RESEARCH ARTICLE 2863

Development 137, 2863-2874 (2010) doi:10.1242/dev.053462© 2010. Published by The Company of Biologists Ltd

Transcriptomic landscape of the primitive streak
Cantas Alev1,2, Yuping Wu1, Takeya Kasukawa3, Lars M. Jakt4, Hiroki R. Ueda3,5 and Guojun Sheng1,*

SUMMARY
In birds and mammals, all mesoderm cells are generated from the primitive streak. Nascent mesoderm cells contain uniquedorsoventral (D/V) identities according to their relative ingression position along the streak. Molecular mechanisms controlling
this initial phase of mesoderm diversification are not well understood. Using the chick model, we generated high-qualitytranscriptomic datasets of different streak regions and analyzed their molecular heterogeneity. Fifteen percent of expressed
genes exhibit differential expression levels, as represented by two major groups (dorsal to ventral and ventral to dorsal). A
complete set of transcription factors and many novel genes with strong and region-specific expression were uncovered. Core
components of BMP, Wnt and FGF pathways showed little regional difference, whereas their positive and negative regulators
exhibited both dorsal-to-ventral and ventral-to-dorsal gradients, suggesting that robust D/V positional information is generated
by fine-tuned regulation of key signaling pathways at multiple levels. Overall, our study provides a comprehensive molecular
resource for understanding mesoderm diversification in vivo and targeted mesoderm lineage differentiation in vitro.

INTRODUCTION
The mesoderm germ layer gives rise to the most diverse array ofcell types in the animal body. One of the earliest steps in generating
this diversity is the patterning of mesoderm precursors along thedorsoventral (D/V) body axis, the molecular mechanisms of which
remain poorly understood. In both vertebrates and invertebrates,
mesoderm cells emerge from the ectoderm through the gastrulation
process, and in amniotes this process takes place in a transitory
structure called the primitive streak (referred to hereafter as thestreak) (Bellairs, 1986; Mikawa et al., 2004; Nakaya and Sheng,
2008; Psychoyos and Stern, 1996a). The streak is composed mainlyof mesoderm precursors, which are still an integral part of theepiblast and with many epithelial characteristics, en route to
becoming true mesoderm cells with mesenchymal morphologies(Nakaya and Sheng, 2009; Nakaya et al., 2008). The streak also
maintains an ‘identity’ gradient within constituent cells and gives
these cells unique D/V positional cues after their exit from thestreak. Along the D/V body axis, mesoderm cells in amniotes arepatterned to contribute later on to five broadly defined tissue
lineages: the axial, paraxial, intermediate, lateral plate andextraembryonic mesoderm. This patterning event starts when
epiblast-located mesoderm precursors enter the streak, and their
D/V identities, although still labile at this stage, are reflected intheir relative positions along the length of the streak, where they
undergo epithelial-to-mesenchymal transition.
At Hamburger and Hamilton stage (HH) 4 of chickdevelopment, which is also known as the full primitive streak stage,fate map analyses have shown that cells located in the node region
1

Laboratory for Early Embryogenesis, RIKEN Center for Developmental Biology,
Kobe, Hyogo 650-0047, Japan. 2Vascular Regeneration Research Group, Institute of
Biomedical Research and Innovation, Kobe, Hyogo 650-0047, Japan. 3Functional
Genomics Unit, RIKEN Center for Developmental Biology, Kobe, Hyogo 650-0047,
Japan. 4Laboratory for Stem Cell Biology, RIKEN Center for Developmental Biology,
Kobe, Hyogo 650-0047, Japan. 5Laboratory for Systems Biology, RIKEN Center for
Developmental Biology, Kobe, Hyogo 650-0047, Japan.
*Author for correspondence (sheng@cdb.riken.jp)
Accepted 5 June 2010

(the anterior ~1/8th of the streak) will give rise to more dorsal
structures, including the axial mesoderm and medial somites,
whereas the more posteriorly located cells in the streak will giverise to progressively more ventral types, including lateral somites
from the remainder of the first quarter and the second quarter,intermediate mesoderm from the second quarter, lateral plate
mesoderm from the remainder of the first quarter and the second
and third quarters, and extraembryonic mesoderm from the second
to fourth quarters (Garcia-Martinez et al., 1993; James andSchultheiss, 2003; Lopez-Sanchez et al., 2001; Nakazawa et al.,2006; Nicolet, 1970; Psychoyos and Stern, 1996a; Selleck andStern, 1991). Although a general fate map is delineated in this way
in avian and mammalian embryos, neither the boundary nor theexact fate is defined sharply at this stage of chick development(Inagaki et al., 1993; Psychoyos and Stern, 1996a; Psychoyos andStern, 1996b). When dissected and cultured in a neutral or ectopic
environment, pieces of streak tissue taken from along its
anteroposterior (A/P) length tend to differentiate into the mesoderm
lineages of their respective D/V identities (Abercrombie andWaddington, 1937; Garcia-Martinez and Schoenwolf, 1992;
Inagaki and Schoenwolf, 1993; Nakazawa et al., 2006). Yet,experiments in which regions of the streak were extirpated orreversed anteroposteriorly indicated a labile D/V specification
among streak cells and a regulative interaction between mesoderm
precursors located in the streak and those located in thesurrounding epiblast region (Abercrombie, 1950; Abercrombie andBellairs, 1954; Garcia-Martinez and Schoenwolf, 1992; Grabowski,
1956; Inagaki et al., 1993; Joubin and Stern, 1999; Psychoyos andStern, 1996b).
The molecular mechanisms by which the streak maintains a
D/V gradient during its brief existence are not well understood.
Central to our current understanding of vertebrate mesoderm D/Vpatterning is the BMP activity gradient generated by a balancing
act between pro-BMP and anti-BMP signals (Dale et al., 1992;
Dosch et al., 1997; Harland, 2004; Imai et al., 2001; Inomata etal., 2008; Jones et al., 1992; Jones and Smith, 1998; Khokha et al.,2005; Munoz-Sanjuan and Brivanlou, 2004; Piccolo et al., 1996;
Schmid et al., 2000; Streit and Stern, 1999). In addition, the Wnt

DEVELOPMENT

KEY WORDS: Primitive streak, Gastrulation, Mesoderm, Chicken, Dorsoventral, Transcriptome

2864 RESEARCH ARTICLE

MATERIALS AND METHODS
Data acquisition and analysis

A flow chart outlining the data acquisition and analysis process is shownin Fig. S9 in the supplementary material. Details are described in thefollowing sections.
Streak tissue collection and RNA in situ analysis

Fertilized hens’ eggs were purchased from Shiroyama Farm (Kanagawa,Japan) and fresh eggs were incubated, without prior storage, at 38.5°C for~18 hours to reach HH4. Embryos were collected in Pannett-Compton
solution (Streit and Stern, 2008). Only embryos at HH4– or HH4 were used
for streak dissection. The entire streak was cut out first and then cut into
four equal pieces along its A/P length. Collected pieces were frozen inliquid nitrogen after pooling ~10 pieces, and ~90 pieces were combinedlater on to be used for RNA isolation as one sample. The numbering ofsamples corresponds to the original embryo/streak pool (e.g. A1, B1, C1
and D1 were derived from the same 85 streaks). Total RNAs were isolatedusing the RNeasy Kit (Qiagen). RNA concentrations were measured andequalized, and RNA quality was checked on a gel. Five micrograms of total
RNA were used for each array. A standard protocol was followed forwhole-mount RNA in situ hybridization analysis. Details of primer sets,probe lengths and corresponding regions of probes generated are shown in
Table S4 in the supplementary material.
GeneChip analysis

cDNA synthesis and cRNA labeling reactions were performed according
to the one-cycle protocol provided by Affymetrix. Affymetrix high-density
oligonucleotide arrays for Gallus gallus (GeneChip Chicken Genome
Array) were hybridized, stained and washed according to the expression
analysis technical manual (Affymetrix). The expression values weresummarized by the RMA method. The resulting expression values wereused in all the subsequent analyses. Raw datasets have been submitted to
NCBI GEO with accession number GSE22230.
Identification and gene ontology (GO) assignments to expressedgenes

For each streak region (A, B, C or D), an ‘expressed gene set’ was first
assembled. Each GeneChip measurement for a given probe set was
assigned with a ‘present’, ‘absent’ or ‘marginal’ call using the Affymetrix
MAS5 detection algorithm. Probe sets with a present call in all three
replicated measurements were retrieved. The Bioconductor 2.5.0 suite(Gentleman et al., 2004) was used for GO term assignment. The numberof genes in the GO analysis was based on unique genes assigned to eachGO term.
Differentially expressed gene analysis, gene clustering andchromosomal mapping

To identify differentially expressed genes, statistical tests with one-way
ANOVA for each probe set were performed. Multiple comparisons werethen corrected with false discovery rates (FDRs) and an FDR of less than
0.1 was chosen as significant (‘significantly differentially expressed
genes’). Stringent sets of the significantly differentially expressed genes
were made by filtering out probe sets with ratios between their maximum
and minimum mean expressions among four streak regions of less than 1.5.
Next, a supervised clustering analysis was performed for classification.
Fourteen template binary patterns, with repeated permutation on (0,1) withlength 4 except for (0,0,0,0) and (1,1,1,1), were prepared. For each probe
set in the significantly differentially expressed genes set, Pearson’s
correlation coefficients between its mean expression values in the four
streak regions (A, B, C, D) and every binary pattern were calculated, andthe most correlated pattern was chosen as its expression pattern. Probe setswith (A,B,C,D)  (1,0,0,0), (1,1,0,0) or (1,1,1,0) were grouped into theAgroup set, and those with (A,B,C,D)  (0,1,1,1), (0,0,1,1) or (0,0,0,1) weregrouped into the Dgroup set. A stringent version of Agroup and Dgroup sets wasmade by applying the same clustering algorithm to the stringent
significantly differentially expressed genes. Heatmaps of Agroup and Dgroup
genes representing expression changes from the overall mean expression
were drawn. For the stringent Agroup and Dgroup sets (ratio ≥1.5), we
counted unique genes to which each GO term was assigned by the same
method as described above. The stringent (ratio ≥1.5) Agroup and Dgroup sets
and the rest of the expressed genes were mapped on the chicken genome
and their chromosomal map was drawn with the Geneplotter package inthe Bioconductor 2.5.0 suite.
Pathway analyses

We used two pathway analysis tools: Ingenuity Pathways Analysis(Ingenuity Systems, www.ingenuity.com) and the Kyoto Encyclopedia of
Genes and Genomes (KEGG) pathway database (Kanehisa and Goto,
2000). Stringent sets of the significantly differentially expressed genes
were analyzed using Ingenuity Pathways Analysis. Molecules from thedataset that met the ratio cut-off of at least 1.5 and were associated witha canonical pathway in Ingenuity’s Knowledge Base were considered forthe analysis. This, and the KEGG pathway database, together withadditional published data from PubMed, were used for the pathway
diagrams in Fig. 4.
Known gene analysis

Examples of genes reported to be expressed differentially in the streak at
this stage of chicken development were manually retrieved from thestringent Agroup and Dgroup sets. A heatmap of these genes representing

DEVELOPMENT

signaling pathway, which is responsible for the initial breaking of
D/V symmetry before streak formation, and the FGF signaling
pathway, which is mainly implicated in an earlier step of
mesoderm induction, also contribute to mesoderm D/V patterning(Furthauer et al., 1997; Furthauer et al., 2004; Keren et al., 2008;
Lekven et al., 2001; Marom et al., 1999; Muraoka et al., 2006;
Yabe et al., 2003). Currently, it is unclear to what extent each ofthese, or any other, signaling pathway contributes to the generationof this D/V gradient. Nor is the exact molecular nature of thisgradient known. Given the labile nature of their fate, it is essential
to identify and understand the differences in global gene
expression profiles among the mesoderm precursor populations
that are destined to become distinct lineages and cell types later
on. The importance of addressing this in vivo is underscored by
the efforts currently being made in the field of stem cell biology
to direct in vitro differentiation of cultured stem/pluripotent cells
towards specific mesoderm lineages (Era et al., 2008; Murry and
Keller, 2008; Takeuchi and Bruneau, 2009; Vijayaragavan et al.,2009).
Here we have taken a transcriptomic approach to address thisquestion. Streak tissues were dissected from stage-matched HH4chick embryos and were further divided into four equal pieces
along its A/P length. Chicken genome arrays were used to obtain
global gene expression profiles of these four streak regions. We
show that ~40% of all chicken genes are expressed in the streak,
one seventh of which exhibit significant differences in expression
levels among the four streak regions. Gene ontology analyses
revealed that different streak regions have overall identicalprofiles among expressed genes and very similar ontological
profiles among differentially expressed genes. Genes involved insignaling and transcriptional regulation are highly represented
among differentially expressed categories. All major groups oftranscription factors and kinases are present in both dorsal-toventral (DrV) and ventral-to-dorsal (VrD) groups, with somesubfamilies exhibiting exclusive DrV or VrD expression. Most
core members of the BMP/TGF, Wnt and FGF pathways are
expressed with no regional difference, whereas both negative andpositive modulators of these pathways are present in both dorsal
and ventral mesoderm precursors. Finally, a large number ofnovel genes with region-specific expression patterns are
uncovered in this study, significantly increasing the scope ofmolecular players currently associated with mesoderm D/Vpatterning.

Development 137 (17)Transcriptome of the streak

RESEARCH ARTICLE 2865

expression changes from the overall mean expression value were thendrawn. We also produced a bar chart representing fold-changes between A
and D expression levels for these genes.
Comparison between streak (S) and neighboring (P) tissues

To identify significantly differentially expressed genes between P and S,
we performed statistical tests with eBayes (Smyth, 2004). Multiple
comparisons were then corrected with FDR, and an FDR of less than 0.1
was chosen as significant. A heatmap was drawn with the significantly
differentially expressed genes set. We also made stringent sets of thesignificantly differentially expressed genes by filtering out probe sets that
had ratios between mean expressions between P and S parts that were lessthan 1.5 and 2.0. For two-dimensional mapping of genes that weredifferently expressed in both A/B/C/D and P/S, these genes were identified
by choosing genes in stringent (ratio ≥1.5 or ≥2.0) differentially expressedgene sets of both A/B/C/D and P/S. To quantify degrees of expression
changes from A to D and from P to S for each commonly differentiallyexpressed gene, linear functions were fitted to data points as [(1, expressionin A), (2, in B), (3, in C), (4, in D)] and [(1, in P), (2, in S)], respectively,
and slopes of the fitted functions were calculated. Finally, two-dimensionalgraphs of the slopes in A/B/C/D and in P/S were drawn for common
stringent sets with a ratio of at least 1.5 or 2.0.
There are 38,535 probe sets in total on the Affymetrix chicken GeneChip.
Of these, 26,277 probe sets have 14,931 unique GeneIDs (unique genes)
and 12,258 probe sets have no GeneIDs. In clusterable significantly
differentially expressed genes (for A, B, C, D), there are 7277 probe sets
in total, with 5514 probe sets having 4362 unique GeneIDs and 1763
probe sets having no GeneID. In significantly differentially expressed
genes with a ratio of at least 1.5 (for A, B, C, D), there are 2250 probe
sets in total, with 1733 probe sets having 1324 unique GeneIDs and 513
probe sets having no GeneID. In Agroup genes with a ratio of at least 1.5,
there are 1173 probe sets, with 887 probe sets having 671 unique
GeneIDs and 286 probe sets having no GeneID. In Dgroup genes with aratio of at least 1.5, there are 1039 probe sets, with 827 probe sets having
633 unique GeneIDs and 212 probe sets having no GeneID. In
significantly differentially expressed genes (P/S), there are 4325 probe
sets in total, with 3015 probe sets having 2608 unique GeneIDs and 1310
probe sets having no GeneID. In significantly differentially expressed
genes with a ratio of at least 1.5 (P/S), there are 571 probe sets in total
with 452 probe sets having 357 unique GeneIDs and 119 probe sets have
no GeneID.

RESULTSStreak tissue preparation and chicken genome
array analysis
We performed a comparative transcriptomic analysis of HH4
tissues from different A/P levels of the streak (Fig. 1A,B),
reflecting the mesoderm D/V axis in early chick embryos.
Although mesoderm cells are generated from the streak
continuously from HH2 to at least HH9, HH4 was chosen because
at this stage the streak is fully elongated, with precursors of all
mesoderm lineages present and fate map analyses most fully
documented (see Introduction). Six hundred embryos, incubatedto the desired stage from freshly laid eggs, were collected. Of
these embryos, 263 had a well-formed streak and no head process
and were selected for dissection (Fig. 1C), corresponding to HH4–
and HH4, but not HH4+. For each embryo, a rectangular piece of
streak tissue, roughly equivalent to the brachyury-expressing
domain, but not including brachyury-positive epiblast cells lateral
to the streak (Fig. 1A,B), was cut out and further dissected into
four equal pieces termed A, B, C and D, with A representing mostanterior and therefore most dorsal, and D the most posterior andtherefore most ventral (Fig. 1B). This division was chosen fortechnical reasons only and does not correspond to boundaries ofFig. 1. Streak tissue sample preparation and sample quality
analysis. (A)HH4 chick embryos stained for brachyury (BRA) (whichmarks the general mesoderm precursor territory) chordin (CHD) (dorsal
mesoderm precursors) and WNT8 (ventral mesoderm precursors) gene
expression. (B)The four streak regions, A, B, C and D, of HH4 embryos
dissected for RNA preparation. (C)Parental strains, number of embryos
and amount of RNA obtained and used for the chicken genome array
analysis.

mesoderm lineages reported from streak lineage-tracing
experiments (see Materials and methods and Discussion for acomparison of these tissue pieces with known lineage territories).
Each of the four regions was represented by three independent
samples, with each sample containing 5-7 g total RNA derived
from 85-93 pooled pieces. Five micrograms of RNA from eachsample were used to screen the Affymetrix chicken genome array
without an amplification step (Fig. 1C). The overall array data
analysis indicated the high quality of all RNA samples (see Fig.
S1 in the supplementary material).
Global profile and gene ontology categorization
The Affymetrix chicken genome array contains 39,000 transcripts,
corresponding to ~22,000 unique genes. We first analyzed thepercentage of transcripts with detectable expression in each of thefour regions based on present/absent calls in the analysis (seeMaterials and methods). Only transcripts with a present call in all
three samples were considered to be expressed. Both totaltranscript-based and unique gene-based calculations indicated that
~40% of all genes in the entire chicken genome are expressed ineach region of the streak. Genes expressed in different regions
showed remarkably overlapping patterns, as more than 35% of all
genes are expressed in all four regions. We next asked whether thedifference in expressed transcripts (less than 4% in pair-wisecomparison between different regions) represents molecularfeatures unique to individual streak regions. To achieve this, wecategorized expressed genes using Bioconductor software based on
NCBI gene ontology (GO) term assignments curated for the
chicken genome. We analyzed all genes that can be assigned a GO
function and plotted GO terms containing more than 20 genes forany given term (see Fig. S2 in the supplementary material). In total,~200 GO terms for molecular functions (see Fig. S2A in the
supplementary material), 300 for biological processes (see Fig. S2B

DEVELOPMENTCounts for various probe sets

in the supplementary material) and 85 for cellular components (seeFig. S2C in the supplementary material) contained more than 20
expressed genes. A uniform distribution for all GO terms using all
three categorization criteria was observed for A, B, C and D
regions (see Figs S2 and S3 in the supplementary material),suggesting that no particular molecular, cellular or biological aspect
is unique for any one of the four streak regions.
Chromosomal location and cluster analysis ofexpressed transcripts
It has been well documented that D/V patterning in vertebrates ismarked by regional differences in gene expression and in signaling
and transcriptional regulation. We asked whether, among all
expressed genes, there is any regional distinction in elevatedtranscript levels. Statistical analysis was performed based on

Development 137 (17)expression values for each transcript in all samples (see Materials
and methods). In total, 6567 transcripts (40% of expressedtranscripts and 16% of all transcripts in the genome array) can begrouped with high statistical confidence into six out of 14 possible
clusters (Fig. 2A), representing ~3700 unique genes. These six
clusters represent either ArD (dorsalrventral) or DrA(ventralrdorsal) asymmetric expression, and constitute over 90%
of transcripts in all 14 possible clusters (Fig. 2A; see Fig. S4 in the
supplementary material). With an arbitrary cut-off ratio of 1.5(highest/lowest) (see Table S1 in the supplementary material for thefull list), 2212 transcripts (14% of expressed transcripts andrepresenting 1200 unique genes) can be grouped into these six
clusters (Fig. 2B). Among them are many genes, the expression
patterns of which have been described at this stage of vertebrate
development (see Fig. S5 in the supplementary material). The top

Fig. 2. Clustering of expressed and differentially expressed genes and GO analysis of differentially expressed genes. (A)Expressed
genes are clustered into one of 14 possible clusters, with six major clusters shown here. Details of the clustering algorithm are given in the Materials
and methods. 1, higher expression levels; 0, lower/absent expression levels. Purple to green in the heatmap indicates high to low expression levels.
(B)Genes in these six clusters with at least a 1.5-fold difference between the highest and lowest expression levels. Agroup (genes with higher levels
dorsally) contains three clusters (1,0,0,0, 1,1,0,0 and 1,1,1,0), and Dgroup (genes with higher levels ventrally) contains three clusters (0,1,1,1, 0,0,1,1
and 0,0,0,1). (C)GO analysis of genes shown in B, comparing Agroup and Dgroup genes. The overall distributions are similar, with some GO terms
showing a difference. (D)Examples of GO terms with over 50 genes. The x-axis indicates the percentage of the total number of differentiallyexpressed genes for a particular GO term that is present in either Agroup (blue) or Dgroup (red). All three main GO categories (asterisks) have equal
numbers in Agroup and Dgroup, as is the case for many specific GO terms (e.g. ATP binding). Prominently, three GO terms have a higher
representation of Agroup genes (receptor activity, cell adhesion and plasma membrane) and three other terms have a higher representation of Dgroup
genes (transcriptional regulator, nucleic acid binding and transcription).

DEVELOPMENT

2866 RESEARCH ARTICLERESEARCH ARTICLE 2867

Transcriptome of the streak

20 genes in each cluster are listed in Table 1. The remaining eightclusters (see Fig. S4 in the supplementary material) contain 36
genes that exhibit differential expression with a 1.5-fold cut-off

ratio (see Table S2 in the supplementary material), including
LEFTY2 (0110 cluster pattern; 4-fold difference). These clusters
will not be discussed further.

Table 1. Top 20 differentially expressed genes in each of the six clusters
Cluster pattern

Ratio

Gene

Cluster pattern

Ratio

Gene

Cluster pattern

Ratio(1,0,0,0)(1,0,0,0)

5.79
4.01

(1,0,0,0)(1,0,0,0)(1,0,0,0)(1,0,0,0)(1,0,0,0)(1,0,0,0)(1,0,0,0)

Gene

FZD8
FOXD3

(1,1,0,0)(1,1,0,0)

5.53
5.03

(1,1,1,0)(1,1,1,0)

3.86
3.80

3.45
3.19
2.96
2.84
2.80
2.59
2.58

ARHGAP15
HHEX
LBH
CRHR1
SST
FOXA2
GRM7

(1,1,0,0)(1,1,0,0)(1,1,0,0)(1,1,0,0)(1,1,0,0)(1,1,0,0)(1,1,0,0)

5.01
4.94
4.21
4.09
4.00
3.52
3.50

ADMP
Unknown(LOC421390)
OTX2
GSC
CHRD
FZD8
ZIC2
RUNX1T1
Unknown(1,1,1,0)(1,1,1,0)(1,1,1,0)(1,1,1,0)(1,1,1,0)(1,1,1,0)(1,1,1,0)

3.08
3.06
2.83
2.76
2.59
2.40
2.25

(1,0,0,0)(1,0,0,0)

2.58
2.56

CA2
SOX2

(1,1,0,0)(1,1,0,0)

3.49
3.49

SFRP1
LHX1

(1,1,1,0)(1,1,1,0)

2.02
1.98

(1,0,0,0)(1,0,0,0)

2.52
2.50

(1,1,0,0)(1,1,0,0)

3.45
3.42

1.93
1.91

2.42
2.29

(1,1,0,0)(1,1,0,0)

3.34
3.17

TMEFF2
Unknown(LOC424623)
GNOT1
CNOT2

(1,1,1,0)(1,1,1,0)(1,0,0,0)(1,0,0,0)

B3GAT2
Unknown(LOC425015)
HDAC9
HFE2

(1,1,1,0)(1,1,1,0)

1.85
1.82

(1,0,0,0)(1,0,0,0)

2.25
2.13

(1,1,0,0)(1,1,0,0)

3.16
3.15

1.77
1.73

2.02

(1,1,0,0)

3.11(1,0,0,0)(1,0,0,0)

1.99
1.98

DMRT3
TNFSF15(1,1,0,0)(1,1,0,0)

3.04
2.94

PCSK5
Unknown(ChEST397p8)
Unknown(ChEST286i13)
THPO
RASD1

(1,1,1,0)(1,1,1,0)(1,0,0,0)

STMN2
Unknown(LOC768462)
ISM1

LRIG3
Unknown(ChEST401i9)
Unknown
CNTN4(1,1,1,0)(1,1,1,0)(1,1,1,0)

1.71
1.60
1.60

NFASC
KIF1A
PHACTR3(0,0,0,1)(0,0,0,1)(0,0,0,1)

3.14
3.07
2.90

MSX2
HOXA9
FLI1

(0,0,1,1)(0,0,1,1)(0,0,1,1)

5.52
4.86
4.06

HOXA2
SZL
KDR

(0,1,1,1)(0,1,1,1)(0,1,1,1)

4.73
3.65
3.41

(0,0,0,1)(0,0,0,1)(0,0,0,1)

2.77
2.61
2.58

(0,0,1,1)(0,0,1,1)(0,0,1,1)

3.71
3.36
3.00

SOCS2
HOXA3
HOXB3

(0,1,1,1)(0,1,1,1)(0,1,1,1)

3.17
3.03
2.95

(0,0,0,1)(0,0,0,1)(0,0,0,1)

2.58
2.51
2.48

(0,0,1,1)(0,0,1,1)(0,0,1,1)

2.96
2.95
2.91

APCDD1
NOXO1
BMP7(0,1,1,1)(0,1,1,1)(0,1,1,1)

2.92
2.73
2.69

MESP2
WNT8A
HAPLN1(0,0,0,1)

2.41

BETA3
FET1
Unknown(ChEST457l4)
ALDH1A2
CORO2A
Unknown(ChEST264i23)
RBP4

CDX4
CDX2
Unknown(CK614519)
HOXB1
WNT5A
MYC

(0,0,1,1)

2.80(0,1,1,1)

2.61

CXCL14(0,0,0,1)(0,0,0,1)

2.38
2.37

GPD1
KITLG

(0,0,1,1)(0,0,1,1)

2.79
2.78

(0,1,1,1)(0,1,1,1)

2.56
2.42

(0,0,0,1)(0,0,0,1)

2.34
2.26

ALDH1A1
VEGFA(0,0,1,1)(0,0,1,1)

2.71
2.61

(0,1,1,1)(0,1,1,1)

2.34
2.24

KLF1
Unknown(ChEST847k15)
PIWIL1
WNT3A(0,0,0,1)

2.22(0,0,1,1)

2.30(0,1,1,1)

2.17

FZD10

(0,0,0,1)(0,0,0,1)(0,0,0,1)

2.12
2.12
2.10

Unknown(LOC771069)
SLC12A3UGT1A1
BPIL2

Unknown(LOC524813)
MT3
Unknown(LOC425711)
KLF15
Unknown(LOC421682)
ADA(0,0,1,1)(0,0,1,1)(0,0,1,1)

2.30
2.30
2.17

(0,1,1,1)(0,1,1,1)(0,1,1,1)

2.15
2.14
2.09

MSX1
SPAM1
COL13A1(0,0,0,1)

2.09

HAND2

(0,0,1,1)

2.16(0,1,1,1)

2.07

ADAMTS3(0,0,0,1)

2.07

RGN

(0,0,1,1)

2.13

PLXNA2
IRF2
Unknown(ChEST594o6)
Unknown(ChEST539d8)
EVX1(0,1,1,1)

2.00

DLX5

Agroup genes

EDNRB
Unknown(BU272039)
FGF8
EOMES
CER1
FGF18
TLR2
RASGEF1B
Unknown(ChEST845i18)
PODXL
Unknown(ChEST228d14)
USP44
BTBD6

Top 20 genes in each of the six clusters. Three of the Agroup (1,0,0,0, 1,1,0,0 and 1,1,1,0) and three of the Dgroup (0,0,0,1, 0,0,1,1 and 0,1,1,1) are listed, indicating theircluster pattern, fold difference (ratio in log2 scale) and gene symbols. Details of each gene can be found in Table S1 in the supplementary material. Prominent among them
are many well-described genes, including FZD8 and ADMP in Agroup and MSX2 in Dgroup. The list also includes many unknown genes or genes previously not associated withmesoderm D/V patterning.

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Dgroup genes

Developmental progression and tissue fate specification often
involve coordinated transcriptional regulation. In mice, it has beenreported that clustered transcriptional hotspots in the genome
accompany the onset of organogenesis (Mitiku and Baker, 2007).
We asked whether a similar phenomenon occurs in streak tissues
fated for different mesoderm lineages. All 6600 transcripts that can
be clustered by our statistical analysis were plotted onto thechicken chromosomes. Transcripts exhibiting a greater than 1.5fold difference are shown in red (ventral high) or blue (dorsalhigh), whereas those with a less than 1.5-fold difference are shownin gray (see Fig. S6 in the supplementary material). Overall, thesegenes are scattered throughout the genome and no hotspot foreither expressed or differentially expressed genes was detected.
These data indicated that, on the one hand, the majority of
expressed genes (60% by statistical clustering and 85% by anarbitrary 1.5-fold cut-off) show no regional difference, whereas, on
the other hand, a large number of genes did show a statisticallysignificant difference in their expression levels. We therefore
performed further analysis on genes exhibiting greater than 1.5-fold
ArD (1000, 1100 and 1110 clusters) or DrA (0001, 0011 and
0111 clusters) asymmetric expression. We asked whether genes inthese six clusters represent specific GO categories that highlightdifferential biological activities involved in D/V patterning. These
genes were grouped as either Agroup (for ArD clusters andrepresenting the dorsal-high group) or Dgroup (for DrA clusters andrepresenting the ventral-high group) genes (Fig. 2B), and a GO
analysis similar to that described above was performed. Among
2212 transcripts, ~40% can be assigned with a GO term in all three
categories. The majority of GO terms still exhibit little or nodifference between Agroup and Dgroup genes (Fig. 2C), and an
approximately equal number of differentially expressed genes are
represented in both the Agroup and Dgroup. Although the number ofgenes assignable to a particular GO term does not necessarily
indicate its importance or bias of usage in regulation, this result didsuggest that even among differentially expressed genes, noparticular aspect of molecular, cellular or biological activities is
unique to, or represented in, dorsal or ventral streak tissue.
Genes involved in transcriptional and signaling
regulation
Patterning events during development are often regulated bygraded signaling and transcriptional activities. We investigatedthese two aspects in more detail. Interestingly, two classes of GO
terms, one representing transcriptional regulation and the otherreceptor-mediated signaling regulation, exhibited their strongest
uneven distribution between Agroup and Dgroup genes. With all three
GO categorization methods, we observed that the Dgroup has ahigher number of differentially expressed genes involved intranscriptional regulation, whereas the Agroup has moredifferentially expressed genes involved in signal transduction (Fig.
2D). To further investigate these differences, we manually curated
all Agroup and Dgroup genes. Among them, a total of 114
transcription factors with definable DNA-binding domains basedon the transcription factor classification program TRANSFAC(BIOBASE, Germany) were found (Fig. 3). Forty-six of thembelong to the Agroup and 68 to the Dgroup (Fig. 3, blue and red,respectively). All four major superclasses (basic domain, zinccoordinating DNA-binding domain, helix-turn-helix and betascaffold) and several unclassifiable transcription factors are
represented. About half of them belong to the helix-turn-helix
superclass, of which four classes (homeodomain, Forkhead/Winged
helix, tryptophan clusters and paired box) are represented, theDevelopment 137 (17)homeodomain class being the largest with 39 genes. A bias wasseen at the subfamily level, with all genes in the Labial, Antp, AbdB, Caudal, Msh and Dll subfamilies of the homeodomain classbelonging to the Dgroup, as were genes of the Cys4 zinc-finger class,nuclear receptor class, Teashirt subfamily and Grainyhead class.
All genes in the Emx homeodomain subfamily, Sox family and all
non-homeodomain-only homeodomain-containing genes belong to
the Agroup. Several large groups (Krüppel subfamily, Prd subfamilyof homeodomain, Forkhead/Winged helix class, Ets family, Tcf
family and Hairy family) have genes in both the Agroup and Dgroup.
In addition to transcriptional regulation, genes involved in signaltransduction represent the other major category revealed by the GO
analysis. We carried out a systematic analysis for all known
signaling pathways using Ingenuity Pathways Analysis software(see Materials and methods). Among 2212 transcripts with a 1.5fold cut-off, 88 pathways are represented with at least four
component genes, the top three signaling pathways being the Wnt,
TGF/BMP and FGF pathways (see Table S3 in the supplementarymaterial). This is in good agreement with these three pathways
being documented as the major players in early D/V patterning (seeIntroduction). Examples of other pathways revealed by our analysis
are (numbers refer to Agroup + Dgroup throughout): keratan sulfate
biosynthesis (5+5; five upregulated in each), reflecting extensive
sugar chain modification; axonal guidance signaling (30+19),
possibly reflecting early neuronal specification of ectoderm cells
mixed with mesoderm-fated cells; ephrin receptor signaling (16+7),
reflecting differential regulation in the migratory behavior ofnascent mesoderm cells; G protein-coupled receptor signaling(15+6); cAMP-mediated signaling (9+6); calcium signaling (8+10);
and integrin signaling (11+5) (for a complete list of pathways andtheir component genes, see Table S3 in the supplementarymaterial). Interestingly, retinoic acid signaling pathway members
were confined to the Dgroup. The actual number of genes involvedin these respective pathways is likely to be higher than thatrecorded here, as our manual curation for three major pathways
indicated that some genes were missed owing to minor differencesin the nomenclature of orthologous genes and to a possibly
incomplete dataset in the Ingenuity Pathways database.
Components of three major pathways: Wnt,
TGF/BMP and FGF
The three best-represented pathways in our analysis, i.e. the Wnt,
TGF/BMP and FGF pathways, are known to be involved inmesoderm induction and its D/V patterning. We asked whether our
global analysis could reveal new features of these signaling
pathways in these events. Our pathway analysis identified 28
differentially expressed genes related to the Wnt pathway (16+12),
13 for the TGF/BMP pathway (4+9) and 12 for the FGF pathway(8+4). In addition to these genes, we manually analyzed theexpressed profiles of all genes shown to be involved in these threepathways by including genes that are expressed but that show a lessthan 1.5-fold difference. These genes are in gray in Fig. 4 as thosewith no significant change, whereas differentially expressed genes(at least 1.5-fold) are marked in blue (Agroup) or red (Dgroup). In
addition to confirming pathway genes that have been shown
previously in experimental settings, we observed three prominent
features in our analysis. First, for all three pathways, most of thecore components are expressed without a D/V asymmetry (gray).
This includes LRP5, DVL1, CTNNB1, GSK3B, AXIN1, PPP2CA
and APC1 for the Wnt pathway; BMPR1A/B, BMPR2, TGFBR1,TGFBR2, ACVR1, ACVR2A/B, INHBA, INHBB, and SMAD1-3 forthe TGF/pathway; and FRS2, GRB2, SOS1, RAS, RAF1, MEK

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2868 RESEARCH ARTICLE

Transcriptome of the streak

RESEARCH ARTICLE 2869

and ERK2 for the FGF pathway. Second, regulatory genes aredifferentially expressed and regulation takes place at multiple levels
for each pathway, including extracellular, receptor, cytoplasmic andnuclear. Third, both positive and negative regulators are present inboth Agroup and Dgroup genes. For the Wnt pathway, Wnt genes(WNT2, WNT3, WNT5A, WNT5B and WNT8A) are present with a
VrD gradient. FZD5/7/8 and FRZB are dorsally upregulated,
whereas FZD10 is ventrally upregulated. Both positive andnegative regulators for the canonical Wnt pathway have both
dorsally (CER1, DKK1, SFRP1, RSPO1/3, SHISA, MARK3,
DACT2, TCF3, TCF4, GBX2, HHEX, SOX3/7/17/18 and TLE4)
and ventrally (NDP, GIPC2, SRC, TCF7, LEF1, NOTUM, GPC3,
SDC3, NKD1, DACT1 and RARA/B) upregulated inputs. For theWnt planar cell polarity (PCP) pathway, however, most regulators,
both positive (DKK1, ROR1, GPC4, SDC2, MAPK8IP1, DAAM1
and DACT2) and negative (SFRP1, PRICKLE2, SHISA and
MARK3), are present only in the Agroup. For the TGF superfamily
pathway, major regulation is observed in the BMP branch of thepathway. All BMPs (BMP2/4/7) are ventrally upregulated, whereas
negative regulators for BMP/BMPR binding are present both
dorsally (ADMP, CER1 and CHRD) and ventrally (SIZZLED,
SDC3, GPC3 and BAMBI). SMAD6/7/9 show ventral upregulationand SMAD5 shows dorsal upregulation. For the FGF pathway, adorsal upregulation is seen for FGF1/8/13/18, FGFR1/2, GPC4,SHISA, SEF, SPRY1, RASGEF1A/B, DUSP6/14 and ETV4,
whereas a ventral upregulation is seen for FGF4/19, SULF1,

DEVELOPMENT

Fig. 3. Categorization of alltranscription factors
differentially expressed in
the streak. Differentiallyexpressed genes that encodea transcription factor with adefinable DNA-biding domain
are grouped based on their
DNA-binding domain
categories, with a total of 114
transcription factors and with46 belonging to the Agroup(blue bars) and 68 belonging
to the Dgroup (red bars). x-axis
indicates the fold difference.
All transcription factor classes
are represented here, withsome families being exclusive
in either Agroup or Dgroup.

2870 RESEARCH ARTICLE

Development 137 (17)

FGFR3, SDC3, PGC3, RASGEF1C, RASGRP1/3, CDX4 and
MYC. Overall, in addition to revealing novel members of thesepathways that are potentially involved in mesoderm D/Vpatterning, our data point to a complex network of positive andnegative regulation for both dorsal and ventral tissues, which
possibly ensures the robustness of the D/V signaling gradient.
Verification by in situ hybridization
Expression data from genome array analysis represent reliablereadouts and are less biased than traditional in situ-based analyses.
Nevertheless, as an alternative verification of our data quality, we
randomly selected genes from our array analysis representing eachof the six clusters for in situ verification. Probes were preparedbased on sequences in the genome array dataset for genes showing
ArD (24 genes) or DrA (18 genes) asymmetric expression (seeMaterials and methods for details). Only genes that have not beenreported in the chick system were selected, representing those ofboth known and unknown molecular function (see Table S4 in the

supplementary material). Overall, a near-perfect correlation wasseen between the in situ expression pattern of a gene and the cluster
category to which it belongs (Fig. 5). Among these are many genesof unknown function that are conserved among vertebrate species
and with strong and specific expression, as are many genes ofknown function unrelated to D/V patterning, including LBH,
CRHR, STK10, PCSK6, EPHB3, ST8SIA2, PODXL, SEMA4G,
EGFL7, FIBIN, PLXNA2, NOXO1, CXCL14 and SULF1. In bothgroups, most of the genes tested showed restricted expression in
the streak and a small percentage had expression domains that
extend into the neural plate territory (for the Agroup) or the nonneural ectoderm territory (for the Dgroup).
DISCUSSION
In this work, we describe a transcriptomic profiling of positional
differences of streak mesoderm precursors in chick embryos, thefirst such report in any vertebrate species. The quality of such ananalysis depends on the amount of developmental stage- and

DEVELOPMENT

Fig. 4. Regulators of the Wnt, TGF/BMP
and FGF pathways among differentiallyexpressed genes. (A-C) The Wnt (A), TGF (B)and FGF (C) pathways are shown. Gray
indicates expressed genes with less than a 1.5fold difference. Blue indicates Agroup genes(dorsal high) and red indicates Dgroup genes(ventral high). Most of the core members ofthese pathways are expressed uniformly.
Negative and positive regulators of eachpathway are present among both Agroup andDgroup genes, representing multiple points ofregulation (extracellular, membrane, intracellularand nuclear). SMAD4 is colored white as it isexpected to be present, but no Affymetrix
probe set can be clearly associated with thisgene. Double line, cell membrane. Dotted line,
nuclear membrane.

Transcriptome of the streak

RESEARCH ARTICLE 2871

region-matched tissue samples that can be collected, and we wereable to achieve this using chick embryos. Our analyses showed thatthe global transcriptomic makeup is highly uniform throughout thestreak. This is likely to be the underlying mechanism for the lability
in fate specification of streak mesoderm precursors.
Despite this overall uniformity, prominent regional differencesin gene expression were observed in our analysis. These differences
offer a ‘bird’s eye view’ of the molecular preparation involved ininitial mesoderm D/V patterning in all vertebrates. Although thestreak is an embryological structure unique to amniotes, molecularmechanisms regulating mesoderm formation and D/V patterning
are considered to be conserved in vertebrates. In birds andmammals, the majority of mesoderm cells emerge from theectoderm by ingressing through the streak, which is positioned
parallel to the future A/P axis of the embryo. D/V patterning of
mesoderm precursors, which in fish and amphibians takes place
perpendicular to the embryonic A/P axis, thus occurs in birds andmammals along the A/P axis of the streak. The developmental
cause for this evolutionary shift in mesoderm internalization inamniotes is unclear. Despite these differences, several key eventsin early vertebrate development are found to be regulated byconserved molecular mechanisms, including roles of the Wnt/catenin pathway in initial embryonic D/V symmetry breaking, of
the FGF and TGF pathways in mesoderm precursor fateinduction, and of the BMP pathway in ectoderm and mesoderm
D/V patterning, the last of which is the focus of this work. The
BMP pathway does not act alone in mesoderm D/V patterning, andit has been suggested that Wnt, FGF and TGF pathways act
together with the BMP pathway in this process (see Introduction).
Our data support these experimental observations. Moreover, wefound that although core members exhibit little difference at thetranscript level, regulatory molecules of each of these three major
pathways clearly show positional differences, with both DrV and
VrD gradients. This suggests that the activities of these pathways
along the streak length are regulated subtly and dynamically,
possibly to ensure a robust gradient that is resistant to perturbation.
The existence of such a dynamic regulation is further supported by
the fact that members of seven out of eight major kinase groups(TK, TKL, CAMK, AGC, STE, CMGC and atypical) known to be
involved in the signaling of these three and other pathways,

DEVELOPMENT

Fig. 5. In situ validation of Agroup
and Dgroup genes. (A-C)RNA in
situ hybridization analyses of 24
genes in the Agroup (A) and 18 in the
Dgroup (B), randomly selected andwith expression patterns notpreviously described for streak
development. Each of the three
Agroup clusters (1,0,0,0; 1,1,0,0 and
1,1,1,0) is represented by eightgenes, and each of the three Dgroupclusters (0,0,0,1; 0,0,1,1 and
0,1,1,1) is represented by six genes.
Gene symbols, when known, areshown in C. Details ofcorresponding gene or expressedsequence tag names and regions
used for generating probes aredescribed in Table S4 in the
supplementary material.

exhibited graded expression in the streak (see Fig. S7 and Table S5in the supplementary material). The exact nature of such a gradientis unclear. One possible scenario is that a signaling ‘tug-of-war’
converges via pathway cross-talk on intracellular BMP signaling
activity (for instance, on the nuclear translocation and activity of
SMAD1/5/9). Alternatively, the gradient could be a combinatorialsignaling status in each of these pathways, conferring unique, yetstill labile, identities to cells at different positions of the streak.
Transcription factors are integral components of receptormediated signaling, often as a readout of receptor signaling or as aconvergence point of multiple signaling pathways. Although targetsof transcriptional regulation may engage in feedback modulationof signaling pathways, it is generally considered that achieving aunique combinatorial code of transcription factors is an essential
early step in cell-lineage/fate specification. It is therefore notsurprising that a large number of transcription factors exhibit
graded levels of expression along the streak. The 114 transcription
factors we found are likely to be an underestimate, as many otherswith uniform transcript levels might exhibit protein or activity
gradients that cannot be discerned in our current analysis. With theobvious limitation of the genome array coverage, our analysis
presents a near complete list of differentially expressedtranscription factors in the streak, making it possible to carry out
computational modeling of transcriptional regulatory networks inthe future for this well-conserved and well-defined developmental
event. It also offers a valuable resource for using combinatorialtranscription factor codes to direct and analyze embryonicstem/induced pluripotent stem (ES/iPS) cell differentiation towardspecific mesoderm lineages in vitro.
As mentioned in the Introduction, the dissection of the streak
into four equal regions was intended for quality and quantity
controls of our analysis, and did not correlate with the known fate
map of the streak. The most anterior A piece can be roughly termed
the organizer region, although chordin, an organizer marker, isexpressed in a narrower domain in chick embryos at this stage (Fig.
1A). According to fate map analyses, this piece will give rise toboth axial and paraxial mesoderm tissues (Selleck and Stern, 1991)
and therefore contains both what is conventionally viewed as thedorsal signaling center (axial mesoderm precursors) and what is
considered as part of the non-axial mesoderm precursors (paraxial).
It has been suggested that the non-axial mesoderm precursors do
not contain much positional information. Our analysis, however,clearly indicates that there is fine-graded positional information
along the entire length of the streak from both directions, separating
the streak not only into axial and non-axial lineages, but also into
multiple subregions of non-axial mesoderm. The complexity ofthese molecular gradients indicates that there could be more than
five mesoderm lineages as traditionally defined. Someexperimental evidence supports such a possibility. For instance,
medial and lateral parts of the paraxial mesoderm have distinct
origins from the streak (Iimura et al., 2007; Psychoyos and Stern,
1996a; Selleck and Stern, 1991), and the extraembryonicmesoderm contains hemogenic and non-hemogenic subregions(Nakazawa et al., 2006).
Genes exhibiting graded levels of expression along the streak
may be involved in developmental regulation other than mesoderm
D/V patterning. The ectoderm at HH4 is being patterned into neuraland non-neural territories and it has been well documented that
dorsal mesoderm precursors contain neural differentiation-inducing
signals (Stern, 2005). The A region in our study also contains
definitive endoderm and neural precursors (Chapman et al., 2007;
Kimura et al., 2006; Lawson and Pedersen, 1987; Matsushita et al.,Development 137 (17)2008; Robb and Tam, 2004; Selleck and Stern, 1991). Genes witha DrV or VrD gradient may not be restricted to the streak and insome cases this might reflect more the graded expression inneighboring ectoderm cells, as revealed by in situ analysis (Fig. 5).
These aspects, although not the focus of this analysis, arenevertheless reflected in our transcriptomic datasets. For instance,some of the genes exhibiting the (1,0,0,0) type expression profile
can be associated with endoderm (SOX17) or neural (SOX3)
differentiation. These biases can in principle be eliminated by
combining our current datasets with data from additionaltranscriptomic profiling of definitive endoderm or neural ectoderm.
Preliminary results from one such experiment, by comparing streaktissue with its immediate lateral tissue, suggest that this can indeed
be achieved (see Fig. S8 in the supplementary material; ourunpublished data).
Aside from the issue of mixed germ layer lineages in the streak,streak mesoderm precursors are under an additional level ofmolecular regulation to control the timing of precursor cell
ingression, which is manifested later on in development in the A/P
positional difference of individual mesoderm lineages. A large
number of Hox genes are expressed with a VrD profile. We thinkthat this is likely to emphasize a role of Hox genes in mesoderm
D/V patterning, as suggested, for instance, from studies of Hox
gene control of early differentiation of hematopoietic cells (asderived from the ventral-most mesoderm in the streak) (Davidson
et al., 2003; Davidson and Zon, 2006; Yue et al., 2009). However,it might also reflect a tight control of ingression timing among
ventral mesoderm precursors by some of the Hox genes (Iimura
and Pourquie, 2006). Taken together, it is very likely that inaddition to their key roles in controlling mesoderm D/V patterning,
the observed signaling and transcriptional regulatory gradients arealso involved in other important developmental events occurring
within and surrounding the streak.
Our analyses further revealed many novel genes with strong anddifferential levels of expression in the streak. They include genesof unknown molecular function, and those for which a function has
been described in other systems. These genes might represent novel
regulatory steps of signaling pathways known to be active in thestreak or of novel pathways. For instance, our transcriptomic (seeTable S1 in the supplementary material) and in situ (Fig. 5; data notshown) analyses revealed that a group of at least 24
glycosyltransferases (see Table S6 in the supplementary material)
exhibits either a DrV (15) or VrD (9) profile. Sugar epitope
modification of receptor and extracellular molecules has beenreported to modulate signaling activities in many other systems(Haecker et al., 2008; Machingo et al., 2006; Tonoyama et al.,2009). Given that several major signaling pathways are key
components in the regulation of positional identities in the streak,it is not surprising that we found these 24 enzymes exhibiting
differential levels of expression in the streak, representing both
early and late steps of O-linked and N-linked glycosyl
modification. Other examples include large numbers of solute
carrier family proteins (5 DrV and 15 VrD) and ion channel
proteins (10 DrV and 3 VrD), and at least ten different cadherins(6 DrV and 4 VrD) that show graded expression along the streak(see Table S6 in the supplementary material). Solute carrier family
proteins have so far not been associated with mesoderm D/Vpatterning, and some potassium channels, albeit different fromthose found in our analysis, have been reported to be involved inearly left-right patterning (Levin et al., 2002). It should also be
noted that the list of A region-specific genes (cluster pattern
1,0,0,0) not only covers all known organizer-specific genes, but

DEVELOPMENT

2872 RESEARCH ARTICLE

represents to our knowledge the most comprehensive and complete
list of organizer genes, including many of unknown function (Fig.
5). Functional studies of these genes might provide novel insight
into the molecular regulation of mesoderm D/V patterning.
In summary, we report in this work the first transcriptomic
analysis of regional differences among vertebrate mesoderm
precursors. Experimental observations of fate lability can be
explained by the global ontological uniformity in expressed genes
among mesoderm precursors fated for different mesoderm lineages,
whereas multi-pronged signaling and transcriptional gradientssuggest complex molecular mechanisms for generating andmaintaining a robust mesoderm precursor identity gradient. Finally,
our datasets provide a valuable resource for in vitro mesoderm
lineage differentiation from ES/iPS cells in translational research
fields.
Acknowledgements
We thank Hiroki Nagai, Fumie Nakazawa and Fujio Toki for help with initial
tissue isolation; Rikuhiro Yamada for help with data analysis; members of the
Functional Genomics Unit for help with GeneChip runs; members of the
Genome Resource and Analysis Unit for help with sequencing; and Yoshiki
Sasai, Shinichi Nishikawa, Masahiko Hibi, Brendan McIntyre, Patrick Tam andClaudio Stern for critical comments. This work was funded by RIKEN.
Competing interests statement
The authors declare no competing financial interests.
Supplementary material
Supplementary material for this article is available at
http://dev.biologists.org/lookup/suppl/doi:10.1242/dev.053462/-/DC1
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