Analysis of Oct4-Dependent Transcriptional Networks Regulating Self-Renewal and - 《stemcells》干细胞学杂志干细胞之家



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发表于 2009-3-5 00:58 |只看该作者 |倒序浏览 |打印

作者：Yasmin Babaiea, Ralf Herwigb, Boris Greberb, Thore C. Brinkb, Wasco Wruckb, Detlef Grothb, Hans Lehrachb, Tom Burdona, James Adjayeb作者单位：aRoslin Institute, Department of Gene Function and Development, Roslin, Midlothian, United Kingdom;bMax Planck Institute for Molecular Genetics, Department of Vertebrate Genomics, Berlin, Germany " x! @/ l# i$ G1 g
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      【摘要】
   The POU domain transcription factor OCT4 is a key regulator of pluripotency in the early mammalian embryo and is highly expressed in the inner cell mass of the blastocyst. Consistent with its essential role in maintaining pluripotency, Oct4 expression is rapidly downregulated during formation of the trophoblast lineage. To enhance our understanding of the molecular basis of this differentiation event in humans, we used a functional genomics approach involving RNA interference-mediated suppression of OCT4 function in a human ESC line and analysis of the resulting transcriptional profiles to identify OCT4-dependent genes in human cells. We detected altered expression of >1,000 genes, including targets regulated directly by OCT4 either positively (NANOG, SOX2, REX1, LEFTB, LEFTA/EBAF DPPA4, THY1, and TDGF1) or negatively (CDX2, EOMES, BMP4, TBX18, Brachyury , DKK1, HLX1, GATA6, ID2, and DLX5), as well as targets for the OCT4-associated stem cell regulators SOX2 and NANOG. Our data set includes regulators of ACTIVIN, BMP, fibroblast growth factor, and WNT signaling. These pathways are implicated in regulating human ESC differentiation and therefore further validate the results of our analysis. In addition, we identified a number of differentially expressed genes that are involved in epigenetics, chromatin remodeling, apoptosis, and metabolism that may point to underlying molecular mechanisms that regulate pluripotency and trophoblast differentiation in humans. Significant concordance between this data set and previous comparisons between inner cell mass and trophectoderm in human embryos indicates that the study of human ESC differentiation in vitro represents a useful model of early embryonic differentiation in humans.
      【关键词】 Human embryonic stem cells Inner cell mass Trophoblast Pluripotency RNA interference OCT CDX Microarrays
   INTRODUCTION" b, c" l/ z- J  I2 j# S
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The earliest differentiation event in the mammalian embryo occurs during formation of the blastocyst, when trophoblast cells delaminate away from a residual cluster of undifferentiated cells, the inner cell mass, containing the pluripotent embryonic founder cells .

The POU domain transcription factor Oct4/OCT4 is a critical regulator of pluripotency in the mammalian embryo and is expressed in unfertilized oocytes, the ICM and epiblasts of pregastrulation embryos, and in primordial germ cells .
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As an extension to our previous work  should provide additional insights into the molecular events that underlie the earliest differentiation event in the human embryo." u1 p6 N% Y8 s' j& \2 `% p% d" z# G
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MATERIALS AND METHODS# [- E) m  p. s  D3 V

Clone Selection and Microarray Fabrication/ z. }- J0 x- C6 b6 [, k  \
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The selection of the 15,529 cDNA clones and fabrication of the arrays was as previously described .2 B" h9 k, I8 N* c
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Cell Culture
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Human ESCs (H1 clone) were grown under feeder-free conditions as previously described . Cells were adjusted to dissociation with 0.5 mM EDTA in phosphate-buffered saline (PBS), applied to the cells at 37¡ãC for 5¨C10 minutes, and routinely passaged in this way. Cells were seeded 24 hours before transfections. For microarray analysis, small interfering RNA (siRNA) transfections were carried out in 75-cm2 flasks in triplicate for each siRNA duplex. Cells were seeded at approximately 5 x 106 cells per flask for analysis at 24 hours after siRNA transfection or approximately 2 x 106 cells per flask for analysis at 72 hours after siRNA transfection. For immunohistochemistry, transfections were carried out in six-well plates, and cells were seeded at 2 x 105 cells per well.

Transfections with siRNA
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siRNA duplexes were obtained from Dharmacon RNA Technologies (Lafayette, CO, http://www.dharmacon.com) and reconstituted following the manufacturer's guidelines. Sense strand sequences for the siRNA duplexes were as follows: enhanced green fluorescent protein (EGFP), AAG AAC GGC AUC AAG GUG AAC; OCT4¨C1, AAG GAU GUG GUC CGA GUG UGG; and OCT4-2, Dharmacon siGENOME duplex 1 (D-019591-05-0010).
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Triplicate ESC cultures were transfected individually with 80 nM siRNA duplexes using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, http://www.invitrogen.com) lipofection reagent prepared in OptiMEM (Invitrogen) following the manufacturer's instructions. The siRNA/Lipofectamine 2000 complex was added to the cells in the appropriate volume of ESC culture medium. Cells were fed with fresh culture medium 1 hour prior to transfection and following the removal of the transfection reagent. Cells were transfected once only for RNAi analysis after 24 hours. For RNAi analysis at 72 hours, cells were transfected twice; the second transfection was carried out 24 hours after the first transfection.
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Immunoblotting; w. ?4 ]4 t' f5 B

Cells were lysed and sonicated in 1% SDS buffer. Lysates were electrophoresed on 10% SDS-polyacrylamide gel electrophoresis gels and immunoblotted as described previously . SHP-2 (1:1,000; sc-280; Santa Cruz Biotechnology Inc., Santa Cruz, CA, http://www.scbt.com), OCT4 (1:1,000; sc-5279; Santa Cruz Biotechnology), SOX2 (1:1,000; sc-17320 X; Santa Cruz Biotechnology), NANOG (1:250; 1997; R&D Systems Inc., Minneapolis, http://www.rndsystems.com), and glyceraldehyde-3-phosphate dehydrogenase (1:5,000; 4300; Ambion, Austin, TX, http://www.ambion.com) antibodies were used. Secondary horseradish peroxidase-conjugated antibodies (Amersham Biosciences, Buckinghamshire, U.K., http://www.amersham.com) were used at a 1:5,000 dilution and detected with the enhanced chemiluminescence reagent (Amersham Biosciences).

Immunohistochemistry
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Cells were fixed with 100% methanol at ¨C20¡ãC for 10 minutes, washed once in PBS, and permeabilized in 100% ethanol at room temperature for 1 minute. Thereafter, the cells were washed twice in PBS and blocked in PBS containing 10% goat serum (Sigma-Aldrich, St. Louis, http://www.sigmaaldrich.com) for 1 hour at room temperature. Primary antibodies for OCT4 (sc-5279) and cytokeratin-18 (sc-6259) were purchased from Santa Cruz Biotechnology and used at 1:100 dilutions in PBS containing 1% goat serum. Alexa Fluor 568 anti-mouse IgG (Invitrogen) secondary antibody was used at a dilution of 1:400 to detect antibody binding. Coverslips were mounted in Mowial (Calbiochem, San Diego, http://www.calbiochem.com) solution with antifade supplemented with 4,6-diamidino-2-phenylindole nuclear stain. All light and fluorescence microscopy was carried out using a Nikon Microphot SA (Tokyo, http://www.nikon.com) microscope and camera., S4 m, R2 H( S2 v. u7 I

RNA Isolation and In Vitro Transcription

Total RNA was isolated using TRIzol reagent (Invitrogen) treated with DNase 1 (Promega GmbH, Mannheim, Germany, http://www.promega.com). Messenger RNA amplifications were carried out using the MegaScript T7 High Yield Transcription kit (Ambion) using 3 µg of total RNA as template. The purity, integrity, and concentrations of generated amplified RNA were evaluated using the Nanodrop Bioanalyzer (Nanodrop Technologies, Wilmington, DE, http://www.nanodrop.com/)./ ~) f) m$ G4 V% z9 l# N+ I/ d3 t

Direct Labeling of RNA and Hybridizations% R* g- R- T$ k
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MIAME (Minimum Information About Microarray Experiments) guidelines were adhered to in our experimental design. Three independent labeling (dye swaps, Cy3, and Cy5) reactions per antisense RNA sample pertaining to each biological replicate were carried out using 3 µg of aRNA per reaction. Full details of labeling and hybridization reactions, slide washing, and scanning have been described previously .8 b. D4 A  ?, h1 V0 A3 {- P/ w  a

Global Data Analysis/ ]4 {' |* {7 ]6 i9 E

Data were normalized in two steps. The first step accounted for the dye effects caused by the difference in Cy3/Cy5 fluorescence labeling in each experimental sample. Here we used the LOWESS method . A full description of the normalization process is detailed in the supplemental online Materials and Methods.
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Pathway Analysis$ T* l( h7 e! `2 N
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Array data were used to test whether entire groups of genes associated with specific pathways show differential expression. Pathways were taken from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (version KEGG2, 01.06.2005, http://www.genome.ad.jp/kegg/). The procedure has been described previously .5 X" G, A* V+ O. P* _
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Real-Time Reverse Transcription-Polymerase Chain Reaction Analysis
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Confirmations were carried out on a set of genes using RNA derived from the two independent OCT4 siRNA transfections. The list of primers used, annealing temperatures, genes under investigation, and experimental details are shown in supplemental online Table 5 and supplemental online Materials and Methods.

Identification of Conserved Downstream Targets of OCT4 in Mouse and Human ESCs- Y' w( p; i% h$ W

Genes differentially expressed 72 hours after OCT4 knockdown were selected from the raw microarray data set on the basis of four independent statistical tests (p value cutoff, .05) yielding sets of approximately 1,104 up- and downregulated genes. HUGO gene symbol IDs for these genes were checked for occurrence in the OCT4-specific target lists generated by Boyer et al. . The complete lists of direct and indirect targets are given in supplemental online Tables 6 and 7.! R5 c0 n' Y, i, e6 W) l- g; q
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Online Database
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To enable a global overview of altered gene expression at 24 and 72 hours post-transfection that can be interrogated, we have presented the expression data as a database for searching for expression levels of specific genes and their related gene ontologies (http://goblet.molgen.mpg.de/cgi-bin/stemcell/pluripotency.cgi). We used gene ontology terminology taken from the Gene Ontology website (http://www.geneontology.org). This was imported into the SQLite database (http://www.sqlite.org). Data analysis was carried out using R statistics software (http://www.r-project.org).

RESULTS0 C' F9 k! b0 |  b  c9 P1 n
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Depletion of OCT4 in Human Embryonic Stem H1 Cells Using siRNA Transfection
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To identify factors associated with early stages in human ESC and trophoblast differentiation, we have combined RNAi and microarray based expression profiling to analyze global changes in gene expression induced by suppression of OCT4 function. Triplicate H1 ESC cultures were transfected with either OCT4 or control EGFP siRNA oligonucleotides, and RNA samples were collected at 24 hours, when the very earliest changes in cell morphology resulting from Oct4 knockdown are first apparent, and at 72 hours, when the appearance of enlarged nuclei and flattening of cells predominates within the cultures (Fig. 1A, 1C, 1D). These morphological changes were accompanied by a reduction in the level of the protein as determined by Western blotting (Fig. 1B) and immunocytochemistry (Fig. 1C). In line with previous experiments, OCT4 siRNAs reduced OCT4 protein levels to less than 30% of the EGFP siRNA controls, consistent with transfection efficiency of more than 70% .
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Figure 1. Downregulation of OCT4 mRNA and protein in H1 human ESCs (hESCs) by small interfering RNA (siRNA) transfection. (A): Morphology of hESCs 72 hours after transfection with EGFP, OCT4 (1), and OCT4 (2) siRNA. (B): Western blot analysis of OCT4 protein levels in siRNA-transfected ESCs. Cell lysates prepared 72 hours from duplicate siRNA transfections were fractionated by SDS-polyacrylamide gel electrophoresis, immunoblotted, and probed with OCT4 and SHP-2 (control) antibodies. The reduction in OCT4 protein in OCT4 (1) and OCT4 (2) transfections was approximately 30% of the control EGFP transfection. (C): OCT4 expression in siRNA-transfected cells. Cells were fixed 72 hours after transfection, immunostained for OCT4, and counterstained with 4,6-diamidino-2-phenylindole (DAPI). (D): Cytokeratin 18 expression in siRNA-transfected hESCs. Cells were fixed 72 hours after transfection, immunostained for cytokeratin 18, and counterstained with DAPI. Abbreviation: EGFP, enhanced green fluorescent protein.. ?7 ]  D) b9 {% k

Global Expression Analysis' k2 [( H; i  _2 d8 f. a
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For each of three transfections harvested at 24 and 72 hours, triplicate RNA samples were labeled with either Cy3 or Cy5, including dye swap. Transcription profiles were then generated by using a cDNA microarray (Ensembl Chip) consisting of 15,529 resequenced and annotated clones. The overall correlations between the OCT4 and EGFP RNAi expression data were 0.993 (24 hours) and 0.943 (72 hours), indicating that the expression levels of the vast majority of genes remain unaltered by the procedures. To judge whether a gene is expressed in the respective cells, we computed a background (BG) tag for its signal. This number reflects the proportion of background signal lower than the actual signal . The vast majority of genes were either expressed at both time points (5,923 genes; 37.83%) or not expressed at all (8,178 genes; 52.23%). The full lists of genes expressed solely at 24 and 72 hours after transfection and also at both time points, together with the corresponding ratios, are presented in supplemental online Tables 1, 2, and 3, respectively. For a global overview of the transcriptional changes resulting from the loss of OCT4 function and insights into the physiological state of human ESCs (hESCs) resulting from OCT4 depletion, we combined the expression data at the 24- and 72-hour time points in an online database for interrogating the expression levels of specific genes and their related gene ontologies (http://goblet.molgen.mpg.de/cgi-bin/stemcell/pluripotency.cgi).

Figure 2. Global data analysis. (A): Effect of LOWESS normalization. Plotted are the ratios of the red and green signals for each spot (log scale, y-axis) and the signal range (log scale, x-axis) of a typical experiment. Whereas the raw data show a nonlinear bias in particular at the extremes of the signal area (top graph), after LOWESS normalization, this bias was eliminated (bottom graph). (B): Venn diagram of genes expressed at the different time points of OCT4 knockdown. Gene expression was judged by a numerical value (BG tag) computed from a negative control sample (bottom panel). (C): Cluster of genes that show expression patterns most similar to that of OCT4 across the experimental conditions. Colors correspond to normalized signals. For each gene, signals were divided by the average gene signal across all conditions (log scale). Red boxes indicate that the signal in the particular condition is higher than the average signal, whereas green boxes indicate the opposite. Hierarchical clustering was performed on 199 genes that showed high variation across the four conditions and a significant difference in the OCT4 and EGFP RNAis using Pearson correlation as a pairwise similarity measure and average linkage as an update rule. The analysis was done using J-Express Pro 2.6 software (MolMine AS, Bergen, Norway http://www.molmine.com). Abbreviations: BG, background; EGFP, enhanced green fluorescent protein; hrs, hours; RNAi, RNA interference.
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To identify genes with altered expression levels as a result of OCT4 knockdown, we compared the 24- and 72-hour replicates, with EGFP knockdown at the same time points using statistical tests for differential expression (described in Materials and Methods). Three distinct tests (Student's t test, the Welch test, and Wilcoxon's rank sum test) were used to minimize individual bias . Using an FDR level of 0.05 identifies 721 of the more than 1,104 genes as significant. However, it should be stressed that FDR assessment can also increase the false-negative rate. For example, ID2, a differentiation marker directly regulated by OCT4 (supplemental online Table 6; Fig. 3) and verified as significant by p value computation, was rejected by FDR assessment. At an FDR level of 0.1, all genes were marked significant.2 l( O2 Z1 d3 |* f, P

Figure 3. Confirmation of gene expression changes of selected genes by real-time PCR (A) and Western blotting (B). (A): SYBR green real-time reverse transcription-PCRs were carried out on RNA samples harvested 72 hours after OCT4 knockdown using two independent siRNA molecules in separate transfection experiments (designated siRNA 1 and siRNA 2). Error bars refer to technical variation. Ratios are represented as log ratio (base 2), with values above 0 denoting overexpression and values below 0 denoting repression of gene expression. (B): Western blots using duplicate samples of protein extract of the same set of transfection experiments. The specificities of the primary antibodies used are indicated on the left. Abbreviations: EGFP, enhanced green fluorescent protein; PCR, polymerase chain reaction; siRNA, small interfering RNA.

By comparing gene expression profiles from 24- and 72-hour-post-transfection samples, we selected genes that show changes in expression similar to those of the selected key genes OCT4, EOMES, and BMP4. The OCT4 hierarchical cluster is shown in Figure 2C and includes genes already implicated in the maintenance of pluripotency and self-renewal, such as NANOG; markers of undifferentiated stem cells LEFTY1, LEFTY2, DPPA4, and THY1; and novel genes.

To have an overview of negatively regulated downstream targets of OCT4, we repeated the profile analysis for EOMES and BMP4, respectively (supplemental online Figs. 1 and 2). EOMES encodes a T-box containing transcription factor expressed in the trophectoderm of human and mouse blastocyst and has been shown to be required for mouse trophoblast development and mesoderm formation . The critical trophoblast stem cell regulator CDX2 could not be been included in this analysis because the clone is not represented on our array. Nonetheless, real-time polymerase chain reaction (PCR) analysis showed that its expression is induced upon depletion of OCT4 (Fig. 3).! q- ]- S4 E6 L4 {
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Included in this set are genes implicated in ESC differentiation, such as (a) the transcription factors ID3, TBX18, GATA6, and HLX1  and may reflect the morphological changes seen upon differentiation of hESCs per se and adoption of trophoblast fate (Fig. 1A, 1D).) d2 G0 t4 S9 b" z) |: k. M" ~
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Expression patterns of a selection of the differentially expressed genes were verified independently using real-time PCR and Western blotting of samples prepared from cells transfected with either of two different OCT4 siRNAs (Fig. 3). The results shown in Figure 3A confirmed the downregulation of key pluripotency-controlling genes, OCT4, SOX2, and NANOG, and ES-associated genes LEFTY1, LEFTY2, TDGF1, DNMT3B, and ZFP42.6 A- D" b% V$ W- P( C! T# E

Expression of mesodermal (T/Brachyury) and ectodermal (PAX6) markers was also downregulated, re-emphasizing the lineage-restricted differentiation of OCT4-depleted cells. The induction of CDX2 is in agreement with results obtained in mouse and human ESCs .

Downstream Targets of OCT4) p4 f+ |# S! I5 ?& I- r- G" x
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Our experimental approach will identify both direct and indirect targets downstream of OCT4. To distinguish between these possibilities, we cross-checked the OCT4-regulated genes with the recently compiled set of transcription targets for OCT4, SOX2, and NANOG identified in hESCs using chromatin immunoprecipitation (ChIP) coupled to promoter microarrays and ChIP-pair end diTag (PET) using mouse ESCs .+ k- S" l" D! r$ r( A, t, a

The list of direct targets of OCT4 in ESCs is given in supplemental online Table 6. An additional 162 are bound by NANOG and/or SOX2 but not by OCT4, indicating that these are regulated indirectly by OCT4 through its regulation of these downstream effectors (supplemental online Table 7).
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In line with the finding that OCT4 regulates its own expression and that of other core hES transcription factors , are positively and negatively regulated, respectively, by OCT4 alone. Additional markers of undifferentiated stem cells identified as positively regulated direct targets were LEFTY2, DPPA4, and TDGF1, whereas ZFP42, LEFTY1, and FLJ10884 were classified as indirect targets. As anticipated, components of signal transduction pathways implicated in the maintenance of pluripotency, such as WNT (DKK1, FZD2), TGFß (NODAL, LEFTY1, LEFTY2, MADH3 ID2 and PITX2), FGF (FGF8 and FGF2), and Hedgehog (PTCH), are regulated by OCT4.0 O, `( I/ z$ D" g
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The remaining genes that are either up- or downregulated upon OCT4 knockdown but do not appear in the data sets of Boyer et al.  may represent either previously undiscovered novel OCT4/SOX2/NANOG targets or genes regulated by downstream targets of OCT4 other than SOX2 and NANOG or simply not included in the promoter analysis (supplemental online Table 4). Moreover, this set of genes would also be expected to include a large number of genes involved in trophoblast differentiation.; A' }7 `% n( ~" U) Y1 n

Signaling and Metabolic Pathways Crucial for the Maintenance of Pluripotency1 y, ?/ b" Y. F7 J- g' b

ESC self-renewal and pluripotency requires inputs from extrinsic factors and their downstream effectors . The analysis, summarized in Table 1, identifies changes in key components of the WNT, transforming growth factor (TGF)ß, fibroblast growth factor (EGF), mitogen-activated protein kinase, NOTCH, Hedgehog, JAK/STAT, and extracellular matrix signaling pathways, as well as regulators of the cytoskeleton, apoptosis, cell cycle, and metabolic processes, such as oxidative phosphorylation, methionine metabolism, and folate biosynthesis. The list of complete KEGG annotated pathways identified as operative in ESCs is given in supplemental online Table 8.

Table 1. Pathways of which gene components show significant expression changes between the OCT4 and EGFP knockdowns at 72 hours after transfection+ a% w+ ^+ k& ]- }! S  D

TGFß and BMP Signaling) }/ [6 o5 ~; R/ ]% l8 l

Consistent with recent reports identifying TGFß/ACTIVIN/NODAL signaling as critical for maintaining hESC pluripotency ./ Z! b4 ^0 R, J3 V. e- i

Figure 4. Comparative expression patterns of genes involved in the transforming growth factor-ß signaling pathway. The BMP and ACTIVIN/NODAL axes of the pathway are presented in (A) and (B, C), respectively. A sequential illustration of the pathways (adapted from the KEGG database) is given above each histogram. Genes within open boxes are those with background tags >0.9, and therefore their expression was deemed as not detected. Abbreviation: BMP, bone morphogenetic protein.) G) Z) y3 Z, a) B4 D8 w

FGF Signaling
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FGF signaling is known to play an essential role in preventing hESC differentiation , and reduced expression of the hESC autocrine factor FGF2 and FGF12 was observed on OCT4 knockdown (Figs. 3, 5A). In contrast, however, expression of FGF8 and the novel FGF-like receptor FGFRL1 was upregulated, indicating that hESC differentiation along the tro-phoblast lineage may involve complex modulation of FGF signaling. It may be significant that a potential NANOG binding site is identifiable within the FGF8 promoter (supplemental online Table 7)./ k5 [6 t5 p% N: Y8 V3 s& ~

Figure 5. Comparative expression patterns of genes involved in FGF (A), apoptosis (B), WNT (C), and NOTCH (D) signaling pathways. Abbreviations: FGF, fibroblast growth factor; FGFR, fibroblast growth factor receptor.
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WNT Signaling% d3 A0 V. V) ]6 P

The role of WNT signaling in human ESCs is controversial because of conflicting reports as to its role in ESC self-renewal , is downregulated (Fig. 5C). The presence of OCT4, NANOG, and SOX2 binding sites within the DKK1, FZD2, and FRAT2 promoters indicates that these WNT components are influenced directly by these key stem cell regulators (supplemental online Table 6).

NOTCH and Hedgehog Signaling# N, X) R# `4 b& X# T4 |
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Although both these pathways regulate the fate of many types of stem cells, there is currently little evidence for their involvement in controlling the fate of embryonic stem cells , is regulated by NANOG and SOX2 (supplemental online Tables 6 and 7). Analysis of Hedgehog (Hh) signaling components showed reduced levels of both PTCH1, a Hh receptor and target for SOX2 and NANOG (supplemental online Table 7), and the Hh-regulated transcriptional repressor GLI3.

Apoptosis5 M, M! B/ _3 Y: h! c* d3 W9 z3 x
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Efficient growth of undifferentiated ESCs (self-renewal) requires the inhibition of apoptosis, as well as differentiation ; we therefore screened the data set for differentially expressed apoptosis-related genes (Fig. 5B). Although expression levels of the pro- and antiapoptotic genes BCL2 and BAX did not change, genes encoding the DNA fragmentation factor (DFFA), the apoptosis-inducing factor (PDCD8), and CASPASE 3 were significantly downregulated, whereas NFKBIA and the calpains CAPN6, CAPN1, and CAPNS1 were upregulated on OCT4 knockdown.7 N: @  e) H- y1 b3 \! _

Epigenetic Control of Pluripotency and Trophoblast Lineage Specification
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Mutant mouse ESCs lacking DNA methyltransferase activity . The de novo methyltransferase DNMT3B was downregulated upon OCT4 depletion, contrasting with the maintenance methylase DNMT1, which showed no significant change. The, histone lysine methyltransferase (H3-K4-HMTase) SET7 was dramatically upregulated upon OCT4 knockdown, contrasting with downregulation of the histone lysine methyltransferase EZH2 (H3-K27-HMTase) (supplemental online Fig. 4B). The acetylases H2AFY and H2AFY2 and the deacetylase HDAC6 also show significant upregulation on OCT4 knockdown (supplemental online Fig. 4C, 4D). These expression patterns perhaps indicate that the hES-to-trophoblast transition is accompanied by significant changes in histone acetylation and methylation patterns.7 A% A" G5 w, Z  C+ T- {+ B& c: w
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The nonhistone chromatin-associated proteins HMGB1, HMGB3, DPPA4, NASP, chromatin assembly factor 1 (CHAF1A), PHF17, PHF5A, POLE3, and retinoblastoma binding protein 7 (RBBP7) are all significantly downregulated as a consequence of OCT4 depletion (supplemental online Fig. 4B). Of these, HMGB1, DPPA4, and HMGB3 have previously been shown to be highly enriched in undifferentiated stem cells and isolated ICM cells .7 ]0 w% O+ a* q8 l, Y7 B
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Interestingly, we also observed downregulated expression of PARP1 (Fig. 3), which encodes a chromatin-associated enzyme, poly(ADP-ribosyl) transferase, capable of modifying nuclear proteins. This DNA-dependent ribosylation has been shown to regulate cell proliferation, transformation, and differentiation .: I% G! e3 i, f. [( [+ S1 b

Altered expression of imprinted genes was also observed (upregulation of CALCR and GNAS and downregulation of KIP2 and UBE3A; supplemental online Fig. 4E). KIP2 (a cyclin-dependent kinase inhibitor) acts as a key regulator of embryogenesis through regulation of cell cycle by blocking the activity of G1 cyclin/Cdk complexes and the regulation of actin dynamics through binding to LIMK-1 .( Y4 t0 x6 T/ Q6 ]4 g

RNAi-Mediated Suppression of OCT4 Function in Human ESCs Recapitulates Primary Differentiation at the Blastocyst Stage of Development% n* i& K; F' \
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To examine how closely the transcriptomes of an ICM and trophectoderm (TE) cell matches that of an undifferentiated ESC and OCT4 RNAi-mediated trophoblast cell, we compared our current data set with that derived from the blastocyst . We identified potential candidate genes that were overexpressed in the TE- and OCT4-deficient ESCs compared with the ICM and undifferentiated ESCs when a cluster analysis of genes coregulated in the same manner as BMP4 was performed (Fig. 6). Genes upregulated in the TE- as well as the OCT4-depleted hESCs are involved in the organization of the extracellular matrix (PDLIM3), cell growth and differentiation (AKR1C3 and PLXND1), transcriptional regulation (PME-1, MGC11349/ZXDC, and KIAA1245/COAS1), signal transduction processes (ARL7, PIP5K1C, RASL12, ARHGAP8, SELM, and DKK3, an inhibitor of the WNT pathway), and novel genes (KIAA1949, C14orf173, and FLJ20507/TMEM127). We do not present detailed analysis of this data set here for the simple reason that the vast amount of data is beyond the scope of this study. In summary, these results would imply that these TE marker genes could serve as additional factors required for inducing trophoblast differentiation and further propagation of these cells.

Figure 6. Cluster analysis of 15 genes bearing expression profiles the most similar to that of the trophoblast marker BMP4. The comparison was made between this study and the previously published expression data on human ICM and trophectoderm cells . Colors correspond to normalized signals. For each gene, signals were divided by the average gene signal across all conditions (log scale). Red boxes indicate that the signal in the particular condition is higher than the average signal, whereas green boxes indicate the opposite. Hierarchical clustering displays subgroups using Pearson correlation as a pairwise similarity measure and complete linkage as an update rule. The analysis was done using J-Express Pro 2.6 software (MolMine AS). Abbreviations: EGFP, enhanced green fluorescent protein; ICM, inner cell mass; MAX, maximum; MIN, minimum; RNAi, RNA interference.

DISCUSSION# K$ W9 q, L& w) o6 x
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The first differentiation event in mammalian development is the formation of the trophectoderm; this event is controlled by antagonism between OCT4 and the trophoblast transcription factors CDX2 and EOMES . To begin dissecting the complex molecular events that underpin this event in humans, we adopted a functional genomics approach using RNAi to suppress OCT4 function in a human ESC line and microarray-based gene expression profiling. The quality of the data set was rigorously tested in several ways, including numerous statistical tests, achieving consistent reproducibility between replicates as measured by the coefficient of variations of intensity for each gene. The data set is therefore qualitative, quantitative, and comprehensive.
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Our microarray analysis shows that OCT4 knockdown in hESCs is accompanied by a reduction in overall complexity of gene expression and differential regulation of more than 1,000 genes, many of which are consistent with a loss of pluripotency and specification of the trophoblast lineage. Among the differentially expressed genes, 60 correspond to direct OCT4 targets identified in human ESCs  may have contributed to the disparity between our list of OCT4 targets. Nonetheless, we cannot exclude the possibility of species differences in the mode of regulation of pluripotency and self-renewal of ESCs. Indeed, our analysis of changes in gene expression and gene ontologies highlights the involvement of cell signaling interactions, epigenetic modifications, chromatin remodeling, and metabolic processes in the ES-to-trophoblast transition.4 a4 E, U) i$ x3 Z1 _9 k
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Examination of differentially expressed components of signal transduction pathways supports previous findings demonstrating the importance of TGFß, BMP, and FGF signaling in regulating hESC differentiation .
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OCT4 downregulation also had significant effects on expression of epigenetic and chromatin modifiers. The reciprocal expression patterns of the histone lysine methyltransferases SET7 (up) and EZH2 (down), as well as downregulation of the DNA methyltransferase DNMT3B and a number of histone and nonhistone chromatin-associated proteins, suggest that loss of pluripotency is associated with global changes in chromatin organization . These changes may be actively involved in ESC differentiation per se, but they may, in addition, specifically reflect the generation of an extraembryonic cell type.
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As anticipated, the list of OCT4-dependent genes includes as yet uncharacterized novel genes that may represent candidates for further investigation into pluripotency and trophoblast differentiation. Our data provide a reference for combining RNAi and functional genomics using human ESCs to study some of the earliest differentiation events of human postimplantation development. This is supported by the finding that the trophoblast marker BMP4 is enriched in both the TE- and the OCT4-depleted cells at both the 24- and 72-hour time points. Furthermore, the global analysis (data not shown) revealed distinct and overlapping expression patterns between the ICM and undifferentiated ESCs, thus implying that the ICM consist of a transit population of pluripotent cells and that cultured ESCs are an in vitro adaptation of these. Alternatively, the differences between the two data sets may be explained by experimental limitations associated with the scarce human embryo material . Detailed analysis and confirmation of these differences are under way and therefore not included here, as they are beyond the scope of the current study. This type of undertaking should also contribute to the construction of a molecular framework that facilitates robust and predicable control of ESC differentiation and their successful and safe application in stem cell-based therapy in the future.: F/ P- _$ m  Y* M' h1 d

DISCLOSURES

The authors indicate no potential conflicts of interest.

ACKNOWLEDGMENTS0 k9 N0 X: A8 f; q! g

We are grateful to the German Resource Centre for Genome Research (Berlin, Germany), to Dr. Claus Hultschig for printing the slides, and to Dr. David Hay for help with immunofluorescence. This work was supported by the Max Planck Society, the Deutsche Forschungsgemeinschaft (DFG-AD 184/4-1), the Biotechnology and Biological Sciences Research Council (T.C.B.) and the Geron Corporation (Y.B.).* P6 S$ i; R2 C; Q: B
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