedged at the luminal side of the vessel wall, the majority of Fli-1ROSAΔHSPCs managed to home into the BM as well as 100% of WT HSPCs.

[0084] Speculating that this small subset of cells failing to home to the BM could represent repopulating HSCs, LSK HSPCs was transplanted prior to Fli-1 deficiency induction and administrated tamoxifen a week later, ensuring proper BM lodgment. Again, Fli-1ROSAΔHSCs failed to repopulate transplanted mice. Furthermore, mixed competitive transplants with WT cells and induction of Fli-1 deletion 4 months post-transplant revealed a gradual multi-lineage collapse of hematopoiesis derived from Fli-1ROSAΔHSPCs, with a very rapid deterioration of the myeloid lineage followed by a decline in the lymphoid lineages. Enhanced frequencies of apoptotic and quiescent HSPCs were observed following Fli-1 deficiency induction in this model. Thus, Fli-1 deficiency in HSCs results in immune lineage developmental defect, impairment of survival, increased quiescence, and hampered self-renewal / differentiation capacities, preventing proper immune regeneration and recovery. Example 3: Fli-1 deficient HSPCs transcriptionally transition into a quiescent state.

[0085] To avoid hematopoietic progeny stress-driven influence and to confirm an HSC specific and autonomous effects following Fli-1 deletion, Fli-1 floxed transgenic mice were backcrossed with a mouse line carrying an HSC specific promoter driven Cre recombinase (SCL-CreERT2) (Gothert, J.R., et al, Blood 105, 2724-2732 (2005) (Fli-1SCLΔ) and a ROSA-driven / Cre-activated Tomato (TMT) fluorescent reporter. Using this approach, a decrease in numbers of both LSK HSPCs and SLAM LSK HSPCs in the BM of induced Fli-1SCLΔmice was observed. A decrease in frequency of Fli-1SCLΔBM TMT+LSK and SLAM LSK HSPCs was also noted, which may result from either enhanced quiescence of Fli-1SCLΔTMT+HSPCs or due to Cre recombinase inefficiency to excise 3 transgenes in Fli-1SCLΔBM cells. Thus, to assess the regenerative potential of Fli-1SCLΔHSCs with high likelihood of full Fli-1 genomic excision, only BM TMT+LSK HSPCs were sorted and transplanted from WT or Fli-1SCLΔmice. Confirming the previous findings, a complete failure of Fli-1SCLΔHSCs to engraft into and reconstitute recipient mice was observed.

[0086] To further assess whether and how Fli-1 confers niche-guided regenerative potential to HSPCs, previously described vascular niche-based regenerative HSPC expansion system (Butler, J.M., et al, Cell Stem Cell 6, 251-264, 2010) was leveraged. This approach mimics physiologicalstress-induced regenerative conditions and permits expansion of a sufficient pool of HSPCs that can be isolated for multi-omics analyses. In this system, Fli-1 deficient HSPCs failed to expand in co-culture with vascular niche cells. Notably, Fli-1 deficient HSPCs were not responsive to the microenvironmental signals, as no beneficial effect for Fli-1ROSAΔHSPCs expansion was observed in the presence of a vascular niche versus no niche in presence (FIG.2a). Analyzing expansion dynamics in co-culture, hematopoietic arrest and collapse very shortly following induction of Fli-1 deletion was noted. Therefore, Fli-1 deficiency may result in the impairment of HSPCs to sense incoming activation cues from a prototypical niche, such as a vascular niche.

[0087] Differential gene expression analysis, of Fli-1ROSAΔversus WT HSPCs undergoing expansion in co-culture with a vascular niche, revealed alteration in thousands of genes. Gene set enrichment analysis (GSEA) for biological processes displayed enhanced biological activities associated with maintenance of quiescence among Fli-1ROSAΔHSPCs, such as ribosome biogenesis (Le Bouteiller, M., et al, J Exp Med 210, 2351-2369, 2013), lysine acetylation (Yang, Y., et al, Blood 139, 845-858, 2022), alongside with negative regulation of myelopoiesis. In agreement, Fli-1ROSAΔHSPCs exhibited a decline in multiple glucose / glycolytic processes which were recently suggested as the main energetic source during HSC activation (Arif, T., et al, Blood 134, 271-271 (2019) (FIG.2b).

[0088] Next, differential chromatin landscape accessibility and chromatin modification for transcriptional priming patterns were examined by ATAC-seq and H3K27ac ChIP-seq analyses, between Fli-1ROSAΔand WT expanding HSPCs in co-cultures. Motif enrichment analysis (MEA) for differential ATAC and H3K27ac ChIP peaks enriched in promoter / enhancer regions from Fli-1ROSAΔHSPCs presented a signature of elements restricting HSC activation, while sustaining and enforcing HSC quiescence, such as the TFs Pu.1 (Spi1) (Staber, P.B., et al, Mol Cell 49, 934-946, 2013) and IRF2 (Sato, T., et al, Nat Med 15, 696-700, 2009) (FIG.2c). Moreover, Spi and IRF factors partner physically in HSCs by IRFs binding to Spi’s PEST domain (Gupta, P., J Cell Mol Med 13, 4349-4363 (2009). Notably, MEA ATAC-seq signature was almost identical to Spi1’s ChIP-seq MEA signature, that was performed on primitive and mostly quiescent HSPCs (Chavez, J.S., et al, J Exp Med 218(2021). Additionally, examining the MEA signature of ATAC and H3K27ac ChIP peaks enriched for WT HSPCs, it was confirmed that Fli-1 deletion in HSPCs results with loss of chromatin accessibility and chromatin priming of binding domains related to Fli-1 and other homologous ETS TFs. Further employing the ATAC-seqdata, computational “footprinting” analysis (Li, Z., et al, Genome Biol 20, 45, 2019) was performed to reveal TF binding activity. This approach further indicates that Fli-1ROSAΔHSPCs contain higher predicted activity of Spi family members (FIG. 2d).

[0089] To probe the differential activation or quiescence programs installed in Fli-1ROSAΔversus WT HSPCs, through their motifs, it was reanalyzed and a published set of hematopoietic TF ChIP-seq data from in vitro activated and expanded HSPCs (Wilson, N.K., et al, Cell Stem Cell 7, 532-544, 2010) was applied. Combining Fli-1 ChIP-seq with the differential RNA-seq expression data for binding and expression target analysis (BETA) (Wilson, N.K., et al, Cell Stem Cell 7, 532-544 (2010) it was found, as anticipated, that Fli-1 was among the top ETS TF motifs associated with the ChIP-seq peaks at downregulated gene targets from Fli-1ROSAΔHSPCs. Unexpectedly, it was discovered that Spi1 surfaced as the top-ranking alternative binding element, whose motif was enriched for Fli-1 targeted genes versus non-targeted ones. As Spi1 and Fli-1 may opposingly regulate a similar set of genes accountable for HSPC activation, Fli-1 and Spi1 ChIP-seq data sets were combined with the differentially expressed RNA data set. Both Fli-1 and Spi1 exhibited overlapping binding activity to the majority of genes which were downregulated in Fli-1ROSAΔHSPCs (FIG.2e). As both RNA- and Spi1 ChIP- seqs were acquired from activated HSPC, Spi1 targeting of upregulated genes in Fli-1ROSAΔHSPCs was not observed. However, applying an alternative Spi1 ChIP-seq data set, acquired from HSPCs highly enriched for dormant HSCs (Chavez, J.S., et al, J Exp Med 218, 2021), it could be confirmed that Spi1 targeting of a portion of genes upregulated in Fli-1ROSAΔHSPCs.

[0090] To confirm Fli-1’s position as a master TF, switching between quiescence to activation programs, changes in transcriptional expression of HSC TFs known to regulate quiescence or activation were evaluated. A significant transcriptional induction of quiescence program genes in Fli-1ROSAΔHSPCs along with a significant transcriptional cellular activation program shutdown in Fli-1ROSAΔHSPCs were determined.

[0091] To interrogate the premise that HSPC quiescence is an active process rather than a passive one, the multi-omics data (RNA, ATAC, and H3K27ac -seqs) were combined and implemented the activity-by-contact (ABC) model (Fulco, C.P., et al, Nat Genet 51, 1664-1669, 2019) to estimate the magnitude of active interactions between enhancer-to-gene-regions, based on chromatin and transcriptional status. Examining the set of HSC quiescence factors, an increased averaged score for activity of regulating enhancers for the majority of quiescencefactors, and / or increased de novo appearance of actively regulating enhancers were noted. Specifically, probing Spi1 genomic loci, increased number of regulating enhancers, with pre- existing ones displaying higher active connectivity score to the Spi1 gene in Fli-1ROSAΔHSPCs were observed (FIG.2f). This observation is bolstered by a previously predicted model in which Spi1, in HSPCs, transcriptionally mediates positive autoregulatory genomic activity, induced by enhancer-gene interaction via active chromosomal looping (Staber, P.B., et al, Mol Cell 49, 934- 946, 2013). Thus, it is suggested that in the absence of Fli-1, transcriptional and chromatin reorganizations are occurring to actively to implement a quiescence program in HSPCs. Indeed, Fli-1ROSAΔHSPCs exhibited reduced cycling in co-culture with a regenerative vascular niche.

[0092] Further observing Spi1 and Fli-1 genomic loci revealed that both genes are mutually targeting each other and that in the absence of Fli-1 there is an increased histone acetylation modification of the chromatin at regulatory sites, suggesting a possible transcriptional priming by Spi1 with no evident change in chromatin accessibility.

[0093] Overall, the data qualifies Fli-1 as a transcriptional master regulator in HSPC activation, possibly counterbalancing Spi1-mediated quiescence, when both are actively binding overlapping / neighboring sites on the chromatin, during regenerative hematopoiesis. Example 4: Fli-1 presets niche co-adoptability through Vegf / Notch signaling.

[0094] In order to gain mechanistic insight regarding processes which augment Fli-1 dependent hematopoietic activation through interaction with the vascular niche, the sets of genes that were suppressed both on the RNA and chromatin accessibility levels in Fli-1ROSAΔHSPCs (FIG.7a) were queried, presuming that those are controlled by a global Fli-1 targeted program. GO for biological pathways analysis revealed that Fli-1ROSAΔHSPCs were transcriptionally inferior to respond to various types of external stimuli, mainly immune stress associated inflammatory activation cues, and displayed impaired capacity for cytokine production (FIG. 7b), two features which are crucial for the interaction and crosstalk between HSPCs to their neighboring niche cells. To confirm this finding, the transcriptome of HSPC sensory elements were examined, and in Fli-1ROSAΔHSPCs, a significant elevated expression in quiescence promoting extracellular sensory components along with suppression of known hematopoietic extracellular activation components were distinguished (FIGS. 7c, d). Protein expression analysis of expanding HSPCs in co-culture with a vascular niche, indicates that Fli-1ROSAΔHSPCs downregulate the dual expression of activation elements such as LIF and CSF1 (G-CSF) receptors (Kaur, S., et al, JHematol Oncol 14, 3, 2021) (Pruijt, J.F., Stem Cells 15, 50-55, 1997) while upregulating quiescence elements such as CD150 (Slmaf1) (Weksberg, D.C., Blood 111, 2444-2451, 2008), although no change was observed in the primitive stem cell marker EPCR (Procr) (Gur-Cohen, S., et al, Nat Med 21, 1307-1317, 2015) (FIGS.7e-h).

[0095] This data indicates that a master transcriptional regulator like Fli-1 presets HSPC activation programs and prepares HSCs to prompt into a regeneratively active state through sensing of the relevant augmenting signals arriving from a cytokine-stimulated microenvironment.

[0096] It has been shown that activation of Notch signaling in HSPCs by vascular niche- expressed Notch ligands augments HSPC developmental choices such as regenerative expansion while limiting premature steady state differentiation (Tikhonova, A.N., et al., Nature 569, 222- 228, 2019) (Butler, J.M., et al., Cell Stem Cell 6, 251-264, 2010). This crosstalk with the vascular niche to reciprocally activate Notch signaling is initiated by HSPCs via secretion of Vegfa to stimulate specialized vascular ECs (Chen, Q., et al., Cell Stem Cell 25, 768-783 e766, 2019).) (Butler, J.M., et al., Cell Stem Cell 6, 251-264, 2010). Thus, dysregulation of Vegf / Notch pathways might explain Fli-1ROSAΔHSPC insensitivity to vascular niche presence (FIG.2a) and support the observed suppression of extracellular sensing elements along with cytokine production defects in Fli-1ROSAΔHSPCs (FIG. 7b). To address this hypothesis, the regulatory role of Fli-1 in masterminding the reciprocal Vegf / Notch pathways crosstalk in HSPCs was interrogated. Negative dysregulation for multiple Notch and Vegf pathway elements was observed in Fli-1ROSAΔHSPCs, among which Vegfa RNA was dramatically downregulated (FIGS. 3a, b). Although the requirement for Notch signaling in HSC maintenance is debated (Lampreia, F.P. et al., Curr Stem Cell Rep 3, 202-209, 2017), Notch1 activation was shown to augment HSC self-renewal (Varnum-Finney, B., et al., Nat Med 6, 1278-1281, 2000) (Stier, S.et al., Blood 99, 2369-2378, 2002) while active Notch signaling robustly specifies long-term repopulating HSCs among HSPCs along with coordination of downstream developmental differentiation choices(Duncan, A.W., et al., Nat Immunol 6, 314-322, 2005). Indeed, BM Fli- 1ROSAΔHSPCs co-cultured with a vascular niche or induced in vivo, displayed reduced Notch1 and Vegfa protein levels, and diminished activation of downstream Notch reporting signal (FIGS. 3c, d and FIGS.8a-d). Further inspection of Notch1 genomic locus combining the multiome analyses indicated that Notch1 locus region contained regulatory elements whichdisplayed Spi1 as well as Fli-1 binding activity. In Fli-1ROSAΔHSPCs these Spi1-targeted regions displayed reduced ATAC signal, representing reduced chromatin accessibility, yet presented an enhanced “footprinting” signal, indicating higher occupancy by a TF (FIG.3e). This signifies that Spi1 may transcriptionally suppress Notch1 in order to prevent HSPC activation. Moreover, few additional elements in the Notch signaling cascade and Vegfa itself displayed Spi1 and Fli-1 targeted regulatory sites in their enhancer / promoter regions (FIG.3f and FIG. 8e).

[0097] Thus, it was proposed that Fli-1 transcriptionally orchestrates the sensing and adaptability to niche-derived Notch signals required to augment a regenerative activation program in HSPCs. Spi-1’s targeting of Notch1, other Notch signaling pathway elements, and Vegfa may indicate for a possible transcriptional suppression of this niche / HSC crosstalk to preserve HSCs in a quiescent non-active state, preventing niche stimulation and the sensing of activation guiding signals arriving from the surrounding microenvironment. Example 5: Induction of Notch1 signaling rescues regenerative capacities of Fli-1 deficient HSPC.

[0098] To determine whether HSPCs are receptive to a customized regenerative vascular niche, rather than purely acting autonomously, Fli-1ROSAΔmice were bred with mice carrying a conditional Cre inducible transgene of the intracellular component of the murine Notch1 gene lacking the c-terminal domain (N1-ICiOE). In this combined mouse line, upon tamoxifen induction there is a simultaneous deletion of Fli-1 alleles and induction of constitutively enforced Notch1 signaling activity (Fli-1ROSAΔN1-ICiOE), mimicking the activation of Notch1 signaling by a stimulated niche. Earlier studies showed that Notch1 overexpression in HSPCs increases self- renewal while hindering differentiation rate, also skewing it towards a lymphoid output (Varnum-Finney, B., et al., Nat Med 6, 1278-1281, 2000) (Stier, S.et al., Blood 99, 2369-2378, 2002). Accordingly, N1-ICiOEHSPCs exhibited a drastic expansion while Fli-1ROSAΔN1-ICiOEHSPCs demonstrated a rescue of HSPC expansion in co-culture with a vascular niche platform, preferentially expanding immature HSPCs, while still lacking megakaryocytic development (FIGS. 4a, b and FIGS.8f-h).

[0099] Hence, combined with the previous data, a mechanistic model was proposed in which Fli- 1 presets an HSPC activation program by producing angiokines such as Vegfa priming and inducing an adaptive and supportive Notch ligand expressing niche. Simultaneously, Fli-1 istranscriptionally coordinating an extracellular receptive sensory machinery for Notch signaling with the intracellular cooperative elements to propagate niche endorsed Notch activation signals for HSPC regenerative expansion (FIG.8i). In support, it was observed that BrdU incorporation, as a marker for active cell cycling, was reduced in Fli-1ROSAΔHSPCs, enhanced above WT levels in N1-ICiOEHSPCs, and rescued to WT levels in Fli-1ROSAΔN1-ICiOEHSPCs, which was in complete correlation with the HSC activation marker CDK6 (Scheicher, R., et al., Blood 125, 90- 101 (2015) expression in co-cultured HSPCs undergoing regenerative expansion(FIGS. 9a-c).

[0100] To study the transcriptional dynamics of HSCs in co-culture in vitro conditions, it has been sorted and single cell RNA-sequenced (scRNA-seq) expanding LSK HSPCs 48 hours post induction of various genetic conditions. As surface protein expression of stem cell markers is vibrant and not stable in vitro, the HSC sub-clusters have been classified using the RNA combination of E-SLAM markers (EPCR+\CD34-\CD150+). Two HSC sub-clusters were identified (#7 and 15#) (FIGS.4d, e). Among these two HSC sub-clusters, Fli-1 deficiency decreased the number of cells in cluster #15, reducing its cellular portion. Induction of Notch1 signaling in Fli-1 deficient HSPCs managed to effectively restore the subset of cells in cluster #15, while Notch1 overexpression alone increased the frequency of cells in this cluster above WT levels (FIGS.9d, e). Interestingly, both Fli-1 deficiency and Notch1 overexpression increased the proportion of cells in cluster #7 (FIGS.9d, e). Interpreting the genomic differences for these two clusters by GSEA for biological pathways, revealed very high and significant expression of genes involved in lysosome processing, which is essential for active maintenance of quiescent HSCs (Garcia-Prat, L., et al., Cell Stem Cell 28, 1838-1850 e1810, 2021), in cluster #7. Cluster #15 exhibited high expression of activation genes defined as stem cell pluripotency pathways and additionally higher expression of genes involved in activity of multiple signaling pathways such as Notch and WNT (FIG. 7f). Indeed, plotting cell cycle scoring of HSC sub- clusters revealed an activated state of cluster #15 and a quiescent state for cluster #7. Cycling cells appear in higher frequency in cluster #15 following Notch1 induction and disappear from cluster #15 following Fli-1 deletion and are restored upon enforced induction of Notch1 signaling in Fli-1 deficient HSPCs (FIG.4g).

[0101] Furthermore, transplantation of expanded Fli-1ROSAΔN1-ICiOEHSPCs revealed an engraftment rescue as these HSPCs contributed both to short- and long-term hematopoiesis, unlike Fli-1ROSAΔHSPCs which completely fail to repopulate recipient mice (FIG. 4h).Unfortunately, recipient mice transplanted with expanded N1-ICiOEHSPCs exhibited poor survival and rapid mortality accompanied with leukopenia, anemia, and thrombocytopenia (FIGS. 8a-d). Closer examination revealed higher level of engraftment of cells derived from N1- ICiOEHSPCs versus WT controls, with a clear differentiation bias towards the T-cell lineage at expense of B-cells and myeloid cells (FIGS. 8e-h). Previously it was reported that when bred with hematopoietic specific Cre inducer, similar N1-ICiOEmouse lines develop T-cell acute lymphoblastic leukemia (T-ALL) (Buonamici, S., et al., Nature 459, 1000-1004, 2009). Additionally, it was shown that, as in this case, superphysiological activation levels of Notch1 expand HSCs, however these HSCs exhaust from prolonged activation and eventually develop into T-ALL (Chiang, M.Y., Shestova, O. et al, Blood 121, 905-917 (2013). Notably, transplanted Fli-1ROSAΔN1-ICiOEHSPCs exhibited an opposing differentiation pattern to WT HSPCs, during repopulation and recovery, reconstituting initially mostly lymphoid B-cell and T- cell output after short term engraftment, but eventually also exhibited restoration of the myeloid lineage, following long-term engraftment period. Thus, in vitro expanded Fli-1ROSAΔN1-ICiOEHSPCs are skewed towards lymphogenesis following transplantation but also may retain a functional HSC population capable of engraftment and multipotent differentiation.

[0102] The results gain additional insight that mice transplanted with Fli-1ROSAΔN1-ICiOE HSPCs demonstrated viability and attenuated T-cell contribution 4 months post-transplant. Therefore, Fli-1 deficiency may have hindered Notch1-driven T-ALL development which results in rapid mortality of recipient mice. This new finding strongly suggests that Fli-1 may play an essential role in malignant T-cell type leukemia instigation, which was not yet reported. Example 6: Maintenance of Notch1 signaling in the absence of Fli-1 rescues HSC functionality.

[0103] To validate the rescue of functional HSCs by niche restored signals, WT and Fli- 1ROSAΔN1-ICiOEdonor-derived immature CD45+ / LineagenegativeBM cells were isolated at 4 months post-transplant and scRNA-seq analysis was performed. Fli-1ROSAΔN1-ICiOEHSPCs displayed multipotent contribution to the more mature transcriptionally defined hematopoietic cell types in the lineage-negative marrow compartment, though with a relative skewing toward lymphoid cells and differential distribution among various myeloid populations compared with WT HSPCs (FIGS. 4i, j). “Zooming in” on the portion of UMAP space representing transcriptionally defined HSCs, multi-potent progenitors (MPP), and lymphoid-primedprogenitors (LPP), it was observed that Fli-1ROSAΔN1-ICiOEHSPCs contribute to the HSC population at a similar frequency as WT HSPCs, with relative skewing towards the LPPs at the expense of the MPPs (FIG.4k). Moreover, using previously published gene signatures derived from scRNA-seq data for functional HSCs (Wilson, N.K., et al., Cell Stem Cell 16, 712-724, 2015) with LTR engraftment potential (Rodriguez-Fraticelli, A.E., et al., Nature 583, 585-589, 2020), it is shown that Fli-1ROSAΔN1-ICiOEHSPCs contain transcriptionally-defined functionally long-term engrafting HSCs (FIG.4l), exhibiting differential transcriptional output.

[0104] Thus, Fli-1-levied HSC regenerative activation program can be rescued by enforced expression of niche-propagated Notch signaling, confirming that niche-derived signals are essential to augment, and support hardwired intrinsic stem cell programs. Example 7: An active human HSPC signature associated with FLI-1 transcriptional activity categorizes cord blood HSCs versus adult mobilized HSCs.

[0105] To translate the potential of Fli-1 dependent triggering of the stem cell activation programs, the attention was focused to adult human HSCs. One of the unmet needs and challenges in the field of human HSPC expansion for immune regenerative purposes is the capability to robustly expand the scarce population of human mobilized peripheral blood (mPB) HSCs. Specifically in cases such as donor mobilization failure, donors with exhaustive BM, or to benefit HSC final yield prior / following genetic therapeutic manipulation (Chen, J., Lazarus, H.M.et al, Blood Rev 47, 100771, 2021). In contrast, there is a significant advancement in the translational ability to expand human cord blood (CB) derived HSPCs (Butler, J.M., et al., Blood 120, 1344-1347, 2012).) (Wilkinson, A.C., et al., Nature 571, 117-121 (2019). To determine why mPB HSPCs are refractory to undergo ex vivo expansion, scRNA-seq analysis of sorted CD45+CD34+HSPCs were performed from both CB and mPB origins, following two days in co- culture with a vascular niche platform to prime the regenerative expansion of these cells. Higher diversity and HSPC heterogeneity were observed amongst CB CD34+cells, which also exhibited an actively cycling state in comparison to mPB CD34+cells that remained unresponsive to the regenerative expansion niche system (FIG. 5a-e, FIG.10a). GO reactome analysis of differentially expressed genes in the HSC containing cluster between CB and mPB, exhibited activation of mitotic cycling pathways amongst CB cells. By contrast, mPB cells displayed inflammatory related pathways, mainly of quiescence associated interferon signaling.

[0106] To unravel if these aberrant HSPC responses were primed by the signals emanating from the niche or were a pre-existing cell intrinsic program, RNA-seq of sorted and highly purified HSCs from CB and mPB origins were analyzed. Repeatedly, CB HSCs revealed a hallmark genomic signature associated with activation of multiple metabolic pathways and myc targets, indicating for their cycling potential. By contrast, the mPB HSCs displayed mainly inflammatory and interferon signaling pathways along with activation of TGFβ signaling and Trp53 pathways. Further applying previously defined gene lists (Venezia, T.A., et al. PLoS Biol 2, e301, 2004) (Roy, A., et al., Cell Rep 36, 109698, 2021) for HSC activation and quiescence states, CB HSC active versus mPB HSC quiescent natures were confirmed (FIG.5e). Next, to ascertain human HSCs FLI-1’s role as activation factor, previously described scATAC-seq data set for human HSPCs (Takayama, N., et al., Cell Stem Cell 28, 488-501 e410, 2021) together with reported FLI-1’s ChIP-seq peaks signature in human HSPCs (Beck, D., et al., Blood 122, e12-22,2013) were reanalyzed. After assigning the active HSC and quiescent HSC signature scores as defined by Takayama et al (Takayama, N., et al., Cell Stem Cell 28, 488-501 e410, 2021), the FLI-1 ChIP-seq signature score was applied to define which HSCs exhibited accessible regions targeted by FLI-1 as indication for FLI-1 activity. Almost a complete overlap was observed between the signatures for FLI-1 ChIP and active HSCs (FIG.5f), confirming the association between FLI-1 transcriptional activity to human HSC activation as well. Moreover, co-cultured CB HSPCs displayed higher expression levels of surface NOTCH1 receptor and internal VEGFA storages compared to mPB HSPCs (FIG.10d, e).

[0107] Thus, enforcing FLI-1 mediated chromatin remodeling may have the potential to override adult mPB HSC quiescence barrier and promote their successful adaptation to a regenerative vascular niche platform, supporting HSC expansion. Example 8: Transient FLI-1 overexpression activates mobilized adult human HSPCs.

[0108] Modified mRNA is an emerging non-immunogenic, efficient, and transient tool for safe induction of protein expression (Chien, K.R., Zangi, L. & Lui, K.O. Cold Spring Harb Perspect Med 5, a014035, 2014), with high relevance for potential oncogenes that can direct cell activation, such as in the case of Pkm2-induced cardiac regeneration (Magadum, A., et al., Circulation 141, 1249-1265, 2020). Modified-mRNA for FLI-1 transient expression in sorted human CD34+HSPCs have been applied, followed by a co-culture with a regenerative vascular niche platform to drive HSPC expansion prior to a pre-clinical study of transplantation intoimmunodeficient mice (FIG.11a). As expected, co-culturing mPB HSPCs with a vascular niche exhibited poor expansion potential in comparison to CB HSPCs (FIGS. 6a, b). Following transduction of FLI-1 modified-mRNA no beneficial effect was observed for CB HSPC expansion probably due to their already active nature, except for the more primitive CD34+CD38negHSPC, that preserve a latent activation resistant sub-population of HSCs (Kaufmann, K.B., et al., Nat Immunol 22, 723-734, 2021) (FIG.6a). Contrary, mPB HSPCs displayed a significant expansion benefit across mature hematopoietic and immature HSPC sub- populations, following FLI-1 modified mRNA transduction, achieving augmented expansion levels comparable to unstimulated CB HSPCs (FIGS. 6b, c). In agreement with the suggested model, introduction of FLI-1 modified mRNA into mPB HSPCs, increased the expression of surface NOTCH1 receptor and the internal storages of VEGFA (FIGS.11b, c). Examining the dynamic expression of FLI-1 internal protein following modified mRNA transduction, elevated levels of FLI-1 was noted which lasted for 48 hours, followed by a strong decline, and return to basal levels of control cells after 96 hours (FIG. 6d). This data indicates that transient modified mRNA-mediated elevation of FLI-1 is sufficient to switch mPB HSPCs from a quiescent to an active mode, evident also by the increased cycling state of FLI-1 transduced state (FIG. 6e). Further transplantation studies of expanded control and FLI-1 transduced mPB HSPCs, demonstrated for the later a superior engraftment and human hematopoietic reconstitution capacity in the peripheral blood (PB), the spleen, and the BM of immunodeficient mice (FIG. 6f), with higher frequency of human HSPCs present in the murine BM (FIGS.6g, h). Secondary transplantation of BM cells confirmed the higher presence of human HSCs in the BM of primary recipient immunodeficient mice engrafted with FLI-1 transduced mPB HSPCs (FIG.6i). Concerned about a possible leukemic transformation HSPCs might undergo due to their Fli-1- mediated hypercycling state, targeted DNA-sequencing analyses were performed for loci of genes known as potential tumorogenic drivers (Cheng, D.T., et al., J Mol Diagn 17, 251-264, 2015) on Fli-1 modified mRNA transduced and control HSPCs from 3 healthy mobilized adult donors, following a week of expansion in co-culture with a regenerative vascular niche platform. As expected from hypercycling cells, a low and non-significant rate of mutations occurred among FLI-1 treated HSPCs. Yet, in addition to their insignificance, these mutations were random among donors, no mutational “hotspots” were detected, and none of the detected mutations is known as a transformative driver resulting with leukemia.

[0109] Hence, transient overexpression of activation factors such as FLI-1 can be applied safely to direct the expansion of quiescent mPB HSCs, that ignore activation signals delivered from a regenerative vascular niche platform (FIG. 11d). This approach for immune regenerative therapeutics, can be potentially leveraged to promote mPB HSC expansion with our vascular niche or other existing platforms, currently effective only for CB HSC expansion. Example 9: Materials and Methods

[0110] Data reporting

[0111] No statistical methods were used to predetermine sample size. The investigators were not blinded to allocation during experiments and outcome assessment.

[0112] Animals

[0113] All animal experiments were performed under the approval of Weill Cornell Medicine Animal Care and Use Committee. Conditional mutants carrying loxP-flanked Fli1 mice (Starck, J., et al., Blood 116, 4795-4805, 2010) were generated by and obtained from Francois Morle’s laboratory. These mice were backcrossed on a C57Bl / 6J background for at least 10 generations. The following transgenic lines were applied in this study to induce specific Cre activity and gene inactivation / expression: Rosa26-CreERT2mice were purchased from Jackson laboratory (stock #008463). SCL-CreERT2mice (Gothert, J.R., et al., Blood 105, 2724-2732, 2005) were kindly provided by the generating Gothert’s laboratory through Levine’s laboratory. TNR-eGFP were purchased from Jackson laboratory and have a C57BL / 6J x SJL / J mixed background (stock #018322). Rosa26-N1-CD were purchased from Jackson laboratory (stock #008159). For human into mouse transplantation experiments NOD.Cg-KitW-41JTyr+PrkdcscidIl2rgtm1Wjl(NBSGW) were purchased from Jackson laboratory (stock #026622). For mouse into mouse transplantation experiments C57Bl / 6J (CD45.2, stock #000664) and congenic B6.SJL- PtprcaPepcb / BoyJ (SJL, CD45.1, stock #002014) mice were purchased from Jackson laboratory. Mice carrying only a Cre transgene, or the additional indicated mutations (without a Cre transgene) were used as wild-type (WT) controls to exclude non-specific effects of Cre activation and / or of floxed alleles mutation. Gene deletion or activation was confirmed by qRT– PCR measurements from isolated LSK HSPCs, by inspection of RNA-seq data from isolated LSK HSPCs, and for some of the mutants also by observing eGFP expression. Male and female mice at 8–16 weeks of age were used for all experiments involving adult mice. All mouse offspring used for this study from all strains were routinely genotyped using standard PCRprotocols. Sample size was limited by ethical considerations and background experience in stem cell transplantation (bone marrow transplantation) which exists in the laboratory for many years and other published manuscripts in the stem cell field, confirming a significant difference between means. No randomization or blinding was used to allocate experimental groups and no animals were excluded from analysis. All mutated or transgenic mouse strains had a C57BL / 6 background unless otherwise indicated. For Rosa26-CreERT2induction, Tamoxifen (Sigma, T5648-5G) was dissolved in sunflower oil (S5007-250ML) at the concentration of 20 mg / ml. Tamoxifen was intraperitoneally injected into mice at the dose of 100 mg / kg for 3 constitutive days. For SCL-CreERT2, 4-OHT (Sigma, 25G) was dissolved in sunflower oil (S5007-250ML) and intraperitoneally injected into mice at the dose of 25 mg / kg for 5 constitutive days.

[0114] Complete blood count (CBC) and mononuclear cell (MNC) count

[0115] Mice were anesthetized within anesthetic vaporizer delivery system, delivering isoflurane into a mouse holding chamber at constant flow rate of 2.5 of vaporized isoflurane (Henry Schein Animal Health 1169567762) at 3-5% for initial induction and then kept at 1-2% after the first 5 min with the oxygen adjustment (Tech Air, New York) to the flow rate of 1.0L / min. Blood was drawn from the retro-orbital plexus using capillary tubes (1.1mm X75 mm Color Code Red, Kimble Chase, 41B2501). One tube of blood (about 65 μl volume) was added into 195 μl of 10 mM EDTA / PBS buffer. Following brief votexing, samples were acquired using ADVIA120 hematology analyzer (Siemens). WBCs, RBCs, platelets, hemoglobin, hematocrit, as well as other differential blood parameters were obtained using this method. Blood, bone marrow, and cultured MNC cells were also counted using hematocytometer and EVOS imaging system (ThermoFisher Scientific) following dilution with Turk’s solution (EMD Millipore).

[0116] Transplantation assays

[0117] In all mouse into mouse transplantation experiments for engraftment purposes (non- homing experiments), mice were lethally irradiated with 475rad + 475rad doses with 5 hours interval in between, using an RS 2000 Biological Research X-ray Irradiator (Rad Source Technologies). Mice were transplanted with cells 24 hours post irradiation. For generation of chimeric mice, 1X105Lineage depleted BM cells from either WT or Fli-1ROSAΔmice were transplanted into C57Bl / 6J WT recipient mice and hematopoietic BM recovery was allowed to proceed for at least 16 weeks before any other experimental procedure. For competitive 2nderytransplantation assays from in vivo induced mice, testing HSC activity, 500 sorted (see flow and sorting section) LSK cells (per genotype and / or condition) were mixed with 2X105total BM cells from congenic SJL mice and transplanted into lethally irradiated WT congenic SJL mice. For generation of primary mixed BM chimeras, 1X105total BM cells from WT or Fli-1ROSAΔchimeric mice were mixed with 2X105Lineage depleted BM cells from congenic SJL mice and transplanted into lethally irradiated WT congenic SJL mice. For competitive transplantation assays from in vitro co-cultures, testing HSC activity, harvested and sorted LSK cells (per genotype and / or condition) were mixed with 5X105total BM cells from congenic SJL mice and transplanted into lethally irradiated WT congenic SJL mice.

[0118] In human into mouse transplantation experiments for engraftment purposes, cultured cells were harvested, collected from each experimental well, and transplanted directly into BSGW immunodeficient mice without any myeloablative pre-conditioning. For secondary transplantation experiments, total bone marrow was harvested from primary recipients after 4 months of engraftment, incubated overnight in human expansion media and transplanted again into BSGW immunodeficient mice without any myeloablative pre-conditioning for additional 4 months.

[0119] To assess levels of chimerism, at indicated time points, mice were anesthetized (as previously described), blood was drawn (as previously described) or bone marrow and spleen were retrieved following recipient mouse sacrifice, RBCs were lysed for 10 min at 4ºc using RBC lysis buffer (Biolegend), washed twice, stained for indicated flow markers prior, and acquired by flow cytometry (see flow and sorting section).

[0120] Methylcellulose assay (CFU-C assay)

[0121] A total of 20,000 bone marrow MNCs were seeded per 35 mm dish with MethoCult media (M3434, STEMCELL Technologies) or 100,000 bone marrow MNCs with MegaCult-C (04900 and 04902, STEMCELL Technologies) supplemented with murine Il-3 (10 ng / mL), human Il-6 (20 ng / mL), and murine TPO (50 ng / mL) (all from Peprotech) and cultured at 20% oxygen for 14 days. Megakaryocyte colonies were fixed and stained for acetylcholinesterase accordingly to manufacturer’s (STEMCELL Technologies) instructions. The type and number of colony-forming units were determined and scored. To help to visualize and define colony type, at day 14-post methylcellulose culture, CFUs were imaged using an automated colony counter, STEMvision (STEMCELL technologies).

[0122] Microscopic imaging

[0123] For bright field and fluorescent live-cell microscopy, a widefield setup was used. Live imaging was performed with a Zeiss Axio Observer Z.1 and a 10X / 0.3NA objective with a reduced condenser aperture for enhanced contrast. Recordings were acquired using a sCMOS with 6.5µm2 pixels (Hamamatsu Flash4.0v2). Live experiments were performed within an incubation chamber at 37ºc with 5% CO2, 5% O2and high humidity (Zeiss Module S1 from Pecon). For acquisition of one-week movies of co-cultures, imaging acquisition intervals were set to 30 min. Acquisition of Hematoxylin and Eosin (H&E) stained bone marrow images was performed under the same setup using a 20X / 0.8 objective paired with a Zeiss AxioCam 305 color camera. Harvested bones were fixed over-night in 4% PFA at 4ºc, washed 3 times with PBS for 10 minutes each time. Bones were then decalcified for 48h using 100mM EDTA solution and washed 3 times with PBS for 10 minutes each time. Next, decalcified bones for paraffined histology were kept in 70% Et-OH and were sent to Histoserv, Inc. to be processed for: H&E. Data was analyzed using Zeiss Zen 2.6 software.

[0124] Intravital confocal and multiphoton microscopy for BM homing assays

[0125] Cell culture and transplantation: Lineage depleted HPCs were expanded for 4 days in culture with E4orf1-HUVEC niche cells, Fli-1 deletion was induced by introduction of 1 ng / mL 4-OHT, and cells were further cultured for 48 hours. After 6 days, cultures were harvested and LSK HSPCs were sorted. WT or Fli-1ROSAΔLSK HSPCs were stained with 10 µM DiI or DiD in hematopoietic expansion media respectively for 20 min at 37ºc. A total of 8,000 collected Dil- Fli-1ROSAΔand 8000 DiD-WT cells in Ca2+ / Mg2+-free phosphate-buffered saline (D-PBS) were then transplanted via retro-orbital injection into an anesthetized 8-12-week-old C57Bl / 6J mice. Before transplantation, recipient mice were sub-lethally irradiated using an x-ray irradiator with a split dose of 300rad with a 5-hour interval between the two doses. Note: To control the dye labeling and detection efficiency, the DiI and DiD dye colors were swapped between WT and Fli-1ROSAΔLSK HSPCs in replicate experiments.

[0126] In vivo Imaging: Mice were anaesthetized with an induction dose of 3–4% isoflurane and a maintenance dose of 1.5–2% isoflurane. Mice were deemed anaesthetized by the toe pinch method. The hair on the calvarium was removed with a mechanical trimmer and then the skin was wiped with alcohol. The mice were then mounted in a designed heated mouse holder. Next, a calvarial skin flap was created with a U-shaped incision to reveal the underlying calvaria. Adrop of D-PBS was applied to the skull as the immersion fluid. The mice were transferred to the stage of a multiphoton / confocal laser-scanning video-rate microscope and an Olympus 25×1.05 numerical aperture water-dipping objective was used for the imaging. The calvarial BM was imaged for 1-3 hours. Z-stack images were acquired with 2-3 µm step size. The excitation wavelength from an Insight X3 (Specra-Physics) was set at 1040 nm (two-photon) for DiD (Invitrogen), DiI (Invitrogen), and second harmonic generation (SHG) from collagen in the bone. The contrast and brightness of figure images and movies were adjusted for display purposes only. After imaging was completed, mice were dismounted from the stage and the skin flap was closed with 6-0 vinyl sutures (Ethicon) to enable repeat imaging the next day. Triple antibiotic ointment (bacitracin, neomycin, and polymyxin-B sulfate) was applied to the top of the surgical site to minimize the chance of infection. Mice were put in a heated cage and monitored until fully awake. Next, 24 hours after transplantation, mice were again prepared as described above and imaged to locate the homed LSK HSPCs in the BM. After locating the homed cells, mice were immediately injected with 100 µl of a vascular label, Fluorescein-Dextran (2,000,000da MW), retro-orbitally to visualize blood vessels (excited with the 1040 nm light). After imaging, mice were removed from the microscope and euthanatized.

[0127] Flow cytometry analysis and sorting

[0128] Cells were isolated and processed as described for each experimental procedure. Cells were incubated with mouse and / or human FcR block (Biolegend) in 50μl MACS buffer for 20 min at 4ºc. Antibodies were added to resuspended cells as indicated per experiment (see antibody list) and cells with antibodies were incubated for 30 min at 4ºc. For all the experiments, unstained sample or fluorescence-minus-one (FMO) rule was used for gating of positive populations. Unstained control and single-stained cells or ultracompensation beads (eBiosciences) were used to calculate and compensate for the fluorescence spillover from all the channels. Samples were acquired using a BD LSR II machine for flow cytometry or sorted using a BD ARIA 2 sorter machine. Dapi staining was performed at a final concentration of 1μg / ml prior to acquisition and / or sorting, to exclude dead cells. Data was analyzed using DIVA and FlowJo software. For apoptosis analysis, harvested and stained cells were washed in MACS buffer, and resuspended in Annexin V binding buffer (BD Pharmigen). AnnexinV was added accordingly to manufactures instructions. Dapi was added and samples were acquired on BD LSRII in less than 30 min post preparation. Prior to murine HSPCs sorting (and for otherexperimental procedure where mentioned), mature lineage positive hematopoietic cells were depleted using the direct lineage depletion kit (Miltcnyi) accordingly to manufacturer’s instructions. For intracellular staining, cells were processed with BD cytofix / cytoperm fixation permeabilization kit (BD, 554714) accordingly to the provided instructions.

[0129] Antibodies table for flow and imaging

[0130] Cell culture media

[0131] All in vitro cell preparations were routinely tested for mycoplasma contamination.Endothelial cell and co-culture harvesting were always performed using accutase solution (Coming).

[0132] Endothelial cell media. M199 (Hyclone), 20% FCS (Coming), 2mM glutagro supplement (Coming), Antibiotic Antimycotic solution (Coming), MEM nonessential aminoacids (Corning), 20 mM HEPES (Invitrogen), 100 μg / mL heparin (Sigma), 25 μg / mL endothelial mitogen (Alfa Aesar) and 10 μM SB431542 (Tocris).

[0133] Hematopoietic expansion media. StemSpan SFEM (STEMCELL Technologies), 10% KnockOut Serum Replacement (Invitrogen), 50 ng / mL human / mouse c-Kit ligand (SCF, Peprotech), 50 ng / mL human / mouse TPO (Peprotech), and 50 ng / mL human / mouse Flt3l (Peprotech), 2mM glutagro supplement (Corning), Antibiotic Antimycotic solution (Corning), MEM nonessential amino acids (Corning), 20 mM HEPES (Invitrogen), and 100 μg / mL heparin (Sigma).

[0134] Generation of vascular niche cells

[0135] E4orf1-HUVECs that were used for HSPC expansion experiments and EHT conversion through reprogramming experiments, were produced as previously described (Barcia Duran, J.G. et al., Nat Protoc 13, 2758-2780, 2018), with some modifications. Briefly, human umbilical vascular endothelial cells (HUVECs) were isolated as previously described ((Barcia Duran, J.G. et al., Nat Protoc 13, 2758-2780, 2018) and cultured in HUVEC media. The E4orf1 gene from human adenovirus subtype 52 (GenBank accession No. ABK35065.1) was cloned into a pCCL- PGK lentivirus vector. HUVECs were transduced at 60-70% confluency with E4orf1 lentivectors at MOI of 1 supplemented with 4 ug of polybrene. HUVECs were incubated with E4orf1 lentivirus for 48 hours followed by 14 days selection using serum free X-VIVO medium (Lonza). E4orf1-HUVECs were used before reaching passage 20 in culture.

[0136] Generation of AGM-derived embryonic niche cells for embryonic EHT in vitro conversion experiments was previously described (AGM AKT-ECs) (Hadland, B.K., et al., J Clin Invest 125, 2032-2045, 2015). Briefly, AGM was isolated from e10.5 embryos, digested as described for EC isolation, and ECs were sorted, cultured and transfected with previously described (Kobayashi, H., et al., Nat Cell Biol 12, 1046-1056, 2010) myrAKT lentivector. Only lines selective for optimal EHT supportive capacity were applied for the EHT conversion experiments described in this manuscript.

[0137] Lentivirus production

[0138] Production of lentiviral delivery particles for E4orf1 was previously described in detail (Barcia Duran, J.G. et al., Nat Protoc 13, 2758-2780, 2018). Briefly, HEK 293T Lenti-X cell line (Clontech) cells were cultured in DMEM (Gibco) supplemented with 10% FCS (Corning), 2mM glutagro supplement (Corning), and Antibiotic Antimycotic solution (Corning) andtransduced using Lenti-X packaging single shot (Clontech) following the manufacturer’s instructions (w / o antibiotics). Viral particles were concentrated using Lenti-X concentrator (Takara) and final titer was determined using Lenti-X p24 Rapid Titer Kit (Takara).

[0139] Construction of IVT templates and synthesis of modified-RNAs

[0140] Clean PCR products generated with plasmid templates purchased from GenScript were used as the template for mRNA. Modified-RNAs were generated by transcription in vitro with a customized ribonucleoside blend of ARCA; 30-O-Me-m7G (50) ppp(50)G (Trilink Biotechnologies); GTP; ATP; CTP ( Life Technologies) and N1-methylpseudouridine-50- triphosphate (Trilink Biotech-nologies). The modified-RNA was purified with the MEGA clear kit (Life Technologies) according to the manufacturer’s instructions or using Amicon Ultra-4 Centrifugal Filter Unit 4 mL,10 kDa (Millipore Sigma) and treated with Antarctic Phosphatase (NEB). It was then re-purified with the MEGA clear kit. Then, modified-RNA was quantified using a Nano Drop spectrometer (Thermo Scientific), precipitated with ethanol and ammonium acetate, and re-suspended in 10 mM Tris-HCl and 1 mM EDTA at the final required concentration.

[0141] HSPC in vitro expansion studies

[0142] Mouse hematopoietic BM sorted LSK HSPCs from different mouse strains were introduced into a co-culture with E4orf1-HUVEC niche cells (unless otherwise indicated), with hematopoietic expansion media, as previously described (Butler, J.M., et al., Cell Stem Cell 6, 251-264, 2010), with few modifications. Deletion of Fli-1, reporter activation, or N1-CD overexpression, was induced by introduction of 1 ng / mL 4-OHT (Sigma-Aldrich). Hematopoietic expansion media was supplemented every other day post 4-OHT induction. Sorted BM LSK HSPCs were allowed to recover and enter the expansion phase for 48 hours prior to Fli-1 deletion. HSPCs were expanded for 6 days post Fli-1 deletion and / or other genomic induction and harvested for further flow sorting and other experimental procedures. For scRNAseq analysis HSPCs were isolated 48 hours post 4-OHT induction.

[0143] Human donor samples arrived from the Department of Pathology and were approved by the institutional review board at Will Cornell Medicine as part of the IRB protocol. Human hematopoietic CD34+HSPCs from either cord blood (CB) or mobilized peripheral blood (mPB) donors, were isolated using human CD34 microbead kit (Miltenyi Biotec) and by passing twice through LS columns (Miltenyi Biotec) attached to a magnetic stand, achieving a purity >95%.Isolated Human hematopoietic CD34+HSPCs were cryo-frozen. Cells were thawed prior to experimental procedures and were allowed to recover in human hematopoietic expansion media for few hours. For modified-RNA transduction, Neon electroporation transfection system (Invitrogen) was applied. For a suspension containing 1X105hematopoietic CD34+HSPCs, 2 µg of GFP (control) or scrambled modified-RNA (control) or FLI-1 modified-RNA was introduced and electroporated accordingly to manufacture’s instruction using the following settings: 1700V, 10ms, 3 pulses. Immediately after electroporation cells were introduced into a co-culture with E4orf1-HUVEC niche cells with hematopoietic expansion media, at a ratio of 1:3 (HSPCs:E4orf1-HUVECs). Hematopoietic expansion media was supplemented every other day for 1 week. For scRNAseq analysis of CB and mPB HSPCs, cells were isolated and sorted 48 hours post introduction into co-culture with E4orf1-HUVEC niche cells.

[0144] Bulk RNA-seq

[0145] Mouse and human HSPCs were flow sorted as described. RNA was extracted and purified with Arcturus PicoPure RNA isolation kit (Applied Biosystems). RNA concentration and integrity were measured using Agilent 2100 Bioanalyzer (Agilent). RNA integrity was indicated by the RNA integrity number (RIN). RNA samples with sufficient concentration and RIN greater than 8.0 were further processed for poly-A selection and non-stranded cDNA library preparation using Truseq library preparation kit (Illumina). DNA library was then sequenced using Illumina HiSeq4000, PE read, 50 cycles. Raw fastq files were checked for quality with FastQC (Andrews, S. FastQC: a quality control tool for high throughput sequence data. (Babraham Bioinformatics, Babraham Institute, Cambridge, United Kingdom, 2010) and adapters trimmed with Cutadapt (Martin, M. Cutadapt removes adapter sequences from high- throughput sequencing reads.201117, 3, 2011).

[0146] For mouse HSPC analysis, reads were aligned to mouse reference genome (mm10) using STAR aligner (Dobin, A., et al., Bioinformatics 29, 15-21, 2013). Raw gene counts were quantified using featureCounts from the Subread package (Liao, Y. et al, Bioinformatics 30, 923- 930, 2014) StringTie2 (Kovaka, S., et al. Genome Biol 20, 278, 2019) was used to quantify Transcripts Per Million (TPM) expression values. After further filtering and quality control, R package edgeR (Robinson, M.D. et al, Bioinformatics 26, 139-140, 2010) was used to calculate library size normalized FPKM and Log2 counts per million (CPM) values and performdifferential gene expression analysis. FPKM normalized bigWig files were generated using deeptools()13

[0147] For human CB versus mPB HSPC comparison, data was normalized, and variance stabilized as a cohort using DESeq2 v1.18.1. Pathway analysis was performed using the gsva function of the GSVA_1.34.0 R package and GSEA_4.1.0 with 2000 permutations. For the GSEA analysis, a rank file was obtained by ranking all genes using the formula -log10(limma t value) that compared gene differential expression between the mPB and CB groups. GSVA results were visualized using the R gplots_3.1.1 heatmap.2 and ggplot2_3.3.3 boxplots.

[0148] Bulk ATAC-seq

[0149] The previously described Omni-ATAC-seq protocol14was followed. Briefly, LSK HSPCs were flow sorted as described. Cells were spun down for at 500rcf for 5 min at 4ºc in a fixed angle. Next, cells were resuspended in RSB buffer and pipetted 3 times, followed up by 3 min incubation on ice. Cell lysate was washed, and nuclei pellet was acquired after spin at 500rcf for 10 min at 4ºc. Nuclei pellet was resuspended in transposition mixture at incubated at 37ºc for 30 min in a thermomixer with 1000 rpm mixing speed. Cleanup reaction was performed with a Zymo DNA clean, and concentrator-5 kit (Zymo). DNA was eluted and amplified using NEBNext X2 MasterMix (NEB). Following additional amplification and cleanup, library concentration was determined using the KAPA library quantification kit (KAPA). DNA library was sequenced on Illumina, using HiSeq4000, PE read, 50 cycles. Raw fastq files were checked for quality with FastQC (Andrews, S. FastQC: a quality control tool for high throughput sequence data. (Babraham Bioinformatics, Babraham Institute, Cambridge, United Kingdom, 2010) and adapters trimmed with Cutadapt (Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads.201117, 3, 2011). Reads were aligned to the mouse (mm10) reference genome using Bowtie2 (Langmead, B. et al., Nat Methods 9, 357-359, 2012). with parameters ‘--very-sensitive -X 2000’. Mitochondrial, duplicate, and low-quality reads were removed with only properly paired reads retained. Reads were shifted + 4bp and - 5bp on the positive and negative strands respectively. Peaks were called using MACS2 (Zhang, Y., et al., Genome Biol 9, R137, 2008) with parameters ‘-f BAMPE -g 1.87e9 --keep-dup all –nomodel --nolambda --call-summits’. BigWig files were generated using deeptools (Ramírez, F., et al., Nucleic Acids Res 44, W160-165, 2016) normalized by reads per genomic content (1x normalization). Differential accessibility was performed with DESeq2 (Love, M.I., Huber, W. &Anders, S. Genome Biol 15, 550, 2014). Computational footprinting was performed with the HINT-ATAC (Li, Z., et al. Genome Biology 20, 45, 2019) and TOBIAS (Bentsen, M., et al., Nat Commun 11, 4267, 2020) frameworks using the HOCOMOCOv11 (Kulakovskiy, I.V., et al., Nucleic Acids Res 41, D195-202, 2013) and JASPAR 2020 (Portales-Casamar, E., et al., Nucleic Acids Res 38, D105-110, 2010) vertebrate core transcription factor motif database respectively. For footprinting, biological replicate alignments were merged, and PCR duplicate reads were removed with the Picard Toolkit (“Picard Toolkit.” 2019. Broad Institute, GitHub Repository. http: / / broadinstitute.github.io / picard / ; Broad Institute). Peaks were recalled on the merged alignment files with the same parameters.

[0150] Bulk ChIP-seq for H3K27ac

[0151] Mouse LSK HSPCs were flow sorted as described. Nuclei were extracted using NP40 buffer and digested into single nucleosomes using diluted MNase (NEB), followed by O / N incubation with the H3K27ac (Active Motif) antibody. The nucleosomes were washed twice with low salt wash buffer and twice with high salt wash buffer at 4ºc in a rotator. DNA was eluted using SDS / NaHCO3 buffer at 65ºc for 2 hours, extracted using phenol:chloroform:isoamyl alcohol (Invitrogen) and precipitated using 2-isopropanol (Sigma) at -80ºc for O / N or longer durations. DNA library was prepared using Kapa Hyper Kit (KAPA) according to manufacturer’s instructions. Adaptors were from KAPA Single-Indexed Adaptor Kit (KAPA). DNA was purified using the DNA purification kit AMPure XP (Beckman Coulter). DNA library was sequenced on Illumina, using Hiseq 4000, single read, 50 cycles. Raw fastq files were checked for quality with FastQC (Andrews, S. FastQC: a quality control tool for high throughput sequence data. (Babraham Bioinformatics, Babraham Institute, Cambridge, United Kingdom, 2010) and adapters trimmed with Cutadapt (Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 201117, 3, (2011). Reads were aligned to the mouse (mm10) reference genome using Bowtie2 (Langmead, B. & Salzberg, S.L. Nat Methods 9, 357-359, 2012) with parameters ‘--very-sensitive -X 2000’. Mitochondrial, duplicate, and low-quality reads were removed. Peaks were called using MACS2 (Zhang, Y., et al., Genome Biol 9, R137, 2008) using input controls with parameters ‘-f BAM -g 1.87e9 --keep- dup all’ BigWig files were generated using deeptools (Ramírez, F., et al., Nucleic Acids Res 44, W160-165, (2016) normalized by reads per genomic content. Differential peak analysis forregulation of histone acetylation was performed with DESeq2 (Love, M.I., Huber, W. & Anders, S. Genome Biol 15, 550, 2014).

[0152] Differential peak motif enrichment analysis (MEA)

[0153] Peaks with an FDR < 0.05 were selected from the ATAC-seq and H3K27ac ChIP-seq comparisons of knockout to wildtype using the above comparison method. Peaks in each of the two assays were then analyzed for enriched KO and WT motifs using the HOMER software's findMotifsGenome function (Heinz, S., et al., Mol Cell 38, 576-589, 2010) with -size given and the default motif database.

[0154] Generation of RNA vs. ATAC dot plots

[0155] Mouse HSPC differentially expressed genes between knockout and wild-type with an FDR value less 0.05 and absolute log fold change value greater than 2.5 were selected for further interrogation. Differentially accessible regions from the ATAC-seq were annotated using the ChIPseeker R library (Yu, G., et al., Bioinformatics 31, 2382-2383, 2015) and only included if this fell within 500bp up or downstream of a transcriptional start site. Accessible regions were then only included if they had a FDR < 0.05, and an absolute log fold change value greater than 0.75 in comparing knockout to wild-type. For any gene annotated to multiple peaks, the greatest absolute value log fold change was selected for plotting to avert one to many relationships and visualize the chromatin changes with the largest magnitude.

[0156] Gene enrichment analysis

[0157] Gene enrichment for gene ontology (GO) biological processes was performed using WebGestalt (Liao, Y., et al., Nucleic Acids Res 47, W199-W205, 2019). Gene set enrichment analysis (GSEA) for selected pathways was performed using the Broad Institute and UC San Diego software (Subramanian, A., et al., Proc Natl Acad Sci U S A 102, 15545-15550, 2005) (Mootha, V.K., et al., Nat Genet 34, 267-273, 2003) ranked by log fold change.

[0158] Binding and expression target analysis (BETA)

[0159] Publicly and by request available Fli-1, PU.1, and IgG transcription factor ChIP-seq samples from the GSE22178 (Wilson, N.K., et al., Cell Stem Cell 7, 532-544, 2010) dataset (were downloaded from the Gene Expression Omnibus (GEO) database, and from Chavez et al.( Chavez, J.S., et al., Cells 11, 2022) (received upon request), were processed using the above methods. BETA (Wang, S., et al., Nature Protocols 8, 2502-2515, 2013) plus was run with thedifferential gene expression results and mm10 reference fasta file used in aligning ChIP-seq and bulk RNA-seq samples.

[0160] Activity by contact (ABC) modeling

[0161] ATAC-seq samples were subset for reads below 100bp to obtain nucleosome free regions (Buenrostro, J.D., et al, Nat Methods 10, 1213-1218, 2013). Candidate enhancer regions were generated by calling peaks on a randomly selected biological replicate using the parameters ‘f BAMPE -g 1.87e9 -p 0.1 –call-summits’ and sorted using bedtools (Quinlan, A.R. & Hall, I.M. Bioinformatics 26, 841-842, 2010). The top 150,000 peaks were selected by absolute read count, resized to 500bp and centered on summit. Blacklisted mm10 regions were removed. Transcriptional start sites in the reference genome were resized to 500bp and included. Enhancer activity was quantified using reads from all H3K27ac ChIP-seq and ATAC-seq biological replicates with transcripts per million (TPM) normalized expression. Enhancers were predicted without cell-type-specific Hi-C data using the powerlaw estimate and a threshold of 0.02 (Fulco, C.P., et al., Nature Genetics 51, 1664-1669, 2019). The Cicero package (Pliner, H.A., et al., Mol Cell 71, 858-871 e858, 2018) was used to visualize the resulting connections between predicted enhancer regions and target genes with the y-axis representing associated powerlaw scores. The ComplexHeatmap R library (Gu, Z., Eils, R. & Schlesner, M., Bioinformatics 32, 2847-2849, 2016) was used to plot powerlaw scores and predicted active enhancers for select genes.

[0162] Single cell / nuclei RNA / ATAC-seq analyses

[0163] Multiome single nuclei RNA / ATAC-seq analysis

[0164] Mice were sacrificed, bones were harvested, flushed, crushed, and processed to flow sort SLAM LSK HSPCs as described above. SLAM LSK HSPCs from 20 C57BL / 6 mice were pooled together, washed, and resuspended in 0.04% BSA / PBS solution. Sorted cell suspension was further processed for nuclei isolation with the Chromium Next GEM Single Cell Mutiome Reagent Kit (10x Genomics, product code # CG000365 and 1000338) using 10X Genomics’ Chromium Controller. Briefly, 200K sorted SLAM LSK cells were suspended in Lysis Buffer and incubated on ice for 5 min. Chilled Wash Buffer was added, mixed well, and cells were centrifuged at 500 rcf for 5 min, then washed twice and resuspended in diluted Nuclei Buffer. The nuclei concentration was determined by Bio-Rad TC20 Cell Counter, and immediately proceeded to Chromium Next GEM Single Cell Mutiome ATAC + Gene Expression. Nuclei suspensions were incubated in a Transposition Mix that includes a Transposase, whichpreferentially fragmented the DNA in open regions of the chromatin. Simultaneously, adapter sequences were added to the ends of the DNA fragments. Single Cell Multiome ATAC + GEX Gel Beads included a poly(dT) sequence that enabled the production of barcoded, full-length cDNA from poly-adenylated mRNA for gene expression (GEX) library and a Spacer sequence that enabled barcode attachment to transposed DNA fragments for ATAC library. Transposed nuclei were loaded into Chromium Controller to generate GEMs by combining barcoded Gel Beads, transposed nuclei, a Master Mix, and Partitioning Oil on a Chromium Next GEM Chip J. Upon GEM generation, the Gel Bead was dissolved. Oligonucleotides containing an Illumina P5 sequence, a 16 nt 10x Barcode (for ATAC), and a Spacer sequence were released. In the same partition, primers containing an Illumina TruSeq Read 1 (read 1 sequencing primer), 16 nt 10x Barcode (for GEX), 12 nt unique molecular identifier (UMI), and a 30 nt poly(dT) sequence were also released. The primers were mixed with the nuclei lysate containing transposed DNA fragments, mRNA, and Master Mix, that included reverse transcription (RT) reagents. Incubation of the GEMs produced 10x Barcoded DNA from the transposed DNA (for ATAC) and 10x Barcoded, full-length cDNA from poly-adenylated mRNA (for GEX). This was followed by a quenching step that stopped the reaction. GEMs were broken and pooled fractions were recovered. Silane magnetic beads were used to purify the cell barcoded products from the post GEM-RT reaction mixture, which included leftover biochemical reagents and primers. Barcoded transposed DNA and barcoded full-length cDNA from poly-adenylated mRNA were amplified via PCR to fill gaps and for generating sufficient mass for library construction. The pre-amplified product was used as input for both ATAC library construction and cDNA amplification for gene expression library construction. P7 and a sample index were added to pre- amplified transposed DNA during ATAC library construction via PCR. The final ATAC libraries contained the P5 and P7 sequences used in Illumina bridge amplification. Barcoded, full-length pre-amplified cDNA was amplified via PCR to generate sufficient mass for gene expression library construction. Enzymatic fragmentation and size selection were used to optimize the cDNA amplicon size. P5, P7, i7 and i5 sample indexes, and TruSeq Read 2 (read 2 primer sequence) were added via End Repair, A-tailing, Adaptor Ligation, and PCR. The final gene expression libraries contained the P5 and P7 primers used in Illumina bridge amplification. Sequencing these libraries with Illumina NovaSeq6000 using 100 cycles kits produced a standard Illumina BCL data output folder that included paired end Read 1N and Read 2N used forsequencing the DNA insert, along with the 8 bp sample index in the i7 read and 16 bp 10x Barcode sequence in the i5 read (50+8+24+49). Chromium Single Cell Multiome Gene Expression libraries comprised cDNA insert with standard Illumina paired-end constructs which began with P5 and end with P7. Sequencing these libraries produced a standard Illumina BCL data output folder. TruSeq Read 1 was used to sequence 16 bp 10x Barcodes and 12 bp UMI, while 10 bp i5 and i7 sample index sequences were the sample index reads. TruSeq Read 2 was used to sequence the insert (28+10+10+90).

[0165] Next, to remove ambient RNA, random UMI swapping, and technical artifacts, CellBender (Fleming, S.J., et al, bioRxiv, 791699, 2019) was run on the single-nuclei RNAseq raw Cell Ranger (10X Genomics) feature counts with 150 epochs, 0.01 fpr, and the total droplets / expected cells selected based on quality control web summary elbow plot. DoubletDetection (Gayoso, Adam & Shor, Jonathan. DoubletDetection. (2018) doi:10.5281 / zenodo.2658730) was also run on the raw features and the overlapping barcodes filtered from the Cellbender expression results. To further filter doublets and poor quality cells, cells with greater than 250 or less than 3400 genes, greater than 14% mitochondrial genes, or RNA counts greater than 350 or less than 10,000 were filtered. Ribosomal and mitochondrial RNA counts were excluded from downstream analysis. Cells with fewer than 2,740 or greater than 69,000 ATAC counts were further excluded. The alignment gene transfer format annotation file was used to define transcriptional start site (TSS) regions as ±3 kb from TSS. TSS enrichment scores were computed using the Signac TSSErichment function. Cells with TSS enrichment <3 were discarded. Peaks were recalled using MACS2 (Zhang, Y., et al., Genome Biol 9, R137, 2008) through the Signac CallPeaks function, parameters effective.genome.size = 1.87e9, extsize = 150, shift = 75, ,-nomodel, --call-summits --nolambda --keep-dup all. Non- standard chromosomes were removed along with any mitochondrial or ChrY chromosome peaks. Regions that overlapped with the mm10 blacklist region were further removed. Peaks were centered on the summit and extended 250bp in each direction. Peaks were sorted by score and any overlapping peaks had the peak with the largest score included. The subsequent top 100,000 peaks sorted by greatest score were included for further analysis. Gene expression was normalized using sctransform (Hafemeister, C. & Satija, R., Genome Biology 20, 296, 2019) version ‘v2’ prior to running principal component analysis. Peaks / accessible regions were processed using the Signac methods RunTFIDF, FindTopFeatures (with min.cutoff = ‘q0’) andRunSVD. Multimodal neighbors were found by constructing a weighted nearest neighbor graph (Hao, Y., et al., Cell 184, 3573-3587 e3529, 2021) using Signac (Stuart, T., et al, Nat Methods 18, 1333-1341, 2021) the Seurat FindMultiModalNeighbors function. The first 50 principal components from the expression data and the 2ndthrough 50thlatent semantic index (LSI) components from the reduced ATAC data were used. The SLM algorithm was then applied to find clusters with a resolution of 0.3. HSC, MPP, EryP, and MkP clusters were annotated based on RNA markers identification using Seurat FindAllMarkers. FindMarkers Seurat function with the Wilcoxon Rank-Sum test identified differentially expressed genes. Differential accessible regions were found using the FindMarkers Seurat function with the logistic regression framework with the number of peaks as a latent variable. Differential motifs were found using the FindMarkers Seurat function with Wilcoxon Rank-Sum test with the average difference calculation on the chromVAR z-score (rowMean). Motif analysis was performed using chromVAR with the CIS-BP 2021 curated mouse motif database database (Weirauch, M.T., et al., Cell 158, 1431-1443, 2014). Cell cycle scores were calculated using the Seurat “CellCycleScoring” function. The HSC signature was calculated using the Seurat “AddModuleScore” function with default parameters with the Rodriguez et al. HSC1 gene list (Rodriguez-Fraticelli, A.E., et al., Nature 583, 585-589, 2020). The Nebulosa R package (Alquicira-Hernandez, J. & Powell, J.E. Bioinformatics 37, 2485-2487, 2021) was used to clearly visualize gene signatures by mitigating sparsity through kernel density estimation. UMAPs and other figures were designed using SCpubR (Blanco-Carmona, E. bioRxiv, 2022.2002.2028.482303, 2022). Heatmaps for RNA and Chromvar motifs activity present the top 30 genes and motifs per cell type by avg_log2FC (RNA) and fold.enrichment (motif), after selected by statistical significance of p adjusted value <0.05. Differential RNA and motif per cluster were determined by applying FindMarkers (RNA) and FindMotifs (motif) Seurat functions by comparing to nearest cell types. HSC and MPP cells were subset without EryP / MkP (n=2965) and had peaks re-called using the above methods. The same dimensional reduction and clustering approaches were re-applied using the first 35 principal comonents, the 2ndthrough 40thLSI components and a cluster resolution of 0.5 due to the smaller amount of cells. We removed a small number of HSC and MPP outlier cells (n=17), that were outliers in low dimensional space and had enrichment for erythroid cell markers (such as hemoglobin and etc.), and reclustered with the same HSC / MPP parameters. SCPubR was used to generate dotplot and violin plots of Chromvar motifs scores for selected TFs. For statistical analysis between HSC1 and HSC2 motifs scores presented on violin plots, Wilcoxon Rank Sum Test (rstatix library v0.7.0) was used to calculate P values as indicated.

[0166] General single cell RNA-seq procedures

[0167] Sorted cells were immediately submitted for 10X Chromium single-cell analysis. The single-cell suspension was loaded onto a well on a 10X Chromium Single Cell instrument (10X Genomics). Barcoding and cDNA synthesis were performed according to the manufacturer’s instructions. In brief, the 10X GemCode Technology partitions thousands of cells into nanolitre- scale gel bead-in-emulsions (GEMs), in which all the cDNA generated from an individual cell share a common 10X barcode. To identify the PCR duplicates, a unique molecular identifier (UMI) was also added. The GEMs were incubated with enzymes to produce full length cDNA, which was then amplified by PCR to generate enough quantity for library construction. Qualitative analysis was performed using the Agilent Bioanalyzer High Sensitivity assay. The cDNA libraries were constructed using the 10X Chromium single-cell 3′ Library Kit according to the manufacturer’s original protocol. In brief, after the cDNA amplification, enzymatic fragmentation and size selection were performed using SPRI select reagent (Beckman Coulter) to optimize the cDNA size. P5, P7, a sample index and read 2 (R2) primer sequence were added by end repair, A-tailing, adaptor ligation and sample-index PCR. The final single-cell 3′ library contains standard Illumina paired-end constructs (P5 and P7), Read 1 (R1) primer sequence, 16- bp 10X barcode, 10-bp randomer, 98-bp cDNA fragments, R2 primer sequence and 8-bp sample index. For quality control after library construction, 1 μl of the sample was diluted 1:10 and run on the Agilent Bioanalyzer High Sensitivity chip for qualitative analysis. For quantification, the Illumina Library Quantification Kit (KAPA) was used. DNA libraries were sequenced on Illumina, using NovaSeq6000, PE read, 50 cycles.

[0168] The Cell Ranger pipeline (10X Genomics) was used to align reads to the mm10 (for murine samples) or to the GRCh38 (for human samples) reference genomes and generate feature barcode matrices.

[0169] Single cell RNA-seq analysis of engrafted murine HSPCs

[0170] Bone marrow was retrieved from recipient mice >16 weeks post transplantation, and viable donor immature hematopoietic population enriched for HSPCs (CD45.2+Lin-Dapi-) was flow sorted. For each donor genotype BM samples were pooled from 5 recipient mice.

[0171] The Monocle 3 (v.3_0.2.3.0) platform was used for downstream analysis45, combining data for cells from each sample for downstream analysis, using a negative binomial model of distribution with fixed variance, normalizing expression matrices by size factors. Counts for UMI (unique molecular identifiers) and unique genes expressed per cell are shown in boxplots in supplementary figures for each sample (showing median values and interquartile ranges; upper / lower whiskers show 1.5X interquartile range with outliers shown as individual dots). Low quality cells were excluded using cut-offs for UMI per cell (<5000) and genes per cell (<1000). R scripts used for analysis are available upon request (R version 3.6.1). The preprocess cds function was used to project the data onto the top principal components (excluding principal components that contributed little to the overall variance, num dim=9). The align cds function was used to remove batch effects between samples, using a “mutual nearest neighbor” algorithm, Batchelor (v.1.2.4) (Haghverdi, L., Lun, A.T.L., Nat Biotechnol 36, 421- 427, 2018). Uniform Manifold Approximation (UMAP) (Becht, E., et al., Nat Biotechnol, 2018) was used for dimensionality reduction with the reduce dimension function, using default settings. Clustering was performed by Leiden method with the cluster cells function, with resolution=2E- 3. Cell type classification was performed using the Garnette package (v.0.2.15) (Pliner, H.A., et al., Nat Methods 16, 983-986, 2019) within Monocle 3. Marker genes based on established cell type-specific genes, as indicated below, were used to train a classifier data set (using the train cell classifier function with default settings), and classify cell types (using the classify cells function, with cluster extend set to TRUE in order to expand cell classifications to cells in the same cluster; settings cluster extend_max_frac_unknown = 0.95 and cluster_extend_max_frac_incorrect = 0.45). Cluster-extend cell types were used for downstream analysis comparing samples.

[0172] Markers for cell type classification

[0173] Gene-set scores were calculated for each single cell as the log-transformed sum of the size factor-normalized expression for each gene in signature / marker gene sets, as indicated, including two published HSC-specific gene sets: 29 genes representing a molecular overlap signature of adult murine bone marrow-derived HSC isolated by different index sorting strategies (Wilson, N.K., et al., Cell Stem Cell 16, 712-724, 2015) and 541 genes representing the molecular signature of serially-repopulating HSC by single cell clonal tracking (Rodriguez- Fraticelli, A.E., et al., Nature 583, 585-589, 2020). Violin plots comparing gene-set scores between samples were generated using ggplot2 (v3.3.2) function with geom violin() and geom boxplot() (boxplots show median values and interquartile ranges; upper / lower whiskers show 1.5X interquartile range). For statistical analysis between samples, Wilcoxon Rank Sum Test (ggupbr package v0.4.0) was used to calculate P values as indicated. Differential gene expression was performed using regression analysis with the fit models() and coefficient table() functions in Monocle 3, to identify genes that were differentially expressed based on significance values (q value) adjusted for multiple hypothesis testing using the Benjamini and Hochberg correction method. Hematopoietic stem / progenitor cell types (HSC, MPP, and LPP) were compared between samples for this analysis, to identify differentially expressed genes in the whole genome (genome-wide) or using signature / marker genes sets that were utilized for gene- set scores as described above.

[0174] Single cell RNA-seq analysis of murine HSPCs from co-cultures

[0175] Sorted BM LSK HSPCs, from all the different transgenic mouse lines, were introduced into co-culture with vascular niche cells as described above. Two days (48 hours) post tamoxifen introduction into co-cultures containing expanding HSPCs, cultures were terminated, harvested, and LSK HSPCs were resorted and further processed for 10X chromium scRNA-seq analysis. Co-culture sorted LSK HSPC samples were loaded into Seurat. For each sample, cells without 100 features and features detected in less than 10 cells were discarded. Each sample was filtered individually for low quality cells and doublets. The WT sample had cells discarded with less than 350 or more than 3750 features and greater than 25% mitochondrial content. The Fli- 1ROSAΔsample had cells discarded with less than 320 or more than 2000 features and greater than 15% mitochondrial content. The Fli-1ROSAΔN1-ICiOEsample had cells discarded with less than 325 features or more than 4200 features and greater than 35% mitochondrial content. The N1- ICiOEsample had cells discarded if they had less than 350 or more than 4500 features and greater than 35% mitochondrial content. Each sample was normalized using sctransform and integrated using 3000 integration features and default parameters. Cell cycles were classified using the CellCycleScoring function along with the Seurat list of cell cycle genes. Principal component analysis was run, and the first 40 principal components were selected for finding neighbors and computed the UMAP based on the elbow method as well as the derivative of an interpolated function fit to the elbow plot showing little change for additional components. The FindClusters function was run with a resolution of 0.6 and HSC clusters were annotated based on the described above. Cells from HSC defined clusters #7 and #15 were selected for further interrogation and the FindMarkers function was used with the RNA assay and default parameters for differential expression analysis between the two populations and the different genetic conditions within each cluster. Gene set enrichment analysis was performed using WebGestalt.

[0176] Single cell RNA-seq analysis of human CB and mPB HSPCs

[0177] CB and mPB enriched CD34+HSPCs were introduced to co-cultures with vascular niche cells, as described above, for 48 hours. CB and mPB CD34+HSPCs were sorted from harvested cultures and further processed for 10X chromium scRNA-seq analysis. Both CB and mPB HSPC samples were first filtered for cells that had less than 100 features and features that occurred in less than 3 cells. To filter out low quality cells and doublets, CB HSPCs with less than 200 features or greater than 7200 features and greater than 12 percent mitochondrial contentwere discarded. Additionally, mPB HSPCs with less than 1000 features or greater than 6100 features and a percent mitochondrial content greater than 11 percent were removed. After merging the samples, the Seurat functions NormalizeData and ScaleData were run with default parameters. The top 4000 variable features were then identified using the FindVariableFeatures routine with the ‘vst’ selection method and cell cycles scored with CellCycleScoring method using Seurat’s list of cell cycle genes. Mitochondrial percentage and the cell cycle difference, calculated as the S.Score minus G2M.Score, were regressed out, the latter so the signal between cycling and non-cycling HSPCs was maintained. After running PCA reduction, Harmony (Korsunsky, I., et al., Nat Methods 16, 1289-1296, 2019) was used to integrate the two different CB and mPB batches. Nearest neighbors and UMAP dimension reduction were calculated using the first 40 corrected Harmony embeddings. Additionally, Nearest neighbors were calculated with k=30 for k-nearest neighbor. The FindClusters function was run with a resolution of 2. To annotate cell types to clusters, a combination of known genes, markers found with the FindAllMarkers function (using the RNA assay with only positive markers and a p-adjusted value < 0.05). Cells were first annotated through the Azimuth reference-based mapping pipeline on human bone marrow (Hao, Y., et al., Cell 184, 3573-3587 e3529, 2021). Clustering and cluster cell assignment was finalized using known cell markers. Additional differential gene expression was performed between cell types, samples, and clusters using the FindMarkers Seurat function with an average log fold change limit threshold of 0.15 for genes between the two comparison groups. Gene set enrichment analysis was performed using WebGestalt.

[0178] Single cell ATAC-seq HSPC analysis of quiescent, active, and FLI-1 HSPC signatures

[0179] Publicly available data for human HSPC scATA-seq (EGAS00001004740) was analyzed, where cells from three sorted CD34+CD38-CD45RA- and three CD34+CD38+populations were processed on the 10X Genomics single cell ATAC-seq platform and retained based on default cellranger QC criterion and chromVAR depth filtering. Cellranger-reanalyze (1.1, 10x Genomics) was subsequently used to map reads over the sites identified in the publicly available human HSPC bulk ATAC-seq catalog (EGAS00001004742), and read counts were binarized. chromVAR (with default settings) was used to calculate the enrichment of the quiescent and active hematopoietic signatures identified in Takayama et al., Cell Stem Cell 28,488-501 e410, 2021), per each single cell, as well as for the HSPC FLI-1 CHIP-Seq (Beck, D., et al., Blood 122, e12-22, 2013) peaks signature.

[0180] Single cell sequencing clusters compositional and permutation analyses

[0181] To compare the proportional differences in cell populations between two conditions, scProportionTest an R library (Sriramkumar, S., et al., PLoS One 17, e0271584, 2022) was used. Statistical analysis was performed using permutation testing and bootstrap sampling. For the permutation testing, the cell identities in the two samples were randomly shuffled. The Log2 proportional difference between cell counts in each population was calculated. This process was repeated 10000 times to generate a distribution of proportional differences. The p-values were determined by counting the number of proportional differences that were as extreme as or more extreme than the observed difference, and then dividing that count by the total number of iterations plus one. To account for multiple comparisons, the resulting p-values were subjected to false discovery rate (FDR) correction. This correction helps control for the increased likelihood of false positives when conducting multiple statistical tests. For generating confidence intervals, bootstrap sampling was employed. Cell identities within each sample were randomly sampled with replacement, and the Log2 fold difference between cell counts in each population was calculated. This process was repeated 10000 times to create a distribution of simulated Log2 proportional differences. The confidence interval was defined as the range between the 0.025 and 0.975 quantiles of the simulated differences. The described methods were applied once across all clusters for all combinations of four different conditions (murine HSPC co-cultures), and once for comparing two different conditions across all clusters (human HSPC CB vs. mPB).

[0182] Statistical analysis

[0183] All statistical analyses were conducted with Prism (* P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001; NS, not significant). All data are expressed as mean ± standard error (s.e.m) and all n numbers represent biological repeats, unless indicated otherwise. Unless indicated otherwise in figure legends, a student’s two-tailed unpaired t-test was used to determine the significance of the difference between means of two groups. One-way ANOVA or two-way ANOVA was used to compare means among three or more independent groups. Bonferroni post-hoc tests were used to compare all pairs of treatment groups when the overall P value was < 0.05. A normal distribution of the data was tested using the Kolmogorov–Smirnovtest if the sample size allowed. If normal-distribution or equal-variance assumptions were not valid, statistical significance was evaluated using the Mann–Whitney test and the Wilcoxon signed rank test.

[0184] Targeted DNA-sequencing MSKCC-IMPACT package

[0185] Co-cultured human mPB CD34+HSPCs were sorted after 7 days of expansion with a vascular niche platform following transduction of either control or FLI-1 modified RNA. Cell pellet was frozen in liquid nitrogen and stored in -80ºc. DNA from frozen cells was extracted with the DNeasy Blood & Tissue Kit (QIAGEN, 69504) according to the manufacturer’s protocol modified by replacing AW2 buffer with 80% ethanol. DNA was eluted in 60 µL 0.5X Buffer AE heated to 55°C. After PicoGreen quantification and quality control by Agilent BioAnalyzer, 100 ng of DNA were used to prepare libraries using the KAPA Hyper Prep Kit (Kapa Biosystems, KK8504) with 8 cycles of PCR. 100 ng of each barcoded library were captured by hybridization in pools of 8-10 samples using the IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets) (Cheng, D.T., et al., J Mol Diagn 17, 251-264, 2015) assay (IDT), designed to capture all protein-coding exons and select introns of 505 commonly implicated oncogenes, tumor suppressor genes, and members of pathways deemed actionable by targeted therapies. Captured pools were sequenced on a NovaSeq 6000 in a PE100 run using the NovaSeq 6000 S2 or S4 Reagent Kit (200 Cycles) (Illumina) producing an average of 983X coverage per experimental sample and 427X per control.

[0186] Data and code availability

[0187] Omics data that was generated for or retrieved for this disclosure have been deposited in the Gene Expression Omnibus (GEO) or in the European Genome-Phenome (EGA) repositories with the following accession codes: Multiomics SuperSeries GSE169431 Mouse HSPC Bulk Fli-1 and Spi1 ChIP-seq GSE22178 Human HSPC Bulk FLI-1 ChIP-seq GSE45144 Human HSPC Bulk RNA-seq GSE125345 Human HSPC scATAC-seq EGAS00001004740 Human HSPC Bulk ATAC-seq EGAS00001004742SEQUENCE LISTING SEQ ID NO: 1 – The open reading frame of Homo sapiens Fli-1 proto-oncogene, ETS transcription factor (FLI1), transcript variant 1 (SEQ ID NO: 2). SEQ ID NO: 2 - Homo sapiens Fli-1 proto-oncogene, ETS transcription factor (FLI1), transcript variant 1, mRNA 3,825 bp linear mRNA Accession: NM_002017.5 CTCTTTCGCTCCGCTACAACAACAAACGTGCACAGGGGAGTGAGGGCAGGGCGCTCGCAGGGGGCACGCA GGGAGGGCCCAGGGCGCCAGGGAGGCCGCGCCGGGCTAATCCGAAGGGGCTGCGAGGTCAGGCTGTAACC GGGTCAATGTGTGGAATATTGGGGGGCTCGGCTGCAGACTTGGCCAAATGGACGGGACTATTAAGGAGGC TCTGTCGGTGGTGAGCGACGACCAGTCCCTCTTTGACTCAGCGTACGGAGCGGCAGCCCATCTCCCCAAG GCCGACATGACTGCCTCGGGGAGTCCTGACTACGGGCAGCCCCACAAGATCAACCCCCTCCCACCACAGC AGGAGTGGATCAATCAGCCAGTGAGGGTCAACGTCAAGCGGGAGTATGACCACATGAATGGATCCAGGGA GTCTCCGGTGGACTGCAGCGTTAGCAAATGCAGCAAGCTGGTGGGCGGAGGCGAGTCCAACCCCATGAAC TACAACAGCTATATGGACGAGAAGAATGGCCCCCCTCCTCCCAACATGACCACCAACGAGAGGAGAGTCA TCGTCCCCGCAGACCCCACACTGTGGACACAGGAGCATGTGAGGCAATGGCTGGAGTGGGCCATAAAGGA GTACAGCTTGATGGAGATCGACACATCCTTTTTCCAGAACATGGATGGCAAGGAACTGTGTAAAATGAAC AAGGAGGACTTCCTCCGCGCCACCACCCTCTACAACACGGAAGTGCTGTTGTCACACCTCAGTTACCTCA GGGAAAGTTCACTGCTGGCCTATAATACAACCTCCCACACCGACCAATCCTCACGATTGAGTGTCAAAGA AGACCCTTCTTATGACTCAGTCAGAAGAGGAGCTTGGGGCAATAACATGAATTCTGGCCTCAACAAAAGT CCTCCCCTTGGAGGGGCACAAACGATCAGTAAGAATACAGAGCAACGGCCCCAGCCAGATCCGTATCAGA TCCTGGGCCCGACCAGCAGTCGCCTAGCCAACCCTGGAAGCGGGCAGATCCAGCTGTGGCAATTCCTCCT GGAGCTGCTCTCCGACAGCGCCAACGCCAGCTGTATCACCTGGGAGGGGACCAACGGGGAGTTCAAAATG ACGGACCCCGATGAGGTGGCCAGGCGCTGGGGCGAGCGGAAAAGCAAGCCCAACATGAATTACGACAAGC TGAGCCGGGCCCTCCGTTATTACTATGATAAAAACATTATGACCAAAGTGCACGGCAAAAGATATGCTTA CAAATTTGACTTCCACGGCATTGCCCAGGCTCTGCAGCCACATCCGACCGAGTCGTCCATGTACAAGTAC CCTTCTGACATCTCCTACATGCCTTCCTACCATGCCCACCAGCAGAAGGTGAACTTTGTCCCTCCCCATC CATCCTCCATGCCTGTCACTTCCTCCAGCTTCTTTGGAGCCGCATCACAATACTGGACCTCCCCCACGGG GGGAATCTACCCCAACCCCAACGTCCCCCGCCATCCTAACACCCACGTGCCTTCACACTTAGGCAGCTAC TACTAGAAGCTTACTCATCAGTGGCCTTCTAGCTGAAGCCCATCCTGCACACTTACTGGATGCTTTGGAC TCAACAGGACATATGTGGCCTTGAAGGGAAGACAAAACTGGATGTTCTTTCTTGTTGGATAGAACCTTTG TATTTGTTCTTTAAAAACATTTTTTTTAATGTTGGTAACTTTTGCTTCCTCTACCTGAACAAAGAGATGA ATAATTCCATGGGCCAGTATGCCAGTTTGAATTCTCAGTCTCCTAGCATCTTGTGAGTTGCATATTAAGA TTACTGGAATGGTTAAGTCATGGTTCTGAGAAAGAAGCTGTACGTTTTCTTTATGTTTTTATGACCAAAG CAGTTTCTTGTCAATACACGGGGTTCAGTATGACACAGAATCATGGACTTAACCCGTCATGTTCTGGTTT GAGATTTAGTGACAAATAGAGGTGGGAAGCTTATAATCTAATTTTAGGAGGACCAAATTCAGTGGATGGC AACTGGAACATTGATTGTAAGGCCAGTGAAGTTTTCACCCAACTGGAATTTGATGGAAAGAAGGTTTGTG TGTTTAAGACGCCAAGGGCATTGCAGAATCCCTCTCAGTGGACAGTATGCACTCAGCTGACCACTCTCTC TAGAAATAGTCAAGATATGAACTAAGAAATTTTAATGCAAATACATACATTCCTGAAAGACGGGGAATTA AATTACTAATTTTTTTTTTTTTTTAAATGATGACAGTGGTCCCAGAACTTGGAAAAGTTGTAGGGATTTC TAAACTCAAGCAGATTCGCAAGTGCTGTGCGCTTGTCAGACCATCAGACCAGGGCCAACCAATCAGAAGG CAACTTACTGTATAAATTATGCAGAGTTATTTTCCTATATCTCACAGTATTAAAAATAAATAATTAAAAA TTAAGAATAAATAAACGAGTTGACCTCGGTCACAAAAGCAGTTTTACTATCGAATCAATCGCTGTTATTT TTTTTAATGTAATTTGTACATCTTTTTTCAATCTGTACATTTGGGCTGTCTGTATGTTTTTATAGCTGGT TTTTAAAAAGCATAATATGCCTATAGCTGAAAAGGAAACAGGGCTGTTTAAGTCACTGACTTATGAGAAAGCAAAGCACTGGTACAGTTATTTAACAGGCATACACAAGCAGGGAAAAGATAATCCATTTAGATCTTTAA TGCTTTGGAAATGCGTGTAACAGTACTGCAATAATCACAGCTCTGGGAAAAACAACGAAACTTTCCCTTG TGGAGAGGAGGGATTTTCCTGCTCTATATAAGCAACATATTTTTAGACATTAAAATATATATAATTTTGC AGGTAATTGTTGACTTTTTTAACTATATTAAGTGTTAAGCTGACAACTGTCAAAGAAGACCATGTTGTAA AATAATTTGACTAAATAAATGGTTCCTTCTCTCAGTGCTGAGGACAGTTTTCTTATTTACCGCCCCCGTT AGGTCAAAGGGTTTTCCCTGGGGAACTTTCCTATTTACTTCTTGCACTATCAAGAATTTTTCGAATGTAC CTACTGCAGTACAGCAGAAGGTAAAAAATCAGTGTGGTTTTTCATTGTTGTTGATGATGTTTGTAGTGTT TTTGTGTGTGTTATTTAAATCTTCCTCCAGCCTAAAAGGGTTTTATAAAACAGCAGCTAAGGCCATGGAT AAACCTGTATGTAAGGACTGGAGCAAAGCGAGCTGGTCTATCCAGACTGGTCTGTGAGATTTAACTCTGC AGCCTCCCCTGGGCACTTCAGACCCAGACGGCCACCTTCTGCCACTCCAGCAAAGAATAAGCGCCCTGCT TCCTTCAGGTCTCAGACCAGGACTTTATGGCTCATGCAGATTTTTAAGGTCATTTTTCTTCCCAAGGAAG AAACTTGCCTCCAGTTCCTTCACTGTTAGGTAGCTTATTTTCATTTTCTCTATTTTACAATGAAAAGAGT GAGACCTGGGAAGTCCTTGATTTGCAAGGAATTAGACTCACAGCATTGGTAACCCTAGAACCTTCTTAGG GTAACACTAAGTACCTTCTAGACAACATGTCTACCTAAATGAAATGGGATGTGTTTCGGAACATTTGTCT CCAGTTTTTTTTTAATCTTGCACCCTGCCATTTAAAAAGATGTGTAAAGCACATATTCTCAACATATGCA CATTGATTTATAAATCATATATACAAACTGTTACATTATTCTTCATATTAGAAAACAAATACAAAATAGA ACATTTTAAATGGTGATATAAAAATAAATTGAAACTGAAATTCTA SEQ ID NO: 3 - Homo sapiens Fli-1 proto-oncogene, ETS transcription factor (FLI1), transcript variant 2, mRNA 3,879 bp linear mRNA Accession: NM_001167681.3 CTCTTTCGCTCCGCTACAACAACAAACGTGCACAGGGGAGTGAGGGCAGGGCGCTCGCAGGGGGCACGCA GGGAGGGCCCAGGGCGCCAGGGAGGCCGCGCCGGGCTAATCCGAAGGGGCTGCGAGGTCAGGCTGTAACC GGGTCAATGTGTGGAATATTGGGGGGCTCGGCTGCAGACTTGGCCAAATGGACGGGACTATTAAGGAATT CTTTCTCTGGGTCATCCACTGCTGAGCCCCCTCCCCAGGAAGTGGAATTGAGGCTCTGTCGGTGGTGAGC GACGACCAGTCCCTCTTTGACTCAGCGTACGGAGCGGCAGCCCATCTCCCCAAGGCCGACATGACTGCCT CGGGGAGTCCTGACTACGGGCAGCCCCACAAGATCAACCCCCTCCCACCACAGCAGGAGTGGATCAATCA GCCAGTGAGGGTCAACGTCAAGCGGGAGTATGACCACATGAATGGATCCAGGGAGTCTCCGGTGGACTGC AGCGTTAGCAAATGCAGCAAGCTGGTGGGCGGAGGCGAGTCCAACCCCATGAACTACAACAGCTATATGG ACGAGAAGAATGGCCCCCCTCCTCCCAACATGACCACCAACGAGAGGAGAGTCATCGTCCCCGCAGACCC CACACTGTGGACACAGGAGCATGTGAGGCAATGGCTGGAGTGGGCCATAAAGGAGTACAGCTTGATGGAG ATCGACACATCCTTTTTCCAGAACATGGATGGCAAGGAACTGTGTAAAATGAACAAGGAGGACTTCCTCC GCGCCACCACCCTCTACAACACGGAAGTGCTGTTGTCACACCTCAGTTACCTCAGGGAAAGTTCACTGCT GGCCTATAATACAACCTCCCACACCGACCAATCCTCACGATTGAGTGTCAAAGAAGACCCTTCTTATGAC TCAGTCAGAAGAGGAGCTTGGGGCAATAACATGAATTCTGGCCTCAACAAAAGTCCTCCCCTTGGAGGGG CACAAACGATCAGTAAGAATACAGAGCAACGGCCCCAGCCAGATCCGTATCAGATCCTGGGCCCGACCAG CAGTCGCCTAGCCAACCCTGGAAGCGGGCAGATCCAGCTGTGGCAATTCCTCCTGGAGCTGCTCTCCGAC AGCGCCAACGCCAGCTGTATCACCTGGGAGGGGACCAACGGGGAGTTCAAAATGACGGACCCCGATGAGG TGGCCAGGCGCTGGGGCGAGCGGAAAAGCAAGCCCAACATGAATTACGACAAGCTGAGCCGGGCCCTCCG TTATTACTATGATAAAAACATTATGACCAAAGTGCACGGCAAAAGATATGCTTACAAATTTGACTTCCAC GGCATTGCCCAGGCTCTGCAGCCACATCCGACCGAGTCGTCCATGTACAAGTACCCTTCTGACATCTCCT ACATGCCTTCCTACCATGCCCACCAGCAGAAGGTGAACTTTGTCCCTCCCCATCCATCCTCCATGCCTGT CACTTCCTCCAGCTTCTTTGGAGCCGCATCACAATACTGGACCTCCCCCACGGGGGGAATCTACCCCAAC CCCAACGTCCCCCGCCATCCTAACACCCACGTGCCTTCACACTTAGGCAGCTACTACTAGAAGCTTACTC ATCAGTGGCCTTCTAGCTGAAGCCCATCCTGCACACTTACTGGATGCTTTGGACTCAACAGGACATATGT GGCCTTGAAGGGAAGACAAAACTGGATGTTCTTTCTTGTTGGATAGAACCTTTGTATTTGTTCTTTAAAAACATTTTTTTTAATGTTGGTAACTTTTGCTTCCTCTACCTGAACAAAGAGATGAATAATTCCATGGGCCA GTATGCCAGTTTGAATTCTCAGTCTCCTAGCATCTTGTGAGTTGCATATTAAGATTACTGGAATGGTTAA GTCATGGTTCTGAGAAAGAAGCTGTACGTTTTCTTTATGTTTTTATGACCAAAGCAGTTTCTTGTCAATA CACGGGGTTCAGTATGACACAGAATCATGGACTTAACCCGTCATGTTCTGGTTTGAGATTTAGTGACAAA TAGAGGTGGGAAGCTTATAATCTAATTTTAGGAGGACCAAATTCAGTGGATGGCAACTGGAACATTGATT GTAAGGCCAGTGAAGTTTTCACCCAACTGGAATTTGATGGAAAGAAGGTTTGTGTGTTTAAGACGCCAAG GGCATTGCAGAATCCCTCTCAGTGGACAGTATGCACTCAGCTGACCACTCTCTCTAGAAATAGTCAAGAT ATGAACTAAGAAATTTTAATGCAAATACATACATTCCTGAAAGACGGGGAATTAAATTACTAATTTTTTT TTTTTTTTAAATGATGACAGTGGTCCCAGAACTTGGAAAAGTTGTAGGGATTTCTAAACTCAAGCAGATT CGCAAGTGCTGTGCGCTTGTCAGACCATCAGACCAGGGCCAACCAATCAGAAGGCAACTTACTGTATAAA TTATGCAGAGTTATTTTCCTATATCTCACAGTATTAAAAATAAATAATTAAAAATTAAGAATAAATAAAC GAGTTGACCTCGGTCACAAAAGCAGTTTTACTATCGAATCAATCGCTGTTATTTTTTTTAATGTAATTTG TACATCTTTTTTCAATCTGTACATTTGGGCTGTCTGTATGTTTTTATAGCTGGTTTTTAAAAAGCATAAT ATGCCTATAGCTGAAAAGGAAACAGGGCTGTTTAAGTCACTGACTTATGAGAAAGCAAAGCACTGGTACA GTTATTTAACAGGCATACACAAGCAGGGAAAAGATAATCCATTTAGATCTTTAATGCTTTGGAAATGCGT GTAACAGTACTGCAATAATCACAGCTCTGGGAAAAACAACGAAACTTTCCCTTGTGGAGAGGAGGGATTT TCCTGCTCTATATAAGCAACATATTTTTAGACATTAAAATATATATAATTTTGCAGGTAATTGTTGACTT TTTTAACTATATTAAGTGTTAAGCTGACAACTGTCAAAGAAGACCATGTTGTAAAATAATTTGACTAAAT AAATGGTTCCTTCTCTCAGTGCTGAGGACAGTTTTCTTATTTACCGCCCCCGTTAGGTCAAAGGGTTTTC CCTGGGGAACTTTCCTATTTACTTCTTGCACTATCAAGAATTTTTCGAATGTACCTACTGCAGTACAGCA GAAGGTAAAAAATCAGTGTGGTTTTTCATTGTTGTTGATGATGTTTGTAGTGTTTTTGTGTGTGTTATTT AAATCTTCCTCCAGCCTAAAAGGGTTTTATAAAACAGCAGCTAAGGCCATGGATAAACCTGTATGTAAGG ACTGGAGCAAAGCGAGCTGGTCTATCCAGACTGGTCTGTGAGATTTAACTCTGCAGCCTCCCCTGGGCAC TTCAGACCCAGACGGCCACCTTCTGCCACTCCAGCAAAGAATAAGCGCCCTGCTTCCTTCAGGTCTCAGA CCAGGACTTTATGGCTCATGCAGATTTTTAAGGTCATTTTTCTTCCCAAGGAAGAAACTTGCCTCCAGTT CCTTCACTGTTAGGTAGCTTATTTTCATTTTCTCTATTTTACAATGAAAAGAGTGAGACCTGGGAAGTCC TTGATTTGCAAGGAATTAGACTCACAGCATTGGTAACCCTAGAACCTTCTTAGGGTAACACTAAGTACCT TCTAGACAACATGTCTACCTAAATGAAATGGGATGTGTTTCGGAACATTTGTCTCCAGTTTTTTTTTAAT CTTGCACCCTGCCATTTAAAAAGATGTGTAAAGCACATATTCTCAACATATGCACATTGATTTATAAATC ATATATACAAACTGTTACATTATTCTTCATATTAGAAAACAAATACAAAATAGAACATTTTAAATGGTGA TATAAAAATAAATTGAAACTGAAATTCTA SEQ ID NO: 4 - Homo sapiens Fli-1 proto-oncogene, ETS transcription factor (FLI1), transcript variant 3, mRNA 3,996 bp linear mRNA Accession: NM_001271010.2 CTCTTTCGCTCCGCTACAACAACAAACGTGCACAGGGGAGTGAGGGCAGGGCGCTCGCAGGGGGCACGCA GGGAGGGCCCAGGGCGCCAGGGAGGCCGCGCCGGGCTAATCCGAAGGGGCTGCGAGGTCAGGCTGTAACC GGGTCAATGTGTGGAATATTGGGGGGCTCGGCTGCAGACTTGGCCAAATGGACGGGACTATTAAGGAGGC TCTGTCGGTGGTGAGCGACGACCAGTCCCTCTTTGACTCAGCGTACGGAGCGGCAGCCCATCTCCCCAAG GCCGACATGACTGCCTCGGGGAGTCCTGACTACGGGCAGCCCCACAAGATCAACCCCCTCCCACCACAGC AGGAGTGGATCAATCAGCCAGTGAGGGTCAACGTCAAGCGGGAGTATGACCACATGAATGGATCCAGGCG CCAGCTGCCTCATTAAAGAGCAGCCTTTTATGCTGGGCTTCACCTGTACCCACCCTGAGCGGCAGCCGTG GAGCCCCATGGCCGCACGCAGGGCTTGCGCTGGCTGGAGGAGGCACGGTGCTTGGGAGCTGCAAGAATGG AGGGAGGACTGGCAGGCGAGCGGGCGAGGGAGTCTCCGGTGGACTGCAGCGTTAGCAAATGCAGCAAGCT GGTGGGCGGAGGCGAGTCCAACCCCATGAACTACAACAGCTATATGGACGAGAAGAATGGCCCCCCTCCT CCCAACATGACCACCAACGAGAGGAGAGTCATCGTCCCCGCAGACCCCACACTGTGGACACAGGAGCATGTGAGGCAATGGCTGGAGTGGGCCATAAAGGAGTACAGCTTGATGGAGATCGACACATCCTTTTTCCAGAA CATGGATGGCAAGGAACTGTGTAAAATGAACAAGGAGGACTTCCTCCGCGCCACCACCCTCTACAACACG GAAGTGCTGTTGTCACACCTCAGTTACCTCAGGGAAAGTTCACTGCTGGCCTATAATACAACCTCCCACA CCGACCAATCCTCACGATTGAGTGTCAAAGAAGACCCTTCTTATGACTCAGTCAGAAGAGGAGCTTGGGG CAATAACATGAATTCTGGCCTCAACAAAAGTCCTCCCCTTGGAGGGGCACAAACGATCAGTAAGAATACA GAGCAACGGCCCCAGCCAGATCCGTATCAGATCCTGGGCCCGACCAGCAGTCGCCTAGCCAACCCTGGAA GCGGGCAGATCCAGCTGTGGCAATTCCTCCTGGAGCTGCTCTCCGACAGCGCCAACGCCAGCTGTATCAC CTGGGAGGGGACCAACGGGGAGTTCAAAATGACGGACCCCGATGAGGTGGCCAGGCGCTGGGGCGAGCGG AAAAGCAAGCCCAACATGAATTACGACAAGCTGAGCCGGGCCCTCCGTTATTACTATGATAAAAACATTA TGACCAAAGTGCACGGCAAAAGATATGCTTACAAATTTGACTTCCACGGCATTGCCCAGGCTCTGCAGCC ACATCCGACCGAGTCGTCCATGTACAAGTACCCTTCTGACATCTCCTACATGCCTTCCTACCATGCCCAC CAGCAGAAGGTGAACTTTGTCCCTCCCCATCCATCCTCCATGCCTGTCACTTCCTCCAGCTTCTTTGGAG CCGCATCACAATACTGGACCTCCCCCACGGGGGGAATCTACCCCAACCCCAACGTCCCCCGCCATCCTAA CACCCACGTGCCTTCACACTTAGGCAGCTACTACTAGAAGCTTACTCATCAGTGGCCTTCTAGCTGAAGC CCATCCTGCACACTTACTGGATGCTTTGGACTCAACAGGACATATGTGGCCTTGAAGGGAAGACAAAACT GGATGTTCTTTCTTGTTGGATAGAACCTTTGTATTTGTTCTTTAAAAACATTTTTTTTAATGTTGGTAAC TTTTGCTTCCTCTACCTGAACAAAGAGATGAATAATTCCATGGGCCAGTATGCCAGTTTGAATTCTCAGT CTCCTAGCATCTTGTGAGTTGCATATTAAGATTACTGGAATGGTTAAGTCATGGTTCTGAGAAAGAAGCT GTACGTTTTCTTTATGTTTTTATGACCAAAGCAGTTTCTTGTCAATACACGGGGTTCAGTATGACACAGA ATCATGGACTTAACCCGTCATGTTCTGGTTTGAGATTTAGTGACAAATAGAGGTGGGAAGCTTATAATCT AATTTTAGGAGGACCAAATTCAGTGGATGGCAACTGGAACATTGATTGTAAGGCCAGTGAAGTTTTCACC CAACTGGAATTTGATGGAAAGAAGGTTTGTGTGTTTAAGACGCCAAGGGCATTGCAGAATCCCTCTCAGT GGACAGTATGCACTCAGCTGACCACTCTCTCTAGAAATAGTCAAGATATGAACTAAGAAATTTTAATGCA AATACATACATTCCTGAAAGACGGGGAATTAAATTACTAATTTTTTTTTTTTTTTAAATGATGACAGTGG TCCCAGAACTTGGAAAAGTTGTAGGGATTTCTAAACTCAAGCAGATTCGCAAGTGCTGTGCGCTTGTCAG ACCATCAGACCAGGGCCAACCAATCAGAAGGCAACTTACTGTATAAATTATGCAGAGTTATTTTCCTATA TCTCACAGTATTAAAAATAAATAATTAAAAATTAAGAATAAATAAACGAGTTGACCTCGGTCACAAAAGC AGTTTTACTATCGAATCAATCGCTGTTATTTTTTTTAATGTAATTTGTACATCTTTTTTCAATCTGTACA TTTGGGCTGTCTGTATGTTTTTATAGCTGGTTTTTAAAAAGCATAATATGCCTATAGCTGAAAAGGAAAC AGGGCTGTTTAAGTCACTGACTTATGAGAAAGCAAAGCACTGGTACAGTTATTTAACAGGCATACACAAG CAGGGAAAAGATAATCCATTTAGATCTTTAATGCTTTGGAAATGCGTGTAACAGTACTGCAATAATCACA GCTCTGGGAAAAACAACGAAACTTTCCCTTGTGGAGAGGAGGGATTTTCCTGCTCTATATAAGCAACATA TTTTTAGACATTAAAATATATATAATTTTGCAGGTAATTGTTGACTTTTTTAACTATATTAAGTGTTAAG CTGACAACTGTCAAAGAAGACCATGTTGTAAAATAATTTGACTAAATAAATGGTTCCTTCTCTCAGTGCT GAGGACAGTTTTCTTATTTACCGCCCCCGTTAGGTCAAAGGGTTTTCCCTGGGGAACTTTCCTATTTACT TCTTGCACTATCAAGAATTTTTCGAATGTACCTACTGCAGTACAGCAGAAGGTAAAAAATCAGTGTGGTT TTTCATTGTTGTTGATGATGTTTGTAGTGTTTTTGTGTGTGTTATTTAAATCTTCCTCCAGCCTAAAAGG GTTTTATAAAACAGCAGCTAAGGCCATGGATAAACCTGTATGTAAGGACTGGAGCAAAGCGAGCTGGTCT ATCCAGACTGGTCTGTGAGATTTAACTCTGCAGCCTCCCCTGGGCACTTCAGACCCAGACGGCCACCTTC TGCCACTCCAGCAAAGAATAAGCGCCCTGCTTCCTTCAGGTCTCAGACCAGGACTTTATGGCTCATGCAG ATTTTTAAGGTCATTTTTCTTCCCAAGGAAGAAACTTGCCTCCAGTTCCTTCACTGTTAGGTAGCTTATT TTCATTTTCTCTATTTTACAATGAAAAGAGTGAGACCTGGGAAGTCCTTGATTTGCAAGGAATTAGACTC ACAGCATTGGTAACCCTAGAACCTTCTTAGGGTAACACTAAGTACCTTCTAGACAACATGTCTACCTAAA TGAAATGGGATGTGTTTCGGAACATTTGTCTCCAGTTTTTTTTTAATCTTGCACCCTGCCATTTAAAAAG ATGTGTAAAGCACATATTCTCAACATATGCACATTGATTTATAAATCATATATACAAACTGTTACATTAT TCTTCATATTAGAAAACAAATACAAAATAGAACATTTTAAATGGTGATATAAAAATAAATTGAAACTGAA ATTCTASEQ ID NO: 5 - Homo sapiens Fli-1 proto-oncogene, ETS transcription factor (FLI1), transcript variant 4, mRNA 3,428 bp linear mRNA Accession: NM_001271012.2 ACAGTCTCTCCATCTGCATCCCCACTTCATCACCATCCCACCGTCTCTCCCTCGCTCCACTCGCGGGTAA CCGAGGCTTCTCCCTCCCAGGCTGGTTCTTGGGCGTTCCCGACCCTTAGCTACCCACGATGTTTCAGACA GTCCCCGACACGTCGTCTTACATCAAGGAGGCTCTGTCGGTGGTGAGCGACGACCAGTCCCTCTTTGACT CAGCGTACGGAGCGGCAGCCCATCTCCCCAAGGCCGACATGACTGCCTCGGGGAGTCCTGACTACGGGCA GCCCCACAAGATCAACCCCCTCCCACCACAGCAGGAGTGGATCAATCAGCCAGTGAGGGTCAACGTCAAG CGGGAGTATGACCACATGAATGGATCCAGGTTCACTGCTGGCCTATAATACAACCTCCCACACCGACCAA TCCTCACGATTGAGTGTCAAAGAAGACCCTTCTTATGACTCAGTCAGAAGAGGAGCTTGGGGCAATAACA TGAATTCTGGCCTCAACAAAAGTCCTCCCCTTGGAGGGGCACAAACGATCAGTAAGAATACAGAGCAACG GCCCCAGCCAGATCCGTATCAGATCCTGGGCCCGACCAGCAGTCGCCTAGCCAACCCTGGAAGCGGGCAG ATCCAGCTGTGGCAATTCCTCCTGGAGCTGCTCTCCGACAGCGCCAACGCCAGCTGTATCACCTGGGAGG GGACCAACGGGGAGTTCAAAATGACGGACCCCGATGAGGTGGCCAGGCGCTGGGGCGAGCGGAAAAGCAA GCCCAACATGAATTACGACAAGCTGAGCCGGGCCCTCCGTTATTACTATGATAAAAACATTATGACCAAA GTGCACGGCAAAAGATATGCTTACAAATTTGACTTCCACGGCATTGCCCAGGCTCTGCAGCCACATCCGA CCGAGTCGTCCATGTACAAGTACCCTTCTGACATCTCCTACATGCCTTCCTACCATGCCCACCAGCAGAA GGTGAACTTTGTCCCTCCCCATCCATCCTCCATGCCTGTCACTTCCTCCAGCTTCTTTGGAGCCGCATCA CAATACTGGACCTCCCCCACGGGGGGAATCTACCCCAACCCCAACGTCCCCCGCCATCCTAACACCCACG TGCCTTCACACTTAGGCAGCTACTACTAGAAGCTTACTCATCAGTGGCCTTCTAGCTGAAGCCCATCCTG CACACTTACTGGATGCTTTGGACTCAACAGGACATATGTGGCCTTGAAGGGAAGACAAAACTGGATGTTC TTTCTTGTTGGATAGAACCTTTGTATTTGTTCTTTAAAAACATTTTTTTTAATGTTGGTAACTTTTGCTT CCTCTACCTGAACAAAGAGATGAATAATTCCATGGGCCAGTATGCCAGTTTGAATTCTCAGTCTCCTAGC ATCTTGTGAGTTGCATATTAAGATTACTGGAATGGTTAAGTCATGGTTCTGAGAAAGAAGCTGTACGTTT TCTTTATGTTTTTATGACCAAAGCAGTTTCTTGTCAATACACGGGGTTCAGTATGACACAGAATCATGGA CTTAACCCGTCATGTTCTGGTTTGAGATTTAGTGACAAATAGAGGTGGGAAGCTTATAATCTAATTTTAG GAGGACCAAATTCAGTGGATGGCAACTGGAACATTGATTGTAAGGCCAGTGAAGTTTTCACCCAACTGGA ATTTGATGGAAAGAAGGTTTGTGTGTTTAAGACGCCAAGGGCATTGCAGAATCCCTCTCAGTGGACAGTA TGCACTCAGCTGACCACTCTCTCTAGAAATAGTCAAGATATGAACTAAGAAATTTTAATGCAAATACATA CATTCCTGAAAGACGGGGAATTAAATTACTAATTTTTTTTTTTTTTTAAATGATGACAGTGGTCCCAGAA CTTGGAAAAGTTGTAGGGATTTCTAAACTCAAGCAGATTCGCAAGTGCTGTGCGCTTGTCAGACCATCAG ACCAGGGCCAACCAATCAGAAGGCAACTTACTGTATAAATTATGCAGAGTTATTTTCCTATATCTCACAG TATTAAAAATAAATAATTAAAAATTAAGAATAAATAAACGAGTTGACCTCGGTCACAAAAGCAGTTTTAC TATCGAATCAATCGCTGTTATTTTTTTTAATGTAATTTGTACATCTTTTTTCAATCTGTACATTTGGGCT GTCTGTATGTTTTTATAGCTGGTTTTTAAAAAGCATAATATGCCTATAGCTGAAAAGGAAACAGGGCTGT TTAAGTCACTGACTTATGAGAAAGCAAAGCACTGGTACAGTTATTTAACAGGCATACACAAGCAGGGAAA AGATAATCCATTTAGATCTTTAATGCTTTGGAAATGCGTGTAACAGTACTGCAATAATCACAGCTCTGGG AAAAACAACGAAACTTTCCCTTGTGGAGAGGAGGGATTTTCCTGCTCTATATAAGCAACATATTTTTAGA CATTAAAATATATATAATTTTGCAGGTAATTGTTGACTTTTTTAACTATATTAAGTGTTAAGCTGACAAC TGTCAAAGAAGACCATGTTGTAAAATAATTTGACTAAATAAATGGTTCCTTCTCTCAGTGCTGAGGACAG TTTTCTTATTTACCGCCCCCGTTAGGTCAAAGGGTTTTCCCTGGGGAACTTTCCTATTTACTTCTTGCAC TATCAAGAATTTTTCGAATGTACCTACTGCAGTACAGCAGAAGGTAAAAAATCAGTGTGGTTTTTCATTG TTGTTGATGATGTTTGTAGTGTTTTTGTGTGTGTTATTTAAATCTTCCTCCAGCCTAAAAGGGTTTTATA AAACAGCAGCTAAGGCCATGGATAAACCTGTATGTAAGGACTGGAGCAAAGCGAGCTGGTCTATCCAGAC TGGTCTGTGAGATTTAACTCTGCAGCCTCCCCTGGGCACTTCAGACCCAGACGGCCACCTTCTGCCACTCCAGCAAAGAATAAGCGCCCTGCTTCCTTCAGGTCTCAGACCAGGACTTTATGGCTCATGCAGATTTTTAA GGTCATTTTTCTTCCCAAGGAAGAAACTTGCCTCCAGTTCCTTCACTGTTAGGTAGCTTATTTTCATTTT CTCTATTTTACAATGAAAAGAGTGAGACCTGGGAAGTCCTTGATTTGCAAGGAATTAGACTCACAGCATT GGTAACCCTAGAACCTTCTTAGGGTAACACTAAGTACCTTCTAGACAACATGTCTACCTAAATGAAATGG GATGTGTTTCGGAACATTTGTCTCCAGTTTTTTTTTAATCTTGCACCCTGCCATTTAAAAAGATGTGTAA AGCACATATTCTCAACATATGCACATTGATTTATAAATCATATATACAAACTGTTACATTATTCTTCATA TTAGAAAACAAATACAAAATAGAACATTTTAAATGGTGATATAAAAATAAATTGAAACTGAAATTCTA SEQ ID NO: 6 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 1, mRNA 4,904 bp linear mRNA Accession: NM_182918.4 GI: 1519314383 ATCCGCTCTAAACAACCTCATCAAAACTACTTTCTGGTCAGAGAGAAGCAATAATTATTATTAACATTTA TTAACGATCAATAAACTTGATCGCATTATGGCCAGCACTATTAAGGAAGCCTTATCAGTTGTGAGTGAGG ACCAGTCGTTGTTTGAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTC CAGCGACTATGGACAGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCA GCCAGGGTCACCATCAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAAT GCAGTGTGGCCAAAGGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACAT GGAGGAGAAGCACATGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCT ACGCTATGGAGTACAGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACG TCAACATCTTGTTATTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAG GCTCACCCCCAGCTACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCA CATTTGACTTCAGATGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAG GGGGTGCAGCTTTTATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGCAAAGAATTACAACTAGGCC AGATTTACCATATGAGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAA GCTGCTCAACCATCTCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGA TTCTTGGACCAACAAGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCAGTTCCTCCT GGAGCTCCTGTCGGACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAGTTCAAGATG ACGGATCCCGACGAGGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACTACGATAAGC TCAGCCGCGCCCTCCGTTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCGCTACGCCTA CAAGTTCGACTTCCACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTGTACAAGTAC CCCTCAGACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGGCGCCCCACC CTCCAGCCCTCCCCGTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTCACCAACTGG GGGTATATACCCCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTACTACTAAAGA CCTGGCGGAGGCTTTTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGGAGAACATGA ATCAAAAGTGCCTCAAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGGAAGAGATCC AAAGACTCTTGGGAGGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAATGTCACGAAT ATGGACATATCATCTGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCTTAAGGACAA AGTGCCAAAGAAAGTGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCACTAATGCAAA CTGGGATGAAACTAAAGCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATGCCATTTTAA GGAAAACTACCTGTATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGAGACTGTGGC CCATCAACAGACGTTGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATACATTCCGTTT GATGGACAGCTGTCAGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTACAGTATTACC GGGACTATGAACTAAAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGACAGAGGGGTG AAGAAGGAGGAGGAAGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAGCAATGAAGA CTGGACTCAGGACATTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCAGTCAGTGTT ATACCAAACCCAGTGTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAATTCAGAAACAAAAATGCGCATCTCTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATATTTAAGAGAA ACATTCAGGACCTCATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGGCCTTCTTGG CTGCCACAATCAGAAATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGTCGCGAACGC TGTGCGTTTGTCAGAATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATTATATAACTT ATGCATTTATACACTACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAAT GTGGCCTTGAATTTTAACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAGAATGCAGAA TGTATGTAATAAAATAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCATTTGCACTTT TTTTAGTGACTAAAGTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATAATTTACTTT GTCCAGGAACTTGTGCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTCAGCCTCTCC AGGTCCTTCTTGCCTCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCCCGGGTTTCA CATTGGAGCCTCCATATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCATTGAGAAATT CTAGTTCAGCACCTGGTCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTTGAACAGTGA ACAAGCTACCACTCGTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGCTGCAATTTC TCACTTTACAGAAACAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCTCTCACTAGG TAGACAGCTTTAGTCCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAGCCCTGAGCC TGATGTTGCTGGCTATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCCTGGGCATCT TTTCTTTGAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAAATACAAGGT GACCGTGCGAAGGCGCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTTCATAGCTGT TTCAGGGCCTGTTTTTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAACCTCTGTGCT GTGGATGTTTTGGCAGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCA TTTGGATTAGACGGAGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAGTGCCCGTAT CTCCTTAGGGAAAATAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTGTGCTAATGG AAAAGATCAGTCATTTTTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGAAATACACAT TTACTTGGATAATCACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAACAAGACATGA TTATCATATTCAATTTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTCCAGGTTATT AGCAAGTCTTATGAGCAACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAAATACATAAT TCTTAAATTGTTTCAAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCCCCCTCCAGG TCATATTCATAATTGCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTGATGTATACT CAGACTCCTGTACAATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAATTGGCTTTC GGGCCTTGTATGTGGTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTTGATGCCCTT ATGTCCCGGAGGGGTTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGCTTCTCCTAA GCCTTCTGCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTGACAGCAGGT GCAGCAGAGATGGCTACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGATGTTCTGCA GCGCCCCAAAGTGACCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTTTATTTAGCT TCTCATTAATTCATTCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTGGACTACTCA AAAA SEQ ID NO: 7 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 2, mRNA 5,042 bp linear mRNA Accession: NM_004449.4 GI: 209954801 GTTTTCACTTGGTCGGAATGGGGAGAGTGTGCAAGAGATCGCTGCGGGACAGGTTCCTAGAGATCGCTCC GGGACGGTCGTGACGGCCCCCGAGGGACATGAGAGAAGAGGAGCGGCGCTCAGGTTATTCCAGGATCTTT GGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAGAAAAAAGATGGCAGAAC CAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTACTGAAGGACATGATTCA GACTGTCCCGGACCCAGCAGCTCATATCAAGGAAGCCTTATCAGTTGTGAGTGAGGACCAGTCGTTGTTT GAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTCCAGCGACTATGGACAGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCAGCCAGGGTCACCAT CAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAATGCAGTGTGGCCAAA GGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACATGGAGGAGAAGCACA TGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCTACGCTATGGAGTAC AGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAACATCTTGTTA TTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAGGCTCACCCCCAGCT ACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCACATTTGACTTCAGA TGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGATTTACCATATGAG CCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAAGCTGCTCAACCATCTC CTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGATTCTTGGACCAACAAG TAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCAGTTCCTCCTGGAGCTCCTGTCGGAC AGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAGTTCAAGATGACGGATCCCGACGAGG TGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACTACGATAAGCTCAGCCGCGCCCTCCG TTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCGCTACGCCTACAAGTTCGACTTCCAC GGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTGTACAAGTACCCCTCAGACCTCCCGT ACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGGCGCCCCACCCTCCAGCCCTCCCCGT GACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTCACCAACTGGGGGTATATACCCCAAC ACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTACTACTAAAGACCTGGCGGAGGCTTTT CCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGGAGAACATGAATCAAAAGTGCCTCAA GAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGGAAGAGATCCAAAGACTCTTGGGAGG GAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAATGTCACGAATATGGACATATCATCTG TGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCTTAAGGACAAAGTGCCAAAGAAAGTG GTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCACTAATGCAAACTGGGATGAAACTAAA GCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATGCCATTTTAAGGAAAACTACCTGTAT TTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGAGACTGTGGCCCATCAACAGACGTTG ATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATACATTCCGTTTGATGGACAGCTGTCAG CTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTACAGTATTACCGGGACTATGAACTAAA AGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGACAGAGGGGTGAAGAAGGAGGAGGAAG AGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAGCAATGAAGACTGGACTCAGGACATT TGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCAGTCAGTGTTATACCAAACCCAGTGT TAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAATTCAGAAACAAAAATGCGCATCTCT TTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATATTTAAGAGAAACATTCAGGACCTCAT CATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGGCCTTCTTGGCTGCCACAATCAGAAA TCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGTCGCGAACGCTGTGCGTTTGTCAGAA TGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATTATATAACTTATGCATTTATACACTA CGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAATGTGGCCTTGAATTTTA ACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAGAATGCAGAATGTATGTAATAAAATA AGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCATTTGCACTTTTTTTAGTGACTAAAGT TGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATAATTTACTTTGTCCAGGAACTTGTGC AAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTCAGCCTCTCCAGGTCCTTCTTGCCTC CCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCCCGGGTTTCACATTGGAGCCTCCATA TTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCATTGAGAAATTCTAGTTCAGCACCTGG TCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTTGAACAGTGAACAAGCTACCACTCGT AAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGCTGCAATTTCTCACTTTACAGAAACA AGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCTCTCACTAGGTAGACAGCTTTAGTCC TGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAGCCCTGAGCCTGATGTTGCTGGCTAT CCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCCTGGGCATCTTTTCTTTGAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAAATACAAGGTGACCGTGCGAAGGCGC TAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTTCATAGCTGTTTCAGGGCCTGTTTTT TTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAACCTCTGTGCTGTGGATGTTTTGGCAG TGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCATTTGGATTAGACGGAG CCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAGTGCCCGTATCTCCTTAGGGAAAATA AATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTGTGCTAATGGAAAAGATCAGTCATTT TTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGAAATACACATTTACTTGGATAATCAC TCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAACAAGACATGATTATCATATTCAATTT TAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTCCAGGTTATTAGCAAGTCTTATGAGC AACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAAATACATAATTCTTAAATTGTTTCAA AATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCCCCCTCCAGGTCATATTCATAATTGC ATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTGATGTATACTCAGACTCCTGTACAAT CTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAATTGGCTTTCGGGCCTTGTATGTGGT AAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTTGATGCCCTTATGTCCCGGAGGGGTT CACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGCTTCTCCTAAGCCTTCTGCACAGATG TGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTGACAGCAGGTGCAGCAGAGATGGCTA CAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGATGTTCTGCAGCGCCCCAAAGTGACC CATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTTTATTTAGCTTCTCATTAATTCATTC AAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTGGACTACTCAAAAATACACCAAAAAA AA SEQ ID NO: 8 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 3, mRNA 5,114 bp linear mRNA Accession: NM_001136154.1 GI: 209954796 GTTTTCACTTGGTCGGAATGGGGAGAGTGTGCAAGAGATCGCTGCGGGACAGGTTCCTAGAGATCGCTCC GGGACGGTCGTGACGGCCCCCGAGGGACATGAGAGAAGAGGAGCGGCGCTCAGGTTATTCCAGGATCTTT GGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAGAAAAAAGATGGCAGAAC CAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTACTGAAGGACATGATTCA GACTGTCCCGGACCCAGCAGCTCATATCAAGGAAGCCTTATCAGTTGTGAGTGAGGACCAGTCGTTGTTT GAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTCCAGCGACTATGGAC AGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCAGCCAGGGTCACCAT CAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAATGCAGTGTGGCCAAA GGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACATGGAGGAGAAGCACA TGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCTACGCTATGGAGTAC AGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAACATCTTGTTA TTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAGGCTCACCCCCAGCT ACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCACATTTGACTTCAGA TGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGGGGGTGCAGCTTTT ATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGCAAAGAATTACAACTAGGCCAGATTTACCATATG AGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAAGCTGCTCAACCATC TCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGATTCTTGGACCAACA AGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCAGTTCCTCCTGGAGCTCCTGTCGG ACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAGTTCAAGATGACGGATCCCGACGA GGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACTACGATAAGCTCAGCCGCGCCCTC CGTTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCGCTACGCCTACAAGTTCGACTTCC ACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTGTACAAGTACCCCTCAGACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGGCGCCCCACCCTCCAGCCCTCCCC GTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTCACCAACTGGGGGTATATACCCCA ACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTACTACTAAAGACCTGGCGGAGGCTT TTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGGAGAACATGAATCAAAAGTGCCTC AAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGGAAGAGATCCAAAGACTCTTGGGA GGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAATGTCACGAATATGGACATATCATC TGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCTTAAGGACAAAGTGCCAAAGAAAG TGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCACTAATGCAAACTGGGATGAAACTA AAGCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATGCCATTTTAAGGAAAACTACCTGT ATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGAGACTGTGGCCCATCAACAGACGT TGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATACATTCCGTTTGATGGACAGCTGTC AGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTACAGTATTACCGGGACTATGAACTA AAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGACAGAGGGGTGAAGAAGGAGGAGGA AGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAGCAATGAAGACTGGACTCAGGACA TTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCAGTCAGTGTTATACCAAACCCAGT GTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAATTCAGAAACAAAAATGCGCATCT CTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATATTTAAGAGAAACATTCAGGACCTC ATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGGCCTTCTTGGCTGCCACAATCAGA AATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGTCGCGAACGCTGTGCGTTTGTCAG AATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATTATATAACTTATGCATTTATACAC TACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAATGTGGCCTTGAATTT TAACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAGAATGCAGAATGTATGTAATAAAA TAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCATTTGCACTTTTTTTAGTGACTAAA GTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATAATTTACTTTGTCCAGGAACTTGT GCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTCAGCCTCTCCAGGTCCTTCTTGCC TCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCCCGGGTTTCACATTGGAGCCTCCA TATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCATTGAGAAATTCTAGTTCAGCACCT GGTCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTTGAACAGTGAACAAGCTACCACTC GTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGCTGCAATTTCTCACTTTACAGAAA CAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCTCTCACTAGGTAGACAGCTTTAGT CCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAGCCCTGAGCCTGATGTTGCTGGCT ATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCCTGGGCATCTTTTCTTTGAATCAC AAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAAATACAAGGTGACCGTGCGAAGGC GCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTTCATAGCTGTTTCAGGGCCTGTTT TTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAACCTCTGTGCTGTGGATGTTTTGGC AGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCATTTGGATTAGACGG AGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAGTGCCCGTATCTCCTTAGGGAAAA TAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTGTGCTAATGGAAAAGATCAGTCAT TTTTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGAAATACACATTTACTTGGATAATC ACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAACAAGACATGATTATCATATTCAAT TTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTCCAGGTTATTAGCAAGTCTTATGA GCAACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAAATACATAATTCTTAAATTGTTTC AAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCCCCCTCCAGGTCATATTCATAATT GCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTGATGTATACTCAGACTCCTGTACA ATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAATTGGCTTTCGGGCCTTGTATGTG GTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTTGATGCCCTTATGTCCCGGAGGGG TTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGCTTCTCCTAAGCCTTCTGCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTGACAGCAGGTGCAGCAGAGATGGC TACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGATGTTCTGCAGCGCCCCAAAGTGA CCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTTTATTTAGCTTCTCATTAATTCAT TCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTGGACTACTCAAAAATACACCAAAA AAAA SEQ ID NO: 9 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 4, mRNA 4,727 bp linear mRNA Accession: NM_001136155.1 GI: 209954807 TTCATTTCCCAGACTTAGCACAATCTCATCCGCTCTAAACAACCTCATCAAAACTACTTTCTGGTCAGAG AGAAGCAATAATTATTATTAACATTTATTAACGATCAATAAACTTGATCGCATTATGGCCAGCACTATTA AGGAACTCTCCTGATGAATGCAGTGTGGCCAAAGGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGA TGAACTACGGCAGCTACATGGAGGAGAAGCACATGCCACCCCCAAACATGACCACGAACGAGCGCAGAGT TATCGTGCCAGCAGATCCTACGCTATGGAGTACAGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAA GAATATGGCCTTCCAGACGTCAACATCTTGTTATTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGA CCAAGGACGACTTCCAGAGGCTCACCCCCAGCTACAACGCCGACATCCTTCTCTCACATCTCCACTACCT CAGAGAGACTCCTCTTCCACATTTGACTTCAGATGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTA ATGCATGCTAGAAACACAGGGGGTGCAGCTTTTATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGC AAAGAATTACAACTAGGCCAGATTTACCATATGAGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCA CCCCACGCCCCAGTCGAAAGCTGCTCAACCATCTCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCT CAGTTAGATCCTTATCAGATTCTTGGACCAACAAGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCC AGCTTTGGCAGTTCCTCCTGGAGCTCCTGTCGGACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCAC CAACGGGGAGTTCAAGATGACGGATCCCGACGAGGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCC AACATGAACTACGATAAGCTCAGCCGCGCCCTCCGTTACTACTATGACAAGAACATCATGACCAAGGTCC ATGGGAAGCGCTACGCCTACAAGTTCGACTTCCACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGA GTCATCTCTGTACAAGTACCCCTCAGACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATG AACTTTGTGGCGCCCCACCCTCCAGCCCTCCCCGTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCAT ACTGGAATTCACCAACTGGGGGTATATACCCCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCT GGGCACTTACTACTAAAGACCTGGCGGAGGCTTTTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAA ACTCTATCGGAGAACATGAATCAAAAGTGCCTCAAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAG GAAGCCGGGGAAGAGATCCAAAGACTCTTGGGAGGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGA TGCTAAAAATGTCACGAATATGGACATATCATCTGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAG CATGAAGTCTTAAGGACAAAGTGCCAAAGAAAGTGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTT GGAATCCCACTAATGCAAACTGGGATGAAACTAAAGCAATAGAAACAACACAGTTTTGACCTAACATACC GTTTATAATGCCATTTTAAGGAAAACTACCTGTATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAG ACACGAGAGAGACTGTGGCCCATCAACAGACGTTGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGA AATCAAATACATTCCGTTTGATGGACAGCTGTCAGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCA ACTCCTTTACAGTATTACCGGGACTATGAACTAAAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGT GATTGTAGACAGAGGGGTGAAGAAGGAGGAGGAAGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAA ACTTCTCAAGCAATGAAGACTGGACTCAGGACATTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAG GGTTCATGCAGTCAGTGTTATACCAAACCCAGTGTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGA AGTAGTAGAATTCAGAAACAAAAATGCGCATCTCTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAAT TGTCTGATATTTAAGAGAAACATTCAGGACCTCATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGG TAAGAGATGGCCTTCTTGGCTGCCACAATCAGAAATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTT TCCTTTGAGTCGCGAACGCTGTGCGTTTGTCAGAATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTA TATAATAATTATATAACTTATGCATTTATACACTACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAATGTGGCCTTGAATTTTAACTCTGTATGCTTAATGTTTACAATATGAAGTTAT TAGTTCTTAGAATGCAGAATGTATGTAATAAAATAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAG GAGTCTGCATTTGCACTTTTTTTAGTGACTAAAGTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATT TTGTGTTATAATTTACTTTGTCCAGGAACTTGTGCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCC AAATGGCGTCAGCCTCTCCAGGTCCTTCTTGCCTCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAAC AGAAGGACCCCGGGTTTCACATTGGAGCCTCCATATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTG GGGTTGTCATTGAGAAATTCTAGTTCAGCACCTGGTCACAAATCACCCTTAATTCCTGCTATGATTAAAA TACATTTGTTGAACAGTGAACAAGCTACCACTCGTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGT CATGGATAGCTGCAATTTCTCACTTTACAGAAACAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCT TTCAGGAGCTCTCACTAGGTAGACAGCTTTAGTCCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGG GATTCACTAGCCCTGAGCCTGATGTTGCTGGCTATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAG TCAGTTTCCCTGGGCATCTTTTCTTTGAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCA AAAGGTGAAAATACAAGGTGACCGTGCGAAGGCGCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAAC TGGCCCTTTTCATAGCTGTTTCAGGGCCTGTTTTTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAA GTTGCCAAACCTCTGTGCTGTGGATGTTTTGGCAGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATG CTCCTGACACCCCGTGTCATTTGGATTAGACGGAGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAG GCCCACAAAGTGCCCGTATCTCCTTAGGGAAAATAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTG ACCCAAACTGTGCTAATGGAAAAGATCAGTCATTTTTATTTTGGAATGCAAAGTCAAGACACACCTACAT TCTTCATAGAAATACACATTTACTTGGATAATCACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGA TCATAAAAACAAGACATGATTATCATATTCAATTTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCC ACCCCCAGTCCAGGTTATTAGCAAGTCTTATGAGCAACTGGGATAATTTTGGATAACATGATAATACTGA GTTCCTTCAAATACATAATTCTTAAATTGTTTCAAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAA TTCCAAAGCCCCCTCCAGGTCATATTCATAATTGCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTG GCTTGCCCTGATGTATACTCAGACTCCTGTACAATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTC TTGTCTTCAATTGGCTTTCGGGCCTTGTATGTGGTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTG TTCCTAGTTTGATGCCCTTATGTCCCGGAGGGGTTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAA GGCTCACTGCTTCTCCTAAGCCTTCTGCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAG CTGCCCTCTGACAGCAGGTGCAGCAGAGATGGCTACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGG AAAGCACAGATGTTCTGCAGCGCCCCAAAGTGACCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAA AAAGCTAGTTTATTTAGCTTCTCATTAATTCATTCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAA AATTACTTTGGACTACTCAAAAATACACCAAAAAAAA SEQ ID NO: 10 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 5, mRNA 5,139 bp linear mRNA Accession: NM_001243428.1 GI: 343478175 GCTGAGCCCGTCGGCGCCGAGGGAGTTAGTGCGACCCGGCTCGGCGCGCACGGCCAAGGCACGCGCGCTG GCACACGCGGGCGCGGACACGCGCGGACACACACGTGCGGGACACGCCCTCCCCCGACGGCGGCGCTAAC CTCTCGGTTATTCCAGGATCTTTGGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTC ACAGAGAAAAAAGATGGCAGAACCAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCT GGCTTACTGAAGGACATGATTCAGACTGTCCCGGACCCAGCAGCTCATATCAAGGAAGCCTTATCAGTTG TGAGTGAGGACCAGTCGTTGTTTGAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGC GTCCTCCTCCAGCGACTATGGACAGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCT CAACCCCCAGCCAGGGTCACCATCAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTC CTGATGAATGCAGTGTGGCCAAAGGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGG CAGCTACATGGAGGAGAAGCACATGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCA GCAGATCCTACGCTATGGAGTACAGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAACATCTTGTTATTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGA CTTCCAGAGGCTCACCCCCAGCTACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACT CCTCTTCCACATTTGACTTCAGATGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTA GAAACACAGGGGGTGCAGCTTTTATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGCAAAGAATTAC AACTAGGCCAGATTTACCATATGAGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCC CAGTCGAAAGCTGCTCAACCATCTCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATC CTTATCAGATTCTTGGACCAACAAGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCA GTTCCTCCTGGAGCTCCTGTCGGACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAG TTCAAGATGACGGATCCCGACGAGGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACT ACGATAAGCTCAGCCGCGCCCTCCGTTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCG CTACGCCTACAAGTTCGACTTCCACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTG TACAAGTACCCCTCAGACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGG CGCCCCACCCTCCAGCCCTCCCCGTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTC ACCAACTGGGGGTATATACCCCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTAC TACTAAAGACCTGGCGGAGGCTTTTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGG AGAACATGAATCAAAAGTGCCTCAAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGG AAGAGATCCAAAGACTCTTGGGAGGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAAT GTCACGAATATGGACATATCATCTGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCT TAAGGACAAAGTGCCAAAGAAAGTGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCAC TAATGCAAACTGGGATGAAACTAAAGCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATG CCATTTTAAGGAAAACTACCTGTATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGA GACTGTGGCCCATCAACAGACGTTGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATAC ATTCCGTTTGATGGACAGCTGTCAGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTAC AGTATTACCGGGACTATGAACTAAAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGAC AGAGGGGTGAAGAAGGAGGAGGAAGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAG CAATGAAGACTGGACTCAGGACATTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCA GTCAGTGTTATACCAAACCCAGTGTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAA TTCAGAAACAAAAATGCGCATCTCTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATAT TTAAGAGAAACATTCAGGACCTCATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGG CCTTCTTGGCTGCCACAATCAGAAATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGT CGCGAACGCTGTGCGTTTGTCAGAATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATT ATATAACTTATGCATTTATACACTACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAAT CGATATAATGTGGCCTTGAATTTTAACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAG AATGCAGAATGTATGTAATAAAATAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCAT TTGCACTTTTTTTAGTGACTAAAGTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATA ATTTACTTTGTCCAGGAACTTGTGCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTC AGCCTCTCCAGGTCCTTCTTGCCTCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCC CGGGTTTCACATTGGAGCCTCCATATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCAT TGAGAAATTCTAGTTCAGCACCTGGTCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTT GAACAGTGAACAAGCTACCACTCGTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGC TGCAATTTCTCACTTTACAGAAACAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCT CTCACTAGGTAGACAGCTTTAGTCCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAG CCCTGAGCCTGATGTTGCTGGCTATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCC TGGGCATCTTTTCTTTGAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAA ATACAAGGTGACCGTGCGAAGGCGCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTT CATAGCTGTTTCAGGGCCTGTTTTTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAAC CTCTGTGCTGTGGATGTTTTGGCAGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCATTTGGATTAGACGGAGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAG TGCCCGTATCTCCTTAGGGAAAATAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTG TGCTAATGGAAAAGATCAGTCATTTTTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGA AATACACATTTACTTGGATAATCACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAAC AAGACATGATTATCATATTCAATTTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTC CAGGTTATTAGCAAGTCTTATGAGCAACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAA ATACATAATTCTTAAATTGTTTCAAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCC CCCTCCAGGTCATATTCATAATTGCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTG ATGTATACTCAGACTCCTGTACAATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAA TTGGCTTTCGGGCCTTGTATGTGGTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTT GATGCCCTTATGTCCCGGAGGGGTTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGC TTCTCCTAAGCCTTCTGCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTG ACAGCAGGTGCAGCAGAGATGGCTACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGA TGTTCTGCAGCGCCCCAAAGTGACCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTT TATTTAGCTTCTCATTAATTCATTCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTG GACTACTCAAAAATACACCAAAAAAAAAA SEQ ID NO: 11 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 6, mRNA 4,703 bp linear mRNA Accession: NM_001243429.1 GI: 343478177 GTTATTCCAGGATCTTTGGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAG AAAAAAGATGGCAGAACCAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTA CTGAAGGACATGATTCAGACTGTCCCGGACCCAGCAGCTCATATCAAGGAACTCTCCTGATGAATGCAGT GTGGCCAAAGGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACATGGAGG AGAAGCACATGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCTACGCT ATGGAGTACAGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAAC ATCTTGTTATTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAGGCTCA CCCCCAGCTACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCACATTT GACTTCAGATGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGATTTA CCATATGAGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAAGCTGCTC AACCATCTCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGATTCTTGG ACCAACAAGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCAGTTCCTCCTGGAGCTC CTGTCGGACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAGTTCAAGATGACGGATC CCGACGAGGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACTACGATAAGCTCAGCCG CGCCCTCCGTTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCGCTACGCCTACAAGTTC GACTTCCACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTGTACAAGTACCCCTCAG ACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGGCGCCCCACCCTCCAGC CCTCCCCGTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTCACCAACTGGGGGTATA TACCCCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTACTACTAAAGACCTGGCG GAGGCTTTTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGGAGAACATGAATCAAAA GTGCCTCAAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGGAAGAGATCCAAAGACT CTTGGGAGGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAATGTCACGAATATGGACA TATCATCTGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCTTAAGGACAAAGTGCCA AAGAAAGTGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCACTAATGCAAACTGGGAT GAAACTAAAGCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATGCCATTTTAAGGAAAAC TACCTGTATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGAGACTGTGGCCCATCAACAGACGTTGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATACATTCCGTTTGATGGAC AGCTGTCAGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTACAGTATTACCGGGACTA TGAACTAAAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGACAGAGGGGTGAAGAAGG AGGAGGAAGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAGCAATGAAGACTGGACT CAGGACATTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCAGTCAGTGTTATACCAA ACCCAGTGTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAATTCAGAAACAAAAATG CGCATCTCTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATATTTAAGAGAAACATTCA GGACCTCATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGGCCTTCTTGGCTGCCAC AATCAGAAATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGTCGCGAACGCTGTGCGT TTGTCAGAATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATTATATAACTTATGCATT TATACACTACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAATGTGGCCT TGAATTTTAACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAGAATGCAGAATGTATGT AATAAAATAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCATTTGCACTTTTTTTAGT GACTAAAGTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATAATTTACTTTGTCCAGG AACTTGTGCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTCAGCCTCTCCAGGTCCT TCTTGCCTCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCCCGGGTTTCACATTGGA GCCTCCATATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCATTGAGAAATTCTAGTTC AGCACCTGGTCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTTGAACAGTGAACAAGCT ACCACTCGTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGCTGCAATTTCTCACTTT ACAGAAACAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCTCTCACTAGGTAGACAG CTTTAGTCCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAGCCCTGAGCCTGATGTT GCTGGCTATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCCTGGGCATCTTTTCTTT GAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAAATACAAGGTGACCGTG CGAAGGCGCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTTCATAGCTGTTTCAGGG CCTGTTTTTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAACCTCTGTGCTGTGGATG TTTTGGCAGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCATTTGGAT TAGACGGAGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAGTGCCCGTATCTCCTTA GGGAAAATAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTGTGCTAATGGAAAAGAT CAGTCATTTTTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGAAATACACATTTACTTG GATAATCACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAACAAGACATGATTATCAT ATTCAATTTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTCCAGGTTATTAGCAAGT CTTATGAGCAACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAAATACATAATTCTTAAA TTGTTTCAAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCCCCCTCCAGGTCATATT CATAATTGCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTGATGTATACTCAGACTC CTGTACAATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAATTGGCTTTCGGGCCTT GTATGTGGTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTTGATGCCCTTATGTCCC GGAGGGGTTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGCTTCTCCTAAGCCTTCT GCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTGACAGCAGGTGCAGCAG AGATGGCTACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGATGTTCTGCAGCGCCCC AAAGTGACCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTTTATTTAGCTTCTCATT AATTCATTCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTGGACTACTCAAAAATAC ACCAAAAAAAAAA SEQ ID NO: 12 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 7, mRNA 1,606 bp linear mRNA Accession: NM_001243432.2 GI: 609878460 GTTTTCACTTGGTCGGAATGGGGAGAGTGTGCAAGAGATCGCTGCGGGACAGGTTCCTAGAGATCGCTCCGGGACGGTCGTGACGGCCCCCGAGGGACATGAGAGAAGAGGAGCGGCGCTCAGGTTATTCCAGGATCTTT GGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAGAAAAAAGATGGCAGAAC CAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTACTGAAGGACATGATTCA GACTGTCCCGGACCCAGCAGCTCATATCAAGGAAGCCTTATCAGTTGTGAGTGAGGACCAGTCGTTGTTT GAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTCCAGCGACTATGGAC AGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCAGCCAGGGTCACCAT CAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAATGCAGTGTGGCCAAA GGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACATGGAGGAGAAGCACA TGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCTACGCTATGGAGTAC AGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAACATCTTGTTA TTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAGGCTCACCCCCAGCT ACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCACATTTGACTTCAGA TGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGGGGGTGCAGCTTTT ATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGCAAAGAATTACAACTAGGCCAGATTTACCATATG AGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAAGCTGCTCAACCATC TCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGATTCTTGGACCAACA AGTAGCCGCCTTGCAAATCCAGGTTGGACCCAATGATCTGCTTTTAATGAATAGAATATAGCAGATGTGA CAGTGTGTGACTTCTGGGACTGGGTCATAGAAGGCAGCGTGGCCTTCTCTTTGCATCACTTATTCTGGGG GAAGAGACTGCCATGTCATGAAGACTTGCAGCCCTACAGAGAAGTGTATGGGATGAGGAAATGAAGCCTC CTGTCAAAAGCCAATTCTCCAGCCCCAGTCAAGCCTTCGTGTAACCTCAGTCTTGGTCAACATCTTAACT GAAACCTCATGAGAGACCCTGAGCCACCAGCCACCCACGTGAGCTGCTTCTGAATGCCTGATCCACCAAA ACTGTGAGATAATAAATGTTTATGGAGAAATTTGTTACACAGCAATAAATAGTTACACAGAAAAAA SEQ ID NO: 13 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 8, mRNA 1,546 bp linear mRNA Accession: NM_001291391.1 GI: 609878487 GTTTTCACTTGGTCGGAATGGGGAGAGTGTGCAAGAGATCGCTGCGGGACAGGTTCCTAGAGATCGCTCC GGGACGGTCGTGACGGCCCCCGAGGGACATGAGAGAAGAGGAGCGGCGCTCAGGTTATTCCAGGATCTTT GGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAGAAAAAAGATGGCAGAAC CAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTACTGAAGGACATGATTCA GACTGTCCCGGACCCAGCAGCTCATATCAAGGAAGCCTTATCAGTTGTGAGTGAGGACCAGTCGTTGTTT GAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTCCAGCGACTATGGAC AGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCAGCCAGGGTCACCAT CAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAATGCAGTGTGGCCAAA GGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACATGGAGGAGAAGCACA TGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCTACGCTATGGAGTAC AGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACGTCAACATCTTGTTA TTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAGGCTCACCCCCAGCT ACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCACATTTGACTTCAGA TGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGGGGGTGCAGCTTTT ATTTTCCCAAATACTTCAGTATATCCTGAAGCTACGCAAAGAATTACAACTAGGCCAGGTACGAAAACAC CCCTGTGTGATCTCTTCATTGAGAGACATCCCAGATGTCCTGCTGAGATCCGTGCCCTAAGTCACGTGAT ACAAAGAGAGCTGATCCCGGAGCTGAAGCCAGTCCCAGACAGTCTTATTCTGCCTCTGTTGATTTGGAGA CTAAATCCACTCAAACCATTTCATTCAAAGACCACACTAAAGGAATTAAGAGCAGATTAGCCCTTTAACT AGCTTTTCAGAAAGACAGATGGGCAAAGAAGGCATCCTGGATGCCTGGCAGTTAGGAATAGGCCGACTTT TGAACTAACAGAAGGATCTGTCCCTCCTCGGGGGAAGAGCACAAAACAAGGACACTCCCCAGATTCACAG TGACCGATTATCAGTATGTCACAAGAAGCCAGTCTTGCAGAGCAGAAGCATGCAACCAGTAGTATTTACATCTGAATCTTACTGCCTGTCCTCCAAATGATTTAATTAGGTAATAAATTTACATGCCATTCATGCAAAAA AAAAAA SEQ ID NO: 14 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 9, mRNA 1,715 bp linear transcribed-RNA Accession: NR_111949.2 GI: 1676453007 GTAGTTTTCACTTGGTCGGAATGGGGAGAGTGTGCAAGAGATCGCTGCGGGACAGGTTCCTAGAGATCGC TCCGGGACGGTCGTGACGGCCCCCGAGGGACATGAGAGAAGAGGAGCGGCGCTCAGGTTATTCCAGGATC TTTGGAGACCCGAGGAAAGCCGTGTTGACCAAAAGCAAGACAAATGACTCACAGAGAAAAAAGATGGCAG AACCAAGGGCAACTAAAGCCGTCAGGTTCTGAACAGCTGGTAGATGGGCTGGCTTACTGAAGGACATGAT TCAGACTGTCCCGGACCCAGCAGCTCATATCAAGTTAAACTCCATTGATGATGCACAGTTGACAAGAATT GCCCCTCCAAGATCTCATTGCTGTTTCTGGGAAGTAAACGCTCCTTAAAAGATTTACTTGTAATACTCAA ATCAACAAATGCCCGCATTCAGGCTCATCATACACGCTATACGATCAAATGAAGCAGCATATGGAATAGA GATCAACAGGGGAGGGGGAAGCTTTTGGAGGGAGGATCCAGTGATCTCATAAAGATCTTGTCTGAGCCTG TTAGTTCTGAGGTGTGTTTTGGACATTGAAAAACCTGAAAGTAATTAACCTTCCCAATCTAAACCGTATT TTCCACAAATAGGTTTGTTGGATACTAGTATTTTCACGTGTAATTAGAAAAGGAATTACTTTCCATTATT AACAAATAGATGTGACTTTGACTCATGTTCATTTTTTTTGGCCACAAATTCTCAGACTTTTGATCTTAAT GGTCAAGTGCAGGTAAGAGGAAATGAAACAAAATTAAGCAATGATTTGAATACATTTTCTCCCTTGTAGA AGACTAATTATAGTTTGGTCATTGAGTAATTTTCTCAGCTGCTTAGGATCTTTAATTAGGTTTGATATTC ACTATGAATGTGTGGCAGGGTTTCTTGGGAAAGTAGAGACGGGATAAAACATAAATGATTTATGTAACTG GATATGTCCCAGAGTGAATGAGACTTTGGTCTCAAGAACTGTTCCAGTGGTTTGTCGTTCTTTGATGAGC TCCGTAAGTGTTGCTCTTCTCAACAGAAGGTTGAATTTTAGGTGAACAGCCTTTCCTGATTGTGTAGATC TGGACCACAGTTTGAAGGTGCCCCTCCCTCTCCCTCTGATTGCCAGAGAACCCCTGCATTATCACAGCAA CCCAAGTCACCCCACGTATTCCCAAACACCCATCTGCTCAGGACAGAAGAGGCATTGCCTCTAGTTGAGA ACCAAGAAGTGGTCATTTCCTTAAAAGCTTTGTCTTGTCTTATTTTAATATTTAAATCAAATGACAGAAC TGTTTATCTATTTTTATCACTAAACTCCATAGTCCAATTTTCGTCTTCATACAAATTAACATGTTTTTAC AAAATCTCTAATCTTATGCACTGCTCACTGGCAACCTCTGTGGTGAACTAAACCGTAATGAATAATAGGC CAGAGAGCCAATGCAGCCTAGGTTGCCTAGAGGACAGAGAAACCCAGTGGCAATTTCTGCAGCTTTGCCA ACAGCCCTGAGTCACCTCGACCCTCCCCTGGCTCCTGGTCCAGTCTGATGAAACAGTTTACAAGATGTCT TCCAGGTTAGCTTTTCTTGTTAGTATCTGCTTTCAACTCAAAATGCACACACTCAATTAAATCTTCTACT TCTGTATGACAATGTTAATAGACTCTTGGAAAAAA SEQ ID NO: 15 - Homo sapiens ETS transcription factor ERG (ERG), transcript variant 10, mRNA 4,832 bp linear mRNA Accession: NM_001331025.2 GI: 1675073824 ATCCGCTCTAAACAACCTCATCAAAACTACTTTCTGGTCAGAGAGAAGCAATAATTATTATTAACATTTA TTAACGATCAATAAACTTGATCGCATTATGGCCAGCACTATTAAGGAAGCCTTATCAGTTGTGAGTGAGG ACCAGTCGTTGTTTGAGTGTGCCTACGGAACGCCACACCTGGCTAAGACAGAGATGACCGCGTCCTCCTC CAGCGACTATGGACAGACTTCCAAGATGAGCCCACGCGTCCCTCAGCAGGATTGGCTGTCTCAACCCCCA GCCAGGGTCACCATCAAAATGGAATGTAACCCTAGCCAGGTGAATGGCTCAAGGAACTCTCCTGATGAAT GCAGTGTGGCCAAAGGCGGGAAGATGGTGGGCAGCCCAGACACCGTTGGGATGAACTACGGCAGCTACAT GGAGGAGAAGCACATGCCACCCCCAAACATGACCACGAACGAGCGCAGAGTTATCGTGCCAGCAGATCCT ACGCTATGGAGTACAGACCATGTGCGGCAGTGGCTGGAGTGGGCGGTGAAAGAATATGGCCTTCCAGACG TCAACATCTTGTTATTCCAGAACATCGATGGGAAGGAACTGTGCAAGATGACCAAGGACGACTTCCAGAG GCTCACCCCCAGCTACAACGCCGACATCCTTCTCTCACATCTCCACTACCTCAGAGAGACTCCTCTTCCA CATTTGACTTCAGATGATGTTGATAAAGCCTTACAAAACTCTCCACGGTTAATGCATGCTAGAAACACAGATTTACCATATGAGCCCCCCAGGAGATCAGCCTGGACCGGTCACGGCCACCCCACGCCCCAGTCGAAAGC TGCTCAACCATCTCCTTCCACAGTGCCCAAAACTGAAGACCAGCGTCCTCAGTTAGATCCTTATCAGATT CTTGGACCAACAAGTAGCCGCCTTGCAAATCCAGGCAGTGGCCAGATCCAGCTTTGGCAGTTCCTCCTGG AGCTCCTGTCGGACAGCTCCAACTCCAGCTGCATCACCTGGGAAGGCACCAACGGGGAGTTCAAGATGAC GGATCCCGACGAGGTGGCCCGGCGCTGGGGAGAGCGGAAGAGCAAACCCAACATGAACTACGATAAGCTC AGCCGCGCCCTCCGTTACTACTATGACAAGAACATCATGACCAAGGTCCATGGGAAGCGCTACGCCTACA AGTTCGACTTCCACGGGATCGCCCAGGCCCTCCAGCCCCACCCCCCGGAGTCATCTCTGTACAAGTACCC CTCAGACCTCCCGTACATGGGCTCCTATCACGCCCACCCACAGAAGATGAACTTTGTGGCGCCCCACCCT CCAGCCCTCCCCGTGACATCTTCCAGTTTTTTTGCTGCCCCAAACCCATACTGGAATTCACCAACTGGGG GTATATACCCCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGGCACTTACTACTAAAGACC TGGCGGAGGCTTTTCCCATCAGCGTGCATTCACCAGCCCATCGCCACAAACTCTATCGGAGAACATGAAT CAAAAGTGCCTCAAGAGGAATGAAAAAAGCTTTACTGGGGCTGGGGAAGGAAGCCGGGGAAGAGATCCAA AGACTCTTGGGAGGGAGTTACTGAAGTCTTACTACAGAAATGAGGAGGATGCTAAAAATGTCACGAATAT GGACATATCATCTGTGGACTGACCTTGTAAAAGACAGTGTATGTAGAAGCATGAAGTCTTAAGGACAAAG TGCCAAAGAAAGTGGTCTTAAGAAATGTATAAACTTTAGAGTAGAGTTTGGAATCCCACTAATGCAAACT GGGATGAAACTAAAGCAATAGAAACAACACAGTTTTGACCTAACATACCGTTTATAATGCCATTTTAAGG AAAACTACCTGTATTTAAAAATAGAAACATATCAAAAACAAGAGAAAAGACACGAGAGAGACTGTGGCCC ATCAACAGACGTTGATATGCAACTGCATGGCATGTGCTGTTTTGGTTGAAATCAAATACATTCCGTTTGA TGGACAGCTGTCAGCTTTCTCAAACTGTGAAGATGACCCAAAGTTTCCAACTCCTTTACAGTATTACCGG GACTATGAACTAAAAGGTGGGACTGAGGATGTGTATAGAGTGAGCGTGTGATTGTAGACAGAGGGGTGAA GAAGGAGGAGGAAGAGGCAGAGAAGGAGGAGACCAGGGCTGGGAAAGAAACTTCTCAAGCAATGAAGACT GGACTCAGGACATTTGGGGACTGTGTACAATGAGTTATGGAGACTCGAGGGTTCATGCAGTCAGTGTTAT ACCAAACCCAGTGTTAGGAGAAAGGACACAGCGTAATGGAGAAAGGGGAAGTAGTAGAATTCAGAAACAA AAATGCGCATCTCTTTCTTTGTTTGTCAAATGAAAATTTTAACTGGAATTGTCTGATATTTAAGAGAAAC ATTCAGGACCTCATCATTATGTGGGGGCTTTGTTCTCCACAGGGTCAGGTAAGAGATGGCCTTCTTGGCT GCCACAATCAGAAATCACGCAGGCATTTTGGGTAGGCGGCCTCCAGTTTTCCTTTGAGTCGCGAACGCTG TGCGTTTGTCAGAATGAAGTATACAAGTCAATGTTTTTCCCCCTTTTTATATAATAATTATATAACTTAT GCATTTATACACTACGAGTTGATCTCGGCCAGCCAAAGACACACGACAAAAGAGACAATCGATATAATGT GGCCTTGAATTTTAACTCTGTATGCTTAATGTTTACAATATGAAGTTATTAGTTCTTAGAATGCAGAATG TATGTAATAAAATAAGCTTGGCCTAGCATGGCAAATCAGATTTATACAGGAGTCTGCATTTGCACTTTTT TTAGTGACTAAAGTTGCTTAATGAAAACATGTGCTGAATGTTGTGGATTTTGTGTTATAATTTACTTTGT CCAGGAACTTGTGCAAGGGAGAGCCAAGGAAATAGGATGTTTGGCACCCAAATGGCGTCAGCCTCTCCAG GTCCTTCTTGCCTCCCCTCCTGTCTTTTATTTCTAGCCCCTTTTGGAACAGAAGGACCCCGGGTTTCACA TTGGAGCCTCCATATTTATGCCTGGAATGGAAAGAGGCCTATGAAGCTGGGGTTGTCATTGAGAAATTCT AGTTCAGCACCTGGTCACAAATCACCCTTAATTCCTGCTATGATTAAAATACATTTGTTGAACAGTGAAC AAGCTACCACTCGTAAGGCAAACTGTATTATTACTGGCAAATAAAGCGTCATGGATAGCTGCAATTTCTC ACTTTACAGAAACAAGGGATAACGTCTAGATTTGCTGCGGGGTTTCTCTTTCAGGAGCTCTCACTAGGTA GACAGCTTTAGTCCTGCTACATCAGAGTTACCTGGGCACTGTGGCTTGGGATTCACTAGCCCTGAGCCTG ATGTTGCTGGCTATCCCTTGAAGACAATGTTTATTTCCATAATCTAGAGTCAGTTTCCCTGGGCATCTTT TCTTTGAATCACAAATGCTGCCAACCTTGGTCCAGGTGAAGGCAACTCAAAAGGTGAAAATACAAGGTGA CCGTGCGAAGGCGCTAGCCGAAACATCTTAGCTGAATAGGTTTCTGAACTGGCCCTTTTCATAGCTGTTT CAGGGCCTGTTTTTTTCACGTTGCAGTCCTTTTGCTATGATTATGTGAAGTTGCCAAACCTCTGTGCTGT GGATGTTTTGGCAGTGGGCTTTGAAGTCGGCAGGACACGATTACCAATGCTCCTGACACCCCGTGTCATT TGGATTAGACGGAGCCCAACCATCCATCATTTTGCAGCAGCCTGGGAAGGCCCACAAAGTGCCCGTATCT CCTTAGGGAAAATAAATAAATACAATCATGAAAGCTGGCAGTTAGGCTGACCCAAACTGTGCTAATGGAA AAGATCAGTCATTTTTATTTTGGAATGCAAAGTCAAGACACACCTACATTCTTCATAGAAATACACATTT ACTTGGATAATCACTCAGTTCTCTCTTCAAGACTGTCTCATGAGCAAGATCATAAAAACAAGACATGATTATCATATTCAATTTTAACAGATGTTTTCCATTAGATCCCTCAACCCTCCACCCCCAGTCCAGGTTATTAG CAAGTCTTATGAGCAACTGGGATAATTTTGGATAACATGATAATACTGAGTTCCTTCAAATACATAATTC TTAAATTGTTTCAAAATGGCATTAACTCTCTGTTACTGTTGTAATCTAATTCCAAAGCCCCCTCCAGGTC ATATTCATAATTGCATGAACCTTTTCTCTCTGTTTGTCCCTGTCTCTTGGCTTGCCCTGATGTATACTCA GACTCCTGTACAATCTTACTCCTGCTGGCAAGAGATTTGTCTTCTTTTCTTGTCTTCAATTGGCTTTCGG GCCTTGTATGTGGTAAAATCACCAAATCACAGTCAAGACTGTGTTTTTGTTCCTAGTTTGATGCCCTTAT GTCCCGGAGGGGTTCACAAAGTGCTTTGTCAGGACTGCTGCAGTTAGAAGGCTCACTGCTTCTCCTAAGC CTTCTGCACAGATGTGGCACCTGCAACCCAGGAGCAGGAGCCGGAGGAGCTGCCCTCTGACAGCAGGTGC AGCAGAGATGGCTACAGCTCAGGAGCTGGGAAGGTGATGGGGCACAGGGAAAGCACAGATGTTCTGCAGC GCCCCAAAGTGACCCATTGCCTGGAGAAAGAGAAGAAAATATTTTTTAAAAAGCTAGTTTATTTAGCTTC TCATTAATTCATTCAAATAAAGTCGTGAGGTGACTAATTAGAGAATAAAAATTACTTTGGACTACTCAAA AA

Claims

WHAT IS CLAIMED IS:

1. A method of activation and expansion of adult non-activated hematopoietic stem and progenitor cells (HSPCs), comprising elevating the expression of the transcription factor Friend of Leukemia Integration-1 (FLI-1) transiently in adult non-activated HSPCs to obtain an expanded pool of activated HSPCs, wherein the transient expression of FLI-1 is achieved by introducing a FLI-1 modified-mRNA into the adult non-activated HSPCs.

2. The method of claim 1, wherein the FLI-1 modified-mRNA has an open reading frame as set forth in SEQ ID NO:

1.

3. The method of any of claims 1-2, wherein the hematopoietic stem and progenitor cells (HSPCs) are human HSPCs.

4. The method of 3, wherein the human HSPCs are adult human bone marrow-derived mobilized peripheral blood (mPB) hematopoietic stem progenitor cells (HSPCs).

5. The method of any of claims 1-4, wherein said elevating the expression of FLI-1 transiently activates adult non-activated human HSPCs without the risk of leukemic transformation.

6. The method of any of claims 1-5, further comprising after said elevating the expression of FLI-1transiently in adult non-activated human HSPCs, coculturing the HSPCs with a regenerative vascular niche platform to expand the HSPCs, or with any other culture conditions allowing human HSPC expansion.

7. The method of claim 6, wherein the fold of expansion of the FLI-1 activated HSPCs is enhanced by at least 2 fold, at least 3 fold, at least 4 fold, at least 5 fold, or at least 10 fold as compared to the non-activated HSPCs without elevating the expression of FLI-1 transiently.

8. The method of any one of claims 1-7, wherein the adult non-activated human HSPCs are obtained from a donor suffering from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), a co-morbidity including diabetes, from a poorly mobilizing donor, or for gene therapy purposes that requires introduction of a correct gene to replace a mutated one in blood related disorders.

9. The method of claim 8, wherein the blood related disorder comprises thalassemia or immunodeficiencies.

10. A population of regenerated and expanded adult hematopoietic stem and progenitor cells (HSPCs) generated by a method according to any one of claims 1-9.

11. The population of regenerated and expanded adult HSPCs of claim 10, wherein the HSPCs are capable of engraftment and full reconstitution in a recipient.

12. The population of regenerated and expanded adult HSPCs of claim 11, wherein the HSPCs are capable of reconstitution in the peripheral blood, the spleen and the bone marrow of the recipient. 13 The population of regenerated and expanded adult HSPCs of any one of claims 10-12, wherein the capability of reconstitution of the HSPCs is enhanced by at least 5-7 fold, as compared to the adult non-activated HSPCs without elevating the expression of FLI-1 transiently.

14. A method of treating a subject in need of activated and expanded adult HSPCs, comprising obtaining hematopoietic stem cells (HSPCs) from the subject or a compatible donor, elevating the expression of Friend of Leukemia Integration-1 (FLI-1) transiently in the obtained HSPCs to obtain regenerated and expanded pool of HSPCs, and administering the regenerated and expanded HSPCs to the subject.

15. The method of claim 14, wherein the subject is in a need for an expanded pool of HSPCs or suffers from an exhausted chemotherapy and / or irradiated stressed bone marrow (BM), or a co-morbidity including diabetes, β-thalassemia, or sickle cell disease that requires an expanded pool of genetically modified HSPCs for transplant.