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: [email protected] 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
This material is protected by U.S. Copyright law. Unauthorized reproduction is prohibited.
For reprints contact: [email protected]
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.
References
1 Smith AG. Embryo-derived stem cells: of mice and men. Annu Rev Cell
Dev Biol 2001;17:435–462.
2 Suda Y, Suzuki M, Ikawa Y et al. Mouse embryonic stem cells exhibit
indefinite proliferative potential. J Cell Physiol 1987;133:197–201.
3 Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells
from mouse embryos. Nature 1981;292:154–156.
4 Martin GR. Isolation of a pluripotent cell line from early mouse embryos
cultured in medium conditioned by teratocarcinoma stem cells. Proc Natl
Acad Sci U S A 1981;78:7634–7638.
5 Thomson JA, Itskovitz-Eldor J, Shapiro SS et al. Embryonic stem cell
lines derived from human blastocysts. Science 1998;282:1145–1147.
6 Abbondanzo SJ, Gadi I, Stewart CL. Derivation of embryonic stem cell
lines. In: Wasserman P, DePamphilis M, eds.Methods of Enzymology,
Guide to Techniques in Mouse Development. Toronto: Academic Press
Inc., 1993:803–823.
7 Keller G, Kennedy M, Papayannopoulou T et al. Hematopoietic commit-
ment during embryonic stem cell differentiation in culture. Mol Cell Biol
1993;13:473–486.
8 Kirschstein R, Skirboll LR. Stem Cells: Scientific Progress and Future
Research Directions. Bethesda, MD: National Institutes of Health,
Department of Health and Human Services, 2001:appendix E, 1–11.
9 Nagy A, Rossant J, Nagy R et al. Derivation of completely cell culture-
derived mice from early-passage embryonic stem cells. Proc Natl Acad
Sci U S A 1993;90:8424–8428.
Palmqvist, Glover, Hsu et al. 679
10 Li E, Bestor TH, Jaenisch R. Targeted mutation of the DNA methyltrans-
ferase gene results in embryonic lethality. Cell 1992;69:915–926.
11 Nichols J, Evans EP, Smith AG. Establishment of germ-line-competent
embryonic stem (ES) cells using differentiation inhibiting activity. Devel-
opment 1990;110:1341–1348.
12 Helgason CD, Damen JE, Rosten P et al. Targeted disruption of SHIP
leads to hemopoietic perturbations, lung pathology, and a shortened life
span. Genes Dev 1998;12:1610–1620.
13 Brazma A, Hingamp P, Quackenbush J et al. Minimum information about
a microarray experiment (MIAME)-toward standards for microarray
data. Nat Genet 2001;29:365–371.
14 Draghici S, Khatri P, Bhavsar P et al. Onto-Tools, the toolkit of the modern
biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Trans-
late. Nucleic Acids Res 2003;31:3775–781.
15 Livak KJ, Schmittgen TD. Analysis of relative gene expression data using
real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Meth-
ods 2001;25:402–408.
16 Bhattacharya B, Miura T, Brandenberger R et al. Gene expression in
human embryonic stem cell lines: unique molecular signature. Blood
2004;103:2956–2964.
17 Brandenberger R, Wei H, Zhang S et al. Transcriptome characterization
elucidates signaling networks that control human ES cell growth and dif-
ferentiation. Nat Biotechnol 2004;22:707–716.
18 Ivanova NB, Dimos JT, Schaniel C et al. A stem cell molecular signature.
Science 2002;298:601–604.
19 Ramalho-Santos M, Yoon S Matsuzaki Y et al. “Stemness”: transcrip-
tional profiling of embryonic and adult stem cells. Science 2002;298:597–
600.
20 Sato N, Sanjuan IM, Heke M et al. Molecular signature of human
embryonic stem cells and its comparison with the mouse. Dev Biol
2003;260:404–413.
21 Sharov AA, Piao Y, Matoba R et al. Transcriptome analysis of mouse stem
cells and early embryos. PLoS Biol 2003;1:E74.
22 Sperger JM, Chen X, Draper JS et al. Gene expression patterns in human
embryonic stem cells and human pluripotent germ cell tumors. Proc Natl
Acad Sci U S A 2003;100:13350–13355.
23 Kelly DL, Rizzino A. DNA microarray analyses of genes regulated
during the differentiation of embryonic stem cells. Mol Reprod Dev
2000;56:113–123.
24 Ginis I, Luo Y, Miura T et al. Differences between human and mouse
embryonic stem cells. Dev Biol 2004;269:360–380.
25 Stewart CL. Production of chimeras between embryonic stem cells and
embryos. In: Wassarman PM, DePamphilis ML, eds. Methods in Enzy-
mology: Guide to Techniques in Mouse Development. Toronto: Academic
Press, 1993:823–854.
26 Niwa H, Miyazaki J, Smith AG. Quantitative expression of Oct-3/4 defines
differentiation, dedifferentiation or self-renewal of ES cells. Nat Genet
2000;24:372–376.
27 Furusawa T, Ohkoshi K, Honda C et al. Embryonic stem cells express-
ing both platelet endothelial cell adhesion molecule-1 and stage-specific
embryonic antigen-1 differentiate predominantly into epiblast cells in a
chimeric embryo. Biol Reprod 2004;70:1452–1457.
28 Williams RL, Hilton DJ, Pease S et al. Myeloid leukaemia inhibitory fac-
tor maintains the developmental potential of embryonic stem cells. Nature
1988;336:684–687.
29 Stewart CL, Kaspar P, Brunet LJ et al. Blastocyst implantation depends on
maternal expression of leukaemia inhibitory factor. Nature 1992;359:76–
79.
30 Shirogane T, Fukada T, Muller JM et al. Synergistic roles for Pim-1 and c-
Myc in STAT3-mediated cell cycle progression and antiapoptosis. Immu-
nity 1999;11:709–719.
31 Ying QL, Nichols J, Chambers I et al. BMP induction of Id proteins sup-
presses differentiation and sustains embryonic stem cell self-renewal in
collaboration with STAT3. Cell 2003;115:281–292.
32 Hosler BA, LaRosa GJ, Grippo JF et al. Expression of REX-1, a gene con-
taining zinc finger motifs, is rapidly reduced by retinoic acid in F9 terato-
carcinoma cells. Mol Cell Biol 1989;9:5623–5629.
33 Rogers MB, Hosler BA, Gudas LJ. Specific expression of a retinoic acid-
regulated, zinc-finger gene, Rex-1, in preimplantation embryos, tropho-
blast and spermatocytes. Development 1991;113:815–824.
34 Tanaka TS, Kunath T, Kimber WL et al. Gene expression profiling of
embryo-derived stem cells reveals candidate genes associated with pluri-
potency and lineage specificity. Genome Res 2002;12:1921–1928.
35 Avilion AA, Nicolis SK, Pevny LH et al. Multipotent cell lineages in early
mouse development depend on SOX2 function. Genes Dev 2003;17:126–
140.
36 Bowles J, Teasdale RP, James K et al. Dppa3 is a marker of pluripotency
and has a human homologue that is expressed in germ cell tumours. Cyto-
genet Genome Res 2003;101:261–265.
37 Chambers I, Colby D, Robertson M et al. Functional expression cloning
of Nanog, a pluripotency sustaining factor in embryonic stem cells. Cell
2003;113:643–655.
38 Mitsui K, Tokuzawa Y, Itoh H et al. The homeoprotein Nanog is required
for maintenance of pluripotency in mouse epiblast and ES cells. Cell
2003;113:631–642.
39 Wilkinson DG, Bhatt SHerrmann BG. Expression pattern of the mouse T
gene and its role in mesoderm formation. Nature 1990;343:657–659.
40 Wiese C, Rolletschek A, Kania G et al. Nestin expression: a property of
multi-lineage progenitor cells? Cell Mol Life Sci 2004;61:2510–2522.
41 Weigmann A, Corbeil D, Hellwig A et al. Prominin, a novel microvilli-
specific polytopic membrane protein of the apical surface of epithelial
cells, is targeted to plasmalemmal protrusions of non-epithelial cells.
Proc Natl Acad Sci U S A 1997;94:12425–12430.
42 Anneren C, Cowan CA, Melton DA. The Src family of tyrosine
kinases is important for embryonic stem cell self-renewal. J Biol Chem
2004;279:31590–31598.
43 Vas V, Szilagyi L, Paloczi K et al. Soluble Jagged-1 is able to inhibit the
function of its multivalent form to induce hematopoietic stem cell self-
renewal in a surrogate in vitro assay. J Leukoc Biol 2004;75:714–720.
44 Xue Y, Gao X, Lindsell CE et al. Embryonic lethality and vascular defects
in mice lacking the Notch ligand Jagged1. Hum Mol Genet 1999;8:723–
730.
45 Burdon T, Chambers I, Stracey C et al. Signaling mechanisms regulat-
ing self-renewal and differentiation of pluripotent embryonic stem cells.
Cells Tissues Organs 1999;165:131–143.
46 Sato N, Meijer L, Skaltsounis L et al. Maintenance of pluripotency in human
and mouse embryonic stem cells through activation of Wnt signaling by a
pharmacological GSK-3-specific inhibitor. Nat Med 2004;10:55–63.
47 Cohen MM Jr. The hedgehog signaling network. Am J Med Genet
2003;123A:5–28.
48 Ogden SK, Ascano M Jr, Stegman MA et al. Regulation of Hedgehog sig-
naling: a complex story. Biochem Pharmacol 2004;67:805–814.
680 Genetic Correlates of Murine ESC Pluripotency
49 Oka M, Tagoku K, Russell TL et al. CD9 is associated with leukemia
inhibitory factor-mediated maintenance of embryonic stem cells. Mol
Biol Cell 2002;13:1274–1281.
50 Rose TM, Weiford DM, Gunderson NL et al. Oncostatin M (OSM) inhib-
its the differentiation of pluripotent embryonic stem cells in vitro. Cyto-
kine 1994;6:48–54.
51 Wheatley SC, Isacke CM. Induction of a hyaluronan receptor, CD44, dur-
ing embryonal carcinoma and embryonic stem cell differentiation. Cell
Adhes Commun 1995;3:217–230.
52 Fortunel NO, Otu HH, Ng HH et al. Comment on “ ‘Stemness’: transcrip-
tional profiling of embryonic and adult stem cells” and “a stem cell molec-
ular signature.” Science 2003;302:393.
53 Evsikov AV, Solter D. Comment on “‘Stemness’: transcriptional profiling
of embryonic and adult stem cells” and “a stem cell molecular signature.”
Science 2003;302:393.
54 Meno C, Saijoh Y, Fujii H et al. Left-right asymmetric expression of the
TGF beta-family member lefty in mouse embryos. Nature 1996;381:151–
155.
55 Tzouanacou E, Tweedie S, Wilson V. Identification of Jade1, a gene
encoding a PHD zinc finger protein, in a gene trap mutagenesis screen
for genes involved in anteroposterior axis development. Mol Cell Biol
2003;23:8553–8552.
56 Schoor M, Schuster-Gossler K, Gossler A. The Etl-1 gene encodes a
nuclear protein differentially expressed during early mouse development.
Dev Dyn 1993;197:227–237.
57 Jones PL, Jones FS. Tenascin-C in development and disease: gene regula-
tion and cell function. Matrix Biol 2000;19:581–596.