A Temporal Chromatin Signature in Human
Embryonic Stem Cells Identifies
Regulators of Cardiac Development
Sharon L. Paige,1,2,3,12Sean Thomas,9,12Cristi L. Stoick-Cooper,2,4,12Hao Wang,5,12Lisa Maves,10Richard Sandstrom,5
Lil Pabon,1,2,3Hans Reinecke,1,2,3Gabriel Pratt,1,2,3Gordon Keller,11Randall T. Moon,2,5John Stamatoyannopoulos,5,6,*
and Charles E. Murry1,2,3,7,8,*
1Department of Pathology
2Institute for Stem Cell and Regenerative Medicine
3Center for Cardiovascular Biology
4Howard Hughes Medical Institute and Department of Pharmacology
5Department of Genome Sciences
6Department of Medicine
7Department of Bioengineering
8Department of Medicine/Cardiology
University of Washington, Seattle, WA 98109, USA
9Gladstone Institutes, San Francisco, CA 94158, USA
10Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
11McEwen Centre for Regenerative Medicine, Ontario Cancer Institute, Toronto ON M5G 2C4, Canada
12These authors contributed equally to this work
*Correspondence: email@example.com (J.S.), firstname.lastname@example.org (C.E.M.)
Directed differentiation of human embryonic stem
for studying molecular mechanisms of human
cardiovascular development. Although it is known
that chromatin modification patterns in ESCs differ
markedly from those in lineage-committed progeni-
tors and differentiated cells, the temporal dynamics
of chromatin alterations during differentiation along
a defined lineage have not been studied. We show
cells is accompanied by programmed temporal alter-
ations in chromatin structure that distinguish key
regulators of cardiovascular development from other
genes. We used this temporal chromatin signature to
identify regulators of cardiac development, including
the homeobox gene MEIS2. Using the zebrafish
model, we demonstrate that MEIS2 is critical for
proper heart tube formation and subsequent cardiac
looping. Temporal chromatin signatures should be
broadly applicable to other models of stem cell
differentiation to identify regulators and provide key
insights into major developmental decisions.
Cardiovascular cells derived from pluripotent stem cells in vitro
have potential both as a cell-based therapy for cardiac regener-
ation and as tools to analyze basic developmental processes
(Murry and Keller, 2008). Insights from model organisms have
permitted harnessing of the signaling pathways controlling
cardiovascular development, enabling the directed differentia-
tion of mouse and human embryonic stem cells (ESCs) into the
major definitive cell types of the heart, namely cardiomyocytes,
smooth muscle cells and endothelial cells (Bu et al., 2009;
Domian et al., 2009; Kattman et al., 2006; Kattman et al., 2011;
Laflamme et al., 2007; Murry and Keller, 2008; Yang et al.,
2008). In contrast to the relatively advanced knowledge of
signaling pathways, the epigenetic alterations that accompany
or potentiate cardiogenesis are largely unexplored.
Methylation of lysine residues on the tail of histone H3
accompanies many major genomic functional processes
(Guenther et al., 2007; Ringrose and Paro, 2004; Schuetten-
gruber et al., 2007). H3K4me3 and H3K36me3 are deposited
by Trithorax group proteins and mark chromatin associated
(Bannister et al., 2005; Li et al., 2007; Vakoc et al., 2006).
H3K27me3 modifications result from activities within the Poly-
comb repressive complex 2 (PRC2), which includes SUZ12
and EZH2 (Boyer et al., 2006; Lee et al., 2006; Simon and King-
ston, 2009). Studies of the distribution of H3K27me3 in both
mouse (Bernstein et al., 2006) and human (Hawkins et al.,
2010; Pan et al., 2007) ESCs have revealed that H3K27me3
deposition is preferentially enriched at promoters of regulatory
genes (Boyer et al., 2006; Lee et al., 2006) controlling diverse
developmental pathways including neuronal (Mohn et al.,
2008a) and hematopoietic lineages (Mazzarella et al., 2011a),
where frequently, in combination with H3K4me3, it may denote
‘‘poising’’ of genes that are destined for rapid activation upon
Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc. 221
lineage commitment (Bernstein et al., 2006; Rada-Iglesias and
Wysocka, 2011). Indeed, ‘‘bivalent’’ promoters marked by
both H3K4me3 and H3K27me3 in pluripotent cells are found
to have either the H3K4me3 or the H3K27me3 mark (but not
both) in definitive cell types, implying that this bivalency
resolves to either a transcriptionally active or silent state
(Mikkelsen et al., 2007). It is currently unknown how Polycomb-
and Trithorax-related histone modification patterns evolve
during the transition from pluripotency to definitive cells during
lineage differentiation. Moreover, because Polycomb-driven
marking of key regulatory genes in ESCs is not specific to any
given lineage, it is currently not possible to identify lineage-
specific regulators simply from the chromatin state of pluripo-
tent stem cells.
We sought to determine whether temporal patterning of
histone modifications during differentiation along a defined
lineage would clarify the relationships among key regulators
regulatory from lineage-specific structural genes. Specifically,
we hypothesized that key regulators of differentiation would
show stage-specific changes in H3K4me3 and H3K27me3
because inappropriate activation or silencing of these genes
could alter cell fate by affecting many downstream target
genes. The differentiation of human ESCs into cardiomyocytes
Laflamme et al., 2007; Yang et al., 2008) and is of great poten-
tial therapeutic importance (Murry and Keller, 2008). We there-
fore asked how chromatin modifications evolve temporally
along the cardiac differentiation axis and whether the temporal
patterning of histone modifications might provide a reliable
signature that could discriminate key known regulators of
cardiovascular development, as well as enable the identifica-
tion of previously undiscovered regulators.
Directed Differentiation of Human ESCs into
Directed differentiation of H7 human ESCs to the cardiovas-
cular lineage was achieved by allowing the cells to form
embryoid bodies (EBs) in the presence of defined serum-free
medium as previously described (Kattman et al., 2011; Yang
et al., 2008). Mesoderm induction was accomplished using
bone morphogenetic protein 4 (BMP4), activin A and basic
fibroblast growth factor (bFGF). On day 5 (T5) of differentiation,
a tripotential cardiovascular progenitor emerges, identified
based on low expression of VEGFR2 (KDR) and PDGFRa
(Kattman et al., 2011). Over time, this progenitor gives rise to
cultures that contain predominantly cardiomyocytes and also
contain endothelial cells and smooth muscle cells, identified
by flow cytometry for cardiac troponin T (cTnT), CD31/
PECAM1, and smooth muscle alpha actin (SMA), respec-
tively (Figure S1 available online). For all genome-wide ex-
periments, parallel samples were maintained in culture after
the times of harvest for immunoprecipitation, and only runs
that were >80% KDR+/PDGFRa+ at the T5 progenitor stage
and >50% cTnT+ cardiomyocytes at the T14 definitive cardio-
vascular cell stage were used.
Chromatin States Measured along the Time Course of
We used chromatin immunoprecipitation coupled to massively
parallel sequencing (ChIP-seq) to map H3K4me3, H3K27me3,
and H3K36me3 modifications genome-wide at five key develop-
mental stages during cardiovascular directed differentiation
including pluripotent cells (T0), mesodermal progenitors (T2),
specified tripotential cardiovascular progenitors (T5), committed
cardiovascular cells (T9), and definitive cardiovascular cells
(primarily cardiomyocytes, T14). We performed differentiation
and ChIP-seq experiments in duplicate, with high reproducibility
between biological replicates at each time point (average
Pearsoncorrelation 0.94). Figure S2A showstwo biological repli-
cates for chromatin modification at the TBX5 locus, a transcrip-
tion factor (TF) implicated in generation of the first heart field
(Takeuchi et al., 2003). Across all time points, all three histone
modification patterns with respect to the transcription start site
(TSS) showed the expected morphologies (Figure S2B), with
H3K4me3 signal peaking within a narrow window around the
TSS, H3K27me3 signal peaking in the vicinity of the TSS (though
more broadly distributed than H3K4me3) with a prominent
decrease over the TSS (consistent with reduced nucleosomal
density and increased turnover in this region [Mo ¨bius and
Gerland, 2010]), and H3K36me3 signal increasing rapidly from
the TSS region to a plateau over the gene body, consistent
et al., 2011).
Identification of Distinct Chromatin Signatures for
Different Functional Categories of Cardiac Factors
To gain insight into the pattern of sequential epigenetic alter-
ations accompanying cardiovascular differentiation, we next
examined the histone modification profiles and RNA expression
of genes with established roles in heart development and func-
tion. These ranged from sequence-specific transcriptional regu-
lators, such as NKX2.5 (Figure 1A), to cardiomyocyte contractile
as well as genes expressed in cardiovascular progenitors,
smooth muscle cells and endothelial cells (Figures S3A–S3C).
A majority of cardiac transcription factors showed high levels
of H3K27me3 during pluripotency that gradually decreased as
differentiation progresses, paralleled by gradual increases in
H3K4me3, H3K36me3, and RNA expression (Figures 1A, 1C,
and 1E). Similarly, many of the members of key signaling path-
ways involved in cardiac development, such as the TGFb family,
Wnt, Notch, Hedgehog, the FGF family, PDGF, and VEGF
showed stage-specific activation (H3K4me3, H3K36me3, RNA
expression) and repression (H3K27me3), compatible with tight
control over signaling pathways that direct cell fate (Figure S3D).
In contrast, although genes encoding cardiomyocyte contractile
proteins showed similar time-dependent increases in H3K4me3,
H3K36me3, and RNA expression, these genes did not have
appreciable levels of H3K27me3 deposition at any time (Figures
fications provides achromatin ‘‘signature’’ thatdifferentiates key
cardiac regulatory genes, including both transcription factors
and soluble signals, from lineage-specific genes encoding
proteins that regulate cardiac function and homeostasis.
222 Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc.
Figure 1. Key Regulators of Cardiac Differentiation Share a Temporal Chromatin Signature
(A–F) At five different time points of directed differentiation of human embryonic stem cells into cardiomyocytes (T0, 2, 5, 9, and 14), the levels of histone
modifications H3K4me3 (activating), H3K27me3 (repressing) and H3K36me3 (transcribed) are shown within a ?50 kb region around (A) NKX2-5, a well-known
regulator of cardiac differentiation (scales used: 1 to 250/150/50 tags per 150 bp for H3K4me3/H3K27me3/H3K36me3) and (B) MYH6, a well-known structural
component of cardiac cells (scales used: 1to 500/100/50 tags per 150bp for H3K4me3/H3K27me3/H3K36me3). The relative levels of histone modifications (red,
The averaged levels of epigenetic marks within ±20 kb of the TSS of (E) known regulators of cardiac differentiation and (F) known cardiac structural factors are
plotted across all five time points (0, 2, 5, 9, 14 = green, yellow, red, blue, purple). For key regulators of cardiac differentiation, levels of H3K4me3 and H3K36me3
increase during differentiation while H3K27me3 begins high and decreases, while H3K27 remains consistently low for cardiac structural factors. Note GATA4 is
shown twice in panel (C) due to activation of two different promoters in our system. See Figure S3 for patterns found for other gene groups. See also Figures S1
Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc. 223
The Temporal Chromatin Signature of Cardiac
To assess the cardiac lineage-specificity of the temporal chro-
matin signature for cardiac regulators, we compared this signa-
ture with the temporal chromatin patterns at genes involved in
specification of noncardiac mesoderm, neuroectoderm and
endoderm fates (Figures S3E–S3I). Similar to cardiac tran-
scription factors, most of the major transcription factor genes
involved in hematopoiesis (e.g., TAL1, RUNX1, HHEX and
LMO2) and skeletal muscle differentiation (e.g., MYOD1,
MYF5, and MYF6) had low levels of H3K4me3 and high levels
of H3K27me3 in the pluripotent state. However unlike cardiac
TFs, noncardiac factors do not activate in this system and
generally resolve to only H3K27me3 by T5. Some lineage-selec-
tive factors such as GATA1, a key regulator of erythroid fate,
showed negligible levels of any of the histone modifications at
any time point. Genes encoding transcription factors involved
in neuroectoderm differentiation, such as NEUROD1, show
high levels of H3K27me3 (often in large domains (Guenther
et al., 2010)) in combination with low H3K4me3 in the pluripo-
tent state (Figure S3H). But whereas H3K27me3 levels at neu-
roectodermal genes remain high throughout differentiation,
they evince a dramatic drop in H3K4me3 by T2. Notably, hema-
topoietic and skeletal muscle transcription factors also show
declines in H3K4me3 but not until T5. This ordering recapitu-
lates the later fate choice for mesoderm subtypes versus the
early choice of primary germ layer (mesoderm versus ecto-
derm). Interestingly, several genes typically associated with
endoderm formation are activated at T5, including FOXA2 and
SOX17. This could be due to the presence of a small number
of endodermal cells in our cultures or the fact that many of
these genes have roles in both mesoderm and endoderm
Identification of New Regulators of Human Cardiac
We next sought to determine if the temporal chromatin signature
of cardiac regulators could be used to identify regulators of
human cardiac development. Using a curated set of known
cardiac regulators (Figure 1), we developed a classifier based
on the concomitant induction of mRNA, loss of H3K27me3
marks, and anticorrelation coefficients of the H3K4me3 and
H3K27me3 signals over the time course (see Experimental
Methods). Next, we scored each gene against the classifier
and rank-ordered each gene at T5, T9, and T14 by its classifica-
a classifier based on mRNA expression only. Figure 2A shows
the top ten genes at each time point using each algorithm, func-
tionally annotated as cardiac developmental regulators, cardiac
structural genes, developmental regulators with unknown
cardiac roles, and all other genes (including unknown cardiac
or developmental roles). A list of the top 100 genes identified
by using expression alone and chromatin + expression at each
time point is shown in Figure S4. Using mRNA expression alone,
14 nonredundant genes comprised the top 10 list at the three
time points. Of these, six (43%) encoded cardiac structural
proteins, five (36%) encoded known cardiac developmental
regulators, one (7%) encoded a developmental regulator with
unknown cardiac function, and two (14%) were genes with
unknown function. Using the chromatin + expression method,
the top ten lists across all time points contained 15 nonredun-
dant genes. In contrast to the mRNA expression-only approach,
11 of these genes (73%) encode developmental regulators with
known cardiac roles, three others (20%) encode developmental
regulators with unknown cardiac roles, and one gene (7%)
encodes a protein of unknown function. Interestingly, this gene
(CCDC92) is predicted to contain a coiled-coil domain, which
is found in many transcription factors. Notably, none of the
top-scoring genes in the combined algorithm encode cardiac
Beyond the top 10, the chromatin + expression algorithm
identified many genes with less well-defined roles in cardiac
proteins, signaling ligands, extracellular matrix proteins, and
enzymes. Gene ontology analysis demonstrated that the top
100 genes identified by using chromatin + expression are highly
enriched for regulation of transcription and differentiation func-
tions (Figure 2B). To determine the accuracy with which each
classifier could discriminate known cardiac regulators from all
other genes, and specifically from cardiac structural genes,
we computed a receiver operating characteristic (ROC) curve
for each class using both the mRNA expression-only and the
chromatin + expression classifier. These showed that the
combined (histone modification + expression) classifier had
extremely high sensitivity and specificity both for discrimination
of cardiac regulators from all genes (ROC = 0.994) and from
cardiac structural proteins (ROC = 1.000) (Figure 2C). By
contrast, a classifier based on temporal mRNA patterns alone
can reasonably discriminate genes with a cardiac role from all
other genes but cannot distinguish regulators from cardiomyo-
cyte structural proteins involved in muscle contraction and
Analysis of Temporal Chromatin Dynamics Identifies
Regulators of Other Cellular Fates
Theselectivediscrimination ofgenesregulating cardiac differen-
tiation by comparison of epigenetic profiles and expression led
us to ask whether we could identify factors not expressed during
the cardiovascular differentiation process that regulate other
lineage fates. To explore this, we first examined a curated list
of neuroectodermal regulatory genes and structurally-related
genes. Remarkably, these showed distinct temporal chromatin
signatures for developmental regulators versus structural gene
classes, even though the constituent genes were not signifi-
cantly expressed at any time in our cardiac directed differentia-
tion system (Figures 3A–3F).
fates, we performed principal component analysis of the chro-
matin modification profiles (see Experimental Procedures). This
analysis revealed that genes with similar roles in cell fate deter-
mination clustered together (Figure 3G), remaining distinct
from other lineage-specific genes. This result suggests that
a rich layer of information on developmental programming can
be mined from temporal analysis even of a single lineage, which
may in turn provide insight into the mechanisms that determine
numerous cell fates.
224 Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc.
Functional Validation of Chromatin Dynamics-Based
We next sought to confirm whether the temporal chromatin
signature of cardiac regulators could identify bona fide cardiac
regulators. Among the genes we identified without known roles
in cardiac development was the homeodomain-containing tran-
scription factor MEIS2 (Figure 4). MEIS transcription factors
interact with HOX and PBX transcription factors to regulate
downstream targets in multiple cellular processes, and previous
studies have demonstrated a requirement for the related gene,
Meis1, in mouse and zebrafish heart development (Maves
et al., 2009; Minehata et al., 2008; Stankunas et al., 2008). As
shown in Figure 4A, MEIS2 shares the histone modification
pattern we have identified as a marker of cardiac regulatory
genes. In zebrafish there are two orthologs of MEIS2: meis2a
and meis2b. Interestingly, in situ time course experiments
carried out in developing zebrafish embryos shows meis2b
expression in the heart field closely resembles that of gata4,
tion, meis2b expression is observed in the developing hindbrain
To validate the predicted role of MEIS2 in cardiac develop-
ment based on its temporal chromatin signature, we utilized
antisense morpholino oligonucleotide (MO) knockdown in devel-
oping zebrafish embryos (Figure 5). We found that delivery of
a splice-blocking MO directed against meis2b (‘‘meis2b-MO’’)
into fertilized zebrafisheggs resultsin defective cardiac morpho-
genesis. Defects are evident as early as 19 hr postfertilization
(hpf), when meis2b-MO embryos fail to fuse their bilateral heart
fields into a linear heart tube at the midline (Figure 5A) (Glickman
and Yelon, 2002). At 24 hpf, heart tubes have formed in meis2b-
MO embryos, but they demonstrate an early looping defect as
evidenced by the midline to right-sided location of the devel-
oping linear heart tube compared to the left-sided developing
heart in control-MO embryos (Figure 5A) (Glickman and Yelon,
2002). By 48 and 72 hpf, control-MO embryos have normally
looped hearts (Glickman and Yelon, 2002), while the meis2b-
MO embryo hearts remain linear, displaying a persistent looping
defect (Figures 5A and 5B). Furthermore, meis2b-MO embryos
have a markedly reduced heart rate at 72 hpf (92 ± 10 beats
per minute) compared with control-MO embryos (154 ± 16 beats
per minute), and they have pericardial edema indicative of
cardiac failure (Figures 5C and S5). These findings indicate
a requirement of meis2b for normal heart function (Figure 5D).
Of note, these phenotypes are not attributable to a general
Figure 2. Accurate Discrimination of Key Regulators of Cardiac
Differentiation from Other Lineage-Specific Genes
(A) All genes were ranked by two different methods in order to identify key
regulators of cardiac differentiation. They were ranked at days 5, 9, and 14 by
a formula using either (left) RNA expression alone, or (right) one that accounts
forlevels ofH3K4me3,H3K27me3and RNAexpression.Ateachtimepoint the
top 10 candidate regulators are depicted for the respective methods. Devel-
opmental regulators with known roles in cardiac differentiation are shown in
white text on red background, developmental regulators with no currently
appreciated role in cardiac differentiation are shown in white text on gray
background, and genes whose function pertains to the structure and function
of heart cells with no known regulatory roles are shown in red text on white
background. All other genes are shown in black text on white background.
Genes that were used in the training set for identifying the chromatin +
expression regulator signature are indicated with an asterisk.
(B) The top 100 candidates provided by each ranked list (see Figure S4) were
analyzed to determine the degree to which the lists were enriched in 11 key
gene ontology functional categories. The size of each circle is proportional to
the significance of the enrichment of genes with the indicated functional role
within the given list of 100 genes at each time point/method of ranking genes.
Ranking genes using H3K4m3, H3K27me3 and RNA expression yields lists
that are not contaminated by structural factors and are more enriched with
known regulators of cardiac differentiation.
specific and sensitive than classification based on expression alone (purple).
Shown are ROC curves for the identification of key regulators of cardiac
differentiation from among all genes (left) or among all genes involved in heart
development (right). The expression-only classifier systematically misclas-
sifies structural factors that are involved in heart function but do not regulate
cardiac development (right), leading to a lower area under the curve when
classifying key regulators from among all genes (left). The genes used to
generate true-positives for cardiac regulatory and structural genes are given in
Figure 1. See also Figure S4.
Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc. 225
developmental delay upon knockdown of meis2b as embryos
were compared based on number of somites (developmental
stage) as well as time postfertilization. These phenotypes are
also unlikely to be attributable to off-target effects because
a separate, translation-blocking meis2b morpholino produces
similar looping defects (Figure S5 and data not shown). These
data establish meis2b as a regulator of cardiac development,
confirming the chromatin signature-based prediction.
The chromatin landscape of both mouse and human ESCs has
been intensively investigated. In the pluripotent state, many
developmental loci are marked with both activating H3K4me3
and repressing H3K27me3 and are thus termed ‘‘bivalent’’
(Azuara et al., 2006; Bernstein et al., 2006; Pan et al., 2007).
The notion is that these genes are simultaneously suppressed
but poised for activation should the cell receive appropriate
cues. Bivalent promoters have also been found at develop-
mental loci in mouse embryos, both in the inner cell mass and
trophectoderm, and also in zebrafish embryos (Dahl et al.,
2010; Lindeman et al., 2010; Vastenhouw et al., 2010). Other
studies have shown that bivalent promoters are present in
progenitor and adult stem cell populations, including neural
progenitors, mesenchymal stem cells, and hematopoietic stem
cells, and that these ultimately resolve to either active or inactive
upon differentiation (Collas, 2010; Cui et al., 2009; Mazzarella
et al., 2011b; Mohn et al., 2008b).
Figure 3. Temporal Chromatin Signatures Enable Cross-Lineage Identification of Key Regulatory Factors
(A–F) The median levels (middle line) and 95% confidence intervals (shaded regions) of H3K27me3 (red), H3K4me3 (green), and RNA expression (blue) at each
time point are depicted for several categories of genes: (A) genes involved in cardiac structure and function, (C) genes involved in neuroectoderm structure/
function, and regulators of differentiation for (B) cardiac, (D) neuroectoderm, (E) mesoodermal and (F) endodermal cells. (A–F) were identically normalized, such
that the lowest and highest values for each individual mark across all time points and gene groups were plotted as 0 and 1, respectively.
(G) Using principle component analysis, the 15 dimensional data for each gene (five time points * three measurements of chromatin and mRNA) were reduced to
two dimensions, and a scatterplot is shown depicted the relative locations of each gene in the reduced-dimensional space. Genes involved in structure and
function of cells are contained within the largest cluster (gray) distinct from the cluster containing key regulators of cellular fate: cardiac (red), neuroectoderm
(blue),endoderm(purple), and mesoderm (yellow). Nonannotatedgenes within eachofthe colored domains haveahigh probabilityof having unappreciated roles
as key regulators of cellular fate.
226 Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc.
We sought to characterize the epigenetic changes that occur
during cardiovascular differentiation from human ESCs by per-
forming genome-wide mapping of three histone modifications,
H3K4me3, H3K27me3, and H3K36me3, at five key develop-
mental time points. Our study shows that the temporal trajecto-
ries of H3K4me3 and H3K27me3 during differentiation are more
complex than a simple ‘‘resolution from bivalency’’ model. As an
example of this, FGF19 and NODAL are highly transcribed in
human ESCs with high levels of H3K4me3 and low levels of
H3K27me3 (Figure S3D). They subsequently lose H3K4me3
and gain H3K27me3 over time. If one were only to have taken
time points T3 (sometime between T2 and T5) and T14, one
Figure 4. MEIS2 Chromatin Modifications during hESC Differentiation and Expression in Developing Zebrafish Embryos Resembles Other
Regulators of Cardiac Development
(A) The temporal pattern of epigenetic marks at the MEIS2 locus is similar to that of other regulators of cardiac development shown in Figure 1 (scales used: 1 to
250/150/25 tags per 150 bp for H3K4me3/H3K27me3/H3K36me3).
(B) Zebrafish meis2b expression are shown for developing embryos at the 1, 3, 5, 8, 10, 18, and 22 somite stages, showing (C) similar expression patterns within
the bilateral heart fields (arrows) to gata4 through the 10 somite stage. By 18 somites, meis2b is no longer expressed in the cardiac mesoderm whereas gata4
Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc. 227
might conclude that the genes began in a bivalent state and then
resolved toward repression, whereas in reality the ‘‘bivalent’’
appearance was merely an artifact of the complete reversal
from H3K4me3 to H3K27me3. Yet another example is the set
of genes involved in mesodermal differentiation (Figure S3E),
Figure 5. meis2b Is Required for Cardiac
(A) Expression of myl7 at 19 hpf, 24 hpf, 48 hpf,
and 72 hpf in control-MO (top row) versus meis2b-
MO (bottom row) injected zebrafish embryos.
Dorsal view, anterior is up in 20 somite and 24 hpf
embryos. Ventral view, anteriorup in 48hpf and 72
hpf embryos. At 19 hpf, meis2b-MO injected
embryos display defects in fusion of the myl7+
cardiac progenitors at the midline compared with
control-MO injected embryos. By 24 hpf, the heart
aberrant cardiac morphogenesis and is either
sitting at the midline or moving down the right side
of the embryo, compared with the control-MO
injected embryos where normal heart develop-
ment proceeds with the heart tube emerging from
under the head, down the left side of the embryo.
At 48 and 72 hpf, control MO injected embryos
display normal cardiac looping, whereas meis2b-
MO injected embryos’ hearts have not looped.
(B) This failure of cardiac looping in meis2b-MO
injected embryos is further evident in vmhc (green)
(C) Heart rate is significantly reduced in meis2b-
MO injected embryos compared with control-MO
injected embryos at 72 hpf (b.p.m. = beats per
minute) Mean heart rate ± SD is shown, n = 10.
p = 4 3 10?9(Student’s t test, two-tailed).
(D) Percentages of embryos displaying the de-
Scale bars, (A, top left), 100 mm, and (A, top third
from the left), 50 mm. See also Figure S5.
which are highly expressed despite being
heavily marked with H3K27me3. These
and other examples point to a complex
regulatory relationship than cannot be
described by a simple ‘‘resolution from
Transcription factors and signaling
molecules known to play critical roles
in cardiovascular development, such as
NKX2.5, showed a unique chromatin
signature that consisted of high enrich-
ment for H3K27me3 in pluripotent ESCs
that gradually decreased as H3K4me3,
H3K36me3, and RNA expression in-
creased over time. In contrast, struc-
tural proteins like alpha-myosin heavy
chain (MYH6) demonstrated markedly
RNA expression at later time points,
The differences in chromatin markings
structural proteins are consistent with previous studies com-
paring pluripotent and differentiated cells. Our study shows
further that the complex temporal chromatin patterns over
a time course of differentiation contain a far richer amount of
between genesregulators and
228 Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc.
information regarding the exact function of the genes they are
To use the information contained within the temporal chro-
matin signatures to identify regulators, we developed a classifier
torankgenesaccording tothelikelihood thatagiven genewould
highly were transcription factors that had not been previously
esis that these genes were in fact previously unappreciated key
regulators of heart development by utilizing morpholino knock-
down technology in zebrafish embryos. Indeed, knockdown of
meis2b resulted in severe defects in heart looping in early stage
zebrafish embryos. This provides in vivo evidence that our
methodology of coupling stem cell differentiation with histone
modification pattern identification can identify regulators of
development. It is worth noting that several of these regulators
could be identified using the rank list of the top 100 genes based
on expression alone (Figure S4). However, these regulators
usually rank much lower down the list and could easily get lost
amidst the noise of so many structural genes. For example,
MEIS2 ranked 4that T5, 4that T9, and 5that T14 using the
chromatin signature ranking but 49that T5, 37that T9, and 48th
at T14 based on expression alone. Our data set will thus serve
as a resource for scientists and clinicians across multiple fields.
The list of cardiac regulators is extensive and each potential
candidate gene warrants further investigation to flesh out its
role in differentiation and/or morphogenesis. One can imagine
that perturbations of these regulators could alter cardiogenesis
during human development. Thus, screening for genetic etiolo-
gies of congenital heart disease could be expanded to include
our list of regulators.
It is interesting to consider why the chromatin dynamics of
genes involved in developmental regulation are so different
from structural genes that regulate the function of differentiated
cells. The principal difference in chromatin signatures is the high
degree to which developmental regulators are repressed by
H3K27me3 prior to their expression, whereas structural genes
show no such modification. We propose that the consequence
of inappropriate activation of developmental regulators is more
deleterious, e.g., by inducing the wrong cell type, proliferative
state, or survival/death signals. These genes therefore require
both loss of repression and gain of activation to be expressed.
Conversely, inappropriate activation of a gene encoding con-
tractile proteins, ion channels, or metabolic enzymes may have
less severe consequences for development, and chromatin
regulation through activation mechanisms achieves sufficient
The establishment of human ESC technology opened the
doors to analyses that can provide insights into human develop-
ment that have not been possible before. Directed differentiation
of human ESCs into numerous cell types has been one of the
major advances in the field over the past 10 years. In addition
to the cardiovascular directed-differentiation model system we
utilized in this study, similar protocols exist for the generation
of other cell types that are particularly relevant to regenerative
medicine, including neurons (Lee et al., 2007) and pancreatic
beta-cells (Phillips et al., 2007). Thus, our approach of mapping
chromatin states over the course of differentiation could easily
be applied to other cell lineages, thereby facilitating the identifi-
cation of regulators of differentiation and development of other
Several limitations of the approach used in this study are
important to note. First, although the directed differentiation
enriched populations of cardiovascular cells; however, noncar-
diac cells are also present in our cultures. Therefore, we cannot
be due to the presence of other cell types, such as noncardiac
mesoderm and endoderm. That said, the cell populations
analyzed in this study contained at least 80% progenitors at T5
and 50% cardiomyocytes at T14, so the majority of the chro-
matin patterns are likely informative for cardiac development.
Another issue is that the efficiency of directed differentiation is
often dependent on the particular ESC cell line used or even
the batch of such cells used. Thus, it will be critical for these
experiments to be repeated in other cell lines beyond the H7
ESC line used in our laboratory. Lastly, although human ESCs
provide a platform to model human development in vitro, it is
presently unclear how well this differentiation system mimics
in vivo development in terms of expression patterns and epige-
netic changes, such as histone modifications. These limitations
are common to many directed differentiation systems, and
reflect the current standard issues shared by stem cell biologists
worldwide. On the other hand, there are currently no other ways
to study early events in human development, and we were able
to utilize our cardiovascular directed-differentiation system to
identify regulators of heart development. Additionally, our study
showed that the temporal chromatin profiles along cardiomyo-
cyte differentiation contained enough information to identify
genes with likely unappreciated roles in neurectodermal devel-
opment, even though the vast majority of cells in the population
split from that cellular-fate quite early in differentiation. As the
chromatin states along other differentiation pathways are
measured, the information from all of these model systems can
be integrated using methods similar to those described in this
Maintenance of Human Embryonic Stem Cells
H7 human ESCs were maintained on mouse embryonic fibroblasts (MEFs)
in medium consisting of DMEM/F12 supplemented with 20% KnockOut
serum replacement (Invitrogen), L-glutamine, nonessential amino acids,
beta-mercaptoethanol, and 8 ng/ml basic fibroblast growth factor (bFGF,
Peprotech). Cells were passaged by using collagenase IV and trypsin, as
well as the ROCK inhibitor Y-27632 (10 mM, Tocris) to enhance cell survival.
Prior to directed differentiation, human ESCs were passaged at least twice
on Matrigel-coated plates to deplete the cultures of MEFs. For growth on
Matrigel, cells were maintained in MEF conditioned medium (MEF-CM) sup-
plemented with 8 ng/ml bFGF.
Cardiovascular Directed Differentiation
H7 human ESCs on Matrigel-coated plates were harvested by using Collage-
nase IV and trypsin as during passaging. For embryoid body formation, cells
were gently broken up into clusters of roughly 25–50 cells and plated into
low-attachment plates in StemPro-34 medium (Invitrogen) supplemented
with L-glutamine, ascorbic acid, transferrin, and monothioglycerol (hereafter
Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc. 229
referred to as StemPro backbone) plus 0.5 ng/ml bone morphogenic protein 4
(BMP4,R+D). After24hr,embryoidbodies weregravity-settledandreplatedin
fresh StemPro backbone plus 10 ng/ml BMP4, 6 ng/ml Activin A (R+D), and
5 ng/ml bFGF. After 3 days, the embryoid bodies were dissociated into single
cells using trypsin and seeded onto Matrigel-coated plates at a density of
5 3 105to 1 3 106cells/cm2in StemPro backbone. Medium was changed
every 3–4 days thereafter until day 14 of differentiation.
Cells were analyzed by flow cytometry at the cardiovascular progenitor (T5)
and definitive cardiovascular cell (T14) stages of differentiation. Cultures
were dissociated into single cells using trypsin enzymatic digestion. Progen-
itor stage cells were stained with mouse anti-human VEGFR2/KDR-PE
(R+D) and mouse anti-human PDGFRa-APC (R+D). For intracellular staining,
cells were fixed in 4% paraformaldehyde for 10 min followed by permeabi-
lization with 0.75% saponin. Cardiomyocytes and smooth muscle cells
were identified by staining with mouse anti-cardiac troponin T (LabVision/
Neomarkers) and rabbit anti-smooth muscle actin (Abcam), followed by
goat anti-mouse-PE (Jackson) and donkey anti-rabbit-APC (Jackson). Endo-
thelial cells were identified using mouse anti-human CD31-PerCP-eFlour710
(eBioscience). Flow cytometric analysis was performed using a BD FACS
Canto II machine.
Chromatin Immunoprecipitation Followed by Massive Parallel
H7 human ESCs at different cardiovascular stages were crosslinked with 1%
formaldehyde (Sigma) and sheared by Diagenode bioruptor. The antibodies
used in ChIP assays were 9751 for histone H3 tri-methyl lysine 4 (Cell
Signaling), 07-449 for histone H3 tri-methyl lysine 27 (Millipore), and ab9050
for histone H3 tri-methyl lysine 36 (Abcam). For each IP, Dynabeads (M-280,
sheep anti-rabbit IgG, Invitrogen) were incubated with antibodies for 6 hr at
4?C and then incubated overnight with ?100 mg sheared chromatin. The
complexes were rinsed sequentially with IP wash buffer I (50 mMTris-HCl
pH 8.0, 150 mM NaCl, 1 mM EDTA [pH8.0], 0.1% SDS, 1% Triton X-100,
0.1% sodium deoxycholate), high salt buffer (50 mMTris-HCl pH8.0, 0.5 M
NaCl, 1 mM EDTA [pH8.0], 0.1% SDS, 1% Triton X-100, 0.1% sodium deox-
ycholate), IP wash buffer II (50 mMTris-HCl [pH8.0], 1 mM EDTA pH8.0, 1%
NP-40, 0.7% sodium deoxycholate, 0.5 M LiCl), and TE buffer (10 mMTris-
HCl [pH8.0], 1 mM EDTA pH8.0). The complexes were incubated with elution
buffer (10 mMTris-HCl [pH 8.0], 0.3 M NaCl, 5 mM EDTA [pH8.0], 0.5% SDS)
supplemented with RNase A (Ambion) at 65?C overnight. After separation, the
DNA was treated with Proteinase K and purified by PCR purification column
(QIAGEN). The sequencing libraries were prepared following a standard
protocol using PE adapters (Illumina). For each library, an Illumina Genome
Analyzer was used to generate 36 base pair sequence reads, yielding
an average of ?18 million tags that mapped uniquely to the human
Affymetrix RNA Expression Array
At the five time points indicated, an aliquot of cells were harvested in RNAlater
(Ambion) and stored at ?20?C. Total RNA was isolated using RNeasy kits
(QIAGEN) according to the manufacturer’s instructions followed by quantifica-
tion and quality assessment using a Bioanalyzer (Agilent). Approximately 3 mg
RNA was subjected to in vitro transcription and labeling followed by hybridiza-
tion to Affymetrix Human Exon 1.0 ST arrays (Affymetrix) according to the
ChIP-seq tag density, the number of uniquely mapping sequenced tags
within±75bp, wascalculatedin20bpbinsacross the(hg18)referencehuman
genome. Using annotated transcription start sites, the ChIP densities for
three chromatin modifications (H3K4me3, H3K27me3, and H3K36me3) within
20 kb of each transcription start sites were collected at 20 bp resolution.
To determine the temporal chromatin profiles for different classes of genes
TSS-centered profiles of chromatin changes were assembled. For H3K27me3
and H3K4me3data, thiswasaccomplished by ‘‘folding’’thedata within 2kbof
each TSS in half and performing a linear regression. The slope and intercept of
the resulting line were directly proportional to the intensity of those signals and
were used to assign a single number to each gene at each time point. For
H3K36me3, the average signal intensity over the gene body was used as the
signal intensity measure.
Two methods were used to rank genes according to potential roles as
regulators of cardiac differentiation. The formulas for ranking genes according
to these measures follow:
bi=ai, ? rk4;k27,
where ‘‘a’’ is the measure based on expression alone, and b is the measure
based on expression (x), H3K4me3 (k4), and H3K27me3 (k27). The measure
was calculated for each gene (i), using data from each of n = 5 time points
(j), and also using information specific to a given time point of interest ‘‘t.’’
the minimum value from a set of numbers.
Principal component analysis was performed in R using 20 data points per
gene, including five time points for each of four measurement types:
H3K4me3, H3K27me3, H3K36me3, and RNA expression. The overview for
all genes was plotted in 2D space according to the top three principal
Zebrafish Morpholino Injections and In Situ Hybridization
The strain Tg(acta1a:GFP) (Higashijima et al., 1997) was used as a wild-type
zebrafish strain and was maintained, crossed, injected, raised, and staged
as described (James et al., 2009) and in accordance with IACUC approved
procedures. Heart rate was assessed in ten randomly selected embryos
from each group (control-MO versus meis2b-MO) by visualizing the heart
beat in living embryos and counting for 1 min. myl7 and vmhc probes were
synthesized from published constructs (Yelon et al., 1999). Stock morpholinos
30 ng/nl, diluted to injection strengths (10 ng/nl for splice blocking E3I3
meis2b-MO [injected 4nl of 2.5ng/nl solution], 6 ng/nl for ATG blocking
meis2b-MO], and 5 ng/nl (1–2 nl injected) Standard control-MO and injected
into one-cell stage zebrafish embryos. The sequences for the morpholinos
are as follows: Splice-blocking E3I3 meis2b-MO: ACCGAAATCAATAA
CTTGCCTGTTT; ATG blocking meis2b-MO: 50-CTTCGTACCGTTGAGCCATC
AGCAT; Standard control-MO: 50-CCTCTTACCTCAGTTACAATTTATA.
RNA in situ hybridizations were performed as previously described (Maves
et al., 2009; Talbot et al., 2010). Phenotype was scored ‘‘affected’’ if the heart
displayed a defect as pictured versus ‘‘unaffected’’ if the heart appeared
normal, compared with controls.
The GEO accession numbers for epigenetics data and for the expression data
are GSE35583 and GSE19090, respectlively.
Supplemental Information includes five figures and can be found with this
article online at http://dx.doi.org/10.1016/j.cell.2012.08.027.
The authors thank Nina Tan, Mark Saiget, James Fugate, Kristen Lee, Rajinder
Kaul, and Stanley Kim for technical expertise.This work was supported by NIH
grants P01 GM081719, U01 HL100405, P01 HL094374, R01 HL084642, R01
HL64387, R03 AR057477, and UW ENCODE Center (U54HG004592).
S.P. was supported through NIH F30 HL095343. H.W. was supported by
R90HG004152. R.T.M. is an investigator of the HHMI.
230 Cell 151, 221–232, September 28, 2012 ª2012 Elsevier Inc.
Received: April 3, 2012
Revised: June 26, 2012
Accepted: August 15, 2012
Published online: September13, 2012
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