Stem Cells 2005;23:663–680 www.StemCells.com

Original Article

Correlation of Murine Embryonic Stem Cell Gene Expression Profiles

with Functional Measures of Pluripotency

Lars Palmqvist,a Clive H. Glover,b Lien Hsu,c Min Lu,c Bolette Bossen,c James M. Piret,b,d R. Keith Humphries,a,e Cheryl D. Helgasonc,f

aTerry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada; bMichael Smith Laboratories, University

of British Columbia, Vancouver, British Columbia, Canada; cDepartment of Cancer Endocrinology, BC Cancer Agency,

Vancouver, British Columbia, Canada; Departments of dChemical and Biological Engineering, eMedicine, and fSurgery,

University of British Columbia, Vancouver, British Columbia, Canada

Key Words. Embryonic stem cells • Markers • Pluripotency • Leukemia inhibitory factor • Gene expression • Microarray

Correspondence: Cheryl D. Helgason, Ph.D., Department of Cancer Endocrinology, BC Cancer Agency, 675 West 10th Avenue, Vancou-ver, BC, Canada, V5Z 1L3. Telephone: 604-675-8011; Fax: 604-675-8183; e-mail: chelgaso@bccrc.ca Received July 13, 2004; accepted for publication January 13, 2005. ©AlphaMed Press 1066-5099/2005/$12.00/0 doi: 10.1634/stemcells.2004-0157

Abstract Global gene expression profiling was performed on murine embryonic stem cells (ESCs) induced to differentiate by removal of leukemia inhibitory factor (LIF) to identify genes whose change in expression correlates with loss of plu-ripotency. To identify appropriate time points for the gene expression analysis, the dynamics of loss of pluripotency were investigated using three functional assays: chimeric mouse formation, embryoid body generation, and colony-forming ability. A rapid loss of pluripotency was detected within 24 hours, with very low residual activity in all assays by 72 hours. Gene expression profiles of undifferentiated ESCs and ESCs cultured for 18 and 72 hours in the absence of LIF were deter-mined using the Affymetrix GeneChip U74v2. In total, 473 genes were identified as significantly differentially expressed, with approximately one third having unknown biological

function. Among the 275 genes whose expression decreased with ESC differentiation were several factors previously identified as important for, or markers of, ESC pluripotency, including Stat3, Rex1, Sox2, Gbx2, and Bmp4. A significant number of the decreased genes also overlap with previously published mouse and human ESC data. Furthermore, sev-eral membrane proteins were among the 48 decreased genes correlating most closely with the functional assays, including the stem cell factor receptor c-Kit. Through identification of genes whose expression closely follows functional properties of ESCs during early differentiation, this study lays the foun-dation for further elucidating the molecular mechanisms reg-ulating the maintenance of ESC pluripotency and facilitates the identification of more reliable molecular markers of the undifferentiated state. Stem Cells 2005;23:663–680

Introduction Embryonic stem cells (ESCs) are characterized by their ability

to both self-renew and differentiate [1, 2]. However, the molec-

ular mechanisms that regulate the decision between these two

processes are poorly understood. Mouse ESCs were originally

isolated from the inner cell mass (ICM) of preimplantation blas-

tocysts [3, 4] and can be maintained in cell culture indefinitely

without loss of their broad pluripotent differentiation capacity as

determined by their ability to give rise to all three germ layers

both in vitro and in vivo [2]. The more recent establishment of

human ESC lines [5] has further increased the interest in ESCs

because they raise hope of an unlimited source of cells for tis-

sue engineering and cell therapies in the future. However, real-

ization of this potential requires an increased knowledge of the

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664 Genetic Correlates of Murine ESC Pluripotency

molecular mechanisms governing self-renewal and pluripotency

to guide the development of processes that control the expansion

and differentiation of stem cells ex vivo.

Unlike hematopoietic stem cells, for which quantitative

assays of stem cell potential have been defined and validated, no

such assays currently exist for ESCs. In the murine system, self-

renewal is measured by the ability of mouse ESCs to continuously

proliferate in culture while maintaining an undifferentiated col-

ony morphology [6]. The most rigorous in vivo assay to establish

functionality of cultured mouse ESCs is blastocyst injection and

measurement of their ability to give rise to chimeric mice because

it requires ESC contribution to all adult tissue, including germ

cells [1]. However, injection of 10 to 15 ESCs into a single blasto-

cyst does not provide a quantitative measure of stem cell potential

at the single-ESC level. Two in vitro assays have been used exten-

sively as surrogates for chimera formation when testing culture

reagents or examining the consequences of genetic manipulation.

The colony-forming cell (CFC) assay is used to determine the

plating efficiency of ESC populations under various conditions

and thus may be considered indicative of self-renewal potential.

Formation of embryoid bodies (EBs) can be performed at a clonal

level in vitro and reflects multilineage differentiation potential

[7]. The correlation between these in vitro assays and chimera

generation has not been determined. Assessment of pluripotency

has also relied on the expression of selected molecular markers.

For murine ESCs, these have included alkaline phosphatase, the

POU transcription factor Oct-4, and stage-specific embryonic

antigen 1 (SSEA-1) [8]. However, the correlation between marker

expression and the various functional assays has not been exten-

sively studied. Knowledge of the intricate mechanisms regulat-

ing ESC pluripotency and differentiation potential is currently

limited to a few signaling pathways (i.e., leukemia inhibitory fac-

tor [LIF]) and regulatory factors (i.e., Oct-4 and Nanog). Thus,

very little is known about the tolerance limits of different culture

conditions for maintaining stem cell function during expansion

or how these relate to altered gene expression patterns in ESCs.

Identification of molecular markers that correlate with pluripo-

tency would be invaluable to enrich for the desired cells, as well as

to monitor their maintenance during expansion protocols.

Achieving the goal of defining the core stem cell regulatory

network requires a precise characterization of the functional

capacities of the cells for which the transcriptional profile is

described. In this study, we established gene expression profiles

during early differentiation of the well-defined R1 ESC line [9]

and correlated gene expression changes with both phenotypic

and functional assessment of the same cells. Functional capac-

ity was determined by blastocyst injections for chimeric mouse

formation, EB assays, and CFC counts. Undifferentiated ESCs

and ESCs cultured without LIF for 18 or 72 hours were cho-

sen for gene-array analysis. We identified 473 unique genes as

significantly differentially expressed during early ESC differ-

entiation, and approximately one third of these have unknown

biological function. Among the 275 genes whose expression

decreased with ESC differentiation were several factors pre-

viously identified as important for, or markers of, ESC pluri-

potency, including Stat3, Rex1, Sox2, Gbx2, and Bmp4. A sig-

nificant number of the decreased genes also overlapped with

previously published mouse and human ESC data. Reverse

transcription–polymerase chain reaction (RT-PCR) valida-

tion showed high correlation with the gene-array data, and sev-

eral genes were also shown to have similar changes after LIF

removal in two other murine ESC lines. Expression of the com-

monly used ESC markers Oct-4 and SSEA-1 was also exam-

ined in parallel with the functional assays. However, a close

correlation was not observed. Interestingly, among a subset of

48 decreased genes that showed the closest correlation with the

functional assays was the stem cell factor (SCF) receptor c-Kit

that can be a useful marker of undifferentiated ESCs.

Materials and Methods

Growth of the Mouse ESC Lines and Mouse Embryonic FibroblastsThe R1 [9], J1 [10], and EFC [11] ESCs were routinely main-

tained at 37°C humidified air with 5% CO2 on a layer of irra-

diated mouse embryo fibroblasts (MEFs) and fed daily with a

complete change of ESC maintenance medium consisting of

high-glucose Dulbecco’s modified Eagle’s medium (DMEM)

(all reagents obtained from StemCell Technologies Inc. [STI],

Vancouver, British Columbia, Canada, unless otherwise indi-

cated) supplemented with 15% ESC-tested fetal bovine serum

(FBS), 0.1 mM nonessential amino acids, 2 mM glutamine,

1,000 U/ml LIF, 100 U/ml penicillin, 100 μg/ml streptomy-

cin, and 100 μM monothioglycerol (MTG) (Sigma, Oakville,

Ontario, Canada). For gene expression profiling, R1 ESCs were

from passage 14 and had been frozen at 106 cells per vial. Cells

were passaged every second day in maintenance cultures. To

passage cells, a single-cell suspension was generated by treat-

ment with 0.25% trypsin and 1 mM EDTA (T/E) (Invitrogen

Life Technologies, Burlington, Ontario, Canada) for 5 minutes

until cells detached from the culture vessel surface. T/E activ-

ity was then quenched with DMEM supplemented with 10%

FBS. The cells were centrifuged at 1,200 rpm for 7 minutes and

resuspended in ESC maintenance medium. Viable cells were

plated at 1 × 106 per 100-mm dish on irradiated MEFs and cul-

tured for a further 48 hours at 37°C, 5% CO2 before harvest for

RNA isolation, differentiation, or functional assessment. In

subsequent experiments, all cells used were within five pas-

sages of initial thawing.

MEFs were maintained at 37°C humidified air with 5% CO2

Palmqvist, Glover, Hsu et al. 665

in DMEM supplemented with 10% FBS, 100 U/ml penicillin,

100 μg/ml streptomycin, and 100 μM MTG. Cells to be irra-

diated were trypsinized, resuspended in 2 ml of medium, and

exposed to 60 Gy from an x-ray source before replating for use as

feeder cells. Alternatively, MEFs for RNA isolation were grown

in ESC maintenance media, trypsinized, pelleted, and placed in

Trizol reagent (Invitrogen).

Preparation of ESCs for Differentiation ESCs were thawed and cultured for two passages over 96 hours as

described above. To prepare cells for differentiation, they were

harvested and washed as described above, resuspended in ESC

maintenance medium, and preplated on tissue culture plates for

1 hour at 37°C, 5% CO2 to deplete contaminating MEFs. At the

end of this preplating step, the nonadherent ESCs were discarded

and the loosely adherent ESCs were collected by gently washing

the surface of the tissue culture plate. Cells were pelleted by cen-

trifugation, and viable cell numbers were determined. The fre-

quency of contaminating MEFs in the undifferentiated (day 0)

ESC samples was estimated to be less than 0.2% based on cell

size during counting.

A portion of the preplated ESCs was suspended at a density

of 1 to 2 × 107 cells per 50 ml in liquid differentiation medium

consisting of Iscove’s modified Dulbecco’s medium (IMDM),

15% FBS selected for its ability to support ESC differentiation,

2 mM glutamine, 150 μM MTG, and 40 ng/ml murine STI and

plated into 4 × 100-mm Petri-style culture dishes (Falcon). Cells

were cultured overnight (18 hours) at 37°C, 5% CO2. The follow-

ing morning, EBs, both in suspension and loosely attached, were

harvested and allowed to settle to the bottom of a 50-ml conical

tube for approximately 10 minutes. The supernatant, containing

mainly single cells, was removed, and the spontaneously pellet-

ing EB fraction was collected by centrifugation at 1,200 rpm for 7

minutes. EBs were disrupted by incubation in T/E for 3 minutes at

room temperature followed by passage through a 21-gauge needle

to achieve single-cell suspensions. The cells were washed with

10% DMEM and suspended in 2 ml of IMDM to count.

The remainder of the preplated ESCs was plated at a density

of 104 cells per 35-mm low-adherence Petri dish in IMDM-based

ES differentiation methylcellulose consisting of 0.9% methylcel-

lulose, 15% FBS, 2 mM glutamine, 150 μM MTG, and 40 ng/ml

murine SCF. Cultures were grown for 3 days and all EBs in each

dish were harvested by carefully flooding the dish with IMDM

and collecting the methylcellulose/EB solution. EBs were washed

twice in DMEM plus 10% FBS to remove the residual methylcel-

lulose and were then pooled and disrupted as described above.

Blastocyst Injection C57Bl/6J mice (used as blastocyst donors) and B6C3 F1 females

(used as pseudopregnant blastocyst recipients) were purchased

from the in-house breeding program at the BC Cancer Agency

Animal Resource Center. All mice were maintained with ster-

ilized food, water, and bedding. All protocols were conducted

according to guidelines set forth by the Canadian Council for

Animal Care and approved by the Animal Care Committee at the

University of British Columbia. R1 ESCs were thawed and main-

tained for two passages on irradiated MEFs with daily feeding of

maintenance medium. After the second passage, cells were har-

vested and subjected to 1 hour of preplating on plastic to deplete

remaining MEFs. Cells were then plated onto gelatin-coated tis-

sue culture dishes and fed with maintenance medium without LIF

for the indicated lengths of time. To produce chimeras, 15 test

cells (either ESCs or differentiated) were injected into 3.5-day

blastocysts from C57Bl/6 mice as described previously [12] and

implanted back into pseudopregnant recipient females to gestate

normally. Coat color was used to identify chimerism of the result-

ing pups. Two independent experiments were performed.

Embryoid Body Formation Assays Single-cell suspensions were collected on day 0 or prepared, as

outlined above, during differentiation. Defined numbers of cells

(500 to 20,000, depending on time after LIF removal) were plated

in 35-mm Petri-style dishes in the ESC differentiation methyl-

cellulose medium described above to determine the efficiency

of EB formation. EB numbers were determined microscopically

after 5–6 days of culture, and colonies were qualitatively scored

as large or small. Three independent experiments were per-

formed. The percent EB formation efficiency was calculated by

dividing the total number of EBs formed by the number of cells

plated multiplied by 100.

CFC Assay Single-cell suspensions collected on day 0 or during differen-

tiation were plated at various densities (500 to 20,000 cells per

gelatinized 60-mm gridded tissue culture dish) to determine ESC

CFC plating efficiency. Colonies were microscopically enumer-

ated after 5–6 days of growth. To enable differential assessment

of the colonies, the protocols outlined in the alkaline phosphatase

detection kit (Sigma; 86-R) were modified for staining in 60-mm

dishes. In brief, the medium was removed from the dishes, and

1 ml of room temperature fixative (prepared as per the Sigma

protocol) was added for 30 seconds. The fixative was removed,

and colonies were washed with 2 ml phosphate-buffered saline

(PBS). Next, 1.5 ml alkaline dye mixture (prepared as per the

Sigma protocol) was added; the dish was incubated in the dark

at room temperature for 15 minutes. Finally, the dye mixture was

removed and the colonies were covered with 2 ml PBS for micro-

scopic evaluation. The numbers of stained (undifferentiated) ver-

sus unstained (differentiated) colonies were determined. Three

independent experiments were performed. The percent CFC

666 Genetic Correlates of Murine ESC Pluripotency

plating efficiency was calculated by dividing the total number of

alkaline phosphatase–positive colonies by the number of cells

plated multiplied by 100.

RNA Extraction and Array Hybridization Single-cell suspensions of test cells were prepared as described

above and resuspended in Trizol (Invitrogen Life Technologies)

at a density of 107 cells per ml. RNA was extracted following the

manufacturer’s instructions. Standard Affymetrix amplifica-

tion protocols were used to prepare probe RNA for Affymetrix

arrays with 5 μg of starting total RNA. Biotin-labeled amplified

RNA was fragmented, and hybridization cocktails were prepared

according to the Affymetrix protocol. The mouse GeneChip

(MG) U74v2 chips were hybridized on a GeneChip System

(Affymetrix) at the Genome Science Centre, BC Cancer Agency,

Vancouver, British Columbia, Canada, according to the manufac-

turer’s instructions. All experiments were performed in triplicate

with the exception of the MEF samples, which were analyzed in

duplicate. The MIAME (minimal information about a microarray

experiment) guidelines were followed for data presentation [13].

Data Analysis The Affymetrix software MicroArray Suite 5.0 (MAS 5.0)

was used to generate absolute expression estimates (absence/

presence calls) from the raw data. Software default thresholds

were used to determine the present (P) or absent (A) calls (α1

= 0.04, α2 = 0.06, and τ = 0.015). The data obtained from MAS

5.0 were then normalized and further analyzed in the Gene-

Spring software version 6.2 (Silicon Genetics, Redwood City,

CA). Per-chip normalization was done as follows: Values below

0.01 were set to 0.01, and then each measurement was divided

by the 50th percentile of all measurements in that sample.

Per-gene normalization was done as follows: Each gene was

divided by the median of its measurements in all samples. If

the median of the raw values was less than 10, then each mea-

surement for that gene was divided by 10. We judged genes to

be differentially expressed during ESC differentiation only

when the difference in expression between two time points was

at least twofold, the gene was identified by MAS 5.0 as pres-

ent in two out of three replicates or present or marginal in all

three replicates at the time point with the highest expression

level, and the extent of difference in expression was statisti-

cally significant (p < .05 in a parametric Welsh analysis of vari-

ance [ANOVA] t-test). Classification of genes into functional

categories was done by collecting annotations and keywords

with the Onto-Express Tool (http://vortex.cs.wayne.edu:8080/

ontoexpress) [14], Affymetrix NetAffx (http://www.affymetrix.

com/analysis/index.affx), and the Simplified Gene Ontology

Tool included in the GeneSpring 6.2 Software. The GenMapp

2.0 software tool was used to analyze signaling pathways (http://

www.genmapp.org).

Quantitative RT-PCR RNA was isolated using Trizol, and the samples were then treated

with DNase I (amplification grade) before RT-PCR according to

the manufacturer’s recommendations (Invitrogen). Complemen-

tary DNA (cDNA) was generated by RT with random primers and

the Superscript II enzyme and RNase inhibitor (Invitrogen). The

RT reaction was incubated at 42ºC for 50 minutes followed by 15

minutes at 70ºC. The cDNA was stored at –20ºC for subsequent

quantitative PCR analysis. Gene transcripts were quantified by

real-time PCR using the iCycler apparatus (BioRad Inc., Hercu-

les, CA) and were detected with SYBR Green as fluorochrome (IQ

SYBR Green Supermix, BioRad Inc.). Gene sequences for primer

design were obtained from the NCBI Reference Sequences data-

base (http://www.ncbi.nlm.nih.gov/RefSeq/). Primers were cho-

sen using the Primer3 software (http://www.broad.mit.edu/cgi-bin

/primer/primer3_www.cgi), and the specificity of all primer

pairs was tested with electronic PCR using the mouse genome

and the mouse transcript database (http://www.ncbi.nlm.nih.

gov/sutils/e-pcr/reverse.cgi). Primer sequences are provided in

the supplemental material (supplementary online Table 1). Prim-

ers were ordered and synthesized at Invitrogen Life Technologies

(http://www.invitrogen.com/). The relative expression changes

were determined with the 2–ΔΔCT method [15], and the housekeep-

ing glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene

transcript was used to normalize the results. PCR efficiency was

tested for each primer pair by dilution series of cDNA to make

sure that the efficiency was appropriate for the 2–ΔΔCT method (i.e.,

95% or above). To identify amplification of any contaminating

genomic DNA and ensure the specificity and the integrity of the

PCR product, melt-curve analyses were performed on all PCR

products. No products were obtained with real-time PCR from

RNA samples when RT was omitted. Samples without template

were included for each primer pair to identify contamination.

Pearson’s correlation and Deming regression analysis were used

to determine correlation and agreement, respectively, between

the microarray and quantitative RT-PCR results using the Excel

plug-in software Analyse-It v1.73.

Flow Cytometry Antibodies used for phenotype analysis included phycoerythrin

-conjugated anti-CD117 (c-Kit, clone ACK45; BD Pharmin-

gen, San Diego) as well as purified anti-SSEA-1 (Clone MC-

480; Chemicon International Inc., Temecula, CA), which was

detected using a fluorescein isothiocyanate–conjugated anti-

mouse immunoglobulin M antibody (BD Pharmingen). Single-

cell suspensions collected on day 0 or prepared from differen-

tiating ESCs were blocked for 10 minutes on ice with 5 μg/ml

anti-mouse CD16/CD32 (Fc Block, BD Pharmingen) in PBS

(STI) plus 2% FBS (PF). Cells were washed once with PF and

then incubated on ice for 20 minutes with the primary mono-

clonal antibody. Cells were then washed once, incubated with

Palmqvist, Glover, Hsu et al. 667

the secondary antibody if needed, washed again, and analyzed

by flow cytometry using a FACSCalibur flow cytometer and

CELLQuest software (BD Pharmingen). The forward- ver-

sus side-scatter profile was used to gate on viable cells, and an

unstained sample was used to determine appropriate gating for

quantification of expression. Cells to be stained for Oct-4 were

resuspended in 100 μl of Hanks’ buffered saline solution (STI)

plus 2% FBS (HF) and fixed with 100 μl of IntraPrep Permea-

bilization Reagent 1 (Immunotech, Westbrook, ME) for 15

minutes at room temperature. Cells were then washed with HF

and permeabilized with IntraPrep Permeabilization Reagent 2

for 5 minutes before incubation with a 1:100 dilution of mouse

anti-mouse Oct3/4 monoclonal antibody (Transduction Labo-

ratories, Lexington, KY) for 15 minutes at room temperature.

Cells were washed with HF before staining with allophycocya-

nin-labeled anti-mouse immunoglobulin G1 (BD Pharmingen).

Samples were analyzed by flow cytometry as outlined above.

Comparison with Other Gene-Array Data Genes indicated as “decreased” in supplementary online Table 2

were split into three separate lists based on the statistical signifi-

cance of the fold change between 0 and 18 hours, 0 and 72 hours,

and 18 and 72 hours. Each of these three gene lists was compared

with the following data tables: Bhattacharya et al. [16], supple-

mentary online Table 2; Brandenberger et al. [17], supplementary

online Table 2; Ivanova et al. [18], supplementary online Table

1 (genes marked as either I or D); Ramalho-Santos et al. [19],

database S1; Sato et al. [20], database 1; Sharov et al. [21], dataset

S7; Sperger et al. [22], supporting supplementary online Table 6;

Kelly et al. [23], supplementary online Table 1; and Ginis et al.

[24], supplementary online Table 3A. Comparison between [18]

and [19] was performed on the basis of Affymetrix gene IDs. In

[19], supplementary online Table 1 was refiltered as outlined in

the original publication. Comparisons with human ES data sets

[16, 17, 20, 22] was done by converting public ID references from

the human data sets into murine Affymetrix codes using EnsMart

(http://www.ensembl.org/Multi/martview). For [21], custom U

codes were converted to Unigene codes using the translation tool

available (http://lgsun.grc.nia.nih.gov/geneindex/). Groups F, I,

L, and O were chosen because these were the lists that contained

genes expressed in ESCs grown in LIF but not expressed in ESCs

grown without LIF for 4 or 18 hours. For [23], Genbank codes

were converted to Affymetrix codes using EnsMart. Following

automated comparisons performed as described above, manual

comparison between known genes was performed using gene

names to ensure accurate comparison.

Results

Pluripotency During Early Differentiation We hypothesized that loss of ESC pluripotency as defined by mea-

surable functional readouts would correlate with significant alter-

ations in gene expression. Identification of these gene expression

changes would thus provide important insights into the genetic

regulation of ESC pluripotency and facilitate the identification

of new molecular markers of the undifferentiated ESC state.

We relied on comparisons of the three measures of ESC poten-

tial (chimera formation, EB formation, and CFC assay) to select

time points for analysis of gene expression profiles. Undifferenti-

ated ESCs were cultured in medium containing LIF on irradiated

primary MEF, which supply several as-yet unidentified factors

that enhance the plating efficiency of the ESCs as well as assist

in the maintenance of the undifferentiated state. Preplating of

ESCs removes the MEF and enriches for ESCs with the capacity

to contribute to the developing blastocyst. It has been suggested

that those ESCs capable of loosely attaching to the feeder layer

in a short (i.e., 1 hour) period of time have the highest likelihood

of forming colonies (i.e., self-renewing) and thus may also be the

most competent at contributing to the germ-line after blastocyst

injection [25]. We thus elected to use only preplated, loosely

adherent mouse ESCs for our analyses.

The baseline activities for undifferentiated ESCs in the three

different assays were first determined. Undifferentiated, pre-

plated R1 ESCs yielded 100% chimeric pups after blastocyst

injection (27 blastocysts injected; six born and analyzed in two

independent experiments), 6.9% ± 1.0% of plated cells differen-

tiated into EBs in the EB formation assay, and 12.50% ± 2.2%

of plated cells gave rise to alkaline phosphatase–positive ESC

colonies in the CFC assay. These results were within the normal

range for the R1 cell line. ESC differentiation was then initiated

by LIF removal and replating without MEF. The morphology of

the ESCs before and after LIF removal is shown in Figure 1. At 18

and 24 hours after MEF and LIF removal, the ESCs looked very

similar to one another and did not exhibit any clear signs of dif-

ferentiation. Morphological differentiation was first apparent at

48 hours, and EBs could be seen after 72 hours. Despite the lack of

appreciable phenotypic differentiation within the first 24 hours,

there were significant changes in the functional properties of the

ESCs. Cultured cells were harvested at various time points during

this culture period and analyzed in the three different assays. The

blastocyst injection assay showed a rapid decrease in the number

of chimeras obtained after initiation of ESC differentiation (Fig.

2A). Only 28% of born pups (84 injected, 25 born and analyzed

in two independent experiments) were chimeras when ESCs had

differentiated for 24 hours, and less than 5% were chimeras after

72 hours of differentiation (66 injected, 29 born and analyzed in

two independent experiments). The EB formation assay (Fig. 2B)

showed approximately 5.5% ± 1.0%, 3.7% ± 0.3%, and 0.3% ±

0.1% readout at 18, 24, and 72 hours after LIF removal, respec-

tively. In contrast, the frequency of cells replating in the CFC

assay increased slightly during the first 24 hours but subsequently

declined rapidly such that only 1.3% ± 0.3% retained this activity

668 Genetic Correlates of Murine ESC Pluripotency

at 72 hours (Fig. 2C). In summary, all three assays showed clearly

that most differentiation potential and self-renewing capacity was

gone after 72 hours of differentiation. However, there was a high

degree of variation during the first 24 hours amongst the in vitro

and in vivo assays, with the EB formation assay correlating most

closely with chimeric mouse formation. For the gene expression

profiling, because both the EB formation and chimera assays

showed a pronounced decrease within the first 18–24 hours, we

elected to use the earlier time point, along with 72 hours of differ-

entiation, to compare against the undifferentiated R1 ES.

In parallel with the functional assays, the expression pat-

terns of two markers commonly used to identify undifferentiated

ESCs, the POU transcription factor Oct-4 and SSEA-1, were also

analyzed to establish the level of correspondence in the read-

outs using each method. Although Oct-4 and SSEA-1 have been

extensively used in ESC research, their expression patterns dur-

ing ESC differentiation have not been studied in detail. Oct-4

is used as a marker for ESCs because of its requirement in ESC

self-renewal [26]. The precise expression level of Oct-4 is impor-

tant for determining ESC fates, and repression of Oct-4 induces

loss of pluripotency and dedifferentiation to trophectoderm [26].

However, forced constitutive expression of Oct-4 cannot prevent

ESC differentiation, and a less than twofold increase in expres-

sion actually causes differentiation into primitive endoderm and

mesoderm [26]. Thus, a critical amount of Oct-4 is required to

sustain stem cell self-renewal but is not sufficient to prevent dif-

ferentiation. SSEA-1 is a glycoprotein expressed during early

embryonic development and by undifferentiated ESCs. However,

the precise role of SSEA-1 in pluripotency and self-renewal has

not been defined. ESCs selected for expression of SSEA-1 and

platelet endothelial cell adhesion molecule 1 are enriched for

cells that differentiate predominantly into epiblast cells in chime-

ric embryos [27]. In the present study, protein expression of both

SSEA-1 and Oct-4 remained relatively unchanged throughout the

first 48 hours of differentiation (Fig. 2D). At 120 hours after LIF

removal, 18.5% ± 1.1% of the cells retained expression of SSEA-1,

whereas 40.6% ± 6.6% of the cells continued to express Oct-4.

Thus there was no clear correlation between expression of these

two markers and the various ESC functional assays.

Gene-Array Analysis Cultured R1 ESCs from matched passage numbers were col-

lected in three separate experiments at 0, 18, and 72 hours of

differentiation after LIF removal and were analyzed using the

Figure 1. Embryonic stem cell (ESC) morphology. Morphology of

the R1 ESCs grown on mouse embryo fibroblasts (MEFs) with leu-

kemia inhibitory factor (LIF) is shown. ESCs were followed for 72

hours after MEF and LIF removal, and pictures were taken at the indi-

cated time points and with the indicated resolution.

Figure 2. Assays of embryonic stem cell (ESC) pluripotency. Com-

parison of in vitro and in vivo functional measures of ESC poten-

tial with expression of the commonly used ESC markers Oct-4 and

stage-specific embryonic antigen 1 (SSEA-1). R1 ESCs were thawed,

cultured, and assayed as outlined in Materials and Methods. The fre-

quency of cells capable of (A) generating chimeric mice (summary

of two independent experiments), (B) giving rise to embryoid bod-

ies (summary of three independent experiments), or (C) giving rise

to colonies in the colony-forming cell assay (summary of three inde-

pendent experiments) is shown as a function of time after leukemia

inhibitory factor removal. (D): Flow cytometric analysis (summary

of three independent experiments) was used to determine the per-

centage of gated cells expressing cell-surface SSEA-1 and intracellu-

lar Oct-4 at the same time points. Data are the mean ± standard error

of the mean for replicated experiments.

Palmqvist, Glover, Hsu et al. 669

Affymetrix GeneChip MG-U74v2 array containing 36,767 dif-

ferent probe sets. Duplicate samples of the MEF feeders were

also collected and analyzed to assess any possible contamination

of the undifferentiated ESCs. Hybridization, scanning, and pro-

duction of raw data files were performed according to standard

protocols. The MAS 5.0 software was used for the initial scal-

ing and expression analysis. The data were then normalized and

further analyzed using the GeneSpring software. To validate the

reproducibility and the overall variation of the data, hierarchical

clustering analysis was performed. The data were first filtered

for genes present in at least one of the three time points (present

in at least two out of three replicates), resulting in 13,002 differ-

ent probe sets. The average number of present genes for each time

point was 12,818 (coefficient of variation [CV], 6%) in undiffer-

entiated ESCs, 11,806 (CV, 4%) at 18 hours, and 12,297 (CV, 1%)

at 72 hours after LIF removal. The number of expressed genes at

the different time points was not statistically significantly dif-

ferent. Hierarchical clustering was applied to the reduced gene

set on individual array samples (three replicates for each time

point) using Pearson’s correlation and average linkage cluster-

ing as implemented in GeneSpring. The individual samples

from the three experiments clustered tightly together according

to their respective time points, as seen in Figure 3, indicating

that the overall interexperimental variation was low. The clus-

tering also reflects the temporal progression of the ESC differ-

entiation. As expected, the first two time points (0 and 18 hours)

clustered more closely together, whereas the 72-hour time point

showed a more distinct expression pattern, resulting in a greater

relative distance from the other two time points, consistent with

the functional data (Fig. 2).

Genes that were differentially expressed after LIF removal

were determined using the following criteria: The difference in

expression level between two time points was at least twofold, the

gene was present in all three replicates at the time points with the

highest abundance, and the extent of difference in expression was

statistically significant (p < .05) in a parametric Welsh ANOVA t-

test. With this approach, 473 unique genes were identified as sig-

nificantly differentially expressed (275 decreased, 194 increased,

and 4 both decreased and increased) during early ESC differen-

tiation after LIF removal (complete gene lists in the supplemen-

tal data, supplementary online Table 2). Unigene and RefSeq IDs

were used to exclude redundant probe sets on the array and to get

the true number of affected genes.

Only preplated, loosely adherent ESCs were used in our

experiments, and visual assessment of MEF contamination of

undifferentiated ESCs suggested it was consistently less than 1 in

500. However, even with these measures, we sought to exclude the

possibility that contaminating MEF cells may have distorted the

data. Duplicate samples of MEFs were therefore also analyzed

on the U74v2 GeneChip. The data from both the MEF and the R1

ESC was scaled in MAS 5.0 and normalized in GeneSpring 6.2

before 1% of the raw value (five times more than the estimated

contamination) obtained for the gene in MEF was subtracted

from the value of the same gene in the undifferentiated R1 ESCs.

The analysis steps to find differentially expressed genes were then

performed as described above. Only genes detected as decreased

during differentiation in the original analysis were reanalyzed.

Genes whose expression increased during differentiation would

not be affected by MEF contamination in a way that would give

false-positive results. This evaluation indicates that none of the

genes that showed a significant twofold or greater decrease in the

initial analysis lost their significance after MEF subtraction (data

not shown) and suggests that the level of MEF contamination was

not sufficient to distort the ESC gene expression data.

Gene Expression Validation The expression patterns of some genes previously implicated in

maintaining ESC pluripotency and self-renewal were analyzed

to validate the data and the approach to identify differentially

expressed genes (Table 1). Mouse ESCs are usually cocultured

on a feeder layer of irradiated MEFs. In addition to providing a

matrix for attachment, MEFs produce LIF, required for propa-

gation of pluripotent mouse ESCs [28]. LIF-null MEFs cannot

support self-renewal [29]. However, LIF also needs to be com-

plemented by fetal calf serum to block differentiation. LIF binds

to the gp130 receptor that leads to activation of the transcription

factor Stat3 [1]. Stat3 was clearly detected in undifferentiated R1

ESCs, and LIF removal decreased Stat3 expression with the most

pronounced effect during the first 18 hours (49% reduction). This

was also seen for two other genes involved in the LIF/gp130 path-

way, the Oncostatin M receptor, Osmr, and the interleukin 6 sig-

Figure 3. Distance tree. Hierarchical clustering of the individual

gene-array samples was carried out using Pearson’s correlation and

average linking clustering to determine reproducibility and interex-

perimental variability. Relative distance values are shown.

670 Genetic Correlates of Murine ESC Pluripotency

nal transducer, Il6st. A known Stat3 target gene, Pim1 [30], was

also decreased significantly at the transcriptional level. Taken

together, these observations confirm that the LIF/gp130/Stat3

pathway was rapidly shut down after MEF and LIF removal. The

bone morphogenic proteins can act in combination with LIF to

sustain self-renewal and preserve multilineage differentiation,

chimera contribution, and germ line transmission properties [31].

Bmp4 transcript levels were significantly decreased during dif-

ferentiation. However, the onset of the decrease was later than

for Stat3 (between 18 and 72 hours, 80% reduction). The same

was seen for Rex-1/Zfp42, known to be highly expressed in undif-

ferentiated ESCs and downregulated after retinoic acid–induced

differentiation [32, 33]. A 90% reduction in Rex-1/Zfp42 expres-

sion was seen between 18 and 72 hours after LIF removal. Tran-

script abundance of the Akp2 gene coding for alkaline phospha-

tase, commonly used as a marker for undifferentiated ESCs, was

also decreased significantly (55% reduction between 18 and 72

hours). The POU transcription factor message, pou5f1, coding for

Oct-4 was highly expressed in undifferentiated ESCs but was not

changed significantly during the first 72 hours after LIF removal

in keeping with the protein expression data (Fig. 2D). Transcript

levels of the embryonal stem cell–specific gene 1 (Esg-1 or devel-

opmental pluripotency associated gene 5, Dppa5) did not change

during differentiation. However, this observation is consistent

with the observation that Esg-1 probably is a downstream target

of Oct-4 and is downregulated slowly after Oct-4 suppression

[34]. The abundance of FoxD3, a gene expressed early in mouse

embryonic development, also remained unchanged during the

first 72 hours after LIF removal. The SRY-box containing tran-

scription factor Sox2 may act to maintain ESC pluripotency and

is expressed in the ICM, epiblast, and germ cells, just like Oct-4

[35]. Sox2 was significantly decreased (60% reduction between

18 and 72 hours, p = .0136). Sox2, together with Oct-4, is involved

in the regulation of fibroblast growth factor 4 (Fgf4), another fac-

tor confined to the ICM of the blastocyst [35]. Although Fgf4 tran-

scripts were not significantly decreased (p = .09), it was reduced

more than twofold (52% reduction between 18 and 72 hours). This

was also the case for the newly discovered marker of ESC plu-

ripotency Dppa3 [36], which decreased 78% between 0 and 72

hours (p = .073). Similarly, the regulatory factor Nanog, which

can rescue ESCs from LIF/Stat3 dependence and maintain Oct-4

expression [37, 38], was not quite significantly decreased during

the first 72 hours of differentiation (p = .07), and the reduction

in expression was less than twofold (41%). Several genes indica-

tive of ESC differentiation were increased after LIF removal. For

example, the mesoderm marker Brachyury [39] increased 15-

fold between 18 and 72 hours (p = .003). The ectoderm marker

Nestin [40] increased approximately threefold between 18 and 72

hours (p = 0.04), and the epithelial cell marker Prominin 1 [41]

increased fivefold between 18 and 72 hours (p = .0010). In conclu-

sion, most of these changes are consistent with the loss of ESC

pluripotency as measured in all three assays and indicate that the

thresholds used to define differentially expressed genes in this

study are reasonable.

RT-PCR Validation To further confirm the fidelity of the gene-array data, a set of 28

genes was selected and their transcript levels were tested using

quantitative RT-PCR in R1 ESCs before and after LIF removal.

The genes selected included some of the genes mentioned above,

as well as other genes increased, decreased, or unchanged after

LIF removal according to the gene-array results. The fold change

was calculated between 0 and 18 hours, 18 and 72 hours, and 0

and 72 hours, respectively. The individual RT-PCR results can be

found in the supplemental data (supplementary online Table 3).

The analysis revealed a high degree of correlation between the

gene-array data and the RT-PCR results (Pearson’s correlation,

r = 0.87, Fig. 4A), with a tendency that the PCR results showed

greater changes than the array suggested (proportional bias 1.2 in

a Deming method comparison analysis, not shown).

Table 1. Genes previously reported as enriched in undifferentiated ESCs or to be markers of ESC differentiation were compared with the genes identified as differentially expressed in the present study

Expression relative to 0 hrs after LIF removal

Gene symbol Accession # 18 hrs 72 hrs p value

Stat3 NM_011486 0.51 0.41 .0128

Osmr NM_011019 0.40 0.18 .0321

Il6st NM_010560 0.62 0.40 .0015

Pim1 NM_008842 1.08 0.36 .0106

Bmp4 NM_007554 0.99 0.40 .0051

Rex1/Zfp42 NM_009556 1.08 0.12 .0005

Akp2 NM_007431 1.24 0.55 .0168

Oct4 NM_013633 1.09 1.01 .4823

Sox2 NM_011443 0.90 0.41 .0136

Fgf4 NM_010202 1.39 0.67 .0902

Nanog XM_132755 0.82 0.59 .0690

FoxD3 NM_010425 1.74 0.95 .5490

Dppa3 NM_139218 1.06 0.24 .0731

Esg1/Dppa5 NM_025274 1.02 0.58 .1430

Brachyury NM_009309 0.48 7.3 .0034

Nestin NM_016701 0.97 2.78 .0384

Prominin 1 NM_008935 1.27 5.53 .0010

Relative expression levels compared with undifferentiated ESCs are listed. The p values for the most significant fold change from Welsh analysis of variance t-tests are listed.Abbreviations: ESC, embryonic stem cell; LIF, leukemia inhibi-tory factor.

Palmqvist, Glover, Hsu et al. 671

To determine if the gene expression changes observed in the

R1 ESCs are general and more broadly observed, the expression

patterns of 15 genes were followed for 72 hours after LIF removal

in two other ESC lines, J1 [10] and EFC [11], and compared with

the R1 ESC line using quantitative RT-PCR (Table 2). Overall,

there was a good correlation amongst all three ESC lines (Figs.

4B–4D). Specifically, RT-PCR analysis was able to verify the

expression changes of genes such as Lox, Ankrd1, and c-Kit that

showed significantly decreased transcript levels after 18 hours in

all three ESC lines tested. Similarly, Rex1, Sox2, Leftb, and Mtf2

were all changed in a similar fashion in the R1, J1, and EFC cell

lines. The RT-PCR results also confirmed that Oct-4 transcript

levels were not decreased significantly during the first 72 hours of

differentiation in any of the cell lines, in agreement with the gene-

array results and the protein level observed (Fig. 2D). In contrast,

although the decrease in Nanog transcripts was not quite signifi-

cant in R1 ESCs according to the gene array, the RT-PCR results

indicated a reduction. Nanog was reduced by 50%–70% after 72

hours in all three ESC lines according to the quantitative RT-PCR

analysis but consistent with delayed reduction in Nanog upon dif-

ferentiation (Table 2). Only two of the tested genes showed dif-

ferent expression patterns amongst the cell lines. The mesoderm

marker Brachyury and the homeobox transcription factor Pbx3

were both increased during differentiation in the R1 and J1 ESCs,

but not in the EFC cell line. This observation suggests that the

various ESC lines might follow slightly altered differentiation

pathways upon LIF removal.

Table 2. Comparison of relative expression levels obtained by quantitative real-time RT-PCR in the R1, J1, and EFC ESC lines during differentiation

Expression relative to 0 hrs after LIF removal

R1 ESC line J1 ESC line EFC ESC line

Gene symbol Accession # 18 hrs 72 hrs 18 hrs 72 hrs 18 hrs 72 hrs

Ankrd1 NM_013468 0.09 0.07 0.02 0.05 0.03 0.002

Lox NM_010728 0.13 0.11 0.09 0.01 0.07 0.008

Kit NM_021099 0.35 0.17 0.22 0.12 0.36 0.12

Leftb NM_010094 0.58 0.41 1.84 0.51 0.69 0.27

Pim1 NM_008842 0.81 0.48 0.66 0.39 0.48 0.22

Oct-4 NM_013633 0.84 1.11 1.27 1.57 2.00 2.46

Nanog XM_132755 0.91 0.53 0.62 0.29 0.59 0.23

Pim2 NM_138606 0.87 4.14 1.87 9.19 1.32 17.15

Rex1 NM_009556 0.90 0.05 1.07 0.01 0.97 0.005

Mtf2 NM_013827 1.00 0.30 0.93 0.13 0.68 0.10

Ptch NM_008957 1.15 0.19 2.00 0.13 1.68 0.23

Sox2 NM_011443 2.07 0.35 1.15 0.11 1.04 0.17

Hck NM_010407 2.30 0.05 1.11 0.01 1.19 0.03

Brachyury NM_009309 0.54 23.4 0.07 14.9 0.15 0.59

Pbx3 NM_016768 2.93 3.73 1.04 2.38 0.24 0.55

Relative expression levels were calculated between undifferentiated ESCs (0 hrs) and the 18- and 72-hr time points, respectively. The RT-PCR results were calculated with the 2–ΔΔCT method. GAPDH was used as an endogenous control to normalize the data. Results represent the mean from two independent RT-PCR reactions.Abbreviations: ESC, embryonic stem cell; LIF, leukemia inhibitory factor; RT-PCR, reverse transcription–polymerase chain reaction.

Figure 4. Correlation between gene array and quantitative reverse

transcription–polymerase chain reaction (RT-PCR). (A): Pearson’s

correlation analysis was done on the log ratio values obtained from

the quantitative real-time RT-PCR and the gene-array fold changes

(n = 84). (B, C, D): Comparison of quantitative real-time RT-PCR

results from the three different embryonic stem cell lines are shown.

Pearson’s correlation analysis was done on the log ratios of the values

obtained with the 2–ΔΔCT method (n = 45 in each comparison).

672 Genetic Correlates of Murine ESC Pluripotency

These validation analyses demonstrate that the early changes

during differentiation uncovered by the gene-array analysis could

be verified with an independent method and could in most cases

be observed in multiple ESC lines. Taken together, they provide

confidence in our approach to identify differentially expressed

genes with a high likelihood of exhibiting true expression level

changes during the loss of ESC pluripotency.

Functional Classification of Differentially Expressed Genes It is likely that genes showing similar functional properties and

expression patterns form interacting networks that contribute

to the phenotypic and functional characteristics of the cells of

interest. Functional classification of the differentially expressed

genes into appropriate biological processes was thus performed

using the NetAffx and GeneOntology Express tools as well as

the simplified gene ontology tool in the GeneSpring software

package. The differentially expressed genes were separated into

13 main categories (Fig. 5A; see supplementary online Table 4

for complete lists). Many differentially expressed genes were, as

expected, classified as being involved in development and dif-

ferentiation (61 genes, 10%) or directly or indirectly involved in

cell-cycle control and cell proliferation (32 genes, 5%). Further-

more, at least 81 genes (13%) were classified as being involved in

intracellular signal transduction, cell–cell signaling, or response

to external stimuli (supplementary online Table 4).

A closer look at the signaling pathways affected during ESC

differentiation revealed that the Yamaguchi sarcoma viral onco-

gene gene (Yes) was decreased significantly between 0 and 72

hours (60%). Yes has recently been shown to be regulated by LIF

and to be important for ESC self-renewal [42]. Yes is a gene cod-

ing for an Src tyrosine kinase expressed in both mouse and human

ESCs and is downregulated when these cells differentiate [42].

Another significantly decreased factor was the Notch ligand Jag-

ged-1 (55% reduction between 0 and 18 hours), which has been

implicated in hematopoietic stem cell self-renewal [43]. Jagged-1

is involved in embryonic vascular development, and a Jag1 knock-

out is embryonic lethal [44].

A signaling pathway that is of particular interest during ESC

differentiation is the mitogen-activated protein kinase (MAPK)

pathway. The self-renewal of ESCs is influenced by the MAPK

pathway, in which expression of Erk and Shp-2 counteracts the

proliferative effects of Stat3 and promotes differentiation [45].

According to the array results, the Erk gene (Mapk1 or Mapk3)

and most other components in this pathway were already pres-

ent in undifferentiated ESCs, and their expression levels did not

change significantly at the transcription level during the first 72

hours of differentiation (data not shown). However, some genes

in the MAPK pathway (e.g., Kras2 and Mapk12) had significantly

increased transcript levels during differentiation, indicating an

activation of the pathway (supplementary online Table 4). Fur-

thermore, the gene coding for Grb2-associated binder 1 (Gab1)

was significantly decreased (58% reduction between 18 and 72

hours, p = .0035). Gab1 binds to Shp-2 and is believed to suppress

the MAPK pathway in ESCs; also, increased synthesis of Gab1

together with Oct-4 may suppress induction of differentiation [1].

Although most of the factors involved in the MAPK pathway are

primarily regulated at the posttranscriptional level, the fact that

transcripts for many pathway members were detected in undiffer-

entiated ESCs suggests that they harbor the required components

to quickly respond to signals that promote differentiation.

The Wnt signaling pathway is important for maintenance of

pluripotency in undifferentiated ESCs, and a recent study also

showed that activation of the Wnt pathway by pharmacological

inhibition of Gsk-3 is able to maintain pluripotency in both human

and mouse ESCs [46]. Most components of the Wnt signaling

pathway could be detected in both undifferentiated and differ-

entiated ESCs, but some factors were also significantly changed

Figure 5. Annotation of differentially expressed genes. All genes

differentially expressed during embryonic stem cell differentiation

were classified according to (A) biological process and (B) cellular

component. Some genes are classified in more than one category,

resulting in the total number of genes indicated in the figures being

greater than the total number of differentially expressed genes.

Palmqvist, Glover, Hsu et al. 673

during differentiation (e.g., Fzd5, Wnt3, and CyclinD3; supple-

mentary online Table 4). However, overall there was no dramatic

change at the transcription level of several important factors

belonging to this pathway during the first 72 hours of differentia-

tion (e.g., β-catenin, Gsk-3, and Axin; data not shown).

The Hedgehog signaling pathway plays a critical role during

development and has been extensively studied in different species

and tissues [47, 48]. In this pathway, two receptors, Ptch and Ptch2,

and two transcription factors, Gli1 and Gli2, were decreased sig-

nificantly during ESC differentiation. Furthermore, at least one

suggested downstream target of this pathway, the Bmp4 gene

already discussed above, had significantly decreased transcrip-

tion, providing additional evidence that this pathway might be

involved in maintaining ESC self-renewal or pluripotency.

Importantly, out of 473 differentially expressed genes, the

largest group consisted of 173 genes or expressed sequence tags

with unknown biological function. Further analyses of the genes

within this group whose expression changes closely correlate

with loss of pluripotency may reveal novel mechanisms involved

in ESC maintenance. Of the 275 genes significantly decreased

during ESC differentiation, 48 genes showed a more than twofold

decrease in transcript levels within the first 18 hours and contin-

ued to decrease or remained at a low level of expression until 72

hours (Table 3). Changes in the transcript levels for these genes

correlated well with the functional assays, especially the chimera

generation and EB formation assays (Fig. 1). At least half of them

have been identified as ESC-enriched or to be downregulated

during differentiation in previous studies [17–23] (see below), but

several of these genes have unknown biological function or have

not previously been implicated in ESC maintenance (e.g., Lox,

Tnc, and Jag1; Table 3).

Molecular Markers of Pluripotency We hypothesized that classification of differentially expressed

genes according to cellular component, in combination with

functional analyses, may lead to the identification of new mark-

ers that more accurately reflect ESC potential. Classification of

the significantly changed genes according to cellular component

is shown in Figure 5B (complete list provided in supplementary

online Table 5). At least 60 gene products (11%) were consid-

ered localized to the plasma membrane and might therefore be

good candidates as markers for undifferentiated ESCs. Genes

increased during differentiation were also included in this list

of possible ESC markers because they can be used to detect the

onset of differentiation or for negative selection strategies for

isolating undifferentiated ESCs (Table 4). Protein expression

analyses of some of these have already been conducted in rela-

tion to ESC differentiation, i.e., Cd9, Cd44, and Osmr [49–51].

Additional gene products of interest include the adhesion mol-

ecule Vcam1 and the hedgehog signaling pathway receptors Ptch

and Ptch2. One gene of special interest encodes the SCF recep-

tor c-Kit. According to the gene-array results, transcript level of

the c-Kit gene was one of the most significant changes during

differentiation (54% reduction between 0 and 18 hours and 75%

reduction between 0 and 72 hours; p = .0016; Table 3), which also

correlated well with the functional assays (Fig. 1). Furthermore,

this finding was also verified in the R1, J1, and EFC ESC lines by

quantitative RT-PCR (Table 2). No c-Kit ligand/SCF was added

to the culture medium used in these experiments, and SCF was

not detected in the undifferentiated R1 ESCs, although it was

indeed present at high levels in the MEF according to the gene-

array results (data not shown). Because c-Kit is expressed on sev-

eral pluripotent cell types, including germ cells and hematopoi-

etic stem cells, and antibodies are commercially available, we

were able to compare the results of the array and RT-PCR experi-

ments with protein expression levels measured by flow cytome-

try (Fig. 6). This analysis revealed that expression of c-Kit on the

cell surface of differentiating ESCs closely paralleled the loss of

functional potential as measured using the EB formation assay

(Fig. 7). At later time points, the correlation was not as close

(i.e., EB formation capacity continued to decrease while protein

expression remained unchanged), suggesting the emergence of

differentiated cell types expressing c-Kit protein.

Comparison with Previously Published Gene-Array Data Sets Gene expression profiling to determine regulatory factors and

signaling pathways present in ESCs has been performed exten-

sively in recent years [16–24, 34]. It has been hypothesized that

the undifferentiated state is conferred on various stem cell popu-

lations through the use of similar molecular mechanisms. Initial

support for this hypothesis came from experiments comparing

the gene expression profiles of multiple stem cell populations

[18, 19, 34]. However, further analysis of available data indicated

minimal overlap between different published stem cell–associ-

ated gene sets [52, 53]. The discrepancy observed amongst these

studies likely arises in large part from significant differences in

the strategies used to identify the stem cell profile. However, true

differences in stem cell biology probably also exist among stem

cells taken from different tissues (e.g., ESCs, neural stem cells,

or hematopoietic stem cells). Some studies have relied on com-

parison of ESCs to terminally differentiated tissues [20, 23, 34]

to establish a list of genes enriched in ESCs. However, this strat-

egy is likely to miss genes involved in pluripotency that are tran-

siently turned off early during the differentiation process but not

uniquely expressed in the stem cell population. Another strategy

used has been to compare stem cell populations arising from the

same tissue source across species. An example is the comparison

of mouse with human ESCs. Although mouse and human ESCs

are both derived from preimplantation blastocysts, they differ in

responsiveness to extrinsic signals and in expression of surface

markers; for example, LIF cannot sustain self-renewal of human

674 Genetic Correlates of Murine ESC Pluripotency

ESCs, even in the presence of serum, suggesting the existence

of other signaling pathways essential for self-renewal in human

ESCs [5]. The evidence that human and mouse ESCs share a com-

mon core molecular program is also somewhat conflicting [16,

Table 3. Genes decreasing during ESC differentiation after LIF removal and most closely correlating with the loss of pluripotency

Gene symbol Accession #

Expression relative to 0 hrs after LIF removal, 18 hrs p value

Expression relative to 0 hrs after LIF removal, 72 hrs p value Reference

Cell adhesionCol1a1 NM_007742 0.05 .00793 0.08 .0278 18Vcam1 NM_011693 0.08 .03805 0.08 .0344 —Thbs1 NM_011580 0.11 .01728 0.13 .0203 17

Cell growth and maintenanceActa2 NM_007392 0.13 .05130 0.10 .0472 18–20Cav NM_007616 0.20 .02880 0.23 .0254 18, 19Emp1 NM_010128 0.22 .10000 0.09 .0381 18, 19S100a6 NM_011313 0.38 .11300 0.16 .0186 —Akap2 NM_009649 0.45 .13100 0.28 .0159 18, 22

MetabolismPrss23 NM_029614 0.36 .04408 0.46 .1740 18, 19Dnajb9 NM_013760 0.38 .06820 0.31 .0216 17Abca1 NM_013454 0.42 .14900 0.05 .0060 22Eif2s2 NM_026030 0.43 .00736 0.17 .0170 —

TranscriptionAnkrd1 NM_013468 0.04 .01611 0.07 .0657 19Fos NM_010234 0.06 .03985 0.11 .0017 —Fosb NM_008036 0.25 .02309 0.33 .0094 —Fosl2 NM_008037 0.26 .02917 0.31 .2830 —AA408868 NM_030612 0.27 .01029 0.50 .0310 —Klf4 NM_010637 0.32 .00361 0.05 .0021 23Bcl3 NM_033601 0.38 .00266 0.38 .1570 —Tbx3 NM_011535 0.41 .01023 0.30 .0214 18, 19Aebp2 NM_009637 0.44 .00747 0.43 .0002 —Egr1 NM_007913 0.49 .02355 0.44 .0258 22Mllt2h NM_133919 0.50 .28300 0.32 .0277 —

Cell development and differentiationCd44 NM_009851 0.08 .00931 0.19 0.04301 —Serpine1 NM_008871 0.11 .00070 0.05 0.06000 18, 19Inhba NM_008380 0.32 .03052 0.29 0.02966 —Csf1 NM_007778 0.36 .03371 0.49 0.07110 —

Signal transductionCcl2 NM_011333 0.04 .06990 0.02 .0279 18, 19, 22Apbb1ip NM_019456 0.18 .04105 0.22 .0664 22Socs3 NM_007707 0.22 .00055 0.15 .0055 22Osmr NM_011019 0.40 .10500 0.18 .0321 22Mras NM_008624 0.43 .04385 0.07 .00001 —Jag1 NM_013822 0.45 .04943 0.47 .0411 —Kit NM_021099 0.46 .09390 0.23 .0016 22Fzd5 NM_022721 0.47 .08780 0.31 .0228 18, 20

Unknown biological processLox NM_010728 0.02 .00272 0.06 .0100 18, 19, 21Fbln2 NM_007992 0.14 .01975 0.09 .0054 18, 19Tnc NM_011607 0.14 .02558 0.09 .0134 18, 19, 21, 22BB120430 AI847445 0.14 .01359 0.18 .0224 —Bgn NM_007542 0.15 .01494 0.10 .0071 18, 19C730049F20Rik AI840339 0.16 .05340 0.22 .0361 —Sdpr NM_138741 0.18 .12300 0.11 .0278 —Hnrph1 NM_021510 0.33 .04185 0.33 .2670 —Timp2 NM_011594 0.41 .03587 0.46 .0298 —AI504685 AI504685 0.44 .01515 0.34 .0004 —C85523 C85523 0.45 .07180 0.38 .0449 —AI115454 NM_175345 0.48 .05960 0.31 .0344 —5730501N20Rik AI882080 0.49 .01931 0.45 .0068 —

Relative expression ratios compared with undifferentiated ESCs and p values from Welsh analysis of variance t-tests are also shown. The refer-ence numbers indicate other studies that have identified the gene to be ESC-enriched or downregulated during ESC differentiation.Abbreviations: ESC, embryonic stem cell; LIF, leukemia inhibitory factor.

Palmqvist, Glover, Hsu et al. 675

20, 24]. However, the molecular mechanisms that confer pluri-

potency are likely evolutionary conserved, and thus comparison

of mouse and human ESC gene-array data might still be informa-

tive.

The gene expression data reported here were compared with

nine different gene-array data sets, comprising four studies on

Figure 6. Fluorescence-activated cell sorting profile. Undifferenti-

ated R1 embryonic stem cells (ESCs) (0 hour) and R1 ESCs differen-

tiated 18 and 72 hours after leukemia inhibitory factor removal were

analyzed with flow cytometry using c-Kit antibody. Abbreviations:

FSC, forward scatter; SSC, side scatter.

Figure 7. Correlation between c-Kit expression and embryoid body

formation. Expression of c-Kit (ó) was monitored at the indicated

times during embryonic stem cell differentiation using flow cytom-

etry, and expression levels were plotted as percent gated cells versus

time (right axis). Embryoid body (EB)–forming cell frequency (°)

determined on the same cell populations is also shown (percent EB

formation indicated on the left axis).

Table 4. Differentially expressed genes with plasma membrane

localization

Expression relative to 0 hrs after LIF removal

p valueGenes symbol Accession # 18 hrs 72 hrs

DecreasedVcam1 NM_011693 0.08 0.08 .0344Cd44 NM_009851 0.08 0.19 .0430Cav NM_007616 0.20 0.23 .0254Emp1 NM_010128 0.22 0.09 .0302Csf1 NM_007778 0.36 0.49 .0337Osmr NM_011019 0.40 0.18 .0321Abca1 NM_013454 0.42 0.05 .0060Jag1 NM_013822 0.45 0.47 .0411Kit NM_021099 0.46 0.23 .0016Fzd5 NM_022721 0.47 0.31 .0228Il6st NM_010560 0.62 0.40 .0058Ly75 NM_013825 0.80 0.31 .0350Icam1 NM_010493 0.81 0.31 .0188Gjb3 NM_008126 0.83 0.46 .0423Cd9 NM_007657 0.99 0.45 .0345Slc2a3 NM_011401 1.00 0.44 .00279430079M16Rik NM_175414 1.00 0.49 .0310Ppap2a NM_008903 1.05 0.49 .0041Gja7 NM_008122 1.10 0.22 .0376Abcb1a NM_011076 1.10 0.35 .0201Enah NM_010135 1.21 0.31 .0074Ptch NM_008957 1.22 0.27 .0012Akp2 NM_007431 1.24 0.55 .0168Slc29a1 NM_022880 1.37 0.44 .0150Trfr NM_011638 1.46 0.68 .0390Fgfr2 NM_010207 1.48 0.67 .0293Utrn NM_011682 1.49 0.59 .0013Ptch2 NM_008958 1.53 0.38 .0054Ak1 NM_021515 1.53 0.66 .0304Cd1d1 NM_007639 1.66 0.45 .0291Adam19 NM_009616 1.82 0.45 .00201600025H15Rik NM_028064 1.88 0.83 .0062Ltb NM_008518 2.29 0.85 .0202IncreasedEnpp2 NM_015744 3.10 9.13 .0118Dgka NM_016811 2.49 0.95 .0079Cldn4 NM_009903 2.36 1.60 .0472Cldn6 NM_018777 2.14 3.40 .0081Btla NM_177584 2.03 14.27 .0034St14 NM_011176 1.73 2.45 .0319Igsf9 NM_033608 1.55 2.22 .0050Podxl NM_013723 1.54 2.54 .0019Itga8 NM_001001309 1.51 2.81 .0298Ddr1 NM_007584 1.50 2.39 .0264Cldn7 NM_016887 1.48 5.97 .00001Spint1 NM_016907 1.35 2.50 .0138Met NM_008591 1.35 2.18 .0311Rnf128 NM_023270 1.34 2.51 .0453Slc39a8 NM_026228 1.33 2.32 .0208Tap1 NM_013683 1.31 2.73 .0074Prom1 NM_008935 1.27 5.53 .0010Calcr NM_007588 1.18 6.05 .0338Sfrp2 NM_009144 1.18 2.28 .0150Tapbp NM_009318 1.08 2.21 .0202Perp NM_022032 1.03 2.39 .0269Cd24a NM_009846 0.90 2.73 0Dlk1 NM_010052 0.82 1.77 .0291Cask NM_009806 0.79 1.91 .0052Gp38 NM_010329 0.79 1.63 .0323Amot NM_153319 0.76 4.10 .0073Lrp8 NM_053073 0.47 2.26 .0255

Relative expression levels compared with undifferentiated embry-

onic stem cells are listed. The p values for the most significant fold

change from Welsh analysis of variance t-tests are listed.

Abbreviation: LIF, leukemia inhibitory factor.

676 Genetic Correlates of Murine ESC Pluripotency

murine ESCs [18, 19, 21, 23], four studies on human ESCs [16,

17, 20, 22], and one study comparing human and mouse ESCs

[24] (summarized in Table 5). Only genes downregulated during

differentiation after LIF removal were used in the comparisons

because most other studies only report ESC-enriched or ESC-

specific genes. Complete gene lists derived from these compari-

sons can been found in supplementary online Table 6.

Overall, there was a large overlap between the downregulated

genes from our data and genes identified as either ESC enriched

or downregulated during ESC differentiation in the other data

sets, despite the wide variety of experimental designs and cell

lines used. Of the genes identified as significantly decreased after

LIF removal in our study, 60% (164 of 275) were found in at least

one other data set, and 28% (78 of 275) were found in at least two

other data sets. There was greater similarity with the murine data

(129 of 275 or 47% were found in at least one other murine data

Table 5. Summary of the published gene expression studies in mouse and human ESCs that were used for comparison

Reference Experimental design Cell lineTechnology platform Gene list used

Number of genes Overlap

Ivanova et al. [18] Undifferentiated ESCs grown on fibroblasts in the presence of LIF, cultured for one passage on gelatin before RNA extraction; expression compared with differentiated bone marrow and fetal liver cells

CCE Affymetrix MGU74v2

Supplementary online Table 1 (refiltered accord-ing to author’s criteria)

2,270 90 (97)

Kelly et al. [23] Undifferentiated ESCs cultured on gelatin in the presence of LIF; expression compared with ESCs differentiated for 96 hrs by treat-ment with 1 μM retinoic acid

D3 Atlas Mouse cDNA expres-sion arrays

Table 1 17 6

Ramalho-Santos et al. [19]

Undifferentiated ESCs grown on irradiated fibroblasts for two passages before RNA isolation; expression compared with dif-ferentiated bone marrow and tissue from the lateral ventricles on the brain

C57/Bl6 Affymetrix MGU74v2

Database S1 1,787 82 (85)

Sharov et al. [21] Expression profiles of 36 tissues from early development and adult stem cells, including undifferentiated ESCs and ESCs differenti-ated for 4 or 18 hrs in the absence of fibro-blasts and LIF

R1 cDNA library construction

Data set S7, groups F, I, L, and O, with compa-rable annotation

260 16 (18)

Bhattacharya et al. [16] Expression profiles of five ESC lines grown on fibroblasts was compared with 8-day-old EB outgrowths

GE01, GE09, BG01, BG02, TE06

Custom oligo-nucleotide glass arrays

Supplementary online Table 2

92 5

Brandenberger et al. [17]

Expression profiles of three undifferenti-ated ESC lines compared with EBs (8 days of differentiation), prehepatocytes (induced by addition of DMSO), and preneural cells (induced by addition of retinoic acid)

H1, H7, H9 Massively par-allel signature sequencing

Supplementary online Table 2

532 19 (20)

Sato et al. [20] Undifferentiated ESCs compared with ESCs induced to differentiated neurons for 3 wks

H1 Affymetrix HGU133A

Database 1 918 39 (40)

Sperger et al. [22] Undifferentiated ESCs compared with mul-tiple cell lines, including germ cell tumor and other differentiated cell lines

H1, H7, H9, H13, H14

Custom cDNA arrays

Supplementary online Table 6

1,760 45 (51)

Ginis et al. [24] Comparison between human and murine undifferentiated ESCs

Human H1, mouse D3

RT-PCR/focused functional microarrays

Table 3A 13 2

Supplementary online Table 2 was split into three separate lists based on the statistical significance of the fold change between 0 and 18 hours, 0 and 72 hours, and 18 and 72 hours. Each of these three gene lists was compared with the gene lists indicated. The experimental design, cell line, and technology used are shown along with the number of genes in the original publication and the number of genes that overlapped with the 275 significantly decreased genes in our data. Numbers in parentheses represent the actual overlap with the 298 probe sets used in the analysis representing the 275 unique genes.Abbreviations: DMSO, dimethyl sulfoxide; EB, embryoid body; ESC, embryonic stem cell; LIF, leukemia inhibitory factor; RT-PCR, reverse transcription–polymerase chain reaction.

Palmqvist, Glover, Hsu et al. 677

set) than with the human data (75 of 275 or 27% were found in at

least one other human data set). Genes that we identified as dif-

ferentially expressed between 0 and 18 hours were the least repre-

sented in other published data (41% between 0 and 18 hours com-

pared with 67% between 18 and 72 hours and 63% between 0 and

72 hours), possibly because our approach to use early time points

during differentiation for defining differential expression has not

been widely used. Only two other studies included comparable

early time points in their study [21, 23]. Within individual data

sets, the degree of overlap depended primarily on the number of

genes in the starting list (Table 5). The data set generated by Kelly

et al. [23] stood out because of its high degree of overlap (35%),

which can potentially be explained by the similarity in the two

studies in terms of experimental design and the similarity of the

genetic background of the ESCs used. However, this encompasses

relatively few genes (6 out of 17 genes). Furthermore, many genes

that we report as decreased during the first 72 hours were reported

as also being present in human ESCs by Sato et al. [20]. However,

they were not identified as differentially expressed in that study.

This discrepancy could possibly be due to the later time point (3

weeks) used for determining differential expression in that study

(data not shown).

No single gene was found enriched in every human and

mouse ESC data set. Jade1, Leftb, and Smarcad1 were the most

commonly identified genes in other data sets (i.e., in six of nine

other data sets). Leftb is a transforming growth factor-beta family

member, which is expressed on the left side of developing mouse

embryos and is implicated in left-right determination [54]. Jade1

was recently identified as a gene involved in anteroposterior axis

development [55]. Smarcad1 has previously been identified as

a marker of preimplantation embryos [56]. The gene coding for

Tenascin-C was downregulated within the first 18 hours after LIF

removal (Table 3) and was also commonly observed as differen-

tially expressed in other data sets (i.e., in four of eight data sets).

Tenascin, also known as hexabrachion and cytotactin, is an extra-

cellular matrix protein with a spatially and temporally restricted

tissue distribution that is tightly regulated during embryonic

development and in adult tissue remodeling [57]. Other com-

monly identified markers of undifferentiated ESCs were also

found in this comparison. Sox2, Rex1, Bmp4, and Gbx2 were all

observed in at least three other data sets. This also included the

gene Lox, coding for lysyl oxidase, found in three other murine

data sets [18, 19, 21]. It was in fact one of the most pronounced

and rapidly downregulated genes detected (Table 3). At least one

study identified c-Kit as enriched in ESCs, intriguingly in human

ESCs [22]. Overall the comparison with previously published

data indicated some intriguing similarities but also showed that

most genes do not overlap in pairwise comparisons. This under-

lines the many differences that might arise when different sources

of cells, culture conditions, microarray technique platforms, and

data analysis tools are used and emphasizes the need to correlate

expression changes with rigorous measures of ESC competence

and differentiation potential.

Discussion The present study is distinct from previous studies in two impor-

tant aspects. First and most important, only a selected popula-

tion of germ line–competent ESCs, grown under carefully con-

trolled, optimized culture conditions, was used to establish the

gene expression profiles. It is likely that substantial variations in

gene expression arise in response to culture variables. Consider-

ing the multiplicity of culture variables that can be important for

the biological heterogeneity of cell populations and their gene

expression profiles, remarkably little information has been pro-

vided about the conditions used to generate the cells for the gene

expression profiles reported thus far [16–24, 34]. Second, few of

the previous studies addressing questions about a shared or com-

mon stem cell gene expression signature among different types

of stem cells, or even different ESC lines, have involved correla-

tive functional assays to assess the pluripotency and self-renewal

capacity of the cells of interest. By combining the gene expression

profiling data with assays measuring ESC pluripotency and self-

renewal, it should be possible to more precisely define the genes

critical for specifying these properties.

We combined defined culture and differentiation conditions

with various measures of ESC pluripotency to determine optimal

times for gene expression analysis using high-density oligonucle-

otide microarray. The results showed that the functional capacity

of ESCs declines rapidly under differentiation conditions, with

the most pronounced changes in function occurring during the

first 18–24 hours of differentiation. The gene expression results

were subsequently used to find genes whose expression corre-

lated with loss of pluripotency and that could explain loss of this

capacity during differentiation or serve as markers for pluripo-

tent ESCs. Analysis of the gene-array data revealed that 473 genes

were differentially expressed during the first 72 hours of ESC

differentiation, suggesting they are potentially important for the

maintenance of ESC pluripotency and self-renewal.

Important roles in the maintenance of undifferentiated

ESCs have previously been demonstrated for several of the

downregulated factors such as Stat3, Rex1, Sox2, Gbx2, and

Bmp4. Intriguingly, one third of the differentially expressed

genes have not been characterized in terms of involvement in

biological processes. More important, a refined list of 48 genes

whose transcript levels closely correlated with the functional

assays (i.e., with early and persistent decreases in transcript

levels after LIF removal) contains several genes with unknown

function or genes that have not previously been suggested to

play a role in ESC maintenance (Table 3). These genes may be

novel candidates to play critical roles in the regulation of ESC

pluripotency and self-renewal. Several of the genes in this list

have also been found in previous gene expression studies in

678 Genetic Correlates of Murine ESC Pluripotency

human or mouse ESCs (e.g., Tnc and Lox; Table 3). Further-

more, several promising candidate markers for pluripotent

ESCs were identified from the gene-array analysis (Table 4).

The changes in transcript levels observed for one gene, c-Kit,

were also verified at the protein level and showed good corre-

lation with functional measures of ESC pluripotency (Fig. 7).

This finding was verified in two other murine ESC lines (Table

2). Two other commonly used ESC markers, Oct-4 and SSEA-1,

were also analyzed in parallel with the functional assays used

in this study but showed poor correlation with the outcome in

these (Fig. 2D). Further studies are needed to determine if our

candidates (e.g., c-Kit) are more reliable markers of, and use-

ful to enrich for, undifferentiated pluripotent ESCs. Additional

work is also required to determine the functional significance

of these observations for ESC maintenance. It is also important

to note in the context of these and other genes of interest that

global gene expression profiling does not discriminate between

changes arising at the level of transcription versus mRNA sta-

bility. Also, changes in transcript levels in a subset of cells may

go undetected, and likewise subtle changes might arise from

changes in just a small proportion of the cells.

Transcriptional profiling of various stem cell populations

has been used to determine the types of regulatory factors and

signaling pathways present in pluripotent cells, including ESCs

[16–24, 34]. Comparing genes that were significantly decreased

in our analysis with both murine and human data sets [16, 17,

20, 22] gave a large overlap with 176 of 298 genes identified in

at least one of these other studies. Of note, 139 of these have

been identified in other murine ESC studies. This analysis was

not able to distinguish biological differences between human

and murine ESCs because of the way it was performed. Undue

emphasis was placed on the findings reported in this publica-

tion by comparing all publications with data. The level of over-

lap between our data and other murine studies was higher than

the overlap with other human studies, but the difference can

probably be accounted for by the increased difficulty of gene

comparison between species. However, additional ESC gene

expression profiling carried out in an analogous stringent man-

ner (i.e., correlating measurable functional properties with tran-

script levels) is needed to accurately assess and determine the

confidence in the degree of overlap in differentially expressed

genes after ESC differentiation. Induction of ESC differentia-

tion by alternative methods or using ESCs derived from mice of

different genetic backgrounds will also be important to properly

assess. Such analyses should be able to discriminate between

treatment-specific or genetic-specific gene expression changes

and those commonly observed under various conditions. These

latter genes are more likely to play an important role in regulat-

ing ESC self-renewal and pluripotency.

Summary In this study, we used a novel strategy to identify genes that may

play a critical role in regulating the pluripotent potential of murine

ESCs. Unlike previous ESC transcriptome analyses, we carried

out comparisons of closely related populations both in terms of lin-

eage and time. The correlation of differentially expressed genes

with functional measures of ESC pluripotency as well as validation

in other murine ESC lines provides added confidence that these

genes may be of functional relevance. Our studies also identify

candidate novel markers of ESC pluripotency. Taken together, this

work provides the foundation for achieving a greater understand-

ing of the molecular mechanisms that govern and reflect the capac-

ity of ESCs for multilineage differentiation and self-renewal.

Acknowledgments The authors wish to thank Rewa Grewal for assistance with blas-

tocyst injections and analysis of chimeric mice. This work was

funded by grants from the Canadian StemCell Network and

Genome Canada to R.K.H. and Mathematics of Information

Technology and Complex Systems NCE grants to J.M.P. L.P. has

a postdoctoral fellowship funded by the Swedish Cancer Soci-

ety. C.D.H. is a Canadian Institutes of Health Research (CIHR)

New Investigator and a scholar of the Michael Smith Foundation

for Health Research. C.H.G. is a recipient of an SCN trainee and

CIHR Doctoral Research Award. R.K.H. and C.D.H. contributed

equally to this study.

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