Quantitative trait gene Slit2 positively regulates murine hematopoietic stem cell numbers

Hematopoietic stem cells (HSC) demonstrate natural variation in number and function. The genetic factors responsible for the variations (or quantitative traits) are largely unknown. We previously identified a gene whose differential expression underlies the natural variation of HSC numbers in C57BL/6 (B6) and DBA/2 (D2) mice. We now report the finding of another gene, Slit2, on chromosome 5 that also accounts for variation in HSC number. In reciprocal chromosome 5 congenic mice, introgressed D2 alleles increased HSC numbers, whereas B6 alleles had the opposite effect. Using gene array and quantitative polymerase chain reaction, we identified Slit2 as a quantitative trait gene whose expression was positively correlated with the number of HSCs. Ectopic expression of Slit2 not only increased the number of the long-term colony forming HSCs, but also enhanced their repopulation capacity upon transplantation. Therefore, Slit2 is a novel quantitative trait gene and a positive regulator of the number and function of murine HSCs. This finding suggests that Slit2 may be a potential therapeutic target for the effective in vitro and in vivo expansion of HSCs without compromising normal hematopoiesis.

Scientific RepoRts | 6:31412 | DOI: 10.1038/srep31412 Lxn expression is negatively correlated with the natural variation of HSC numbers: high Lxn level is associated with low HSC numbers in B6 mouse, whereas low Lxn expression is linked to high stem cell numbers in D2 mice. Lxn regulates the HSC population via a concerted mechanism of increasing stem cell self-renewal proliferation and decreasing apoptosis 20 . In an extension of this phenotypic genomic approach, several studies employed a panel of genes differentially expressed between B6 and D2 cells as a trait to map QTL that modulate gene expression (i.e., expression QTL, or eQTL) 21 . Distinct groups of eQTL, acting as either cis-or trans-controlling elements, were identified to define gene expression profiles that are specific to a single cell type and its functions, or to cellular differentiation state in a group of developmentally related cells [22][23][24] .
In this study, we employed the classic phenotypic genomic approach, and we report the finding of an additional, novel QTG, Slit2, which also modifies HSC number variation in B6 and D2 strains via a unique mechanism unlike that of Lxn. Slit2 expression is positively correlated with HSC numbers and is affected by the genetic background. Increased expression of Slit2 led to a three-fold in vitro and in vivo expansion of the HSC compartment and conferred a competitive advantage to HSCs upon transplantation. These findings may prove to be of clinical value in strategies for the effective expansion of HSCs in bone marrow transplantation for treatment of hematologic malignancies.

Results
Generation of chromosome 5 congenic strains. We previously identified three QTLs that contribute to natural variation in HSC number between B6 and D2 mice. We produced congenic mouse strains for each QTL, and successfully discovered a QTG (Lxn) on chromosome 3 (Chr3) and confirmed its function in HSC regulation 13,20 . In the current study, we focus on a QTL on chromosome 5 (Chr5; Fig. 1A) and aim to unravel novel HSC regulatory mechanisms. Mouse strains congenic for the Chr5 QTL were generated by crossing the genomic interval harboring the QTL using B6 as the donor strain and D2 as the recipient strain (symbolized as D.B Chr5), and vice versa (B.D Chr5). The two reciprocal congenic strains were derived and genotyped as described previously 25 . Both congenic lines were homozygous within their respective congenic intervals. The congenic interval in Chr5 that is mutually inclusive in reciprocal strains spans from 20.8 Megabases (Mb) (9.8 centiMorgan (cM ± 1cM)) to 53 Mb (28.5cM ± 1cM), and the location of the marker (D5Mit352) most tightly linked to the trait is in 35.9 Mb (18.4cM ± 1cM) (Fig. 1B).
Confirmation of the functional effect of Chr5 QTL in congenic strains. To validate QTL linkage analysis, we performed a long-term in vitro culture assay, the cobblestone area-forming cell (CAFC) assay, on bone Linkage analysis identified Chr5 QTL as a highly associated genomic locus for HSC number variation in B6 and D2 mouse strains. Limit of detection score shows the microsatellite marker (D5Mit352) with highest association. The 95% confidence interval locates between 29-55 Mb. (B) Schematic illustration of genomic map of reciprocal Chr5 congenic intervals. B6-derived genomic interval harboring Chr5 QTL (black bar) was introgressed onto the D2 background (shaded bar) in congenic D.B Chr5 mice, and vice versa. The consensus congenic interval (striped bar) extends from 20.8 Mb (9.8cM ± 1cM) to 53 Mb (28.5cM ± 1cM), and includes the marker (D5Mit352) at 35.9 Mb (18.4cM ± 1cM) with the highest linkage to the trait. The non-consensus congenic interval in D.B Chr5 mice is the chromosomal region derived from B6 mice but not overlapped with B.D Chr5 line, which extends from 53 Mb to 65 Mb. The total length of Chr5 (~152 Mb) is indicated on the top.
Scientific RepoRts | 6:31412 | DOI: 10.1038/srep31412 marrow cells derived from Chr5 congenic mice and determined cobblestone areas at day 35 of culture, which is a proxy for the number of long-term HSCs that were present in the seeded bone marrow cells. Introgression of D2 alleles onto a B6 genetic background in the B.D Chr5 congenic line led to a three-fold increase in HSC number as compared to B6 background ( Fig. 2A), whereas transfer of B6 alleles onto the D2 genetic background decreased HSC number by 50% in the D.B Chr5 strain. Moreover, cell counts for peripheral blood leukocytes, erythrocytes and platelets, and numbers for CAFC days 7 and 21, which represent hematopoietic progenitor cells at different stages, showed no difference between Chr5 congenic and their respective parental strains, except for CAFC day 21 between D2 and D.B Chr5 mice (Suppl. Table 1), suggesting that the non-consensus congenic region in D.B Chr5 (53 -65 Mb, see Fig. 1B) mouse may affect hematopoietic progenitor cell (HPC) number. To further confirm the CAFC result, we quantified the immunophenotypic HSCs, which are defined as cells negative to lineage markers (Lin-), positive for Sca-1 and c-kit (Sca-1+ and c-Kit+ ), and negative for CD34 (CD34-) (Fig. 2B). Consistently, the result showed that B.D Chr5 mice had more HSC/HPC-enriched Lin-Sca-1 + c-Kit+ (LSK) cells (Fig. 2C) and HSC-enriched LSKCD34-cells (Fig. 2D) than B6 mice, whereas reciprocal D.B Chr5 mice had fewer cells in these two populations compared to D2 mice. Altogether, these results suggest that Chr5 QTL specifically regulates the size of the HSC population, and that the D2 allele is associated with an increased stem cell number whereas the B6 allele is associated with decreased stem cell number.

Chr5 QTL enhances HSC repopulation capacity in a cell-intrinsic manner. To determine whether
Chr5 QTL can intrinsically regulate HSC number and function, we performed the competitive repopulation assay, in which B6 or B.D Chr5 bone marrow cells were transplanted into the same recipients (or environment) and repopulated their blood system (Fig. 3A). B.D Chr5-derived cells made a greater contribution to reconstitution of peripheral blood leukocytes, especially T lymphocytes, total bone marrow cells, and HSC/HPC-enriched LSK cells (Fig. 3B-D), suggesting that D2 QTL enhances HSC repopulation capacity. Moreover, The increased level of LSK cells in B.D Chr5 cells reconstituted recipients was similar to that in B.D Chr5 congenic mice (Fig. 2C), indicating the cell-intrinsic role of this congenic interval. It should be noted that the recipient mice carrying CD45.1 markers are not commercially available on D2 genetic background, which precluded us from performing competitive repopulation assay on D2 and D.B Chr5 bone marrow cells. We further determined the cell cycle and apoptotic status of congenic and background HSCs because both cellular mechanisms contribute to maintenance of the HSC pool. No differences in percentages of cycling and apoptotic cells were detected in congenic strains compared to their respective background strains (B.DChr5 vs B6, and D.BChr5 vs D2) (Supp. Fig. 1A,B). However, a significantly higher percentage of LSKCD34-HSCs underwent apoptosis in mice with B6 background than those with D2 background (Supp. Fig. 1B), suggesting the effect of genetic background on the function of HSCs. Altogether, these results imply that Chr5 QTL and underlying QTGs are involved in the regulation of repopulation and multi-lineage differentiation of HSCs in a cell-intrinsic manner.
Identification of candidate QTGs by microarray and quantitative polymerase chain reaction (PCR). In order to investigate QTG underlying Chr5 QTL, we obtained gene expression profiles on HPC/ HSC-enriched LSK cells of B6, B.DChr5, D2, and D.BChr5 strains using the Illumina microarray platform. We revealed 1,791 differentially expressed genes between B6 and B.DChr5 HSCs and 470 differentially expressed genes between D2 and D.BChr5 cells (GEO Accession # GSE21896), in which 153 genes overlapped between the two comparison groups (Fig. 4A). We screened these genes on the basis of genomic location within the 95% confidence interval (20.8-53 Mb) surrounding the Chr5 QTL and identified three candidate genes: Slit2, QDPR and Gpr125. Quantitative real-time PCR confirmed that only Slit2 showed reproducible patterns of differential expression in LSK cells in both congenic-parental strain comparisons (Fig. 4B). The presence of D2 alleles in the congenic interval resulted in a high level of Slit2 expression relative to almost undetectable levels in mice bearing the B6 genotype. A roughly 30-fold increase in Slit2 expression was observed in B.D Chr5 LSK cells relative to B6 and a similar fold decrease in D.BChr5 LSK cells relative to D2. These data suggest that Slit2 expression is positively correlated with HSC numbers, and its expression pattern in HSCs is dramatically affected by genetic background. eQTL is associated with the differential expression of Slit2 between B6 and D2 mice. Differential expression of Slit2 between both congenic and parental strains suggests that Slit2 expression is governed by a polymorphic regulatory region within the congenic interval. Consistent with this observation, 3 consecutive, highly significant eQTL were identified for the Slit2 transcript in HSCs using the "genetical genomics" approach (http://genenetwork.org/webqtl/main.py). The peak eQTL (Likelihood Ratio Statistic = 37.952) corresponds to 13 consecutive markers spanning 45.6-53.1 Mb on Chr5 (Fig. 4C), and encompasses the entire Slit2 transcript (48.376032-48.696750 Mb). In addition, the overlapping green line in the eQTL peak suggests that the D2 allele is associated with high Slit2 expression, which corroborates our microarray and real-time PCR results. Our discovery of Slit2 differential expression in B6 and D2 LSK cells and the search for responsible eQTL are consistent with results by Gerrits et al., which also identified distinct specificity of Slit2 eQTL in a stem cell population 23 . These results suggest that the Slit2 gene is cis-regulated and the single nucleotide polymorphisms flanking the Slit2 gene most likely contribute to its differential expression in B6 and D2 HSCs.
Ectopic Slit2 expression results in expansion of functional HSCs. Having established a positive correlation between Slit2 expression and HSC numbers under physiologic conditions, we enforced Slit2 expression in HSC/HPCs and determined its direct regulatory role in HSC number and function. Using the same overexpression strategy as previously published 20 , we cloned the Slit2 cDNA into a retroviral vector containing the green fluorescent protein (GFP) reporter, and overexpressed Slit2 in HSC/HPCs from B6 mice, which normally express little or no Slit2. HSC number was measured by CAFC assay on GFP positive bone marrow cells (GFP control or Slit2-GFP) (Fig. 5A). The increased expression of Slit2 at mRNA and protein levels was confirmed Data are shown as the average (± SD) of two independent experiments (n ≥ 9). P-values were calculated using the student's T-test with statistic significance cutoff p < 0.05. * represents p < 0.05. by real-time PCR and Western blot, respectively, in Slit2-GFP cells compared to control GFP cells (Fig. 5B,C). Overexpression of Slit2 resulted in a 3-fold increase in the number of HSCs (CAFC day 35) (Fig. 5D), strongly suggesting Slit2 as a positive regulator of HSC number. In order to determine in vivo function of Slit2 in hematopoiesis, we transplanted 2 × 10 5 Slit2-GFP or control GFP cells along with the same number of competitor cells (a standard approach in murine bone marrow transplantation studies to ensure recipient survival) into lethally irradiated recipient mice and measured reconstitution of GFP+ cell in peripheral blood at different time-points post-transplant. Slit2-overexpressing cells (Slit2-GFP) made a greater contribution to blood reconstitution at both short-term (4 weeks and 8 weeks) and long-term (16 weeks) post-transplant (Fig. 5E), demonstrating that Slit2 can increase the repopulating capacity of HSCs. This result is consistent with that seen in B.D Chr5 congenic HSCs, which have naturally high levels of Slit2 expression (Fig. 3B). To further confirm the positive regulatory role of Slit2 in HSC numbers, we performed a more stringent assay (i.e., long-term limiting-dilution analysis in competitively repopulated hosts) to functionally identify and quantify HSCs in vivo. We found that overexpression of Slit2 caused a 3-fold increase in the number of long-term repopulating HSCs (Fig. 5F). Thus these results robustly suggest Slit2 as a positive regulator of HSC number and function.

Discussion
In this study, we identified a new quantitative trait gene, Slit2, as the positive regulator of HSC number and function. We used the QTL mapping method, which is a powerful approach for discovering genetic determinants of complex traits 8 . We began with the observation of natural HSC number variation between two genetically distinct In the two Illumina microarray data sets, 153 differentially expressed transcripts were common between the two comparisons. Three transcripts were located within the 95% confidence interval for the Chr5 QTL. (B) Slit2 mRNA expression in HSCs. Identical number of LSK cells were sorted from each strain and Slit2 mRNA level in these cells was quantified by real-time PCR (normalized to endogenous control GAPDH expression). Slit2 is expressed at significantly higher levels in the LSK population of mice bearing D2 alleles at the Chr5 QTL position (* * * p < 0.001). Results are the average (± 1 SD) of 8-12 measurements derived from two to three independent biological samples. Statistical significance of strainspecific expression differences was determined using the 2-tailed T-test. (C) Slit2 expression is cis-regulated. Linkage analysis was performed on GeneNetwork to search for the eQTL that influences Slit2 expression. It revealed a highly significant eQTL (LRS = 38 on Chr5; blue line). The entire mouse genome is labeled across the x-axis (Mb). The LRS score is indicated on the y-axis. The positive additive coefficient (solid green line) indicates that D2 alleles increase trait values. mouse strains (Fig. 6): the B6 strain has lower stem cell numbers and the D2 strain has higher numbers. Genetic mapping analysis identified a locus on chromosome 5 that is associated with this natural variation. We then generated reciprocal congenic mouse strains in which the genomic locus harboring the QTL was exchanged between the B6 and D2 strains. Quantification of HSC number in these congenic strains confirms that the chromosome 5 QTL and the candidate gene(s) must not only be located within the congenic interval but, if functioning at the level of the transcript, the regulatory element governing expression must also be present in the congenic interval. The congenic mice were also particularly valuable in microarray analyses to identify candidate genes. Among the 2,261 unique differentially expressed transcripts identified in the Illumina microarray experiment, only 153 were common between the two congenic/background strain comparisons, representing a 94% reduction in the number of genes differentially expressed between the B6 and D2 parental strains alone. This reduction greatly facilitated our selection of Slit2 as a candidate gene because it is the only differentially expressed gene that is present in the consensus congenic interval. Therefore, given the novel role for Slit2 in the hematopoietic system, we benefited greatly from the ability of the QTL mapping approach to eliminate bias introduced by selecting genes on the basis of a priori knowledge about function. Elimination of Slit2 in knock-out mice results in embryonic lethality 26 . Unlike mutagenesis techniques, lethality or nonspecific effects are not hampered by QTL-based gene discovery, thus preventing detection of a phenotypic effect on adult tissue.
The mechanisms by which Slit2 regulate hematopoiesis have not been identified. However, several recent publications have reported the function of its binding partner, Robo4, in HSC regulation 27,28 . Smith-Berdan and colleagues unraveled the important role of Robo4 in anchoring HSCs to bone marrow niche. Loss of Robo4 specifically decreased the number of HSC in bone marrow and impaired bone marrow engraftment capability. Interestingly, absence of Robo4 was compensated with up-regulation of CXCR4, which led to less efficient mobilization of HSCs from bone marrow to the periphery. The authors also investigated the role of Slit2 in Robo4 function and found that Slit2 didn't affect HSC proliferation and migration in vitro. The study by Shibata et al. showed that Slit2 was specifically expressed in bone marrow stromal cells of the B6 strain, but not HSCs, and overexpression of Slit2 led to the differentiation of primitive HSCs to less-primitive marrow cells. In addition to HSCs, Figure 6. Forward genetic approach leads to the discovery of Slit2 as a quantitative trait gene. Forward genetic approach begins with strain-specific quantitative trait. Linkage analysis identifies quantitative trait loci (QTL) that are responsible for the trait. Generation of congenic mouse strains in which the QTL are exchanged between parental strain will facilitate the confirmation of QTL and their functional effect. Gene expression profiles will identify the underlying quantitative train genes (QTGs). The regulatory role of QTGs in quantitative trait needs to be further confirmed by gain or loss of gene function. By following this pathway, our study identified Chr5 and underlying Slit2 as QTG that accounts for the natural variation in HSC number between C57BL/6 (B6) and DBA2 (D2) mouse strains. Slit2 expression level positively correlates with HSC number. Slit2 level is lower in B6 mice that have less HSC number whereas its level is higher in D2 mice that have more HSCs. Ectopic expression of Slit2 leads to the increased HSC number and function in B6 mice, further confirming Slit2 as a positive regulator of HSCs.
Scientific RepoRts | 6:31412 | DOI: 10.1038/srep31412 a recent study has shown that Slit2 transgenic mice have increased intestinal stem cell numbers 29 . Our findings are in agreement, at least partly, with these literature reports. We found that Slit2 and the Slit2-containing Chr5 QTL do not influence HSC proliferation and apoptosis (Supp. Fig. 1). Like intestinal stem cells, overexpression of Slit2 led to the increased number of functional clonogenic and repopulating HSCs (Fig. 5). More importantly, our study demonstrates for the first time the strain-specific difference in Slit2 expression in physiological conditions. Indeed, the function of Slit2 in HSCs seems to be overlooked due to the fact that very little or no detectable Slit2 transcript was present in HSCs of the B6 mouse strain compared to the D2 strain (Fig. 4B). This observation not only explains the reason that Slit2 was not detected in HSCs in Shibata's study, but also reveals the importance of genetic background in modification of critical stem cell regulatory genes. It would be intriguing to employ the D2 mouse strain as a model to investigate Slit2 function in the regulation of HSCs and stromal cells in future studies.
The role of Slit2 as a secreted protein in governing cellular migration, spatial orientation, organogenesis and development in other tissues is well known [30][31][32][33][34] . Here, we provide strong evidence to support the cell-intrinsic role of Slit2 in increasing HSC numbers. In competitive repopulation assays in which B6 or B.D Chr5 cells were injected into the same environment (recipients), B.D Chr5 showed an advantage in repopulating blood and bone marrow stem/progenitor cells (Fig. 3). Moreover, Slit2 overexpressing cells showed a similar increase in their repopulating capacity and in the absolute number of repopulating cells upon transplantation (Fig. 5E,F). Such changes are similar to what we observed in the B.D Chr5 congenic mice in situ, strongly supporting that Slit2 plays an intrinsic role in regulating HSC function. However, because Slit2 is also highly expressed in the bone marrow niche cells, such as osteoblast and mesenchymal stem cells 35 , we cannot exclude the possibility that Slit2 regulates HSC numbers by influencing stem cell-niche interaction. It is possible that high Slit2 expression may result in preferential localization in niches that favor stem cell self-renewal, and low Slit2 expression results in occupation of niches that favor differentiation [36][37][38] . In addition, compensatory alterations in other signaling pathways, such as CXCR4, may account for important differences in HSC number and functions between B6 and D2 mice. Further experiments, such as reciprocal transplantation with B6 or B.D Chr5 mice as recipients, will be interesting to determine the cell-intrinsic and/or cell-extrinsic role of Slit2 in regulating HSC function.
Our previous studies identified Lxn on the Chr3 QTL as a negative regulator of HSC number, and Chr3 and Chr5 QTLs as contributing loci for the natural variation of HSC number in B6 and D2 mouse strains 20 . In combination with discovery of Slit2 as a positive regulator herein, it will be of great interest to investigate synergetic and/or additive roles of these genes in homeostatic maintenance of the HSC population size. It may unravel a novel signaling pathway for HSC regulation. Although no evidence functionally links Lxn and Slit2, a recent study showed that Lxn is co-localized with Robo4 in hematopoietic stem/progenitor cells, and its ablation reduces the abundance of Robo4 protein 39 . We speculate that loss of Lxn expands the HSC population and HSCs reflexively down-regulate Robo4 expression and decease HSC numbers. Thus, Lxn and Slit2/Robo4 signaling pathways may counteract each other and cooperatively control HSC population size in normal physiological conditions. We are currently investigating this hypothesis. If it can be experimentally supported, it highly underscores the importance and power of the QTL approach in uncovering a genetic regulatory network in stem cell function. Uncovering the genetic networks that govern natural variation in complex traits such as stem cell numbers make it possible to identify a specific group of regulatory genes as well as their cooperative roles in determining stem cell functions. It would be difficult to appreciate the complexity of such networks, governing a homeostatic mechanism like the maintenance of hematopoiesis, without the QTL to QTG strategy.
In summary, we report compelling evidence for the identification of Slit2 as a QTG on mouse Chr5 that influences HSC numbers in mice. Gene expression analysis of primary hematopoietic cells, overexpression, and functional studies reveal a novel role for Slit2 as a positive regulator of HSC numbers. It is likely that polymorphisms between B6 and D2 in the Slit2 or a nearby cis regulatory element are responsible for strain-dependent differential expression. These findings may lead to effective strategies for in vitro and in vivo expansion of the HSC population, enhancement of HSC mobilization and engraftment, and improved strategies for HSC transplantation therapy.

Methods
Animals. Six to 16 week old female C57BL/6J(CD45.2), B6.SJL/J(CD45.1) and DBA/2J mice were purchased from The Jackson Laboratory (Bar Harbor, ME) and congenic mice generated by our laboratory were used in all experiments. Mice were given food and acidified water ad libitum and housed in pathogen free conditions in the animal facility of the University of Kentucky and were maintained according to NIH guidelines for animal welfare. All animal and experimental procedures were approved by IACUC and IBC offices of the University of Kentucky with protocol numbers 2012-0999 (IACUC) and B13-2133 (IBC).
Generation of Chr5 congenic strains. Congenic strains were generated by selective, marker-assisted breeding as previously described 25 . The genomic interval carrying the QTL from B6 was transferred onto a D2 genetic background to generate the D.B Chr5 congenic strain. The reciprocal congenic, designated B.DChr5 was generated by transfer of the D2 QTL region onto the B6 background. Both strains were bred to homozygosity at all loci, as verified by genotype analysis with 100 microsatellite markers distributed across the mouse genome. The consensus congenic interval ranges from 20.8-53 mega bases on Chr5, encompassing the entire 95% confidence interval identified by linkage analysis.
Peripheral blood cell counts. Anesthetized mice were bled from the retro-orbital venous plexus.
Circulating leukocyte, erythrocyte and platelet counts were measured by analysis of 40 ul blood using a System 9118 + Hematology Series Cell Counter (Biochem Immunosystems, Allentown, PA). Cobblestone area-forming cell assay. CAFC assay was performed as previously described to quantify hematopoietic stem and progenitor cells 20 . We performed simultaneous analysis of CAFCs in B6, D2, and congenic strains as well as in Slit2-GFP vs GFP control cells. In brief, a confluent monolayer of FBMD-1 stromal cells was established in 96-well tissue culture-treated plates (Costar, Cambridge, MA). After 7 to 10 days, wells were seeded either with unfractionated marrow or GFP+ cells at a dose of 81,000, 27,000, 9,000, 3,000, 1,000, or 333 cells per well. Twenty replicate wells per cell number were evaluated. The cells were cultured in Iscove's Modified Dulbecco Medium, containing 20% horse serum, 80 U/mL penicillin, 80 mg/mL streptomycin (all from Life Technologies), 10 −4 ß-mecaptoethanol, and 10 −5 M hydrocortisone (both from Sigma, St. Louis, MO). Individual wells were screened at days 7, 14, 21, 28 and 35 for the presence of a cobblestone area, defined as a colony of at least 5 small, non-refractile cells growing underneath the stroma. The longer the latency before cobblestones appear, the more primitive the cells forming that cobblestone. Thus, the most primitive HSCs show cobblestones at day 35, whereas colonies that appear earlier are derived from more committed progenitor cells. Frequencies of CAFCs were calculated by using maximum likelihood analysis and equals 1 divided by the number of cells yielding 37% negative wells. Statistical comparisons were performed using the L-Calc software package from Stem Cell Technologies (Vancouver, Canada). Statistically significant difference between populations being compared was determined using a p-value threshold of 0.05.
Cell cycling and apoptosis. Bone marrow cells suspended in HBSS (Gibco, Grand Island, NY) containing 2% FCS (Life Technologies) were blocked with anti-CD16/32 (clone 2.4G2, Fc Block) to prevent non-specific binding. Cells were labeled as described in the immunofluorescence staining section. Cells were fixed and permeabilized in BD Cytoperm/CytoFix buffer (BD Bioscience). Subsequent co-labeling with Ki-67 and DAPI enabled the determination of cell cycle stage and DNA content. Cells negative for Ki-67 and DAPI are in G0 phase, cells positive for Ki-67 but negative to DAPI are in G1 phase, and cells positive for both markers are in S/ G2/M phases of cell cycle. Apoptotic cells were stained with Annexin V and 7-AAD as previously described 20 . Briefly, bone marrow cells were prepared and immunofluorescently stained as described above. Fluorescein isothiocyanate-conjugated Annexin V and 7-AAD were used to identify apoptotic cells, which are Annexin V positive and 7-AAD negative. Thymocytes were used as the control to distinguish Annexin V-positive and -negative cells (Pharmingen, San Diego, CA). Three independent experiments were performed in each strain, and at least 3 mice were analyzed in each experiment. All experiments were carried out on ice and completed within 1.5 hours. Flow cytometric analysis was performed on a triple-laser FACSAriaII (Becton Dickinson Immunocytometry Systems, San Jose, CA). All antibodies used in this assay were purchased from BD Pharmingen (NJ).
Competitive repopulation assay. 1  Illumina Sentrix-Mouse 6 Whole Genome Expression Beadchip. Signal intensities corresponding to each probeset were evaluated for similarity in mean expression values. Mean and variance of normalized expression values were similar for the two chips (12 individual microarrays) with the exception of a single microarray used to analyze one of the D2 samples. This sample was excluded from further analysis. The signal intensities were then normalized using the Rank Invariant normalization method, which is recommended for evaluating gene expression across similar chips. Differences in gene expression were identified using the Illumina Custom differential expression algorithm, which accounts for: 1) sequence specific biological variation; 2) nonspecific biological variation; and 3) technical error. The data were filtered by removing probesets that were absent across all chips and considered differentially expressed if the Illumina Custom differential expression algorithm generated a mean p-value of less that 0.05 (Illumina diffscore ≤ 13 or > 13).
Quantitative real-time PCR. Identical numbers 200,000 of cells from each of the four strains, as well as Slit2-GFP and GFP control cells, were sorted via flow cytometry. Total RNA from these cells was extracted and reverse transcribed into cDNA using Taqman Reverse Transcription Reagents (Applied Biosystems, Foster City, CA) and stored at −20 °C. Real-time PCR reactions were performed in TaqMan Universal PCR MasterMix with pre-made primer and probe mixes for mouse genes Slit2, QDPR, GPR125, Robo4, and endogenous GAPDH control (Applied Biosystems, CA) according to manufacturer's instructions. PCR reactions were set up according to manufacturer's instructions using TaqMan ® universal PCR master mix (PN 4304437). Analyses of gene expression were performed in single reporter assays in an ABI PRISM 7700 sequence detection system (PE Biosystems, Foster City, CA).
Western blots. Cell samples were lysed at a concentration of 2 × 10 7 cells/ml in protein lysis buffer containing: 10 mM Tris pH7.5, 50 mM NaCl, 30 mM sodium pyrophosphate, 50 mM NaF, 5 μ M ZnCl2 and 1% Triton X-100, 2.8 ug/ml aprotinin (Sigma), 1 mM phenylmethylsulfonyl fluoride (Sigma), 1 mM sodium vanadate (Na3VO4) 1 ug/ml pepstatin, and 1 μ g/ml leupeptin (Oncogene Research, MA). Lysate was incubated on ice for 30 min, and then centrifuged at 15,000 × g for 10 min to remove debris. The resulting supernatant was then aliquoted and stored at −80 °C. For Western blot, protein lysates were thawed and mixed with running buffer and a reducing agent (Novex, San Diego, CA, per manufacturer's instructions) and heated at 95 °C for 5 min. Samples were then analyzed by denaturing PAGE (Novex, 10% bis-Tris gel) using the equivalent of 4 × 10 5 cells per lane. Following electrophoresis, samples were electro-transferred onto immunobilon-P membranes (Millipore, Bedford, MA), which were subsequently blocked and probed with polyclonal rabbit anti-Slit2 Ig-G antibody at a 1:3000 dilution. Primary antibodies were detected using alkaline phosphatase-conjugated secondary antibodies (Santa Cruz Biotechnology) and electro-chemifluorescent reagent (Pharmacia Biotech) according to the manufacturer's instructions. Blots were visualized using a Molecular Dynamics STORM 860 system and Imagequant software. Following the detection and quantification of anti-Slit2 antibody, immunobilon-P membrane was sequentially stripped in 40% methanol and the buffer containing 100 mm ß-mercaptoethanol, 2% sodium dodecyl sulfate and 62.4 mM Tris-HCl to remove electro-chemifluorescent reaction product and antibodies, respectively. The stripped membrane was re-probed with anti-actin antibody (Sigma) at 1:500,000 dilution and detected as described previously 20 .

Retroviral transduction of primary mouse bone marrow cells.
The retroviral vector, Sfbeta 91, served as a control and the backbone for cloning of Slit2 cDNA. It contained the 5′ -long terminal repeat derived from myeloproliferative sarcoma virus (MPSV) and a 3′-long terminal repeat derived from spleen focus forming virus (SFFV). The internal ribosomal entry site sequence derived from the encephalomyocarditis virus was used for simultaneous translation of gene insert and the gene for enhanced GFP. The Slit2 cDNA sequence was cloned upstream of the IRES of the Sfbeta91 vector (MPSV-IRES-GFP-SFFV) to create a recombinant Slit2-carrying vector (MPSV-Lxn-IRES-GFP-SFFV). The Slit2 cDNA was amplified from hematopoietic cells using Slit2 forward primer: 5′ ATTTGCGGCCGCAAGATGAGTGGCATTGGC3′ and Slit2 reverse primer: 5′ GGCCTCGAGTTAGGAGGCACATCTCGCGCA3′ . Production of high-titer helper-free retrovirus was carried out by standard procedure in ectotropic Phoenix packaging cells as described previously 20 .

Infection of primary murine bone marrow cells. Primary mouse bone marrow cells were transduced
as previously described 20 . Briefly, bone marrow cells were harvested from mice treated 4 days previously with 150 mg/kg body weight 5-fluorouracil (5-FU; Sigma, St. Louis, MO) and cultured for 24 h in Dulbecco's modified eagle's medium supplemented with 10% FBS, 1% penicillin/streptomycin (Gibco Technologies, Carlsbad, CA), 50 ng/mL recombinant mouse stem cell factor, 10 ng/mL mouse interleukin 6 (mIL-6), and 10 ng/mL mouse interleukin 3 (mIL-3; R&D Systems, Minneapolis, MN). The cells were then harvested and slowly spread on the top surface of the membrane of a Transwell insert (Corning Incorporated Life Sciences, Acton, MA) at a density of 2 × 10 6 cells per well. The viral supernatants were added to the Transwell inserts along with 4 μ g/ml of polybrene and were cultured with cells for a further 48 h. The viral supernatant was changed 3 times during this period of time. Retrovirally-transduced, i.e. GFP positive, bone marrow cells were flow cytometrically sorted using a FACSAriaII (Becton-Dickinson) and used for CAFC assay and transplantation assays.
Functional analysis of transduced cells. GFP marker was used to select transduced hematopoietic cells.
GFP positive cells infected with the empty Sfbeta vector and the Slit2-containing vector were plated in limiting dilutions on confluent layers of FBMD-1 stromal cells for CAFC analysis. CAFC analysis was performed as previously 20 described to measure the effects of Slit2 expression on HSC and HPC numbers. Competitive repopulation assays with GFP positive cells were performed by co-transplantation of 2 × 10 5 GFP + cells with equal numbers of CD45.1 helper cells to two groups of lethally irradiated mouse recipients (10 recipients of GFP cells and 10 recipients of Slit2-GFP cells). Relative engraftment was determined by measuring the level of GFP positive cells in the peripheral blood of each recipient mouse 4-16 weeks post-transplant. In the limiting-dilution competitive repopulation assay as described previously 20 , graded numbers (6,000; 20,000; 60,000) of B6 GFP+ or B6 Slit2 GFP+ cells (CD45.2) were admixed with a radio-protective dose (2 × 10 5 ) of competitor cells (CD45.1) and injected intravenously into lethally irradiated (900 Gy) CD45.1 recipient mice. Relative engraftment was determined by measuring the level of GFP positive cells in the peripheral blood of each recipient mouse 12 weeks post-transplant as described above. The frequencies of long-term HSCs (CRU) were calculated from the proportions of negative recipients in each cell dose group, in which < 1% of the circulating B, T and myeloid cells were regenerated by CD45.2 "test" stem cells, by using L-Calc software (StemCell Technologies Inc., Vancouver, BC).
Mapping of eQTL for Slit2 in BXD mice. We queried gene expression data in hematopoietic stem cells of 23 BXD recombinant inbred strains using the UMCG Hematopoietic Stem Cells Illumina database in Genenetwork (http://genenetwork.org/webqtl/main.py) to map regulatory elements governing the expression of Slit2 in these strains. Data for eight Illumina probes was available through in this database. We selected Illumina probe ILM1940037 which corresponded to the probe identified as differentially expressed in our microarray analysis and performed Interval mapping across the entire genome to identify regulators of Slit2 expression or eQTL.
Statistical analysis. Data were analyzed by either Student t-test with P < 0.05 (two-tail), or one-way ANOVA. All experimental methods were run in accordance with relevant guidelines.