The quantitative trait gene latexin influences the size ofthe hematopoietic stem cell population in miceYing Liang1, Michael Jansen2,3, Bruce Aronow2, Hartmut Geiger3 & Gary Van Zant1

We mapped quantitative trait loci that accounted for the variation in hematopoietic stem cell (HSC) numbers betweenyoung adult C57BL/6 (B6) and DBA/2 (D2) mice. In reciprocal chromosome 3 congenic mice, introgressed D2 allelesincreased HSC numbers owing to enhanced proliferation and self-renewal and reduced apoptosis, whereas B6 alleles hadthe opposite effects. Using oligonucleotide arrays, real-time PCR and protein blots, we identified latexin (Lxn), a gene whosedifferential transcription and expression was associated with the allelic differences. Expression was inversely correlated withthe number of HSCs; therefore, ectopic expression of Lxn using a retroviral vector decreased stem cell population size.We identified clusters of SNPs upstream of the Lxn transcriptional start site, at least two of which are associated withpotential binding sites for transcription factors regulating stem cells. Thus, promoter polymorphisms between the B6and D2 alleles may affect Lxn gene expression and consequently influence the population size of hematopoieticstem cells.

Natural variation in the size of endogenous stem cell populations isimportant for homeostatic tissue regeneration, stem cell transplanta-tion, aging and, potentially, organismal longevity. Using the HSCpopulation as a model, we sought to identify genes that regulatenatural variation in HSC population size. We and others1–5 havedemonstrated the extensive variation in HSC number between strainsof laboratory mice. Based on these natural variations and the avail-ability of genetic tools afforded by certain strain comparisons, weinvestigated the genetic determinants underlying variation betweenthe C57BL/6 (B6) and DBA/2 (D2) strains. D2 mice, when young,have at least three times as many HSCs as B6 (refs. 1,6). Longitudinalstudies of hematopoiesis in embryo-aggregated chimeric mice com-pounded from these two strains have demonstrated that stem cellcontributions are cell autonomous and strain specific, which suggeststhat polymorphic genes account for at least part of the interstrain stemcell variations, possibly including population size7.

Recombinant inbred (RI) mouse strains generated by crossing B6and D2 progenitor strains (BXD) are a useful mapping panel to linkHSC phenotypes with genetic markers whose physical genomic loca-tions are known8. Accordingly, we have performed linkage analyses ofseveral phenotypes of primitive hematopoietic cells, including thefraction of the HSC population sensitive to hydroxyurea toxicity6, andthe change in HSC population size during aging9,10. Linked locicontributing to these quantitative traits (quantitative trait loci orQTL) have been mapped and in some cases have been shown tocoincide with genomic locations of QTL independently mapped for

contributing to significant variation in the natural lifespan between B6and D2 mice11–13.

Thus, in the present study, we used a forward genetic approach14

using a variety of techniques to identify a quantitative trait gene,latexin, that contributes to the natural variation in the size of the HSCpopulation between young adult B6 and D2 mice.

RESULTSLinkage analysisWe performed the cobblestone area–forming cell (CAFC) assay toquantify bone marrow primitive hematopoietic cells in B6, D2 and 26BXD RI strains (Supplementary Table 1 online). In this in vitro assay,cobblestone areas, each representing the clonal amplification of asingle stem or progenitor cell, arise in a chronological continuum. Thelonger the latency before a primitive hematopoietic cell begins clonalexpansion, the more primitive it is. Here, cobblestone areas werecounted after 35 d of culture, a late time point. Primitive hemato-poietic cells measured at this time correlate highly with long-termrepopulating stem cells (LTRCs) in vivo15. Genome-wide linkageanalysis from GeneNetwork (Fig. 1a) showed that three QTL onchromosomes 3, 5 and 18, respectively, were genetically linked to thesize of the HSC population at a statistically ‘suggestive’ level ofassociation12. The positive additive regression coefficient for eachQTL indicates that D2 alleles increase the trait, whereas B6 alleleshave negative effects. Here we describe studies leading to the identi-fication of the gene associated with the chromosome 3 QTL.

Received 15 September 2006; accepted 17 November 2006; published online 14 January 2007; doi:10.1038/ng1938

1Departments of Internal Medicine and Physiology, University of Kentucky, Lexington, Kentucky 40536, USA. 2Department of Biomedical Informatics, CincinnatiChildren’s Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, USA. 3Division of Experimental Hematology, Departmentof Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, USA. Correspondence should beaddressed to G.V.Z. (gvzant1@uky.edu).

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Generation of congenic strainsWe generated mouse strains congenic for the chromosome 3 QTL bycrossing the genomic interval harboring the QTL using D2 as thedonor strain and B6 as the recipient strain (symbolized as B.D Chr3)and vice versa (D.B Chr3). The two reciprocal congenic strains werederived by a ‘speed-congenic’ approach involving at least eight back-crosses with the respective background strains16,17. Both congenic lineswere homozygous within their respective congenic intervals andgenotyped exclusively for background strain alleles using 100 micro-satellite markers scattered throughout the noncongenic genome. Amap of the congenic intervals in the reciprocal strains is depicted inFigure 1b. The congenic interval mutually inclusive in the two reci-procal strains spans from 36.5 Mb (19.2 cM ± 1 cM (s.d.)) to 67.8 Mb(33 cM ± 1 cM), and the marker (D3Mit5) most tightly linked to thetrait is at 50.4 Mb (25 cM ± 1 cM).

Validation of the linkage analysis and heritabilityTo validate the linkage analysis, we performed whole–bone marrowCAFC day 35 assays in the reciprocal congenic strains and their B6 andD2 background strains. The results showed that in B.D Chr3 congenicmice, introgression of D2 alleles onto the B6 background in the regionof the QTL caused nearly a twofold increase in the day 35 CAFCnumber (P ¼ 0.003), whereas introgression of B6 alleles onto the D2background caused a B40% decrease (P ¼ 0.02; Fig. 2a). Moreover,CAFC numbers for day 7 and day 21 (which represent hematopoieticprogenitor cells (HPCs) at different stages) as well as cell counts forperipheral blood leukocytes, erythrocytes and platelets did not showany differences between congenic and background strains (Supple-mentary Table 2 online), suggesting that a chromosome 3 QTLspecifically regulates the HSC population.

A bone marrow population (LSK cells) null for cell markerscharacteristic of lineage-specific differentiated blood cells (Lin-negative) and positive for the Sca-1 and c-Kit cell markers is highlyenriched for HSCs and comprises about 0.03% of total marrow.We sorted this population using flow cytometry and assayed for day35 CAFC numbers in the four strains. We obtained results similar tothose from unfractionated marrow: D2 alleles significantly increasedday 35 CAFC number in the LSK population, whereas B6 allelesdecreased this number (Po 0.05; Fig. 2b). Recently, populations withhigher HSC purity have been identified using antibodies directedagainst the SLAM family receptor proteins CD150 and CD48(refs. 18,19). CD150+ CD48– marrow cell populations contained21% LTRCs. We therefore measured the percentage of CD150+

CD48– cells in bone marrow to test whether there was variation inthis rare population between Chr 3 congenic and background strainmice. Marrow from D2 mice, after Ficoll gradient separation to enrichfor low-density cells, contained 0.19% (± 0.02%) CD150+ CD48– cells,a figure almost four times higher than that for B6 mice (0.05% ±0.01%) (P o 0.001). As expected, replacement of B6 alleles at theQTL with D2 alleles in B.D Chr3 congenic mice caused a significantincrease in the number of CD150+ CD48– cells, whereas replacementwith B6 alleles decreased the size of this population in D2 mice(P o 0.05; Fig. 2c).

We next performed a stringent functional assay, long-term limiting-dilution analysis in competitively repopulated hosts, to identify andquantify HSCs in vivo20. Graded numbers of bone marrow cells fromB.D Chr3 congenic or B6 mice were admixed with a fixed dose ofcompetitor cells and transplanted into groups of lethally irradiatedmice. Lymphomyeloid reconstitution by either B.D Chr3–derived orB6-derived cells was assessed in the peripheral blood cells 20 weeks

36.0

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4.0

2.0

1 2 3 4 5 6 7 8 9 10 11 12 15 16 17 18 19 X13 14

D3Mit5 D5Mit352 D18Mit53250.00

200.00

SignificantLRS threshold

SuggestiveLRS threshold

Additiveeffects

Microsatellitemarketrs

50.00

0.00

–50.00

–100.00

–150.00

Likelihood ratio statistics (LRS)Additive effectSignificant LRS = 16.1

Trait ID: record ID: 10233881,01Interval mapping for dataset: BXD, mapping on all chromosomesUsing haldane mapping function with no control for other QTLs

Suggestive LRS = 9.2

0 40 80 120 160 (Mb)

D.B Chr3

B.D Chr3

Consensus congenic interval

36.5 Mb (19.2 cM ± 1 cM) 50.4 Mb (25 cM ± 1 cM)

D3Mit5

67.8 Mb (33 cM ± 1 cM)

a

b

Figure 1 Linkage analysis and Chr3 congenic

mouse strains. (a) Genome-wide linkage analysis

for day 35 CAFC frequency from GeneNetwork.

The day 35 CAFC numbers per femur for B6, D2

and 26 BXD recombinant strains were derived

from previously published data (Supplementary

Table 1 online)6,12 and used for linkage analysis.

Three quantitative trait loci (QTL), on

chromosomes 3, 5 and 18, respectively, were

mapped at a ‘suggestive’ statistical level of

association, in which the likelihood ratio statistic

(LRS) values for the corresponding markers

(D3Mit5, D5Mit352, D18Mit53) are located

between suggestive and significant threshold. The

19 autosomes and X chromosome of the mousegenome are labeled across the top, and some

microsatellite markers are listed across the

bottom. The positive additive regression

coefficient for each QTL indicates that D2 alleles

increase the trait, whereas B6 alleles decrease

the trait. (b) Schematic illustration of the

genomic map of reciprocal Chr3 congenic mouse

strains. The B6-derived genomic interval

harboring Chr3 QTL (filled bar) was introgressed

onto the D2 background (open bar) in congenic

D.B Chr3 mice, and vice versa. The consensus

congenic interval (cross-hatched bar) extends

from 36.5 Mb (19.2 cM ± 1 cM) to 67.8 Mb

(33 cM ± 1 cM) and includes marker D3Mit5

at 50.4 Mb (25 cM ± 1 cM), which has the

highest linkage to the trait. The total length

of chromosome 3 (B160 Mb) is indicated

on the top.

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after transplantation. D2 alleles introgressed in the region of thechromosome 3 QTL caused a 73% increase in the number of long-term repopulating HSCs (P ¼ 0.04) in B.D Chr3 mice compared withB6 mice (Fig. 2d; compiled from two independent experiments).Thus, qualitatively and quantitatively, these results corroborate theresults obtained in vitro.

Together, these four independent studies support that a chromo-some 3 QTL in the congenic intervals confers the phenotype withwhich the linkage analysis was originally performed. In the context ofthese congenics, the QTL accounts for a significant portion of thenatural variation in this parameter between the progenitor strains,despite ‘suggestive’ linkage of the trait to two other QTL on chromo-some 5 and chromosome 18 and the presence of several other QTLthat approach ‘suggestive’ linkage (Fig. 1a).

Potential mechanisms accounting for HSC number variationTo address the role of chromosome 3 QTL in HSC replication, wedirectly measured the proportion of LSK cells in S phase of the cellcycle by measuring the incorporation of 5-bromodeoxyuridine(BrdU). In agreement with previous data21,22, 4.5% (± 1.7%) of B6LSK cells were labeled with BrdU 1 h after administration in vivo,whereas more than twice as many D2 LSK cells were labeled under thesame conditions (11% ± 2.5%; P ¼ 0.01). Introgression of D2 allelessignificantly increased the BrdU-positive LSK population (15% ±1.4%; P ¼ 0.0001) in B.D Chr3 congenic LSK cells, a proportionsimilar to that found in D2 cells. As expected, B6 alleles resulted indecreased BrdU incorporation and conferred the B6 phenotype to D.BChr3 cells (5.9% ± 1.2%; P ¼ 0.02; Fig. 3a). In another demonstrationof the effects of the QTL on cell cycle kinetics, we measured thefraction of day 7 CAFC progenitor cells killed by hydroxyurea in thereciprocal congenic strains and in B6 and D2 mice (Fig. 3b). D2alleles in and around the chromsome 3 QTL in a B6 backgroundquantitatively reproduced the greater killing seen in D2 mice.

Similarly, B6 alleles on a D2 background reproduced the entirevariation in this trait between B6 and D2 mice. These results under-score an important effect of the chromosome 3 QTL on the cell cyclekinetics of not only HSCs but also their immediate progeny. Notably,the number of progenitor cells and differential blood cell counts didnot show any differences among the congenic and backgroundstrains, demonstrating that compensatory mechanisms during down-stream amplification of differentiating cells obviated variation infinal cell outputs in the multiple blood cell lineages (Supple-mentary Table 2).

We tested the self-renewal capacity of B.D Chr3 congenic HSCs inserial transplant experiments in which they, along with B6.SJL(CD45.1) marrow cells, competed for engraftment in lethally(9.0 Gy) irradiated CD45.1 recipients. Four months after transplant,we harvested marrow from the primary recipients and transplantedit into secondary recipients. We repeated the identical regimentwice more, culminating in engrafted quaternary hosts. At eachtransplant, we analyzed peripheral blood, bone marrow and bonemarrow LSK cells for the presence of either congenic or B6 cellsand compared the respective repopulating contributions. Congenicstem cells maintained their competitive advantage at every roundof transplantation in each cell population (Fig. 3c), demonstrat-ing that they retained the hallmark of functional stem cell abilitiesto self-renew and give rise to normal differentiated progeny in the faceof replicative stress. Further attesting to the extensive self-renewal ofB.D Chr3 stem cells was the finding that all 16 of the quaternaryrecipients transplanted with congenic cells survived long-term,whereas half (8 of 16) of the recipients receiving B6 cells failed tosurvive to the 10-week evaluation time point in fourth-iterationrecipients. Thus, serial bone marrow transplantation in a competitiverepopulation setting demonstrates that D2 Chr3 QTL confer higherself-renewal capability to HSCs and that this capacity is intrinsic tothe HSCs.

200

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FC

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fem

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Chr

3 co

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com

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ith th

eba

ckgr

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mic

e (%

)

B.D Chr3 / B6 D.B Chr3 / D2 B.D Chr3 / B6 D.B Chr3 / D2

B.D Chr3 / B6 D.B Chr3 / D2

CA

FC

day

35

num

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per

100,

000

LSK

cel

lsin

Chr

3 co

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ic m

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com

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ith th

e ba

ckgr

ound

mic

e (%

)

*

*

(P = 0.02)

(P = 0.003)

*

*

(P = 0.03)

(P = 0.016)

CD

150

CD48

B6 (0.05% ± 0.01%) D2 (0.19% ± 0.02%)

B.D Chr3 (0.09% ± 0.02%) D.B Chr3 (0.14% ± 0.01%)

2.5

2

1.5

1

0.5

0

BM

CD

150

+ C

D48

– ce

lls in

cong

enic

mic

e co

mpa

red

with

back

grou

nd m

ice

(%) *

*

3,000

2,000

1,000

0B6

LTR

C n

umbe

r pe

r fe

mur

B.D Chr3

*(P = 0.04)

a b dc

Figure 2 HSC frequency in Chr3 congenic mice. (a) Day 35 CAFC frequency per femur (mean ± s.e.m.) in reciprocal Chr3 congenic mice (B.D Chr3 andD.B Chr3) compared with the corresponding background strain (B6 and D2) (n 4 9). The absolute numbers of day 35 CAFC per femur (± 1 s.e.m.) for all

strains were 397 ± 59 (B6), 724 ± 73 (B.D Chr3), 1,978 ± 684 (D2) and 1,532 ± 286 (D.B Chr3). (b) Day 35 CAFC frequency per 100,000 Lin– Sca-1+

c-kit+ (LSK) cells (mean ± s.e.m.) in reciprocal Chr3 congenic mice compared with the corresponding background strain (n 4 9). The absolute numbers

(± s.e.m.) of day 35 CAFC per 100,000 LSK cells for all strains were 1,316 ± 172 (B6), 2,000 ± 218 (B.D Chr3), 10,000 ± 1,010 (D2) and 7,143 ± 721

(D.B Chr3). (c) Analysis of bone marrow HSC frequencies based on the expression of CD150 and CD48 markers in Chr3 congenic, B6 and D2 mice. Light-

density bone marrow mononucleated cells were separated by Ficoll gradient and stained with PE-CD150 and FITC-CD48 antibodies. Upper panel shows

representative flow cytometric profiles for highly purified CD150+ CD48– HSCs and proportions of this population in the bone marrow in each strain

(mean ± s.d.; n ¼ 10). Lower panel compares the frequencies of CD150+ CD48– HSCs between congenic and background strain. *, P o 0.05. (d) Total

number of long-term repopulating HSCs (LTRC) in B.D Chr3 congenic and B6 mice (mean per femur ± s.e.m.).

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To determine whether allelic differences in the chromosome 3congenic interval affected steady-state apoptosis in the HSCpopulation, we assessed annexin V staining of bone marrow LSKcells (Fig. 3d). We found a significant variation (P ¼ 0.04) in annexinV staining in the LSK populations of steady-state B6 (2.7% ± 0.4%)and D2 (0.9% ± 0.2%) bone marrow (Fig. 3e). Introgression of D2alleles around the chromosome 3 QTL, in the B.D Chr3 congenicstrain, resulted in an apoptotic LSK subpopulation (0.6% ± 0.1%)similar to that of D2 mice, which suggests that the congenic intervalconferred the entire phenotype. Notably, analysis of marrow from thereciprocal congenic strain uncovered a very low rate of apoptosis(0.3% ± 0.03%) in the LSK population. Thus, B6 alleles at and aroundthe QTL do not confer the B6 phenotype onto D2 HSCs. In fact,apoptosis was significantly lower (P ¼ 0.02) than in the D2 back-ground strain itself. This result may be due to genes in the mutuallyexclusive congenic intervals of the reciprocal strains or genes in the D2background that have strong negative effects on HSC apoptosis.Irrespective of the cause, the results suggest that the QTL may actthrough a mechanism influencing apoptosis in HSCs.

Candidate gene screeningWe used oligonucleotide arrays to screen for genes in the consensuscongenic interval whose differential expression may account for theobserved phenotypic variations. We sorted LSK cells from bone

marrow of the reciprocal congenic mice and the two background-strain mice. To avoid representational skewing of low-abundancemRNAs that may accompany amplification by PCR, we elected toobtain large, independently sorted biological samples for total RNAextraction. We collected triplicate RNA samples, each independentlyobtained from at least 550,000 LSK cells, sorted and pooled from aminimum of 40 mice, from the four strains. We hybridized each RNAsample (four strains � three replicates ¼ 12 in all) to an individualmicroarray chip (Affymetrix MG U74Av2). We analyzed resultsobtained from the triplicate chips for each strain using AffymetrixMicroarray Suite software and compared results using one-wayanalysis of variance (ANOVA) for each congenic-background strainpair. Between the B.D Chr3 and B6 strains, 96 genes were differentiallyexpressed (P o 0.05); between D.B Chr3 and D2, 84 were differen-tially expressed (P o 0.05; Supplementary Tables 3 and 4 online).Because the congenic intervals represent o1% of the entire genome,these numbers are significantly lower than the 940 differentiallyexpressed genes measured between B6 and D2 LSK cells in theseexperiments (data not shown). Only 17 genes on 11 differentchromosomes were mutually inclusive in the comparisons betweenthe reciprocal congenics and their respective background strains(Table 1). Of those 17 differentially expressed genes, we found thatD2 and B6 alleles had opposite effects on transcription in 9. Four ofthese were found on Chr3, but only one of the four was located in the

100

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00 1st 2nd 3rd 4th

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cells

Peripheral blood BM nucleated cells BM LSK cells Survival of quaternaryrecipients

Lin-Cou

nts

c-ki

t

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7 A

AD

Annexin V

Sca-1

Sca-1+,c-kit+18

12

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0

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cent

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of B

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LS

K c

ells

B6

**(P = 0.0001)

*(P = 0.01)

**(P = 0.02)

**(P = 0.02)

*(P = 0.0002)

**(P = 0.03)

B.D Chr3 D2 D.B Chr3 B6 B.D Chr3 D2 D.B Chr3

50

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0Per

cent

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of C

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ay 7

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0B6 B.D Chr3 D2 D.B Chr3

Pro

port

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of a

popt

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LS

K c

ells

(%

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**(P = 0.01)

**(P = 0.02)

*(P = 0.04)

B.D Chr3B6

0 1st 2nd 3rd 4th 0 1st 2nd 3rd 4th

a d

c e

b

Figure 3 Replication, self-renewal and apoptosis analysis of Chr3 congenic HSCs. (a) Replication of HSCs was measured by BrdU incorporation in animals

given a single pulse of BrdU (mean ± s.d. of the fraction of BrdU-positive LSK cells; n ¼ 8 per strain). (b) Proliferation of HPCs measured by day 7 CAFCcells killed by hydroxyurea (HU) in reciprocal congenic and B6, D2 strains (mean ± s.d. of three independent experiments; n Z 9). (c) Self-renewal analysis

of HSCs in serial bone marrow transplantation. B.D Chr3 or B6-derived peripheral blood leukocytes, bone marrow (BM) nucleated and BM LSK cells were

analyzed 16 weeks after they were transplanted into primary, secondary, tertiary and quaternary recipients. Each data point represents the mean for groups

of mice (n Z 16). The survival rate of quaternary recipients transplanted with either B.D Chr3 or B6 cells is shown in the rightmost panel. (d) Immuno-

phenotypic identification of apoptotic HSCs. The two upper plots show the gates to identify Lin– Sca-1+ and c-kit+ (LSK) stem cells. Lower left plot identifies

annexin V–positive, 7AAD-negative apoptotic cells in the LSK cell population. The plots at right are from the thymocyte control for determination of annexin

V and 7AAD quadrants. Plots are from one representative animal. (e) Proportion of apoptotic LSK cells in congenic and background strain (mean ± s.d. for

eight animals). * indicates statistical significance for a comparison of B6 and D2, and ** indicates statistical significance for a comparison of congenics and

the corresponding background mice.

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consensus congenic interval, near the marker of highest linkage in themapping (D3Mit5). That gene was latexin (Lxn), whose expressionwas upregulated by B6 alleles and downregulated by D2 alleles, apattern expected from the linkage analysis. We next measured Lxntranscript levels in LSK cells using real-time PCR, which confirmed themicroarray results (Fig. 4a) both qualitatively and quantitatively andsuggests an inverse relationship between Lxn expression and the day35 CAFC number. As predicted, B6 alleles in the congenic intervalincreased Lxn transcripts by approximately threefold in LSK cells(P ¼ 0.00003) and reduced day 35 CAFC numbers by more thanhalf. In contrast, D2 alleles significantly decreased Lxn expression(P ¼ 0.02) and increased HSC numbers (Fig. 2).

Lxn expression in different hematopoietic cell populationsLxn was first identified in neurons of the lateral neocortex of the brainand has been used as a marker for regional specification duringdevelopment23,24. Because it is highly expressed in differentiatedneurons of the nervous system, we next determined its expressionalong the differentiation pathway in the hematopoietic system. Wequantified Lxn transcripts by real-time PCR in peripheral bloodleukocytes, whole bone marrow, Lin-negative bone marrow cells,

LSK cells and CD150+ CD48– cells in each of the four strains(Fig. 4b,c). Two points are noteworthy from the compiled results ofthree independent experiments. First, overall expression of Lxn per cellin each of the populations increased in concert with the content ofprimitive hematopoietic cells. Second, Lxn expression per cell in eachof the cell populations accurately reflected the presence of B6 (higherexpression) or D2 (lower expression) alleles in the two congenic andbackground strains.

Latexin protein amounts in hematopoietic cellsWe next determined the amounts of latexin protein in hematopoieticcells of the congenic and background strain mice. We generated arabbit polyclonal IgG antibody to mouse latexin from the latexin-specific amino acid sequence CKHNSRLPKEGQAE at the C terminus.Because enough Lxn transcripts were present in unfractionated bonemarrow and in Lin-negative cells (Fig. 4b), we used cell lysates of thesepopulations for protein blotting. The antibody was immunoreactivewith a protein (latexin) of the expected size (29 kDa) in bone marrowcells (Fig. 4d). Consistent with the real-time PCR results, Lin-negativecells contained more latexin than bone marrow cells (Fig. 4e). Morenotably, the cellular content of latexin in both whole bone marrow and

Table 1 Genes differentially expressed in reciprocal Chr3 congenic, B6 and D2 HSCs

Probe set Gene name Gene symbol

Chromosomal

location (Mb)

Entrez

gene ID Molecular function

101209_at Fc receptor, IgE, high-affinity I,

alpha polypeptide

Fcer1a 1 (173) 14125 Receptor activity; IgE binding

102260_ata Growth factor–independent 1B Gfi1b 2 (28) 14582 ATP binding

96065_ata Latexin Lxn 3 (67) 17035 Enzyme inhibitor activity;

metalloendopeptidase

inhibitor activity

92770_atb S100 calcium-binding protein

A6 (calcyclin)

S100a6 3 (91) 20200 Calcium ion binding; protein binding;

growth factor activity

98600_ata S100 calcium binding protein

A11 (calizzarin)

S100a11 3 (93) 20195 Cytokine activity; calcium

ion binding

103257_at RIKEN cDNA 4930577M16 gene

(transmembrane

protein 56)

4930577 M16Rik

(Tmem56)

3 (121) 99887 Unknown

94559_at General transcription factor III A Gtf3a 5 (145) 66596 DNA binding

102011_at RIKEN cDNA 2610507L03 gene 2610507L03Rik 7 (23) 72140 Unknown

94286_at RIKEN cDNA 9130011J15 gene 9130011J15 Rik 8 (71) 66818 Unknown

93498_s_ata Amyloid beta (A4) precursor-like protein 2 Aplp2 9 (31) 11804 DNA binding; protein binding; serine-type

endopeptidase inhibitor activity

101026_atb Pituitary tumor-transforming 1 Pttg1 11 (43) 30939 Cysteine protease inhibitor activity

16128_ata MYB-binding protein (P160) 1a Mybbp1a 11 (72) 18432 Protein binding; transcriptional repressor activity

93134_at Neuronal pentraxin 1 Nptx1 11 (119) 18164 Calcium ion binding

100391_at Mitogen activated protein kinase 8 Mapk8 14 (29) 26419 Kinase activity; transferase activity

100343_atb Tubulin, alpha 1 Tuba1 15 (99) 22142 GTPase activity; GTP binding; structural

constituent of cytoskeleton

103282_atb RAS, guanyl releasing protein 2//

similar to calcium

and DAG-regulated guanine nucleotide

exchange factor I

Rasgrp2//

LOC381240

19 (6) 19395 // 381240 Guanyl-nucleotide

exchange factor activity; calcium ion

binding; diacylglycerol binding;

kinase activity

160391_at Fatty acid desaturase 1 Fads1 19 (9) 76267 Linoleoyl-CoA desaturase activity;

oxidoreductase activity

Total RNA isolated from LSK cells in B.D Chr3, D.B Chr3 congenic, B6 and D2 mice was reverse transcribed into cDNA and subsequently used for the synthesis of cRNA. cRNA waslabeled with biotin and hybridized onto the Affymetrix Mouse Genome U74Av2 chip. Gene expression in LSK cells was quantified and averaged from three independent experiments.The gene expression levels were compared between congenic and repective background mice using one-way ANOVA with a statistical cutoff of P o 0.05. Seventeen genes weredifferentially expressed among all four strains. ‘//’ indicates a synonymous gene symbol or protein name.aGenes whose expression is upregulated by the B6 alleles (high expression in D.B Chr3 and B6 cells) but downregulated by the D2 alleles (low expression in B.D Chr3 and D2 cells). bGenes whoseexpression is upregulated by the D2 alleles but downregulated by the B6 alleles.

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Lin-negative cells was significantly higher in mouse strains with B6alleles at and around the Lxn locus. Both B6 and D2 Lxn allelesresulted in a greater increase or decrease, respectively, of Lxn expres-sion when present on an opposite-strain background than whenpresent in the native context. These results suggest an influence ofother loci acting through epistatic interactions to optimize Lxnexpression in the two strains.

QTL that influence Lxn expressionBecause we detected and quantified Lxn expression in LSK cells of the30 BXD RI strains in the GeneNetwork database, we performedlinkage analysis to search for QTL that modify Lxn expression25,26.When we queried modifiers of Lxn expression using such an approach,we found suggestive linkage (LRS 4 9.6) to a genomic intervalspanning from 56.9 Mb to 66.8 Mb on chromosome 3, very close tothe genomic locations of D3Mit5 and Lxn, a finding consistent with cisregulation (Fig. 5). Moreover, the negative additive effects of allmarkers in this genomic interval suggest that the B6 allele increasesLxn expression, which corroborates our results from microarray, real-time PCR and protein blot analyses. Therefore, these results not onlysuggest the existence of a regulatory element in the upstream region ofthe Lxn sequence but also corroborate D3Mit5 as a marker, presum-ably the primary one, for a QTL directly or indirectly responsible forthe phenotypes conferred by the chromosome 3 QTL. It is formally

possible that another gene in the chromosome 3 congenic intervalmakes a contribution toward the linkage peak.

Overexpression of Lxn decreases stem cell numbersBecause D2 and B.D Chr3 congenic mice have lower Lxn expressionand higher stem cell numbers, we artificially enhanced Lxn expressionin both strains to test the hypothesis that overexpression of Lxn wouldreduce stem cell numbers. We infected bone marrow cells in vitro withretroviral vectors containing either GFP alone (control vector) or Lxnand GFP (Lxn-GFP) and subsequently transplanted them into reci-pients myeloablated by irradiation. At Z12 weeks after transplant,when all hematopoiesis originated from the transplanted stem cellgrafts, we harvested marrow from the primary recipients and sorted

4

3

2

1

0B.D Chr3 / B6

*(P = 0.02)

*(P = 0.00003)

D.B Chr3 / D2

Lxn

mR

NA

exp

ress

ion

in c

onge

nic

LSK

cells

com

pare

d w

ith c

orre

spon

ding

B6

and

D2

cells

10

5

0

Lxn

mR

NA

exp

ress

ion

norm

aliz

ed to

GA

PD

H

Lxn

mR

NA

exp

ress

ion

inC

D15

0+ C

D48

– ce

lls(n

orm

aliz

ed to

GA

PD

H)

PB BM Lin– LSK

B6D2

B.D Chr.3D.B Chr.3

B6D2

B.D Chr.3D.B Chr.3

0

0.8

1.6

B6

B.D

Chr

.3 D2

D.B

Chr

.3

4.5

3.0

1.5

0BM Lin–

LXN

exp

ress

ion

norm

aliz

ed to

act

in

75 kDa

50 kDa

35 kDa

30 kDa

Pro

tein

ladd

er

B6

BM

D2

BM

LXN29 kDa

BM

Lin–

LXN

B6B.DChr3

D2D.BChr3

Actin

LXN

Actin

a b c d

eFigure 4 Differential expression of Lxn in congenic, B6 and D2 mice. (a) Lxn transcript

expression in congenic HSCs. Identical numbers (2 � 105) of LSK cells were sorted from

each strain, and Lxn mRNA level in these cells was quantified by real-time PCR and

compared between congenic and respective background mice. Results are the mean

(± s.d.) of 12 measurements derived from three independent biological examples.

(b) Lxn expression in differentiated peripheral blood leukocytes (PB), bone marrow

nucleated cells (BM) and primitive hematopoietic cell-enriched population, including

lineage-negative cells (Lin–) and HSCs (LSK cells) (mean ± s.d.; n ¼ 12). (c) Lxn

transcript expression in CD150+ CD48– cells. Thirty thousand CD150+ CD48– cells

were isolated from Chr3 congenic, B6 and D2 strains, and quantitative real-time PCR

measurements were performed for Lxn mRNA expression. Lxn expression significantly

differs between congenic and background stem cells (P o 10–7; mean of three

independent experiments and at least four replicate samples for each experiment).

(d) Detection of latexin protein by antibody to latexin. A 29-kDa protein (the expected size

of latexin) was detected by protein blot on B6 and D2 bone marrow (BM) samples using rabbit polyclonal IgG antibody to mouse latexin (specific to the

latexin C terminus). (e) Protein blot of BM nucleated and Lin– cells (one representative analysis out of four independent experiments). Blots are quantified at

right. Latexin (LXN) expression differed significantly among congenic, B6 and D2 mice (P o 0.05). Actin was used as the internal normalization control.

LRS

10.64010.64010.64010.64010.64010.64014.37914.37914.37914.37911.43611.43611.43611.43611.436

Additive effects

– 0.163– 0.163

– 0.163– 0.163– 0.163– 0.163– 0.183– 0.183– 0.183– 0.183– 0.167– 0.167– 0.167– 0.167– 0.167

LocusChromosomelocation (Mb)

3 (56.96)3 (57)

3 (57.46)3 (57.64)3 (58.1)3 (60.9)3 (61.8)3 (62.2)3 (65.0)3 (65.3)3 (66.1)3 (66.1)3 (66.2)3 (66.3)3 (66.8)

mCV22953681rs13477128rs363066

Gnf03.054.694rs6301139

CEL-3_59198871rs13477144rs13477148rs6191597

rs13459069rs3674751

rs13477166D3mit241

Gnf03.063.824rs13477169

17.515.0

12.5

10.0

LRS

7.5

2.5

5.0

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150Chromosome position (Mb)

SNPs

Suggestive LRSthreshold

Significant LRSthreshold

Mb

Figure 5 QTL regulating Lxn expression. Linkage analysis was performed

on GeneNetwork to search for the QTL that influence Lxn expression. Agenomic region on chromosome 3 ranging from 56.9–66.8 Mb is shown to

be associated with the Lxn expression with suggestive LRS values (between

gray and pink lines). The linked QTL (locus) are listed with corresponding

LRS scores and additive effects. The SNPs across chromosome 3 are shown

as orange tick marks on the x axis.

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cells expressing GFP using flow cytometry. We then assayed the GFP-positive population for day 35 CAFC content in D2-derived cells andLTRC frequency in B.D Chr3–derived cells (Fig. 6a). Real-time PCRand protein blots confirmed that Lxn transcripts and protein weremarkedly higher in Lxn-GFP cells (data not shown and Fig. 6b,respectively). The frequency of these primitive stem cells was signifi-cantly reduced (P o 0.05) in the population infected with theLxn-GFP vector relative to cells infected with the GFP control vector(Fig. 6c,d). The number of HSCs in Lxn-overexpressing cells wasapproximately three times lower in these cells, precisely reflecting the

difference between two parental B6 and D2 strains. Therefore, theseresults further confirm Lxn as the primary quantitative gene negativelyregulating HSC numbers.

SNPs in the regulatory region of LxnWe next asked what mechanisms might contribute to the differentialexpression of Lxn, focusing on our subsequent analyses on possiblecis-regulating factors. We used several databases (see Methods) tosearch for SNPs and potential transcription factor binding sites in thegenomic region spanning the interval immediately upstream of theLxn transcription start site (67535000–67565000 bp), uncoveringseveral notable genomic features (Fig. 7). First, the Lxn gene wasembedded in the intron of another much larger gene, G elongationfactor 1 (Gfm1), but with opposite transcriptional orientation. Second,19 SNPs found between B6 and D2 were located in introns as well asin the 5¢ and 3¢ UTRs. We did not detect any exonic SNPs. Mostnotably, potential upstream regulatory regions of Lxn that have eithera high density of transcription factor binding sites that are colinear inthe human LXN promoter (TraFaC regulatory regions) or regionsidentified by the ESPERR algorithm were enriched for SNP clusters(ESPERR regulatory potential was concordant with SNPs 1, 2, 3 and 4,and TraFaC high density with SNPs 10 and 11). We confirmed all sixof these SNPs between B6 and D2 by genomic sequencing (Supple-mentary Table 5 online), suggesting that they are important forvariation in binding of transcription factors, which subsequentlyresults in the differential Lxn expression.

DISCUSSIONNearly 3,000 QTL have been ascribed to a wide variety of physiologicaland behavioral traits in laboratory mice and rats, but the underlyingquantitative trait gene has been identified for fewer than 1% of these(ref. 27). Thus, the bottleneck in uncovering the multiple genes thatcontribute to complex quantitative traits is not in identifying QTL thatcontribute to the phenotype but rather in finding the underlyinggenetic source of the polymorphism. Several factors contributed to

SNPs

ESPEER

TraFac

Lxn gene

Gfm1 exons

67535000 67565000Genomic region (bp)

12 101134

Figure 7 SNPs in Lxn gene regulatory regions of B6 and D2 alleles. SNPs

and potential transcription factor binding sites are present in the genomic

region spanning the Lxn gene and parts of the 5¢ and 3¢ UTRs. We identified

19 SNPs between B6 and D2 alleles in the genomic region spanning

67535000–67565000 bp. All were located in introns or in the 5¢ and 3¢UTRs of the Lxn gene. Two clusters of SNPs (labeled ‘1, 2, 3, 4’ and ‘10,

11’, respectively, and highlighted in the blue box) are in upstream regulatory

regions of Lxn, in the canonical promoter, and have a high potential for

transcription factor binding sites identified by the ESPERR algorithm andthe TraFaC high-density algorithm. The Lxn gene, illustrated by six exons

(boxes) and five introns (line), is embedded in the intron of the much larger

G elongation factor 1 (Gfm1) gene, but with opposite transcriptional

orientation (indicated by arrows). The figure depicts only part of the Gfm1

gene (exons 12–17, from a total of 19).

GFP: 5′

Lxn- GFP: 5′

LTR

LTR Lxn

IRES GFP

GFP

LTR 3′

3′

Transfection

Eco-Phoenix

LTRIRES

5-FU

4 dBM cells

InfectionViral supernatant

Transplantation6 Gy

~12 weeks

Functional analyses (CAFC, LTRC) of GFP+ BM cells

LXN

ACTIN

Pos

itive

con

trol

GF

P

Lxn-

GF

P

2.5

2

1.5

1

0.5

25

15

20

10

0

LTR

C n

umbe

rpe

r 10

6 G

FP

+ c

ells

5Pos

itive

cont

rol

GFP

Lxn-

GFP

LXN

exp

ress

ion

norm

aliz

ed to

AC

TIN GFP Lxn-GFP

40

30

20

10

0

CA

FC

day

35

num

ber

per

106

GF

P+

cel

ls

*

*

D2 BM cellstransduced with vectors

GFP Lxn-GFP

B.D Chr3 BM cells transduced with vectors

a b c

d

Figure 6 Overexpression of Lxn decreases the number of HSCs. (a) Structure of the Lxn-containing retroviral vector and scheme of experimental design.

Lxn-GFP: Lxn-containing vector; GFP: empty vector control. (b) High amounts of latexin protein were expressed in bone marrow (BM) cells transduced with

Lxn-GFP vector, compared with those transduced with GFP control vector. GFP+ cells were sorted from the BM of the recipient mice and were transplanted

with either Lxn-GFP–transduced or GFP-transduced cells. Protein blots were performed to measure latexin protein content in GFP+ cells. (c) Day 35 CAFC

numbers in D2 BM cells that were transduced with either GFP control or Lxn-GFP vectors. * P ¼ 0.0059 (t-test, one-tailed). (d) Long-term repopulatingcell (LTRC) numbers in B.D Chr3 congenic BM cells that were transduced with either GFP control or Lxn-GFP vectors. * P ¼ 0.0458 (t-test, one-tailed).

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our discovery in this study that differential expression of Lxn isimportant in determining natural variation in HSC population size.First, the interstrain variation in HSC population size was large, andthe contribution of the QTL to the phenotype was substantial. It wasestimated to contribute 31% of the phenotypic variation from thelinkage analysis carried out in the RI mice. Second, not only didreciprocal congenic strains show an allele-specific phenotype, but thequantitative effect of the respective alleles on the opposite strainbackgrounds was as large or larger than the interstrain variationbetween young adult mice of the B6 and D2 strains. Thus, thephenotypic effects of the QTL were exaggerated in a congenic context,which, if it also holds true for QTL with small phenotypic effects, maymake QT gene identification more tractable27. Third, differential geneexpression rather than post-translational protein modifications, forexample, accounted for the phenotype and enabled the effective use ofdifferential gene expression comparisons among the reciprocalcongenic and background strains. Fourth, studies at the proteinlevel were made possible because differential Lxn expression wasentrained in the progeny of HSCs. If differential gene expressionhad been developmentally restricted to the HSC population, itwould have been difficult, if not impossible, to obtain sufficient cellsto use standard techniques to demonstrate allele-specific variationin protein expression.Lxn was first discovered in the developing lateral cortex of the brain,

an anatomical site from which its name was derived28. In addition tothe central and peripheral nervous system, Lxn was also found invarious other tissues29,30. In our study, we report that Lxn is highlyexpressed in primitive hematopoietic cells and that its differentialexpression at both the mRNA and protein level is associated with theallelic difference between B6 and D2 at chromosome 3 QTL. Wealso provide strong evidence linking Lxn with regulation of thenumber of HSCs. However, very little is known about potentialunderlying mechanisms.Lxn is the only known endogenous carboxypeptidase A inhibitor in

mammals. Its physical structure includes two nearly identical domainsthat have high conformational homology with the cystatins thatfunction to inhibit cathepsins in the lysosomal protein degradationpathway29,31. In this regard, Lxn has been ascribed an inflammatoryrole in activated macrophages31. Therefore, Lxn might be involved inmetabolism of specific proteins that are essential for HSC functions.Lxn contains two potential Ca2+/calmodulin–dependent proteinkinase sites and one cGMP-dependent protein kinase phosphorylationsite32,33, suggesting that cGMP-protein kinase G and/or calcium/calmodulin signaling pathways might be involved in the Lxn-mediatedregulation of HSCs. This hypothesis is supported by our observationsof differential expression of S100a6 and S100a11 (Table 1), which arelocated in a cluster of calcium-binding protein genes, between bothsets of congenics and their respective background strains. Last, thedeletion of a human candidate gene that has 85% homology withmouse latexin is associated with an increased incidence of ovariancancer32. Further studies showed that Lxn has about 30% sequencesimilarity, but greater structural homology, with a tumor suppressorgene, tazarotene-induced gene 1 (TIG1)31, which is downregulated orabsent in an extensive list of tumor types. Induction of expression ofTIG1 by 5-aza-2¢-deoxycytidine implicates methylation as a potentialmechanism for its inactivation34–37. We were not surprised to find thatMethPrimer software detected a 360-bp CpG island that surrounds theLxn transcription start site and the immediate 5¢ UTR as well as a 124-bp CpG island in the 3¢ UTR. These findings suggest that differentialmethylation status might similarly serve as an epigenetic mechanismfor differential expression of Lxn. It also suggests that Lxn may be a

‘tumor progenitor gene’ with an occult role in early stages of cancerdevelopment38. In aggregate, each of these possible pathways may besynergistically or independently involved in the regulation of cycling,apoptosis and/or self-renewal of HSCs, with consequences for HSCpopulation size.

The molecular architecture of Lxn and the identification of multipleSNPs in potential regulatory regions deserve further comment. Thelocation of Lxn within an intron of Gfm1, which encodes a transla-tional elongation factor in mitochondria, is unusual but is not aunique genomic arrangement. It should be noted that Gfm1 was notdifferentially expressed among the congenic and background strainsused in these studies (data not shown). Thus, differential transcrip-tional regulation was unique to the embedded Lxn and suggests thatregulatory sites are highly gene specific, pointing to a local role forpolymorphisms in the specific promoter and/or enhancer regions ofLxn for differential gene regulation. The fact that clusters of confirmedSNPs in the potential promoter region of Lxn are spatially concordantwith two putative binding sites for transcription factors known toregulate stem cells suggests a potential mechanism of differential geneexpression between B6 and D2 alleles. For example, a cluster of SNPs(SNPs 1–4) in the canonical Lxn promoter region is concordant with aregion identified by ESPEER as possessing potential regulatory activ-ity. SNP3 is in the middle of the canonical core binding site in one oftwo adjacent potential binding sites for the transcription factor CBF1.CBF1 is associated with the Notch signaling pathway, which is knownto be important in determining stem cell population size39. SNPs 10and 11 are either close to or in potential regulatory regions identifiedby TraFaC. HNF1/TCF1, a transcription factor with two adjacentbinding sites close to SNP11, mediates events downstream ofcanonical Wnt–b-catenin signaling, which is also important forregulating HSCs and interacts with the Notch signaling pathway40.Further experiments will focus on the influence of each of theSNPs, and their possible interactions, on the regulation of Lxnexpression in HSCs.

In summary, we identify Lxn as a quantitative trait gene and reportcompelling evidence of a new function for it in the regulation of HSCpopulation size. These findings affect the broad understanding ofmolecular mechanisms important in stem cell regulation and maycontribute to understanding of the neoplastic transformation of stemcells, developing effective stem cell expansion strategies for cellular-based clinical therapies, and understanding age-related changes instem cells41.

METHODSAnimals. C57BL/6 (B6) (Ptprcb [CD 45.2]) and DBA/2 (D2) mice were

background strains and were purchased from the Jackson Laboratories.

Chromosome 3 congenic mice were generated as described previously19.

Congenic mice were genotyped every 6 months through genetic marker–based

PCR. All primers for simple sequence repeat (SSR) element markers were

bought from Research Genetics. Two strains of Chr3 congenic mice were

generated and maintained: B.D Chr3 (14 cM ± 1 cM B33 cM ± 1 cM)

congenics, with D2 QTL introgressed onto the B6 background, and their

reciprocal congenic strains D.B Chr3 (19 cM ± 1 cM B60c M ± 1 cM) with B6

QTL on a D2 background. B6.SJL (Ptprcb [CD 45.1]) mice from Charles River

Laboratories were used as transplantation recipients in competitive repopula-

tion experiments. All mice were 6- to 10-week-old females and were housed in

the animal facilities of the University of Kentucky under pathogen-free

conditions according to NIH-mandated guidelines for animal welfare. They

were fed with acidified water and food ad libitum.

Immunofluorescent staining of HSCs. Bone marrow cells suspended in Hank’s

balanced salt solution (HBSS, Gibco) containing 2% FCS (Life Technologies)

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underwent Ficoll gradient separation and were subsequently blocked with anti-

CD16/32 (clone 2.4G2, Fc Block) to prevent nonspecific binding. For Lin– Sca-

1+ c-kit+ (LSK) stem cell isolation, cells were stained with the fluorescein

isothiocyanate (FITC)-conjugated lineage markers, including CD5 (clone

53-7.3), CD8a (clone 53-6.7), CD45R/B220 (clone RA3-6B2), CD11b/Mac-1

(clone M1/70), Ly-6G/Gr-1 (clone RB6-8C5), TER119/Ly-76 (clone TER-119)

and stem cell–specific markers, phycoerythrin (PE)-conjugated Ly-6A/E (Sca-1;

clone E13-161.7) and allophycocyanin (APC)-conjugated CD117 (c-kit; clo-

ne2B8). For the isolation of highly purified CD150+ and CD48– stem cells, cells

were stained with PE-conjugated anti-mouse CD150 (clone TC15-12F12.2) and

FITC-conjugated hamster anti-mouse CD48 (BCM). The viable cells were

distinguished by their ability to exclude propidium iodide (PI) (5 mg/ml). All

monoclonal antibodies were purchased from Pharmingen. Flow cytometric

analysis was performed on a triple-laser FACSVantage (Becton Dickinson

Immunocytometry Systems) to sort HSCs.

Cobblestone area-forming cell (CAFC) assay. The CAFC assay was carried

out as described previously2,6,12, using both whole bone marrow cells and

sorted LSK cells. In brief, a confluent monolayer of FBMD-1 stromal cells was

established in 96-well tissue culture-treated plates (Costar). After 7 to 10 d,

wells were seeded either with unfractionated marrow at a dose of 81,000,

27,000, 9,000, 3,000, 1,000 or 333 cells per well or with sorted LSK cells at a

dose of 1, 3, 10 or 30 cells per well using an automated cell deposition

unit. We evaluated 20 or 60 replicate wells per cell number in experiments

with unfractioned or sorted cells, respectively. The cells were cultured in

Iscove’s Modified Dulbecco Medium (IMDM) containing 20% horse serum,

80 U/ml penicillin, 80 mg/ml streptomycin (Life Technologies), 0.1 mM

b-mercaptoethanol and 0.01 mM hydrocortisone (both Sigma). 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 five small, non-refractile

cells growing underneath the stroma. The longer the latency before cobble-

stones 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 (HPCs). Frequencies of CAFCs were calculated by using maximum

likelihood analysis and equal 1 divided by the number of cells yielding 37%

negative wells.

Linkage analysis. The frequencies of day 35 CAFC in BXD RI mouse

strains shown in Supplementary Table 1 were derived from previously

published studies6,12. The GeneNetwork website25,26 was used for genome-wide

linkage analysis.

Bone marrow transplantation. In limiting-dilution competitive repopulation

assay, graded numbers (6,000, 20,000 and 60,000) of B.D Chr3 congenic or B6

‘test’ cells (CD45.2) were admixed with a radioprotective dose (2 � 105) of

competitor cells (CD45.1) and injected intravenously into lethally irradiated

(9 Gy) CD45.1 recipient mice. Recipients were bled from the retroorbital sinus

20 weeks after transplantation. Erythrocytes were depleted by hypotonic lysis

using NH4Cl. The leukocytes were stained in triplicate with fluorescein

isothiocyanate (FITC)-conjugated monoclonal anti-CD45.2 (clone ALI4A2)

and phycoerythrin (PE)-conjugated monoclonal antibodies (Becton-Dickin-

son-PharMingen) specific for either B (anti-CD45R/B220; clone RA3-6B2),

T lymphocytes (anti-Thy-1.2; clone 30H12) or granulocytes (anti-Ly6G/Gr-1;

clone RB6-8C5) and macrophages (anti-CD11b/Mac-1; clone M1/70). Samples

were analyzed using a FACScan instrument (Becton-Dickinson Immunocyto-

metry Systems). The frequencies of long-term HSCs were calculated from the

proportions of negative recipients in each cell dose group, in which o5% of the

circulating B, T and myeloid cells were regenerated by CD45.2 ‘test’ stem cells,

using L-Calc software (StemCell Technologies). In serial bone marrow trans-

plantation, B.D Chr3 congenic or B6 ‘test’ cells were injected into the primary

recipients along with equal number of competitor cells (1 � 106). We harvested

marrows from the primary recipients 16 weeks after transplant and trans-

planted them into secondary recipients. An identical regimen was repeated

twice more, culminating in the engrafted quaternary hosts. At each transplant,

the peripheral blood, bone marrow and bone marrow LSK cells were analyzed

as described above. The competitive advantage and self-renewal capacity were

analyzed by comparing the percentage of B.D Chr3 congenic–derived or B6-

derived cells at each round of transplantation.

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 ml of blood using a System 9118+ Hematology

Series Cell Counter (Biochem Immunosystems).

Measurement of proliferative activity. The proliferative activity of the various

primitive cells was assessed using two independent approaches. First, in vivo

BrdU incorporation was used to determine the cells in S phase of the cell cycle.

Mice were injected intraperitoneally with BrdU (1 mg per kg body weight) and

killed 90 min later. Bone marrow LSK cells were identified as described above.

Analysis of BrdU incorporation in LSK cells was performed using BrdU Flow

Kit (Pharmingen) according to the manufacturer’s instructions. The second

method was used to measure the fraction of cells killed by 1-h in vitro

incubation with hydroxyurea, which blocks DNA synthesis and stops cell

division by inhibiting ribonucleotide reductase. Briefly, all bone marrow cell

suspensions were diluted to a concentration of 1 � 107 cells/ml. Hydroxyurea

(200 mg/ml; a total volume of 10 ml; Sigma) was added to one sample, and the

sample was incubated with the untreated sample for 1 h at 33 1C. The standard

CAFC assay was then used to assay both hydroxyurea-treated and -untreated

samples. The fraction of cells killed by hydroxyurea was calculated by dividing

the difference in the CAFC frequency between the hydroxyurea-treated and

untreated samples by the hydroxyurea-untreated value.

Apoptotic analysis of HSCs. Bone marrow cells were prepared and immuno-

fluorescently stained as described above. FITC-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 annexin V–negative cells (Pharmingen). Three inde-

pendent experiments were performed in each strain, and at least two mice were

analyzed in each experiment. All experiments were carried out on ice and

completed within 1.5 h. Flow cytometric analysis was performed on a triple-

laser FACSVantage (Becton Dickinson Immunocytometry Systems).

Microarray analysis of LSK cells. Oligonucleotide array analysis of LSK cells

was performed by the Microarray Facility Center at the University of Kentucky.

Briefly, total RNA was extracted from at least 550,000 sorted LSK cells from a

minimum of 40 mice using the RNeasy Kit (QIAGEN). The extracted RNA was

reverse transcribed into cDNA, which was subsequently used to synthesize

biotin-labeled cRNA. The labeled cRNA was then fragmented and hybridized to

the Mouse Genome U74Av2 chips (MGU74Av2, Affymetrix). The gene chips

were then washed and stained and subsequently scanned for quantification of

gene expression. Three independent biological samples were obtained for each

strain, and each was run on an individual chip. The gene expression levels were

compared among all four strains using one-way ANOVA with a statistical cutoff

of P o 0.05. The genes that were differentially expressed were classified

according to their genomic locations and functions.

Quantitative real-time PCR. Identical numbers (200,000) of cells were used for

total RNA extraction in each type of cell population (peripheral blood, bone

marrow, Lin-negative and LSK cells) for each mouse strain. But as for the rare

CD150+ CD48– stem cells, only 30,000 cells were used. Isolated total RNA was

reverse transcribed into cDNA using random hexamers in a TaqMan reverse

transcription solution (PN N8080234) and stored at –20 1C. In real-time PCR

reactions, primer and probe mix for Lxn were purchased from Applied

Biosystems. TaqMan rodent glyceraldehyde-3-phosphate dehydrogenase

(GAPDH) (PN 4308313) served as an endogenous control for normalization

of Lxn expression. PCRs were set up according to the manufacturer’s instruc-

tions 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).

Protein blots. Cell samples were lysed at a concentration of 2 � 107 cells/ml in

protein lysis buffer containing: 10 mM Tris pH 7.5, 50 mM NaCl, 30 mM

sodium pyrophosphate, 50 mM NaF, 5 mM ZnCl2 and 1% Triton X-100,

2.8 mg/ml aprotinin (Sigma), 1 mM phenylmethylsulfonyl fluoride (Sigma),

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1 mM sodium vanadate (Na3VO4), 1 mg/ml pepstatin and 1 mg/ml leupeptin

(Oncogene Research). The lysate was incubated on ice for 30 min and

then centrifuged at 15,000g for 10 min to remove debris. The resulting

supernatant was then aliquoted and stored at –80 1C. For protein blot, protein

lysates were thawed and mixed with running buffer and a reducing agent, per

manufacturer’s instructions (Novex) and heated at 95 1C for 5 min. Samples

were then analyzed by denaturing PAGE (Novex, 10% Bis-Tris gel) using

the equivalent of 4 � 105 cells per lane. After electrophoresis, samples were

electrotransferred onto Immunobilon-P membranes (Millipore), which

were subsequently blocked and probed with polyclonal IgG rabbit antibody

to latexin (1:3,000). This antibody was generated from the Lxn-specific amino

acid sequence CKHNSRLPKEGQAE at the C terminus and was produced

by Bethyl Laboratories. Primary antibodies were detected using alkaline

phosphatase–conjugated secondary antibodies (Santa Cruz Biotechnology)

and electrochemifluorescent (ECF) reagent (Pharmacia Biotech) according to

the manufacturer’s instructions. Blots were visualized using a Molecular

Dynamics STORM 860 system and Imagequant Software. After the detec-

tion and quantification of latexin antibody, Immunobilon-P membrane was

sequentially stripped in 40% methanol and the buffer containing 100 mM

b-mercaptoethanol, 2% SDS and 62.4 mM Tris-HCl to remove ECF

reaction product and antibodies, respectively. The stripped membrane

was reprobed with antibody to actin (Sigma; 1:500,000) and detected as

described above.

Retroviral vectors. The retroviral vector Sfbeta 91 served as a control and the

backbone for cloning Lxn cDNA. It contained the 5¢ long terminal repeat (LTR)

derived from myeloproliferative sarcoma virus (MPSV) and a 3¢ LTR derived

from spleen focus forming virus (SFFV). The internal ribosomal entry site

sequence derived from the encephalomyocarditis virus was used for simulta-

neous translation of the gene insert and the gene for enhanced green fluorescent

protein (GFP). The Lxn cDNA sequence was cloned upstream of the IRES of

the Sfbeta91 vector (MPSV-IRES-GFP-SFFV) to create a recombinant Lxn-

carrying vector (MPSV-Lxn-IRES-GFP-SFFV). Production of high-titer helper-

free retrovirus was carried out by standard procedure in ectotropic Phoenix

packaging cells (Fig. 6a).

Infection of primary mouse bone marrow cells. Primary mouse bone marrow

cells were transduced as previously described with modifications specified

below42. Briefly, bone marrow cells were harvested from mice treated 4 d

previously with 150 mg/kg body weight 5-fluorouracil (5-FU) (Sigma) and

cultured for 24 h in DMEM supplemented with 10% FBS (FBS), 1% penicillin/

streptomycin (Gibco Technologies), 50 ng/ml recombinant mouse stem cell

factor (mSCF), 10 ng/ml mouse interleukin 6 (mIL-6), and 10 ng/ml mouse

interleukin 3 (mIL-3) (R&D Systems). The cells were then harvested and slowly

spread on the top surface of the membrane of a Transwell insert (Corning

Incorporated Life Sciences) at a density of 2 � 106 cells per well. The viral

supernatants were added to the Transwell inserts along with 4 mg/ml of

polybrene and were cultured with cells for further 48 h. The viral supernatant

was changed three times during this period. The recovered cells were then

transplanted into sub-lethally irradiated (6 Gy) recipient mice at a dose of at

least 1 � 106 cells per mouse. Around 12 weeks after transplantation, retro-

virally transduced (that is, GFP-positive) bone marrow cells were flow cytome-

trically sorted from primary recipient mice using a FACSVantage (Becton-

Dickinson) and used for the CAFC assay and limiting-dilution competitive

repopulation assay (Fig. 6a).

Functional analysis of retrovirally transduced cells. Identical numbers of

bone marrow cells transduced with either the GFP control vector or the Lxn-

GFP vector were sorted from the primary recipient mice. The CAFC and

limiting-dilution competitive repopulation assays of these GFP-positive cells

were performed as described above. The HSC frequencies (CAFC day 35 and

LTRC) were calculated and compared to measure the effects of Lxn over-

expression on HSC numbers.

Confirmation of SNPs by genomic sequencing. Six SNPs (numbered with 1,

2, 3, 4, 10 and 11 in Fig. 7) between B6 and D2 in the upstream regulatory

region of Lxn were confirmed by PCR-based genomic sequencing. The genomic

sequences including each SNP were BLASTed and aligned with mouse genomic

sequence. The primers for amplifying SNP-containing genomic region were

designed according to the BLASTed sequences and listed in Supplementary

Table 5 online. The genomic DNA was purified from 2 � 106 B6 and D2 Lin–

cells with QIAamp DNA Mini Kit (QIAGEN) and served as the template. The

PCR reaction was carried out in AmpliTaq Gold PCR Master Mix according to

the manufacturer’s instruction (Applied Biosystems). The annealing tempera-

tures for all primers were 60 1C for 30 s. Hot-start PCR (95 1C, 5 min; 35 total

cycles) was used in all PCR amplifications. Denaturation and extension

cycles were 95 1C for 30 s and 72 1C for 1.5 min, respectively. The sizes of

amplified fragments are listed in Supplementary Table 5 online. The PCR

products were purified with QIAquick PCR purification kit and sequenced

by MWG-BIOTECH.

Statistical analysis. Data were analyzed either by Student’s t-test assuming

unequal variance with P o 0.05 (two-tailed or one-tailed as indicated) or one-

way ANOVA.

URLs. MethPrimer software: http://www.urogene.org/methprimer/index.html.

GeneNetwork: http://www.GeneNetwork.org. SNP information was obtained

from http://www.ncbi.nlm.nih.gov/projects/SNP/MouseSNP.cgi. Lxn and Gfm1

genomic and exon sequences were from http://www.ensembl.org/

Mus_musculus/index.html. ESPEER regulatory potential was obtained through

http://genome.ucsc.edu/cgi-bin/hgGateway. The conserved (colinear) transcrip-

tion factor binding sites as well as the location of these binding sites with

respect to SNPs in Lxn was obtained through http://genomeTraFaC.cchmc.org.

Sequences were BLASTed and aligned using http://www.ncbi.nlm.nih.gov/

BLAST/. The NCBI Build 36 assembly was used for all information regarding

the mouse genome. Databases were accessed during July and August, 2006.

Note: Supplementary information is available on the Nature Genetics website.

ACKNOWLEDGMENTSWe acknowledge the flow cytometric expertise of B. Grimes, the technicalassistance of C. Swiderski and the editorial assistance of P. Thomason. This workwas supported by the US National Institutes of Health (grants AG020917,AG024950 and AG022859).

AUTHOR CONTRIBUTIONSY.L. performed the majority of the experimental work in the course of her Ph.D.dissertation project, contributed to the design of the study and contributed to thewriting of this paper. M.J. and B.A. contributed to the Lxn promoter SNPanalyses and identification of potential regulatory sites. H.G. generated thecongenic strains, carried out initial phenotyping of the congenics and contributedto the writing of this paper. G.V.Z. was largely responsible for the design of thestudy and writing of this paper.

COMPETING INTERESTS STATEMENTThe authors declare that they have no competing financial interests.

Published online at http://www.nature.com/naturegenetics

Reprints and permissions information is available online at http://npg.nature.com/

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