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Keywords:

  • Preimplantation development;
  • Blastocyst;
  • Inner cell mass;
  • Trophectoderm;
  • Pluripotency;
  • Embryonic stem cells;
  • Trophoblastic stem cells;
  • OCT4;
  • CDX2;
  • Differentiation;
  • Microarrays

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The primary differentiation event during mammalian development occurs at the blastocyst stage and leads to the delineation of the inner cell mass (ICM) and the trophectoderm (TE). We provide the first global mRNA expression data from immunosurgically dissected ICM cells, TE cells, and intact human blastocysts. Using a cDNA microarray composed of 15,529 cDNAs from known and novel genes, we identify marker transcripts specific to the ICM (e.g., OCT4/POU5F1, NANOG, HMGB1, and DPPA5) and TE (e.g., CDX2, ATP1B3, SFN, and IPL), in addition to novel ICM- and TE-specific expressed sequence tags. The expression patterns suggest that the emergence of pluripotent ICM and TE cell lineages from the morula is controlled by metabolic and signaling pathways, which include inter alia, WNT, mitogen-activated protein kinase, transforming growth factor-beta, NOTCH, integrin-mediated cell adhesion, phosphatidylinositol 3-kinase, and apoptosis. These data enhance our understanding of the first step in human cellular differentiation and, hence, the derivation of both embryonic stem cells and trophoblastic stem cells from these lineages.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The earliest stages of human cellular differentiation occur during the transition from the morula to blastocyst stage of preimplantation development and give rise to divergent lineages. These are the trophectoderm (TE), which gives rise to the cytotrophoblast and syncytiotrophoblast of the placenta, and the inner cell mass (ICM), which generates the embryo proper and extraembryonic tissues [1]. The immediate outcomes of blastocyst morphogenesis, namely epithelial differentiation and segregation of the ICM, are mainly regulated autonomously, and they involve temporally regulated gene expression, cell polarization, and cell–cell interactions leading to the generation of differentiated progeny. The ICM and TE are the sources of embryonic stem (ES) cells and trophoblastic stem (TS) cells, respectively. ES cells are pluripotent, which implies that they are capable of differentiating into cells representing the three primary germ layers—endoderm, ectoderm and mesoderm [2]. In contrast, TS cells have a more restricted developmental potential and are only capable of forming trophectodermal cell lineage in vivo or giant cells in vitro, as demonstrated in the mouse [3].

Several stemness genes have been identified in murine [47] and human [812] embryonic stem cell lines under culture conditions. However, the weak overlap between these genes (∼25%) may be a consequence of the heterogeneous genetic backgrounds of the various cell lines or epigenetic and chromosomal instability after differentiation in vitro [13, 14]. Hence, genes for stemness may be better identified at source within the pluripotent ICM of the mammalian blastocyst.

Although specific markers for the TE and ICM, such as CDX2 and OCT4 [1517], have been identified, these are limited and underexplored. In this study, we provide the first global analysis of differential gene expression in intact human blastocysts and immunosurgically isolated ICM and TE cells for identifying novel marker genes specific to these lineages. We have uncovered gene expression patterns that suggest that the delineation of the ICM and TE from the morula may be controlled by signaling pathways, which are also crucial for determining cell fate later in embryonic development, in the ontogenesis of some cancers, and for advances in technology and the maintenance of human ES and TS cells in vitro.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Clone Selection and Microarray Fabrication

All transcripts in the human Ensembl catalog v.3.26.1 were blasted against the 5′ ends of previously sequenced clones from the human UniGene set RZPD2.1. Sequences sharing a best hit with any of these transcripts were assigned to the corresponding Ensembl gene. All matches had to fulfill two criteria: >96% identity over more than 50 nucleotides, which corresponds to a score of 100, and an e-value of 1e-20. To avoid redundancy, a single clone was selected for each Ensembl gene. For the generation of microarray slides, cDNA inserts from a collection of 15,529 annotated human cDNAs were amplified, purified, spotted, and processed as previously described [18].

Preimplantation Embryos and Generation of T7-Linked Double-Stranded cDNA and Amplified RNA

Preimplantation embryos surplus to requirement for in vitro fertilization (IVF) treatment were donated by patients for research attending the Jones Institute at Eastern Virginia Medical School (EVMS) (Norfolk, VA) and Leeds General Infirmary (LGI) (Leeds, U.K.). The IVF-derived blastocysts were similar to those used for deriving ES cells, i.e., fully expanded with a well-defined ICM and TE, lacking signs of degeneration, and at stage 3 according to the grading system described [19].

All samples were obtained after informed consent under protocols approved by the Institutional Review Board at EVMS and Research Ethics Committee of the LGI and licensed by the Human Fertilisation and Embryology Authority (U.K.). Permission was also granted by the ethics commission of the Free University Berlin, allowing the use of the generated RNA samples in Germany. Samples were washed in phosphate-buffered saline, lysed, and stored at −80°C in 50 μl Dynal lysis buffer (Dynabeads, Dynal Biotech, Bromborough, Wirral, UK, http://www.dynalbiotech.com) supplemented with 10% RNAlater (Ambion, Austin, TX, http://www.ambion.com).

cDNA samples were derived from duplicate intact blastocysts. The TE and the ICM of the human blastocyst were generated as follows: 10 pronucleate embryos were cryopreserved and, after thawing, cultured for up to 6 days in sequential medium (Irvine Scientific, Santa Anna, CA, http://www.irvinesci.com). At the blastocyst stage, the embryos underwent immunosurgery to separate the TE and ICM [20]. Unhatched blastocysts were exposed briefly to acidified Tyrode's medium (Irvine Scientific) for removing the zona pellucida. They were exposed to a rabbit antiserum raised against the BeWo trophoblastic cell line (Atlantic Antibodies, Windham, ME) and subsequently incubated with guinea pig complement (GIBCO, Grand Island, NY, http://www.invitrogen.com). Degenerated TE cells were separated from the ICM by pipetting through a finely drawn Pasteur pipette. The isolated ICM cells were washed three times in fresh medium and checked microscopically for the absence of adhering TE cells before being added to a tube containing 50 μl of RNAlater. The lysed TE cells, together with the microdroplet of medium, were also collected, washed, and transferred to separate tubes for analysis. Samples were stored for 1 month at −80°C before shipping to the U.K.

cDNA Amplification and In Vitro Transcription

T7 promoter–linked double-stranded cDNA samples derived from ICM, TE, and intact blastocysts were generated according to published protocols [21]. Briefly, mRNA was extracted from thawed lysed cells using Oligo-dT magnetic beads (Dynabeads). cDNA was generated using T7 promoter–linked oligo-dT primers for the reverse transcription (RT) step, and whole-transcriptome amplification was executed using a modified SMART amplification protocol (BD Biosciences, San Jose, CA, http://www.bdbiosciences.com). Amplified RNA was generated using the MegaScript T7 High Yield Transcription kit (Ambion). RNA purity, integrity, and concentrations were evaluated on the Agilent 2100 Bioanalyzer.

Direct Labeling of RNA and Hybridizations

Minimum Information About Microarray Experiments (MIAME) guidelines were adhered to in our experimental design [22].

Four independent labeling (including dye swaps, i.e., Cy3 and Cy5) reactions per an RNA sample (ICM, TE, and intact blastocyst) were carried out using 3 μg aRNA per reaction. Direct incorporation of Cy3 and Cy5 during RT was carried out in a 20-μl reaction volume using 1 μg of a random hexamer primer. Purification of labeled cDNAs, hybridizations, slide washes, and capturing of fluorescence images are described in detail in the online supplemental methods.

Data Analysis

Data normalization was carried out as described previously [23]. Gene expression was judged according to the comparison with a negative control sample (full details in the online supplemental methods).

For each cDNA, we performed statistical tests based on the replicate signals in experiments with ICM and TE samples. This was done for the two blastocysts separately. Three standard tests were used in parallel—Student's t-test, the Welch test, and Wilcoxon rank sum test [24]. To evaluate differential expression of the genes, p values of Wilcoxon rank sum test were preferred as a reference because this test does not depend for its validity on a specific distribution (e.g., Gaussian). A recursive function was implemented for calculating the exact p values.

Pathway Analysis

Array data were used to test whether specific pathways showed differential expression. Pathways were taken from the KEGG database. Consider for each pathway i the set of related genes (xil, yil),...,(xmath image, ymath image). Here, xij, yij denotes the expression level of the j-th gene in TE and ICM, respectively. Wilcoxon matched-pairs signed rank test was used to calculate a Z-score for the differences dij = xij − yij for each pathway i. These differences were ranked, and the ranks of differences with negative signs,Rneg, and those with positive signs,Rpos, were summed. The test statistic is the smaller of the two numbers, R = min{Rpos, Rneg}. If the pathway is not affected by the treatments, Rneg and Rpos will be fairly equal, but if there is a trend of underexpression or overexpression, the test statistic will be small. The Z-score is defined as

  • equation image

where E is the expectation and Var is the variance of R. These were calculated as

  • equation image

respectively [25].

Real-Time Reverse Transcription–Polymerase Chain Reaction Analysis

This was carried out for a set of genes on the ABI PRISM 7900HT Sequence Detection System (Applied BioSystems, Foster City, CA, http://www.appliedbiosystems.com). Full details of the experimental set up and list of primers, annealing temperatures, and genes under investigation are shown in supplemental online Table 10 and in the online supplemental methods.

Functional Annotation of Expressed Genes

We used the gene ontology (GO) terminology related to Ensembl version 3.0 to characterize the following subsets of our expression data: All, all genes on the array; TE, all genes highly expressed in the TE (>0.9); ICM, all genes highly expressed in the ICM (>0.9),and BL, all genes highly expressed in the blastocyst (>0.9).

The GO vocabulary was taken from the Gene Ontology Web site in May 2004 (http://www.geneontology.org). This was imported into the sqlite database (http://www.sqlite.org). Data analysis was carried out using the R-Statistics software (http://www.r-project.org). We have developed a web application on our Goblet webserver (http://goblet.molgen.mpg.de/blastocyst) that allows users to view genes based on their expression pattern or on their GO annotation.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Validation of Messenger RNA Isolation and Amplification

Using a modification of previously described protocols [21], we have generated microgram amounts (106-fold amplification) of amplified RNA (aRNA) from isolated mRNAs from duplicated sets of ICM, TE, and intact blastocysts from separate individuals. Similar protocols have been used to generate microgram amounts of aRNA needed for expression profiling [2628]. To verify the success of immunosurgery, mRNA isolation, and subsequent in vitro transcription to generate enough aRNA for hybridizations, gene-specific RT-polymerase chain reaction (PCR) was performed for previously established markers of both ICM and TE (Figs. 1A–1C). The transcription factors OCT4, NANOG, REX1/ZFP42, and SOX2 and the gene encoding the signal transduction adaptor protein, DAB2, are overexpressed in the ICM. During mouse preimplantation development, Oct4, Nanog, and Dab2 are required in vivo and in vitro for the establishment and maintenance of the pluripotent ICM in blastocysts and in cultured ES cells [16, 2832]. All of the ICM-enriched transcripts shown in Figure 1C have been designated as stemness genes [210]. Trophoblastic-determining genes HCG/CGB5, KRT18, HAND1, PSG3, CDX2, and TBX1 [33] were enriched in the TE samples. Among these genes, the transcription factor Cdx2 has been shown to be instructive for TE differentiation during mouse preimplantation development [34]. Having satisfactorily established that the pools of the TE and ICM aRNA samples do indeed reflect the transcriptomes of these cells, we proceeded to carry out whole-genome expression analysis. Transcription profiles were generated by using a cDNA microarray (Ensembl Chip) consisting of 15,529 resequenced and annotated clones.

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Figure Figure 1.. Isolation of ICM and TE cells, RNA amplification, and expression of known ICM and TE markers. (A): Photograph of ICM cells isolated by immunosurgery. (B): RNA amplification of cells derived from duplicate sets of ICM, TE, and intact blastocysts, with RNA size standard shown to the left. (C): Confirmation of expression of known ICM/ES and TE markers. β-ACTIN and GAPDH are used as endogenous controls. Abbreviations: ICM, inner cell mass; TE, trophectoderm.

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The reproducibility of amplification and subsequent hybridizations between replicates were assessed by calculating Pearson correlation coefficients (supplemental online Fig. 1). The values indicate a high degree of reproducibility in mRNA isolation, amplification, and array hybridization.

Expression Profiling Distinguishes ICM from TE

ICM and TE cells were isolated from two blastocysts from different individuals. Four independent hybridization experiments were performed for each biological replicate, including Cy-dye swaps. Additionally, RNA from two blastocysts was pooled to generate a reference sample. An overview of comparative gene expression in ICM and TE cells is shown in Figure 2A and reveals as expected a high overall correlation between the data (0.90), which helps to validate them. To judge whether a given gene is expressed in these cell types, we compared its signal against a negative control sample and computed a numerical value to judge gene expression (BG-tag; see Materials and Methods). This number reflects the proportion of background noise in relation to the actual signal [23]. Typically, a BG-tag of 0.9 indicates a detectable signal for the probe (Fig. 2B). Using this criterion, we found that 7,481 (48%) genes represented on the chip (probes) were detected in one of the three cell types (ICM, TE, or blastocyst). As demonstrated in Figure 2B, most of these genes are either specific to the intact blastocyst (2,880) or common to all three cell types (2,031). The number of genes that are expressed exclusively in the immunosurgically isolated ICM or TE is rather low (292 and 345, respectively).

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Figure Figure 2.. Global statistics. (A): Regression analysis revealed a global correlation (r) between mean TE (X-axis) and ICM (Y-axis) signals of 0.90, representing 4,601 probes corresponding to expressed genes, i.e., mean BG >0.9 in TE or ICM. There was no general trend in overexpression and underexpression. The box shows the regression parameters for the linear regression model y = 1.01x + 0.19. The lines show the twofold (blue) and fourfold (magenta) boundaries, and the signal range was approximately three orders of magnitude. (B): Venn diagram. Probes expressed in the different tissues. Expression was judged by signal detectability using a negative control sample present on each array. The average proportion of negative sample that is expressed below the probe's signal threshold across the replicate experiments indicates the detectability (BG value). An illustration with spots with different BG values shows that the level correlates with visual detectability. A BG level of 0.9 was used to judge expression of genes. (C): Global cell–type clustering. Principal component analysis (PCA) on approximately 600 preselected genes revealed no separation between biological replicates but rather between cell types, i.e., TE-1 and ICM-1 in blastocyst 1 and TE-2 and ICM-2 in blastocyst 2, and the pool of the two other blastocysts. The small image shows the same effect with a hierarchical clustering of the cells performed with approximately 8,000 genes using Pearson correlation as pairwise similarity measure and average linkage as an update rule. (D): Cell-type clustering using ICM- and TE-specific markers. PCA and hierarchical clustering on the set of 78 markers shows a clear biological separation across the individual blastocysts. Cluster analysis and PCA were generated with the J-Express Pro software (http://www.molmine.com). Abbreviations: BL, pool of two entire blastocysts; ICM, inner cell mass; TE, trophectoderm.

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Although these global statistics might point to trends in overexpression and underexpression of genes, it should be noted that, globally, the differences between ICM and TE are not large enough to account for the variance in biological replicates. For example, if we apply standard statistical procedures, such as principal component analysis (PCA) and hierarchical clustering for grouping the biological replicates using a large unfiltered set of genes, we observe that the clustering result reflects technical reproducibility rather than biological characteristics (Fig. 2C). To specifically address biological significance, the two blastocysts were analyzed separately. This was accomplished by comparing the TE and ICM replicates pertinent to each blastocyst using statistical tests for differential expression (see Materials and Methods). Three distinct tests in parallel (Student's t-test, Welch test, Wilcoxon rank sum test) were used to help overcome individual bias [24]. By adopting this approach, a subset of 78 candidate marker genes was identified, consisting of genes that are differentially expressed in ICM and TE (within one of the blastocysts) at the 0.05 level of significance. Of these 78 genes, 23 (29%) were completely novel and 17 were common to both blastocysts. By repeating the PCA and clustering analysis using these genes, we observed a clear biological separation of ICM and TE across the biological replicates (Fig. 2D).

These newly identified genes may complement existing markers for ICM and TE, such as OCT4 and CDX2 (Figs. 1B, 3A, 3B) and represent diverse biological functions. For example, the TE marker SFN (stratifin) is an epithelial cell antigen, which is exclusively expressed in keratinocytes. Its role in cell proliferation and apoptosis suggests that the protein could be relevant to the regulation of growth and differentiation of multiple cell types through the protein kinase C signaling pathway [35]. Among the putative ICM markers, HMGB1 and GLTSCR2 have been identified as potential stemness genes based on expression studies in the human ES lines HSF-1, HSF-6, and H9 [10]. HMGB1 is a member of the high-mobility group of transcription factor–encoding proteins that act primarily as architectural facilitators in the assembly of nucleoprotein complexes, as in the initiation of transcription of target genes. Murine Hmgb1 has been shown to be a coactivator of Oct4 [36]. GLTSCR2 is a gene of unknown function residing in the glioma tumor suppressor region of chromosome 19q. Of the proposed list of stemness genes [4, 5, 12], only ITGA6 (integrin alpha 6 chain) appeared in all the stem cell lines analyzed, but by comparing this list with our ICM markers, we have also identified ITGA5 as another candidate for stemness. These findings highlight the potential importance of integrins in cell adhesion as well as in cell surface–mediated signaling for establishing and maintaining pluripotency.

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Figure Figure 3.. Validation of selected markers. (A): Hierarchical clustering of the 78 markers shows biological separation of TE and ICM. For each cDNA, the log-ratio (base 2) of the signal intensity and the mean intensity across all five different samples were calculated. Samples were ICM and TE from two blastocysts (ICM-1 and ICM-2, TE-1 and TE-2) and a pool of two intact blastocysts. Clustering shows a clear separation of the biological material. Two large groups are obtainable, ICM-overexpressed genes (lower part of the dendrogram) and TE-overexpressed genes (upper part). (B): Real-time polymerase chain reaction confirmation of array-derived expression ratios in duplicate TE and ICM samples derived from blastocysts 1 and 2. Array-derived ratios are denoted as BL1 (yellow) and BL2 (light blue) and real-time ratios as BL1 (dark blue) and BL2 (violet). The genes IPL and OCT4 were not on the chip. Because ratios were presented as log-ratio (base 2), values above zero denote TE >ICM expression whereas values under zero indicate ICM >TE expression. The data represent averages from four independent hybridization experiments and triplicate reverse transcription–polymerase chain reactions. (C): Box-plots. Four independent experiments, including a dye swap, were performed for each cell type in both of the blastocysts (TE-1, TE-2, ICM-1, ICM-2). Boxes show the range of the two inner replicates; the whiskers extend to the minimum and the maximum within each sample. The line displays the median value. Abbreviations: BL, pool of two entire blastocysts; ICM, inner cell mass; TE, trophectoderm.

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The expression levels obtained from microarrays were verified independently for selected markers using real-time PCR (Fig. 3B). For example, ATP1B3, a Na+/K+-ATPase, is overexpressed approximately threefold in TE, thus reflecting the roles played by these ATPases in driving transepithelial Na+ and fluid transport for blastocoele formation [37]. Another ICM marker, HMGB1, is also overexpressed to the same degree. Unexpectedly, the ribosomal proteins RPL14, RPL7A, RPL19, and RPL32 were identified as ICM-specific markers, corroborating previous findings implying that some large subunits of ribosomal proteins are stem cell markers [210] and that these proteins might bind and inhibit the translation of specific mRNAs.

The full sets of data for global gene expression in the duplicate ICMs, TEs, and pooled blastocysts are presented (supplemental online Table 1). In general, the magnitude of expression recorded after RT-PCR was greater than from microarrays, an observation that is consistent with previous findings [4, 26].

Functional Annotation of Expressed Genes

The GO vocabulary provides a unified terminology for the description of genes and their products [38]. It is divided into three main categories: Molecular Function, Biological Process, and Cellular Component. A comparative analysis of these three categories at a global level within the ICM, TE, and intact blastocyst did not reveal a bias toward a particular category in these cell types (data not shown). In contrast, by repeating this analysis on Molecular Function using the 78 marker genes, 51 of which have GO annotations, we observed a slight bias toward specific molecular functions within ICM and TE cells (Fig. 4). For example, the ribosomal proteins RPL14, RPL7A, RPL19, and RPL32, under structural molecular activity (GO:0005198), are all expressed in the ICM (Fig. 4A). A more detailed description of these markers with respect to their chromosomal localization and ontology is presented (supplemental online Table 2). For a global overview, we combined the expression data from the ICM, TE, and intact blastocysts to create a database for searching for expression levels and related GOs (http://goblet.molgen.mpg.de/blastocyst).

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Figure Figure 4.. Functional annotation of ICM and TE marker genes. (A): Distribution of the genes with respect to the molecular function (GO:0003674) of the gene product. The terms under “obsolete function” are those that have been removed from the active function ontology by the GO curators. Full details of the obsolete lineages can be viewed in online supplemental Table 2. (B): Distribution of genes within the lineages of molecular function (GO:0005488) defined as having binding activity. A high proportion of genes bind to nucleic acids, i.e., transcription factors, chromatin, and RNA binding proteins. (C): Distribution of genes within the lineages of molecular function (GO:0003824) defined as having catalytic activity. Abbreviations: GO, gene ontology; ICM, inner cell mass; TE, trophectoderm.

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Developmentally Conserved Signaling Pathways

During embryogenesis, the specification and proper arrangement of new cell types require the coordinated regulation of gene expression and precise interactions between adjacent cells. These morphogenetic changes depend on the interaction of extracellular ligands with their receptors.

Delineation of signaling pathways will be fundamental for understanding the mechanisms regulating pluripotency and self-renewal in cultured ES cell lines. We searched the ICM and TE data for components of these pathways by assigning p values using Wilcoxon matched-pair signed rank test, as described in Materials and Methods. This strategy is distinct from the commonly used strategy for identifying differentially expressed genes using repeated measurements with a two-sample location test, such as Student's t-test or Wilcoxon rank sum test, because we directly involve groups of genes associated with particular pathways instead of conventional gene-wise analysis. The data indicate the involvement of WNT, mitogen-activated protein kinase (MAPK), transforming growth factor-β (TGF-β)/bone morphogenic protein (BMP), NOTCH, integrin-mediated cell adhesion, apoptosis-signaling pathways, and metabolic processes such as glycolysis, sterol biosynthesis, androgen, and estrogen metabolism. The full list of signaling and metabolic pathways identified by these analyses is in Table 1 and supplemental online Table 3. Pathway annotations were adopted from the KEGG (Kyoto Encyclopedia of Genes and Genomes; http://www.genome.jp/kegg) database.

Table Table 1.. Analysis of metabolic and signaling pathways operative in the blastocyst
  1. a

    Abbreviations: ICM-up, inner cell mass upregulation; TE-up, trophectoderm upregulation.

IDPathway description# GenesZ-ScorepvalueTE-upICM-up
hsa04010Mitogen-activated protein kinase signaling pathway1315,6948426,19205E-099734
hsa00500Starch and sucrose metabolism434,9869553,07171E-07358
hsa04310Wnt signaling pathway724,6296471,83341E-065418
hsa00632Benzoate degradation via coenzyme A ligation363,9276444,29089E-05306
hsa03010Ribosome443,7928137,45E-05935
hsa00562Inositol phosphate metabolism313,7821337,77705E-05247
hsa04620Toll-like receptor signaling pathway323,6836910,000114972248
hsa00561Glycerolipid metabolism613,6452590,0001335954615
hsa00350Tyrosine metabolism293,6002630,000158985227
hsa00280Valine, leucine, and isoleucine degradation283,5751130,000175077244
hsa04510Integrin-mediated cell adhesion373,5377340,00020183289
hsa04610Complement and coagulation cascades383,4877970,000243554308
hsa00340Histidine metabolism243,3142860,000459445213
hsa00380Tryptophan metabolism473,2593050,0005584893710
hsa04070Phosphatidylinositol signaling system303,2189450,000643379228
hsa00760Nicotinate and nicotinamide metabolism323,2162180,0006495242210
hsa00903Limonene and pinene degradation173,0533080,001131736161
hsa00230Purine metabolism702,9992440,0013533214921
hsa00480Glutathione metabolism122,9809650,001436777111
hsa00071Fatty acid metabolism312,9394820,001643875256
hsa04110Cell cycle542,9317790,00168523915
hsa00361Gamma-hexachlorocyclohexane degradation272,931050,00168916234
hsa00600Sphingoglycolipid metabolism362,9221670,001738093279
hsa04350Transforming growth factor-beta signaling pathway392,8328650,0023067062811
hsa00650Butanoate metabolism262,7810790,002708986215
hsa00240Pyrimidine metabolism432,7651640,0028447663013
hsa00910Nitrogen metabolism122,7456260,003019833102
hsa00590Prostaglandin and leukotriene metabolism132,6905980,003566252112
hsa00360Phenylalanine metabolism152,6126240,004492541132
hsa00450Selenoamino acid metabolism142,5424480,005503972113
hsa00220Urea cycle and metabolism of amino groups152,4990320,006226668132
hsa00790Folate biosynthesis112,4895040,00639608692
hsa00640Propanoate metabolism142,4796710,006575193113
hsa00310Lysine degradation332,4568270,007008514276
hsa05010Alzheimer disease212,4156570,007853421174
hsa00563Glycosylphosphatidylinositol (GPI)–anchor biosynthesis152,385440,008529342132
hsa00020Citrate cycle (TCA cycle)162,3786030,008689179115
hsa00300Lysine biosynthesis72,3664320,00898022270
hsa00626Nitrobenzene degradation72,3664320,00898022270
hsa00642Ethylbenzene degradation72,3664320,00898022270
hsa00860Porphyrin and chlorophyll metabolism132,3411690,009611712103

Such explorative approaches have also been used by means of expressed sequence tag and array data generated from undifferentiated and differentiated human ES cells [8, 39] and array data relating to mouse preimplantation development [27, 28].

Apoptosis in the Mammalian Blastocyst

Regulation of cell population size and lineage determination is mediated by cell cycle control, differentiation, and programmed cell death or apoptosis. The latter is characterized by chromatin condensation, nuclear membrane blebbing, and fragmentation in the cytoplasm and nucleus [40].

Apoptosis is evident at the blastocyst stage, if not earlier. It is mainly restricted to the ICM to regulate the size of the cell mass and perhaps to eliminate cells retaining the potential to form TE ectopically [41]. A list of expressed genes involved in the apoptosis signaling pathway is provided in supplemental online Table 4.

NOTCH Signaling in the Blastocyst

Cell–cell signaling mediated by the Notch receptor determines cell fate and regulates pattern formation in many phyla. The Notch signaling pathway is operational in both the ICM and TE and is known to function in the mouse blastocyst [27]. We observed expression of several ligands and receptors in this pathway (supplemental online Table 5), consistent with a mouse model in which Wnt and Notch act sequentially to set up the initial asymmetry in the zygote and thus influencing polarity of the developing embryo [27].

TGF-β Signaling

The TGF-β family consists of multifunctional growth and differentiation factors regulating many cellular processes through complex signal-transduction pathways. The family members include TGF-β isoforms, activins, and BMPs. Expression of the signaling type I and type II receptors for TGF-β in mouse and human fertilized oocytes and blastocysts suggested a role for TGF-β in early preimplantation development, potentially in the outgrowth of parietal endoderm [42]. Differential expression of TGF-β isoforms, activins, BMPs, and MADHs/SMADs was also evident. In particular, BMP4, previously shown to induce the differentiation to trophoblast when overexpressed in human ES cells [43], is 2.28-fold enriched in the TE. Other components of the TGF-β signaling cascade are shown (supplemental online Table 6).

Integrin and Cadherin-Mediated Cell Adhesion

The ICM and TE originate from the division of polar blastomeres when their cleavage furrows parallel their apical surfaces. These blastomeres polarize in response to asymmetric cell-cell contact. Pathway analysis identified signaling pathways related to integrin-mediated cell adhesion. In addition, several Na+/K+-ATPases (e.g., ATP1B3; Fig. 3B) were overexpressed in TE, reflecting their presumptive roles in driving fluid transport across this epithelium. Other cell adhesion–related genes were also detected, as expected where intercellular junctions are important for controlling blastocyst permeability [44]. However, there was overexpression in the TE of a subset of these genes, including Desmocollin 2 (DSC2 x1.55), Protocadherins (PCDH7 x1.67, PCDH11 x1.57, PCDHB7 x1.62), E-cadherins (CDH19 x1.9, CDH24 x1.54, CDH22 x1.82), tight junction proteins (TJP1 x1.4, TJP2 x1.8), Claudins (CLDN2 x1.4, CLDN16 x1.79, CLDN10 x2.25), and seven-pass transmembrane receptor of the cadherin superfamily (CELSR2 x1.46). For the tight junction constituents OCLN (occludins), JAM-2, (Junction adhesion molecule 2), and CGN (Cingulin), a lack of overexpression in the TE may be due to the fact that translational rather than transcriptional control is operative due to cell contact symmetry [44]. A comprehensive listing of these genes and their expression ratios is given in supplemental online Tables 1 and 7.

WNT Signaling in the Blastocyst

The WNT gene family consists of numerous conserved glycoproteins that regulate pattern formation during embryogenesis in a wide variety of tissues, including the nervous system. It has recently been shown that activation of the canonical WNT/Wnt pathway is sufficient to maintain self-renewal of both human and mouse ES cells [45] and also that this pathway is operative during human and mouse preimplantation development [21, 27]. We detected differential expression of transcripts encoding WNT ligands (WNTs), receptors of the Frizzled gene family (FZD), Frizzled-related protein family (SFRP), and intracellular signal transducers and modifiers (DVL1, AXIN). The genes encoding Casein kinase 1 alpha (CSNK1A), disheveled activator of morphogenesis 1 (DAAM1), which are agonists of the WNT pathway, are both overexpressed in the TE (Supplementary Table 8). These agonists were upregulated in differentiated ES cells [39]. In addition, we found that GSK-3B (glycogen synthase 3 kinase) expression is downregulated in the ICM, thus corroborating the reported inactivation of GSK-3B, which leads to the activation of the WNT pathway in maintaining the undifferentiated state of ES cells [45].

MAPK Signaling Pathway

The MAPK pathways regulate cell growth, differentiation, proliferation, and death. All members of the MAPK pathway have been shown to be expressed during mouse preimplantation development [46]. Differential expression of the various genes involved is shown in supplemental online Table 9.

Epigenetic Regulation of Lineage-Specific Gene Expression

De novo methylation of DNA by cytosine-5-methyltransferases is a well-characterized mechanism of epigenetic transcriptional control, and it has been shown that this mode of transcriptional control may contribute to the differentiation of the ICM and TE at the blastocyst stage [47]. Dnmt3b protein is specifically localized in the ICM of mouse blastocysts [48]. In addition, expression of DNMT3B and DNMT3A is enriched in undifferentiated human embryonic stem cells [810, 49] as well as in the ICM cell lineage (Fig. 1C). This expression pattern suggests an important role in ICM-specific methylation in the blastocyst [47]. In contrast, transcripts of DNMT3L were expressed in both ICM and TE (Fig. 1C). We also detected differential expression of several methyltransferases (supplemental online Table 1).

Other epigenetic regulators of X-inactivation, imprinting, maintenance of pluripotency, and the establishment of the TE lineages, including EZH2 (enhancer of zeste homologue 2), EED (embryonic ectoderm development), and CTCF (CCCTC-binding zinc finger protein), are expressed at high levels in the blastocyst and all ICM and TE samples [5052].

Imprinting

Several imprinted genes (H19, GRB10, SNURF, MEST, NAP1, UBE3A, DLX5, MAGEL2, OSBPL5/OBPH1, and ATP10A) were expressed at medium to high levels (BG-tag 70% to >90%) in the ICM, TE, and blastocyst. Our strict criteria for determining statistically significant differential expression between ICM and TE based on the microarray data may occasionally obscure more subtle differential expression patterns that are revealed when assayed by alternative methods. Real-time PCR identified a clear TE-biased (30-fold higher) expression for the imprinted gene IPL (imprinted in placenta and liver) (Fig. 3B). Significantly, IPL/PHLDA2 is a marker of human cytotrophoblast and in the mouse Ipl restricts placental growth [53]. Thus, such imprinted genes that can act as regulators of nutrient supply at the feto-maternal interface may also influence growth and development of the early embryo.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

This is the first report of gene expression in the ICM compared with TE cells from human blastocysts obtained after immunosurgery. Obtaining molecular profiles at the primary stage of differentiation during human embryogenesis has required extensive internal and external validation because only minute amounts of RNA from a few score cells were available in each specimen. Considering the potential sources of biological and technical variation, the results were surprisingly consistent, and the immunosurgery had evidently not caused significant degradation of RNAs from either compartment of the blastocyst. The results were also compared with global reference data obtained from intact blastocysts. There were minor differences in expression profiles between intact blastocysts and the ICM or TE cells, which might be accounted for by loss of primitive endoderm or even blastocoelic fluid, although studies in the mouse have indicated that total loss of endoderm is unlikely [54]. Major factors that could have contributed to the variabilities in the number of genes detected as expressed in the intact blastocysts and isolated ICM and TE cells include the cryopreservation and immunosurgical procedures adopted in this study. Although these procedures have been shown to affect the normal pattern of gene expression in preimplantation embryos [55, 56], we must stress that both studies were based on RT-PCR analysis on single genes and therefore are not conclusive. Additionally, although blastocysts have high implantation potential, there may well be considerable variability as a result of slight differences in maturity and competence [49].

The molecular profiles were consistent with expectations based on experimental mammalian embryology and were predictive of cellular physiology. For example, transcripts representing integrin- and cadherin-mediated cell adhesion, MAPK, and other gene products involved in the cell cycle and in apoptosis were identified. These components were anticipated in view of the rapid growth and dynamic morphogenesis of embryos at this transitional stage. Likewise, molecules representing pathways for glucose and sterol biosynthesis were also unsurprising. Absentees were presumably the less-abundant transcripts from these pathways.

The most interesting and potentially significant findings were among the representatives of key signaling pathways. Members of the WNT, TGF-β/BMP, NOTCH, and phosphatidylinositol 3-kinase pathways were found. These genes are likely to be finely regulated to determine cell fate, adhesion, and migration because when expression goes awry, stem cells may undergo malignant transformation [57]. The expression of OCT4 and NANOG is already established as a marker of pluripotency, but there were other genes that were expressed in a similar temporal and spatial pattern. It will be important to investigate whether these genes are candidate markers of the ICM and their role in maintaining an undifferentiated state.

Perspectives

These data provide a reference for both normal development of the blastocyst in vivo and in vitro and for derivatives of the ICM and TE. Many human blastocysts generated in vitro fail to implant after transfer to a receptive uterus, and not all ICMs give rise to competent ES cell and trophoblastic stem cell lineages in culture. Markers of pluripotent stem cells are valuable tools for predicting cellular phenotype and are needed for advancing ES cell technology. Identification of other molecules that have roles in intracellular signaling is critical for the control of cellular differentiation and fate. This knowledge is critical for the key goal of directing the differentiation of stem cells or maintaining them as proliferating populations of pluripotent precursors, and preferably without feeder cell layers [45]. Some genes that are regulated epigenetically evidently have an unstable imprinting status, and research to safeguard the health of children born after assisted reproductive technologies must carefully assess the impact of culture conditions on the expression of these genes in preimplantation embryos [58]. Thus, there are many reasons why the molecular profiles of the ICM and TE cells in the human blastocyst are valuable, and, in the long term, they carry implications for fertility, reproductive health, and the prospects of stem cell–based technologies for treating human diseases.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We are grateful to the microarray support staff, the German Resource Centre for Genome Research (RZPD, Berlin) for the clones, and Wasco Wruck for the image analysis. This work was funded by the German Ministry for Education and Research (BMBF) as part of the National Genome Research Network (NGFN) and the European Union under Framework 6 (LSHG-CT-2003-503269).

Disclosures

The authors indicate no potential conflicts of interest.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
SC050113SuppData.pdf61KSupplemental Data Legends
SC050113SuppFig.jpg382KSupplemental Figure
Adjaye_Suppl_Table1.xls10225KSupplemental Table 1
Adjaye_Suppl_Table_2.xls174KSupplemental Table 2
Adjaye_Suppl_Table3.xls35KSupplemental Table 3
Adjaye_Suppl_Table4.xls19KSupplemental Table 4
Adjaye_Suppl_Table5.xls10KSupplemental Table 5
Adjaye_Suppl_Table6.xls18KSupplemental Table 6
Adjaye_Suppl_Table7.xls18KSupplemental Table 7
Adjaye_Suppl_Table8.xls23KSupplemental Table 8
Adjaye_Suppl_Table9.xls31KSupplemental Table 9
AdjayeSuppMethods.pdf49KSupplemental Methods
Adjaye_SuppLegends.pdf49KSupplemental Legends
SC050113SuppFig1.pdf397KSupplemental Figure 1
Adjaye_Suppl_Table10.pdf50KSupplemental Table 10

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