A Meta-Analysis of Human Embryonic Stem Cells Transcriptome Integrated into a We - 《stemcells》干细胞学杂志干细胞之家



免疫细胞治疗专区	欢迎关注干细胞微信公众号

12 3 4 5 6 7 8 9 10 ... 25 下一页

返回列表

查看: 435639\|回复: 241	go A Meta-Analysis of Human Embryonic Stem Cells Transcriptome Integrated into a We [复制链接]

江边孤钓

版主

Rank: 7 Rank: 7 Rank: 7

积分: 0
威望: 0
包包: 483

楼主

发表于 2009-3-5 00:56 |只看该作者 |倒序浏览 |打印

作者：Said Assoua,b,c,d, Tanguy Le Carroura, Sylvie Tondeura,b,c, Susanne Strme, Audrey Gabellea,b, Sophie Martya,b,c, Laure Nadala, Vronique Pantescob, Thierry Rmea,b, Jean-Philippe Hugnotf,g, Stphan Gascaa,b,h, Outi Hovattae, Samir Hamamaha,b,c,h, Bernard Kleina,b,c, John De Vosa,b,c作者单位：aCentre Hospitalier Universitaire de Montpellier, Institute for Research in Biotherapy, Hpital Saint-Eloi, Montpellier, France;bInstitut National de la Sant et de la Recherche Mdicale, U, Montpellier, France;cUniversit Montpellier, Unit de Formation et de Recherche de mdecine, Montpellier, France;
   ( a" x8 P" Q' i$ A, ^7 i3 |0 L
   4 \- M3 I+ O7 Y  U1 k. m

                     ' F# R+ R& n6 }& p
         0 V# K3 i* D& T; q

         3 ^7 {0 F: O1 x7 c% h5 p' S$ G9 S
         8 C) Y0 }5 H5 S/ e4 Q
                  ! ^7 o& O* ?* k) z& t3 H


      ! e2 _+ P4 ^6 u1 @+ P
      【摘要】; l, p0 ^* P5 `0 x( a1 F+ W6 F6 e& U
   Microarray technology provides a unique opportunity to examine gene expression patterns in human embryonic stem cells (hESCs). We performed a meta-analysis of 38 original studies reporting on the transcriptome of hESCs. We determined that 1,076 genes were found to be overexpressed in hESCs by at least three studies when compared to differentiated cell types, thus composing a "consensus hESC gene list." Only one gene was reported by all studies: the homeodomain transcription factor POU5F1/OCT3/4. The list comprised other genes critical for pluripotency such as the transcription factors NANOG and SOX2, and the growth factors TDGF1/CRIPTO and Galanin. We show that CD24 and SEMA6A, two cell surface protein-coding genes from the top of the consensus hESC gene list, display a strong and specific membrane protein expression on hESCs. Moreover, CD24 labeling permits the purification by flow cytometry of hESCs cocultured on human fibroblasts. The consensus hESC gene list also included the FZD7 WNT receptor, the G protein-coupled receptor GPR19, and the HELLS helicase, which could play an important role in hESCs biology. Conversely, we identified 783 genes downregulated in hESCs and reported in at least three studies. This "consensus differentiation gene list" included the IL6ST/GP130 LIF receptor. We created an online hESC expression atlas, http://amazonia.montp.inserm.fr, to provide an easy access to this public transcriptome dataset. Expression histograms comparing hESCs to a broad collection of fetal and adult tissues can be retrieved with this web tool for more than 15,000 genes.
; D9 S1 o" R/ g: G
Disclosure of potential conflicts of interest is found at the end of this article. 4 u& A% M& ^. F# p' O
      【关键词】 Pluripotent stem cells Gene expression profiling Microarray analysis) ]- v) P5 S. t
   INTRODUCTION, C# Z; Y( v: \$ H
: J  U/ b( p, d( K. g
In the preimplantation mammalian embryo, the inner cell mass is able to differentiate into any cell type of the embryo proper. It has been recognized in mice since 1981 that embryonic stem cells (ESCs) with a prolonged proliferative capacity in vitro can be derived from the inner cell mass . Moreover, extensive knowledge on hESCs should help in designing protocols for the isolation and production of other multi-/pluripotent stem cells derived from tissues of adult individuals.
. F% T" C" N: |2 ?/ N: n
Microarrays are a major technical breakthrough that can monitor the expression of a whole genome in one experiment. Application of this technology to hESCs has largely contributed to our knowledge on the mechanisms underlying the maintenance of pluripotency of hESCs and their in vitro differentiation. Unfortunately, the datasets generated are heterogeneous both in accessibility (public databases or supplemental online data) and in the techniques used (variability in microarray design, sample labeling techniques, choice of control samples, and computational tools). Despite our findings of 38 original publications reporting hESC transcriptome analyses, the disparities between datasets, the variety of sources, the substantial know-how needed for transcriptome data mining discourage most nonspecialists from consulting this information. Thus, large amounts of data are very much underused, and there is a lack of alternative interpretations because only the conclusions reflecting the analysis carried out by the authors are presented. This situation has led to initiatives such as ONCOMINE in the field of cancer . We present here the first effort in compiling all publicly available microarray data relating to hESCs. From the 38 original publications studying the hESC transcriptome, we identified genes that were consistently overexpressed in hESCs when compared to differentiated samples ("consensus hESC gene list") and underexpressed in hESCs ("consensus differentiation gene list") in different studies. These lists will further deepen our knowledge on this unique cell model of developmental biology. Concurrently, we created an online database, Amazonia!, which provides an easy access to this public transcriptome dataset.

MATERIALS AND METHODS

Lists of Genes Differentially Expressed
2 O9 `0 D) [8 G1 M( z" x
Analyzing 38 original studies using transcriptome analysis to study hESC, we were able to collect 20 lists of transcripts that were upregulated in hESCs compared to differentiated cell types and 11 lists of transcripts that were downregulated (supplemental online Tables 1¨C3). We selected only transcripts lists that provided a fold ratio of the mean expression in hESCs to that in differentiated cells. Each list was mapped to UniGene build 176. When the mean value of expression in differentiated cells was 0, which occurred with expressed sequence tags (ESTs) and serial analysis of gene expression (SAGE), the hESC/differentiation ratio was arbitrarily set at 50. Only genes with a fold ratio greater or equal to 2 (hESC genes), or lower or equal to 0.5 (differentiation genes) were selected. The Gene Ontology (GO) annotation analysis was carried out using the Fatigo  tool on the Babelomics website (http://babelomics.bioinfo.cipf.es) using gene symbols . Only annotations with a false discovery rate-adjusted p value below .05 were considered significant.

Integrating Affymetrix GeneChip Datasets Obtained from Distinct Studies
) l0 C9 \1 O. j& y' W8 D* A! H& S
To compare the transcriptome of hESCs to that of differentiated cell populations, we built an expression compendium by combining the U133A (Affymetrix, Santa Clara, CA, http://www.affymetrix.com) microarray data from eight publications . The number of samples amounted to 217, including 24 hESC samples (11 different hESC lines). All samples were normalized before analysis with the GCOS 1.2 software (Affymetrix), using the global scaling method, with a target intensity (TGT) value set to 100. The detection call can be "present," when the perfect match probes are significantly more hybridized than the mismatch probes; "absent," when both perfect match and mismatch probes display a similar fluorescent signal; or "marginal," when the probe set complies with neither the present nor the absent call criteria. When several probe sets measured the same gene, only the probe set with the maximal number of present detection call across all samples was selected. This step reduced the list of probe sets to 14,074. This dataset is available as supplemental online Table 4 and can be accessed on our website, http://amazonia.montp.inserm.fr.

Table 1. hESCs: Laboratory of origin and karyotype
5 n' ^- c  Q7 ~
Table 2. Forty-three original studies or reviews analyzing the hESC transcriptome9 F+ |% \4 J; q- C+ |
' I4 D: s9 D, l$ e: N& [
Table 3. Forty-eight genes overexpressed in hESCs compared to differentiated cell types in at least 10 studies

Table 4. Forty genes specifically expressed in hESCs
- I5 i# N# J9 G
Hierarchical Clustering$ x, P. g* e# i. a7 |

Hierarchical clustering was carried out on the detection call data with the CLUSTER and TREEVIEW software packages . The value 1 was assigned to present calls, ¨C1 to absent calls, and 0 to marginal calls. This matrix was clustered without further mathematical transformation. Only genes were clustered (i.e., the order of the samples is the order used on the Amazonia! website and is based on grouping according to the embryonic germ layer origin of the sample).

hESC Lines and Karyotype" ]8 q/ R0 E; G- L' y8 c

The hESC lines used and their respective karyotypes are listed in Table 1.& `2 F; J6 `: z4 m% Z
2 P" B) J" z2 f1 `
hESC Culture; j# n( \! X$ i$ K3 c! z% ?

After approval from the French Ministry of Research, the French Ministry of Health, and the Agence de la Biom¨¦decine, HUES1 and HUES3 hESCs were imported from Douglas Melton's laboratory (Harvard University, Cambridge, MA) and cultured as described previously ) or endodermal lineage (-fetoprotein; supplemental online Figure 1 and data not shown).# j/ H8 h. g: E7 u- w4 D" U

Figure 1. Meta-analysis of published hESC and differentiation gene lists. One thousand nine hundred fifty-nine different genes were found to be overexpressed in hESCs compared to differentiated tissues by at least 2 of 20 independent studies (purple pyramid) (A). Of these, 1,076 genes were found by at least 3 studies, 48 genes by at least 10 studies, and only 1 gene (POU5F1) by all studies. Eleven studies provided lists of genes downregulated in hESCs compared to more differentiated samples (yellow pyramid) (B). One thousand five hundred sixty genes were found to be downregulated in hESC by at least 2 studies, 783 by at least 3 different studies, 3 by at least 9 different studies, and none by all studies. (C): Heat map of gene expression detection for the hESC gene list across 24 hESC and 193 fetal and adult tissues samples analyzed with the U133A microarray (828 probe sets). Red stands for a present detection call (i.e., gene expression confidently detected according to the GCOS 1.2 software . Only genes were clustered. Comparison of Gene Ontology (GO) annotations between hESC genes and differentiation genes (D). We compared the frequency of GO annotations of genes overexpressed in hESCs to those underexpressed in hESCs. The statistical analysis was carried out using the Babelomics web tool (http://babelomics.bioinfo.cipf.es). Histograms show the percentage of genes with the specified GO annotation in the group of genes overexpressed in hESCs (purple) or in differentiated tissues (yellow). P represents the false discovery rate-adjusted p value. Abbreviations: AD, adipocytes; CNS, central nervous system; DT, digestive tract; H&M, heart and muscle; HEMATO, various hematopoietic tissues; hESC, human embryonic stem cell; hFF, human foreskin fibroblasts; K&P, kidney and prostate; LU, lung; OV, ovary; PL, placenta; PNS, peripheral nervous system; SK, skin and keratinocytes; TH, thyroid; UT, uterus.( ^" R' G* R2 e: @

The HS293 and HS235 hESC lines were cultured in the Department of Obstetrics and Gynecology (CLINTEC) at the Karolinska University Hospital as described previously . Briefly, hESCs were cultured on hFF (CRL-2429; American Type Culture Collection, Manassas, VA, http://www.atcc.org) mitotically inactivated by irradiation (40 Gy), in KO-DMEM 20% knockout SR, 2 mM GlutaMAX, 0.5% penicillin-streptomycin, 1% nonessential amino acids, 0.5 mM ß-mercaptoethanol (all from Gibco, Paisley, U.K., http://www.invitrogen.com); 1% insulin-transferrin-selenium (Sigma-Aldrich); and 8 ng/ml of basic FGF (R&D Systems, Oxford, U.K., http://www.rndsystems.com).5 I4 r% O  M0 T/ [- U
: \: m! c( O5 ]; V8 a
For karyotype analysis, hESCs were treated with 75 ng/ml final Karyomax Colcemid (Invitrogen) for 1 hour, trypsinized, incubated in 0.0375 M KCl for 20 minutes, and fixed in fresh 3:1 methanol/acetic acid solution. One-two spreads were counted for chromosome number, and 12¨C16 banding patterns were analyzed at a resolution of 300¨C500 bands.: U- T2 {! G5 n! O1 l5 v1 j

Flow Cytometry Analysis% S6 L$ M0 R; A' J9 x' T7 ]; T& ]; o
. \! d0 A7 {7 B* b2 [1 n
hESCs and fibroblasts were dissociated with trypsin (0.25%)-EDTA (1 mM) (Gibco) for 3 minutes. Cells were then washed with phosphate-buffered saline (PBS) and incubated for 30 minutes at 4¡ãC in PBS with the corresponding monoclonal antibody (MAb): anti-CD24 MAb conjugated to phycoerythrin (dilution 1:50; clone ALB9, Immunotech, Marseille, France, http://www.immunotech.com) and/or anti-CD44 MAb conjugated to fluorescein isothiocyanate (dilution 1:50; clone J-173; Immunotech). After PBS washes, cells were suspended in FACSFlow (Becton Dickinson, San Jose, CA, http://www.bdbiosciences.com) and fluorescence was analyzed with a FACSCalibur flow cytometer (Becton Dickinson) or sorted with a FACSAria cell sorter (Becton Dickinson). Appropriate isotype controls were included in all analyses.
+ u# ~! ?9 x. X1 @# ?
Immunofluorescence2 a0 B+ y6 B# u7 M3 k( \/ D

hESCs cultured on coverslips were fixed for 20 minutes in 4% paraformaldehyde and washed three times in PBS. Cells were permeabilized with 0.1% Triton X-100 (Sigma). After blocking at room temperature for 60 minutes in PBS with 5% donkey serum (S30; Chemicon International, Temecula, CA, http://www.chemicon.com), cells were incubated for 1 hour at room temperature with primary antibody diluted in PBS with 5% donkey serum: POU5F1/OCT3/4 (sc 9081 1:300; Santa Cruz Biotechnology, Santa Cruz, CA, http://www.scbt.com) and SEMA6A (AF1146; 1:50; R&D). Cells were washed three times in PBS and incubated for 1 hour at room temperature with Alexa Fluor 488 donkey anti-rabbit (A-11034; 1:1,000; Molecular Probes, Eugene, OR, http://probes.invitrogen.com) and Cy3 donkey anti-goat (1:400; Jackson ImmunoResearch, West Grove, PA, http://www.jacksonimmuno.com) secondary antibodies, for POU5F1 and SEMA6A, respectively. Unbound antibodies were removed by three washes in PBS. Hoechst staining was added to the first wash (5 µg/ml; Sigma-Aldrich).
- k6 V( n7 Q* E5 j, G/ ~
RESULTS
/ G0 r4 d3 Z4 _
Compiling hESC Expression Profiles# T/ h* W6 o- R7 \4 j' K: Z
: g) a3 H! s0 _/ K1 P
As of October 1, 2006, we identified 38 original studies, one protocol description, and four reviews analyzing the transcriptome of hESCs (Table 2). The original studies used various hESCs, control cells, and gene expression analysis techniques (summarized in supplemental online Table 1). Twenty-eight different hESC lines were used, and transcriptome techniques included microarrays (seven different types of chips), ESTs scanning, SAGE, massively parallel signature sequencing (MPSS), and Illumina beads (Illumina, San Diego, CA, http://www.illumina.com). One study compared chromatin immunoprecipitation chip data with transcriptome data in hESCs . Nevertheless, some common features emerged such as the frequent investigation of the H1, H9, and BG01 hESCs (in 12, 12, and 11 studies, respectively), and the use of the GeneChip (Affymetrix) microarray system (in 16 studies; supplemental online Table 1).
- D5 a; f6 {) k
Meta-Analysis of Genes Differentially Expressed Between hESCs and Nonpluripotent Cells
# R0 t& v: `3 m! I
One main objective of large-scale gene expression analyses of hESCs is to identify the set of genes that are overexpressed in this unique cell type (hESC genes) or underexpressed (differentiation genes). We reasoned that bona fide hESC or differentiation genes would be repeatedly uncovered by independent groups, regardless of the hESC lines, the control cells, the assay format, or the statistical method that had been used. We collected, from these 38 original studies, 20 lists of transcripts overexpressed in hESCs (hESC genes), and 11 lists of genes underexpressed in hESCs (differentiation genes).

The 20 lists of hESC genes comprised 5,567 different genes. As illustrated in Figure 1A, we observed a marked heterogeneity between these lists, with only 1,076 genes found to be overexpressed in hESCs by three or more independent studies, 48 genes by 10 or more studies, and only one gene by all 20 lists (supplemental online Table 2). The 48 genes found to be overexpressed in at least 10 studies are listed in Table 3. Of note, the pivotal ES transcription factor POU5F1/OCT3/4 is the one gene found by all 20 lists, whereas genes found in at least 10 studies include the transcription factors NANOG and SOX2 and the growth factors TDGF1/CRIPTO and Galanin (GAL) that are known to be highly expressed by hESCs. Thus, according to hESC transcriptome analyses published to date, this list of 1,076 genes found to be overexpressed in hESC cells by three or more studies can be viewed as a consensus hESC gene list.
) U. j8 F, a* x
To get further insights into this hESC list, we built an expression compendium by combining the data from five publications using the U133A GeneChip microarray to analyze hESC transcriptome and three publications providing the transcriptome of various normal fetal and adult tissues (see Materials and Methods; supplemental online Table 4). This compendium included the gene profiling of 24 hESC samples and more than 190 various fetal and adult tissues samples. A heat map was generated for the consensus hESC gene list in this expression compendium based on the detection call provided by the GCOS 1.2 software. The detection call is a way to evaluate whether a gene is expressed in a given sample. Hierarchical clustering (Fig. 1C) delineated four major clusters of genes: cluster A was a group of 40 genes specifically detected in hESCs (hESC-specific genes; Table 4), including expected genes such as POU5F1/OCT3/4, NANOG, TDGF1, LIN28, CLDN6, GDF3, and DNMT3A, but also genes such as CYP26A1, HELLS, or GPR19; cluster B featured genes that were detected in both hESCs and central nervous system samples such as the GABA receptors GABRB3 and GABRA5, and the growth factor FGF13; cluster C genes detected in samples characterized by a high mitotic index such as SKP2, MYC, the cyclin CCNA2, and the MCM genes MCM2, MCM5, MCM6, and MCM7; and cluster D genes overexpressed in hESCs but also expressed in a majority of the tissues included in this dataset such as PGK1, HSPA9B, and the ribosomal genes RPLP0, RPL6, RPL7, and RPL24. The complete lists of genes composing these clusters are available as supplemental online Table 5. The expression histograms of the 40 hESC-specific genes are shown in supplemental online Figure 2. These results show that, although all 1,076 genes of the consensus hESC gene list have been found to be overexpressed in hESCs compared to non-hESC samples by at least three different studies, 40 genes are indeed hESC specific (cluster A), but most are nonetheless also expressed in adult tissues to various extent.! _) i0 V9 d4 k! P2 u+ q. L

Table 5. Thirty selected genes underexpressed in hESCs compared to differentiated cell types and found by at least six studies

Figure 2. CD24 and SEMA6A are two new hESC markers. Expression histograms of CD24 across the U133A compendium (A). These histograms were obtained from our Amazonia! website from the U133A oligonucleotide microarray (Affymetrix) datasets. The y-axis features the signal value obtained with GCOS 1.2 software (Affymetrix). Microarray expression histograms of CD24 gene before and after nonlineage differentiation into embryoid bodies (EBs; data from the study of ) (J). Mean U133A microarray signal value of SEMA6A in 24 hESC samples compared with two human fibroblast samples (K). Indirect immunofluorescence localization of SEMA6A, POU5F1/OCT3/4, or both, and corresponding Hoechst nuclear staining in the HUES1 (L) and HUES3 hESCs (M) cultured on murine embryonic and human fibroblasts, respectively. Scale bar = 25 µm. The white arrow represents MEF (L) or hFF (M). Abbreviations: AD, adipocytes; CNS, central nervous system; DIF, differentiated hESC; DT, digestive tract; H&M, heart and muscle; HEMATO, various hematopoietic tissues; hESC, human embryonic stem cell; hFF, human foreskin fibroblasts; K&P, kidney and prostate; LU, lung; OV, ovary; PL, placenta; PNS, peripheral nervous system; SK, skin and keratinocytes; TH, thyroid; UT, uterus.
. m3 \# s' I1 a3 X% E
The 11 lists of differentiation genes totaled 4,798 genes, and we noted a similar heterogeneity as in the hESC lists (supplemental online Table 3). Of these 4,798 genes, only 783 were found to be underexpressed in hESCs by at least 3 different studies, composing a consensus differentiation gene list, 3 genes (lumican and collagen 1A1 and 3A1), by 9 studies, and none by all 11 studies (Fig. 1B). Table 5 shows 30 selected genes found by at least 6 studies, which include the bone morphogenetic proteins (BMP) 1 and 4, keratin 7 and keratin 18, insulin-like growth factor 2 (IGF2), heart and neural crest derivatives expressed 1 (HAND1), and the transducing chain IL6ST/GP130. The complete consensus differentiation gene list can be found in supplemental online Table 3.- O- K7 V2 n5 F' e$ }0 {
8 t: t! T4 T8 I3 @
We compared functional GO annotations of the hESC genes to the differentiation genes. Several functional annotations were more represented in each category (Fig. 1D). There were significantly more genes involved in "metabolism," "mitosis," "RNA splicing," "nuclear pore," and "DNA repair" in the hESC gene list, reflecting the intense proliferation, DNA replication, and DNA remodeling taking place in these cells. Conversely, GO annotations such as "organ development," "skeletal development," "extracellular matrix," "cell adhesion," "cell communication," "integral to plasma membrane," and "signal transduction," were significantly more frequent among genes upregulated in differentiated tissues, in agreement with the idea that hESC differentiation mimics early organogenesis, which is associated with the development of complex cell-cell communication and cell-extracellular matrix interactions.
, h  d: @) ^% U, q- E) Q! R
CD24 and SEMA6A Are hESC Markers  ?: e' m6 H2 N* Y1 G4 \

We next inquired whether we could find, among the hESC genes, new markers that may be useful to identify, isolate, and qualify hESCs in vitro. We focused on two cell surface hESC genes: CD24 and SEMA6A. These two genes have been found to be overexpressed in hESCs by, respectively, 9 and 15 studies, and are, therefore, good candidates as new hESC markers.

CD24 is a sialoglycoprotein known to be expressed on mature granulocytes and B-cell subpopulations  cultured on hFF and evidenced two distinct cell populations, one CD24  and one CD24¨C (Fig. 2E). To demonstrate that the CD24  population corresponded to hESCs and the CD24¨C population to hFFs, we took advantage of CD44, a strong fibroblast marker not expressed by hESCs (Figs. 2D, 2G). Double staining of hESCs cultured on hFF showed that these two markers were expressed in a mutually exclusive manner and delimited a hESC CD24  CD44¨C population that did not overlap with the fibroblast CD24¨C CD44  population (Fig. 2H). Using CD24/CD44 labeling, we were able to separate hESCs from fibroblasts and obtain pure hESC populations that recovered the cell sorting procedure and grew in vitro while retaining POU5F1 and cardinal cell surface markers of pluripotency expression (supplemental online Fig 3 and data not shown).- J; y- m3 T: z' c2 }! q

Figure 3. Expression of selected genes using Amazonia!. Expression histograms of five hESC-specific genes (POU5F1, NANOG, GPR19, HELLS, and CYP26A1), two genes expressed in non-lineage-differentiated hESC cells (HAND1 and IGF2), two factors highly expressed by human fibroblasts and smooth muscle that may contribute to the supporting properties of fibroblasts to hESC culture (Gremlin and MMP1), one hematopoietic marker (CD45), one CNS-specific gene (GFAP) and one ubiquitously expressed gene (ribosomal protein L3  (D). Comparison of the expression of CD24 mRNA across NL and ML samples (E), and across normal hematopoietic (NH) and B acute lymphoblastic leukemia (ALL) and T-ALL samples (F). Abbreviations: AD, adipocytes; CNS, central nervous system; DIF, differentiated hESC; DT, digestive tract; EC, embryonic carcinoma; H&M, heart and muscle; HEMATO, various hematopoietic tissues; hESC, human embryonic stem cell; hFF, human foreskin fibroblasts; K&P, kidney and prostate; LU, lung; NL, normal lung; ML, malignant lung; OV, ovary; PL, placenta; PNS, peripheral nervous system; SK, skin and keratinocytes; TH, thyroid; UT, uterus; YSC, yolk sac carcinoma.

SEMA6A is a class 6 semaphorin . Comparison of RNA expression in hESCs and normal adult tissues showed that, in addition to hESCs, SEMA6A was also expressed at high-level in adult samples from the central and peripheral nervous system and placenta (Fig. 2I). As for CD24, SEMA6A mRNA is downregulated on EB differentiation and is not detected in human fibroblasts (Fig. 2J, 2K). Immunofluorescence analysis showed a membrane localization of SEMA6A on hESCs, in contrast to POU5F1/OCT3/4, which had a strict nuclear localization (Fig. 2L, 2M). In summary, we showed that CD24 and SEMA6A have indeed a preferential expression in hESCs, that this expression is confirmed at the protein level, and that it declines on EB differentiation. Thus, these markers can be used to distinguish hESCs from feeder fibroblasts.& ~- ?, o, ]* [# t8 v
: A+ [: {* x# |) X
hESC Transcriptome Data Visualization Through an Open-Access Web Interface
* d9 T0 `' G8 j* `" t
We developed a website, Amazonia! (http://amazonia.montp.inserm.fr), to allow the scientific community access to these public data. This website is dedicated to the visualization of large, publicly available human transcriptome data (T. Le Carrour, C. Berthenet, S. Assou, L. Lhermitte, G. Palenzuela, N. Lamb, T. R¨¨me, B. Klein, J. De Vos, manuscript submitted). A main topic of this website is human embryonic stem cells. Data are visualized as expression histograms with a color code facilitating the recognition of cell type. Genes are accessed either by keywords or through lists of genes. Most interestingly, when data were obtained using the same platform format, sample labeling, and data normalization, it was possible to combine different experiments in a single virtual experiment. The U133A expression compendium comprises, for example, more than 200 different samples from eight publications including hESCs and normal adult tissues. Thus, Amazonia! provides the expression profile of approximately 15,000 different genes in approximately 100 different tissues types or purified cell populations, including 11 hESCs (H1, H9, HS181, HS235, HS237, FES21, FES22, FES29, FES30, I6, and HES-2). Figure 3A illustrates this feature of our website with the expression histograms of five hESC-specific genes (POU5F1, NANOG, GPR19, Helicase lymphoid-specific ).
1 Z8 u' u- ^6 r
Another important feature of Amazonia! is the possibility to compare, on the same web page, the expression of a gene of interest in various datasets. Figure 3B shows that the expression of Frizzled 7 (FZD7) was markedly upregulated in hESCs, was downregulated during nonlineage differentiation into EBs, and was also highly expressed in embryonal carcinoma and yolk sac carcinoma samples. The combination of these three histograms evidences a preferential FZD7 mRNA expression in normal and malignant embryonic cells, suggesting that FZD7 may play a major role in these pluripotent cell types.
4 u/ R" e( B6 c9 G
To facilitate access for the scientific community to the lists of genes from published transcriptome analyses, we implemented a list manager in our Amazonia! website. Thus, one can access these lists straightforwardly and obtain an expression histogram for each gene in various public transcriptome collections. This feature is of particular interest to challenge a list of genes, such as an hESC gene list, with other hESC datasets or even with non-hESC datasets such as cancer datasets. Indeed, once a gene is selected, the user can navigate between various thematic pages, switching for instance from the "stem cells" page to the "leukemia and lymphoma," "lung cancer," or other pages. Using this feature of the Amazonia! website, we could observe that the sialoglycoprotein CD24 was also highly expressed in acute lymphoblastic leukemia, lung cancer, and glioma samples when compared to the corresponding normal samples (Fig. 3C and data not shown).- V8 G$ X3 c3 g( B& A) Y0 d

DISCUSSION1 h! N2 X' `$ _, v6 K0 o$ R

Human ESCs are remarkable in their ability to both self-renew and generate virtually any cell type, hence carrying many hopes for cell therapy. It is anticipated that genome-wide expression analyses, by providing an extensive molecular taxonomy, will help understanding this unique cell model of stem cell pluripotency. Transcriptome results can be viewed as a nonbiased, genome-wide expression catalog. Many groups have published the transcriptome of hESCs, but, as a direct consequence of the massive data generated, access to this data on a routine basis was precluded for most researchers. Therefore, the construction of a database collecting publicly available hESC transcriptome and accessible through a user-friendly interface is of utmost interest for the hESC research community. We found 38 original studies or reviews analyzing the transcriptome of hESCs. Expression data and gene lists extracted from these studies were included into Amazonia! and are now readily accessible. Interestingly, the frequent use of the U133A oligonucleotide microarrays allowed us to construct a virtual expression dataset of approximately 15,000 different genes in more than 200 tissue samples from various origins, including 24 hESC samples. Hence, the expression of each gene in hESCs is directly contrasted with that of normal fetal and adult tissues, as illustrated in Figure 3A.

Unearthing the hESC gene panoply may help to define what makes hESCs unique. To achieve this goal, most studies compared hESC transcriptome data to that of more differentiated cell types and obtained lists of genes over- or underexpressed in hESCs. Comparison of different transcriptome surveys of hESCs gave us the unique opportunity to identify genes that were identified by several authors as being differentially expressed in hESCs. However, a striking heterogeneity was observed among the 20 lists of hESC genes, and only 48 genes were found to be highly enriched in hESCs in at least 10 publications, among 5,567 genes found in at least one publication. Some of these differences may be explained by platform-to-platform or lab-to-lab variability, but this is likely not the main explanation, as suggested by transcriptome platform comparisons . However, the raw data were not available for many studies analyzed here, which prevented us from applying this approach in our study. Nevertheless, the 1,076 hESC gene list provides the opportunity to the scientific community to examine the genes that have been found to be over- or underexpressed in hESC by several authors. These lists provide further molecular insight into the biology of this unique stem cell model and are now starting points for many new research directions in the field of hESC. In the future, it will be interesting to extend this list by investigating additional hESC lines. The collection of additional transcriptome data is ongoing, and we will update the database according to new publications on the hESC genome expression.
* M  a. ]  l, Z: U* O% t6 {/ J; [
As one can easily notice by browsing the consensus hESC gene list in the U133A "embryonic and adult samples" dataset, we found very few genes that are completely hESC specific. Indeed, most genes found to be overexpressed in hESCs are also expressed in other tissues (Fig. 1C), and only 40 genes, grouped in cluster A, comprised genes for which expression was not detected in most other tissues (supplemental online Figure 2). Of note, genes can be labeled as hESC specific only with respect to the different tissues and cell populations that have been tested. As new cell types are investigated, some of these genes may be found to be expressed in these new samples and, thereby, cease to be specific to hESCs. Specificity also depends on the sensitivity of the assay investigating expression of a given gene. For example, POU5F1/OCT3/4 has been reported to be expressed in germinal cells and even in bone marrow by reverse transcriptase polymerase chain reaction assays . By contrast, microarray analysis show that this gene, clearly expressed at a high level in hESCs and teratocarcinoma samples, is not detected by this technique in testis, ovary, bone marrow samples, nor in a pure oocyte population (Fig. 3A and unpublished data). These observations suggest that the properties of hESCs, comprising self-renewal, unrestrained proliferation, and pluripotency, are mediated by the expression of few specific genes, if any, together with genes that, individually, are not hESC specific, but whose combined expression is specific to hESCs. The consensus hESC gene list should encompass many of those genes contributing to the embryonic stem cell characteristics.
; D( R' p3 d! |$ v
Transcriptome approaches have several limitations. Each technique has its own technical limits, but this meta-analysis partly circumvented these by the simultaneous analysis of different, complementary methods. Another drawback is that by looking at the transcriptome, we consider gene expression at the RNA level only, eluding all forms of post-transcriptional regulation. It will, therefore, be important in the future to look at the differential expression of the genes described in the hESC and differentiation lists at the protein level. For that matter, this meta-analysis provides a list of pertinent genes for further protein validation. In line with this proposition, we chose to investigate more thoroughly two cell surface protein-encoding genes, which may serve as new hESC markers: CD24 and SEMA6A. Although these two genes have been found to be overexpressed in hESCs by 9 and 15 studies, respectively, we found that hESCs shared this RNA expression with several adult tissues, as substantiated by microarray results (Fig. 2). However, purification of hESCs requires only distinguishing them from differentiating stem cells and from the cocultured feeder cells. CD24 expression is low in differentiating hESCs, and is absent in human fibroblasts. We were thus able to purify pure hESC populations by flow cytometry. This provides a new tool to isolate highly enriched populations of hESCs for subsequent experiments, including microarray analysis. We observed that CD24 was also highly expressed on various malignant cell types, as previously reported . The role of CD24 in hESCs is less clear because P-selectin is not expressed by human fibroblasts nor by hESCs themselves (data not shown), suggesting that CD24 may have other molecular functions. Semaphorins have been initially identified for their role in neuronal guidance as chemorepellents, but it is becoming clear that this large family of genes also plays important roles in organogenesis, vascularization, angiogenenesis, and B-lymphocyte signaling. We show here a clear protein expression of semaphorin 6A in hESCs, with an overexpression in hESCs compared to many other cells types, suggesting a functional role for this transmembrane molecule in cell-to-cell interaction or signaling in hESCs.
  S- P( E$ X: q4 ^
The clustering of the consensus hESC gene list based on the detection call identified a cluster of 40 genes with a high specificity in hESCs, with no expression in most samples from more than 100 different fetal and adult cell tissues (Table 4). In addition to genes clearly expected such as POU5F1/OCT3/4, NANOG, or TDGF1, this cluster included genes whose hESC specificity had been overlooked. For example, the expression of the G protein-coupled receptor 19 (GPR19) is restricted to hESCs and, if functional, may offer a possibility for in vitro intervention on proliferation or pluripotency of hESCs. Other hESC-specific genes comprise the cytochrome P450 CYP26A1, which is responsible for retinoic acid degradation .- z8 A; L9 f8 r
5 a, Z2 _/ r, m7 D( y- a5 I7 V
CONCLUSIONS, C. t$ {/ F$ P% y! S

We analyzed 38 publications studying the hESC transcriptome. We propose a consensus hESC gene list and a consensus differentiation gene list that identifies the genes found to be, respectively, up- or downregulated in hESCs compared to differentiated samples by at least three publications. We provide the first tool to directly visualize the expression of most human genes in hESCs, and provide direct comparison with their expression in many normal and malignant tissues. This tool may be considered the first hESC expression atlas online. By providing an easy access to this large public data, we hope that Amazonia! will help boost the translation of this invaluable expression information into biological applications.

DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
) K& ~; Z+ z" Z7 Y0 j" g: c: b& V  O, ]
The authors indicate no potential conflicts of interest.% Q3 S6 z) g; ]) U. Y

ACKNOWLEDGMENTS
- O) M; Q6 X2 I
We thank the various labs that gave free access to their complete transcriptome data, in agreement with the Minimum Information About a Microarray Experiment recommendations ; Ned Lamb and Cyril Berthenet for support with informatics (Institut de G¨¦n¨¦tique Humaine de Montpellier), and Hassan Boukhaddaoui for cell imaging (Montpellier RIO Imaging); Isabelle Rodde-Astier, Antoine H¨¦ron and Val¨¦rie Duverger (MacoPharma) for decisive support for this project; and Genevi¨¨ve Lefort, Marie Ponset, and Franck Pellestor for assistance in hESC karyotyping.  n- W( ?0 Z9 ^
      【参考文献】
8 }% C6 {% _: G# Z7 v$ x1 Z

Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells from mouse embryos. Nature 1981;292:154¨C156.

Thomson JA, Itskovitz-Eldor J, Shapiro SS et al. Embryonic stem cell lines derived from human blastocysts. Science 1998;282:1145¨C1147.
9 g& k! h9 y5 o2 L$ k1 h0 X
Chambers I, Colby D, Robertson M et al. Functional expression cloning of Nanog, a pluripotency sustaining factor in embryonic stem cells. Cell 2003;113:643¨C655.

Nichols J, Zevnik B, Anastassiadis K et al. Formation of pluripotent stem cells in the mammalian embryo depends on the POU transcription factor Oct4. Cell 1998;95:379¨C391.

Hanna LA, Foreman RK, Tarasenko IA et al. Requirement for Foxd3 in maintaining pluripotent cells of the early mouse embryo. Genes Dev 2002;16:2650¨C2661.2 u- o, C, N  B

Rogers MB, Hosler BA, Gudas LJ. Specific expression of a retinoic acid-regulated, zinc-finger gene, Rex-1, in preimplantation embryos, trophoblast and spermatocytes. Development 1991;113:815¨C824.% b7 y" f' C: U# E( G# a
- D" T7 Z# Q6 M/ f! |& y
Graham V, Khudyakov J, Ellis P et al. SOX2 functions to maintain neural progenitor identity. Neuron 2003;39:749¨C765.
. d0 o( t# I; z5 q" P: G
Feldman B, Poueymirou W, Papaioannou VE et al. Requirement of FGF-4 for postimplantation mouse development. Science 1995;267:246¨C249.% c) C! `% n, X/ K. F

Lee TI, Jenner RG, Boyer LA et al. Control of developmental regulators by polycomb in human embryonic stem cells. Cell 2006;125:301¨C313.
& c8 y8 t6 C. V( S
Boyer LA, Lee TI, Cole MF et al. Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 2005;122:947¨C956.
% [" D) f0 f$ h. R6 b: Q
Rhodes DR, Yu J, Shanker K et al. ONCOMINE: A cancer microarray database and integrated data-mining platform. Neoplasia 2004;6:1¨C6.$ y$ o5 |' X! _# ]( o

Al-Shahrour F, Minguez P, Vaquerizas JM et al. BABELOMICS: A suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Res 2005;33:W460¨CW464.0 y  _  k, Q# E7 j
2 g9 B% l5 O8 a1 n
Su AI, Wiltshire T, Batalov S et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A 2004;101:6062¨C6067.7 [8 V& O2 t  I# S. D: }

Golan-Mashiach M, Dazard JE, Gerecht-Nir S et al. Design principle of gene expression used by human stem cells: Implication for pluripotency. FASEB J 2005;19:147¨C149.$ D1 }% J) x/ ]9 C

Sato N, Sanjuan IM, Heke M et al. Molecular signature of human embryonic stem cells and its comparison with the mouse. Dev Biol 2003;260:404¨C413.
" U1 @7 g# p) k7 F# m
Skottman H, Mikkola M, Lundin K et al. Gene expression signatures of seven individual human embryonic stem cell lines. STEM CELLS 2005;23:1343¨C1356.) L3 k% k& N8 }1 b% t2 A

Ge X, Yamamoto S, Tsutsumi S et al. Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. Genomics 2005;86:127¨C141.

Lenburg ME, Liou LS, Gerry NP et al. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data. BMC Cancer 2003;3:31.- I6 A" p  \0 q; d* |0 q3 }
' W% O; Q7 S: I2 h3 B9 n- s. P6 h
Hirst CE, Ng ES, Azzola L et al. Transcriptional profiling of mouse and human ES cells identifies SLAIN1, a novel stem cell gene. Dev Biol 2006;293:90¨C103.2 g, }% B3 R; s
$ L) G2 p3 d4 T) u' k
Perez-Iratxeta C, Palidwor G, Porter CJ et al. Study of stem cell function using microarray experiments. FEBS Lett 2005;579:1795¨C1801.
1 T& \6 M4 g* ~( h( B7 b; k
Haferlach T, Kohlmann A, Basso G et al. A multi-center and multi-national program to assess the clinical accuracy of the molecular subclassification of leukemia by gene expression profiling. Blood 2005;106:224a.
1 H0 ~! d6 e7 w- Y: D
Irizarry RA, Warren D, Spencer F et al. Multiple-laboratory comparison of microarray platforms. Nat Methods 2005;2:345¨C350.

Eisen MB, Spellman PT, Brown PO et al. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998;95:14863¨C14868.
8 V& R$ }1 C( z, q7 y& z' I4 ^; K7 h% r
Cowan CA, Klimanskaya I, McMahon J et al. Derivation of embryonic stem-cell lines from human blastocysts. N Engl J Med 2004;350:1353¨C1356.
( d- Y4 v8 y+ E# I6 S
Inzunza J, Gertow K, Stromberg MA et al. Derivation of human embryonic stem cell lines in serum replacement medium using postnatal human fibroblasts as feeder cells. STEM CELLS 2005;23:544¨C549.
: z. f( L6 K, W7 M8 l
Elghetany MT, Patel J. Assessment of CD24 expression on bone marrow neutrophilic granulocytes: CD24 is a marker for the myelocytic stage of development. Am J Hematol 2002;71:348¨C349.$ k9 ^; v' Q8 G

Semaphorin Nomenclature Committee. Unified nomenclature for the semaphorins/collapsins: Semaphorin Nomenclature Committee. Cell 1999;97:551¨C552.
1 Z9 r) P8 Y6 \0 ^
Assou S, Anahory T, Pantesco V et al. The human cumulus-oocyte complex gene expression profile. Human Reproduction 2006;21:1705.

Sperger JM, Chen X, Draper JS et al. Gene expression patterns in human embryonic stem cells and human pluripotent germ cell tumors. Proc Natl Acad Sci U S A 2003;100:13350¨C13355.

Brandenberger R, Wei H, Zhang S et al. Transcriptome characterization elucidates signaling networks that control human ES cell growth and differentiation. Nat Biotechnol 2004;22:707¨C716.
/ d4 R% o: [+ |
Wei CL, Miura T, Robson P et al. Transcriptome profiling of human and murine ESCs identifies divergent paths required to maintain the stem cell state. STEM CELLS 2005;23:166¨C185.  y& v: m/ V3 Z* I+ V  H( e, [5 H3 ]

Fortunel NO, Otu HH, Ng HH et al. Comment on "¡®Stemness': Transcriptional profiling of embryonic and adult stem cells" and "A stem cell molecular signature.". Science 2003;302:393 author reply 393./ ^- o' |( i# y9 F% T8 o
8 n1 H/ j! P8 e' {, Q/ E
Su¨¢rez-Fari&ntilde;as M, Noggle S, Heke M et al. Comparing independent microarray studies: The case of human embryonic stem cells. BMC Genomics 2005;6:99.
$ M$ S4 ]& c* E5 X8 @
Johnson J, Bagley J, Skaznik-Wikiel M et al. Oocyte generation in adult mammalian ovaries by putative germ cells in bone marrow and peripheral blood. Cell 2005;122:303¨C315.
  W. }4 f2 u. L# H6 A- B
Cauffman G, Van de Velde H, Liebaers I et al. Oct-4 mRNA and protein expression during human preimplantation development. Mol Hum Reprod 2005;11:173¨C181.2 N# I# }: X. m5 }) O' t
" M. H. T9 c9 Q( ~1 ^/ N8 j
Kristiansen G, Schluns K, Yongwei Y et al. CD24 is an independent prognostic marker of survival in nonsmall cell lung cancer patients. Br J Cancer 2003;88:231¨C236.
+ x* K9 e* I3 S6 K
Lavabre-Bertrand T, Duperray C, Brunet C et al. Quantification of CD24 and CD45 antigens in parallel allows a precise determination of B-cell maturation stages: Relevance for the study of B-cell neoplasias. Leukemia 1994;8:402¨C408.; x, o* n8 x& M+ Y$ I0 G  T
3 u9 ^  A: S4 \
Aigner S, Sthoeger ZM, Fogel M et al. CD24, a mucin-type glycoprotein, is a ligand for P-selectin on human tumor cells. Blood 1997;89:3385¨C3395.

White JA, Beckett-Jones B, Guo YD et al. cDNA cloning of human retinoic acid-metabolizing enzyme (hP450RAI) identifies a novel family of cytochromes P450. J Biol Chem 1997;272:18538¨C18541.0 ^( \! P* K  P" W
2 |& M# c) `1 b$ [" B; \2 U
Geiman TM, Durum SK, Muegge K. Characterization of gene expression, genomic structure, and chromosomal localization of Hells (Lsh). Genomics 1998;54:477¨C483.4 }6 s/ {+ H( Q7 @

Sato N, Meijer L, Skaltsounis L et al. Maintenance of pluripotency in human and mouse embryonic stem cells through activation of Wnt signaling by a pharmacological GSK-3-specific inhibitor. Nat Med 2004;10:55¨C63.

Ball C, Sherlock G, Parkinson H et al. A guide to microarray experiments¨Can open letter to the scientific journals. Lancet 2002;360:1019.- T5 Z! x5 i0 W& V1 o3 C6 E
5 \: n  ?/ D5 m3 u/ S
Abeyta MJ, Clark AT, Rodriguez RT et al. Unique gene expression signatures of independently-derived human embryonic stem cell lines. Hum Mol Genet 2004;13:601¨C608.: e! |5 e! [4 H' m# p

Aghajanova L, Skottman H, Stromberg AM et al. Expression of leukemia inhibitory factor and its receptors is increased during differentiation of human embryonic stem cells. Fertil Steril 2006;86 (suppl 4):1193¨C1209.
& t+ u' U  o6 d% m
Armstrong L, Hughes O, Yung S et al. The role of PI3K/AKT, MAPK/ERK and NFkappabeta signalling in the maintenance of human embryonic stem cell pluripotency and viability highlighted by transcriptional profiling and functional analysis. Hum Mol Genet 2006;15:1894¨C1913.2 O. c# v0 i, N4 S4 \" \6 X
, L3 R2 l3 P6 Z. c
Beqqali A, Kloots J, Ward-van Oostwaard D et al. Genome-wide transcriptional profiling of human embryonic stem cells differentiating to cardiomyocytes. STEM CELLS 2006;24:1956¨C1967.* l* K: C; z" P7 M! r7 `$ V) M4 X

Bhattacharya B, Miura T, Brandenberger R et al. Gene expression in human embryonic stem cell lines: Unique molecular signature. Blood 2004;103:2956¨C2964.

Bhattacharya B, Cai J, Luo Y et al. Comparison of the gene expression profile of undifferentiated human embryonic stem cell lines and differentiating embryoid bodies. BMC Dev Biol 2005;5:22.& ~. p2 \. ?, _. {

Brandenberger R, Khrebtukova I, Thies RS et al. MPSS profiling of human embryonic stem cells. BMC Dev Biol 2004;4:10.
; j1 H2 v5 B9 i/ `
Brimble SN, Zeng X, Weiler DA et al. Karyotypic stability, genotyping, differentiation, feeder-free maintenance, and gene expression sampling in three human embryonic stem cell lines derived prior to August 9, 2001. Stem Cells Dev 2004;13:585¨C597.4 l/ G- p) D, e% w9 `

Brimble SN, Sherrer ES, Uhl EW et al. The cell surface glycosphingolipids SSEA-3 and SSEA-4 are not essential for human ES cell pluripotency. STEM CELLS 2007;25:54¨C62.8 v* q9 O: m" f! Q) M$ I) S
# L% W3 k( |. V
Cai J, Chen J, Liu Y et al. Assessing self-renewal and differentiation in hESC lines. STEM CELLS 2006;24:516¨C530.$ ?# a1 V* M+ X
4 w: e; A/ S6 m/ Q
Calhoun JD, Rao RR, Warrenfeltz S et al. Transcriptional profiling of initial differentiation events in human embryonic stem cells. Biochem Biophys Res Commun 2004;323:453¨C464.- N* \1 ~1 }# v3 ^! V
- {# z1 x1 E- r9 Q' X% }
Darr H, Mayshar Y, Benvenisty N. Overexpression of NANOG in human ES cells enables feeder-free growth while inducing primitive ectoderm features. Development 2006;133:1193¨C1201., |/ W" t" ]5 \) a9 @* t3 C. ?2 n
& L  V0 _& X$ j. K' l5 V% T
Dvash T, Mayshar Y, Darr H et al. Temporal gene expression during differentiation of human embryonic stem cells and embryoid bodies. Hum Reprod 2004;19:2875¨C2883.
2 g" K* i: b4 G9 U
Enver T, Soneji S, Joshi C et al. Cellular differentiation hierarchies in normal and culture-adapted human embryonic stem cells. Hum Mol Genet 2005;14:3129¨C3140., R; n8 c0 p( }" f4 _
, a6 R; [/ \& ?6 c6 ?; P6 {
Ginis I, Luo Y, Miura T et al. Differences between human and mouse embryonic stem cells. Dev Biol 2004;269:360¨C380.

Josephson R, Sykes G, Liu Y et al. A molecular scheme for improved characterization of human embryonic stem cell lines. BMC Biol 2006;4:28.0 H$ _, ~7 q$ L7 ?+ k( D; |$ u
3 U& s$ F: o& i0 C
Kim CG, Lee JJ, Jung DY et al. Profiling of differentially expressed genes in human stem cells by cDNA microarray. Mol Cells 2006;21:343¨C355.# M- I- q' l" p$ P" C
' }, ~  L, @9 M2 `% g. c4 P' J
Li H, Liu Y, Shin S et al. Transcriptome coexpression map of human embryonic stem cells. BMC Genomics 2006;7:103." K0 l' Q+ W6 ]; R# ]! V" o
6 {- u/ o* B' Y3 _1 b5 A
Liu Y, Shin S, Zeng X et al. Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines. BMC Dev Biol 2006;6:20.

Miura T, Luo Y, Khrebtukova I et al. Monitoring early differentiation events in human embryonic stem cells by massively parallel signature sequencing and expressed sequence tag scan. Stem Cells Dev 2004;13:694¨C715.
# N: \: _8 f( o7 L
Player A, Wang Y, Bhattacharya B et al. Comparisons between transcriptional regulation and RNA expression in human embryonic stem cell lines. Stem Cells Dev 2006;15:315¨C323.
4 }1 @8 a1 K- [- Z
Pyle AD, Donovan PJ, Lock LF. Chipping away at ¡®stemness.¡¯. Genome Biol 2004;5:235.

Rao M. Conserved and divergent paths that regulate self-renewal in mouse and human embryonic stem cells. Dev Biol 2004;275:269¨C286.
3 P* \! w% x' f6 \! R
Rao RR, Calhoun JD, Qin X et al. Comparative transcriptional profiling of two human embryonic stem cell lines. Biotechnol Bioeng 2004;88:273¨C286.+ V& ~: B+ x$ N( x0 Q( _$ d/ M
" g7 R9 C& y8 q3 D" ~& K
Rao RR, Stice SL. Gene expression profiling of embryonic stem cells leads to greater understanding of pluripotency and early developmental events. Biol Reprod 2004;71:1772¨C1778.; ^5 j% E5 Q$ D' Q, N8 O+ y
% m8 @- v2 L1 e& ~$ h/ C" q. B2 ?
Richards M, Tan SP, Tan JH et al. The transcriptome profile of human embryonic stem cells as defined by SAGE. STEM CELLS 2004;22:51¨C64.

Richards M, Tan SP, Chan WK et al. Reverse serial analysis of gene expression (SAGE) characterization of orphan SAGE tags from human embryonic stem cells identifies the presence of novel transcripts and antisense transcription of key pluripotency genes. STEM CELLS 2006;24:1162¨C1173.
1 z( x7 \+ T* ]$ z9 `+ ~
Robson P. The maturing of the human embryonic stem cell transcriptome profile. Trends Biotechnol 2004;22:609¨C612.- F; ]& V$ E" o* u. g

Sato N, Brivanlou AH. Microarray approach to identify the signaling network responsible for self-renewal of human embryonic stem cells. Methods Mol Biol 2006;331:267¨C283., g, C/ q3 O+ M' Y

Skottman H, Stromberg AM, Matilainen E et al. Unique gene expression signature by human embryonic stem cells cultured under serum-free conditions correlates with their enhanced and prolonged growth in an undifferentiated stage. STEM CELLS 2006;24:151¨C167.

Sun BW, Yang AC, Feng Y et al. Temporal and parental-specific expression of imprinted genes in a newly derived Chinese human embryonic stem cell line and embryoid bodies. Hum Mol Genet 2006;15:65¨C75., @3 }% U9 I  w3 p$ c" l% C

Xu RH, Chen X, Li DS et al. BMP4 initiates human embryonic stem cell differentiation to trophoblast. Nat Biotechnol 2002;20:1261¨C1264.
, @8 {0 `$ e2 O
Zeng X, Miura T, Luo Y et al. Properties of pluripotent human embryonic stem cells BG01 and BG02. STEM CELLS 2004;22:292¨C312.

收藏0 分享0 顶0 踩0