Hum. Reprod. Advance Access originally published online on June 21, 2006
Human Reproduction 2006 21(10):2495-2513; doi:10.1093/humrep/del195
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Temporal expression profiling of the uterine luminal epithelium of the pseudo-pregnant mouse suggests receptivity to the fertilized egg is associated with complex transcriptional changes
1 Department of Anatomy 2 Department of Pathology 3 MRC Rosalind Franklin Centre for Genomics Research (RFCGR), Cambridge, UK 4 Present address: The Scottish Centre for Genomic Technology and Informatics, College of Medicine, The University of Edinburgh, 49 Little France Crescent, Edinburgh EH16 4SB, UK
5 To whom correspondence should be addressed at: Department of Anatomy, Downing Street, Cambridge CB2 3DY, UK. E-mail: mhj21{at}cam.ac.uk
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Abstract |
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BACKGROUND: The molecular basis of changes underlying the altered sensitivity of the uterine luminal epithelium (LE) to the embryo over the peri-implantation period is not fully understood. METHODS: Microarray analysis was performed on purified LE isolated from the pseudo-pregnant mouse uterus at 12-h intervals from pre-receptivity through the implantation window to refractoriness. The aim was to identify genes whose expression changes in the LE during this period. RESULTS: A total of 447 transcripts were identified whose abundance changed more than 2-fold in the LE but which did not change in the underlying stroma (S) and glands. Six major patterns of changing expression were noted. Of the 447 genes, 140 were expressed in LE at least 15-fold higher than in S and glandular epithelium (GE) (101 of these more than 20-fold). Detailed spatiotemporal expression profiles were derived for several genes previously implicated in implantation (including Edg7, Ptgs1, Pla2g4a and Alox15). CONCLUSIONS: Functional changes in LE receptivity are characterized by changing constellations of gene expression. Pre-receptivity has a different molecular footprint to refractoriness. Because we have used the pseudo-pregnant mouse model, these changes are driven solely by endocrine signals rather than events downstream of embryo attachment. Some of these genes have been described in previous microarray studies on endometrium, but for the majority, this is the first time they have been implicated in implantation. The 140 genes enriched in the LE greatly expand the list of epithelial markers and provide many novel candidates for further studies to identify genes playing important roles in receptivity and embryo attachment.
Key words: embryo receptivity/implantation window/mice/microarray/uterine luminal epithelium
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Introduction |
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Implantation is essential for the establishment of a normal pregnancy. In preparation for implantation, the endometrium undergoes growth and cyto-differentiative changes in response to the rise and fall of ovarian estradiol (E2) and progesterone (Psychoyos, 1986
). Rodent and human implantation is initiated with a physical interaction (apposition) between the trophoblast and the apical surface of the luminal epithelium (LE), which is followed rapidly by adhesion, and then penetration through the LE to the underlying stroma (S), which responds by decidualization (Abrahamsohn and Zorn, 1993). Implantation can only occur over a restricted period after ovulation called the ‘implantation window’ (Psychoyos, 1994). In the human, this period is thought to be between approximately days 20 and 24 of the menstrual cycle (Navot et al., 1991; Wilcox et al., 1999). In the mouse, it is shorter, lasting for 
24 h spanning early on the fourth day of pregnancy to the middle of the fifth day. Before this window (late day 3), the uterus is pre-receptive and unresponsive to blastocysts (or other decidualizing signals), and after this window, the uterus becomes increasingly refractory to the embryo (late day 5; Psychoyos, 1986). The changing output of ovarian progesterone and E2 defines the limits of the window, a period of 24–48 h of progesterone priming being followed by superimposed E2.
The precise location and nature of the hormonal effects within the uterus that bring about the receptive state are not understood fully. Study of the molecular basis of implantation, especially its earliest stages, is challenging because of the endometrial tissue complexity, comprising LE, glandular epithelium (GE) and S, and also the dynamic changes that occur within each component tissue. Moreover, tissues that show gene-expression changes following steroid manipulations may have been affected directly or indirectly. For example, responses of LE cells to steroids in the mouse (Cunha and Young, 1992; Cooke et al., 1997; Kurita et al., 2000; Grant-Tschudy and Wira, 2004; Crane-Godreau and Wira, 2005) and the expression of 
v
3 integrin in the human LE (Lessey et al., 2000) are both indirect consequences of the action of steroids on the underlying S. Similarly, the action of E2 on the GE stimulates the synthesis and secretion of leukaemia-inhibitory factor (LIF), which then, inter alia, acts on the LE to sensitize it to the blastocyst (Bhatt et al., 1991; Stewart et al., 1992). The blastocyst itself stimulates a number of molecular changes in the LE (Das et al., 1994, 1997a), which thus also lie downstream of, but depend on, the actions of progesterone and E2. This complex dialogue in time and space means that dissecting components of the molecular language used is difficult. Despite this difficulty, considerable progress has been made to identify genes that play essential roles in the process of embryo attachment.
Serendipitous observations on mutant mice combined with intelligent intuition about potential molecular players have provided, on a gene-by-gene basis, much useful information (Carson et al., 2000; Paria et al., 2002; Sharkey and Smith, 2003; Dey et al., 2004). Latterly, use of microarray technology has provided larger databases about transcriptomes in the uterus and endometrium of mouse and primate at different points in the cycle or under different experimental or pathological conditions (Carson et al., 2002; Borthwick et al., 2003; Kao et al., 2003; see Discussion for non-pathological references). However, the tissue complexity of the endometrium has not been addressed in these studies because they have used whole endometrium; hence knowledge of the gene-expression changes in each compartment is very limited. Moreover, in most studies, only restricted pair-wise time-point comparisons have been used to investigate a continuous process. Finally, because studies of receptivity can be complicated by rapid changes in the endometrium induced by the presence of an embryo or decidualizing stimulus, the identification of a distinct gene-expression profile characterizing the receptive state is difficult.
Here we report on the application of microarray analysis on isolated LE at timed intervals during the peri-receptive period in the pseudo-pregnant mouse. We focus on the LE because (i) it is the site of implantation initiation, (ii) earlier evidence suggests that changes within the LE are critical for the acquisition of receptivity and (iii) the LE acts as a transducer of the embryo’s presence to elicit underlying stromal responses. We use a pseudo-pregnancy model so as to limit our study to the pre-attachment phase of implantation and thereby to isolate receptivity changes from the complications of downstream post-attachment events. Our objective has been to identify the genes and pathways altered during these events, thereby providing molecular targets for future study.
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Biological materials
All work was conducted and licensed under the Animals (Scientific Procedures) Act, 1986, and had local ethical approval. MF1 female mice (6–8 weeks; Harlan, Oxford, UK) were maintained in a 12 : 12-h light/dark regime, with food and water available ad libitum. Females were caged with vasectomized males overnight and those plug positive for pseudo-pregnancy (designated day 1) removed to a separate cage. Five pseudo-pregnant females were subsequently killed by cervical dislocation at each of the following times: third day at 21.00 (D3:21.00; pre-receptive), fourth day at 9.00 (D4:9.00; early receptive) and at 21.00 (D4:21.00; receptive), fifth day at 9.00 (D5:9.00; receptive) and at 21.00 (D5:21.00; post-receptive; Cheng et al., 2001
). The uterus was dissected in phosphate-buffered saline (PBS), the fat removed and the ovaries were checked to confirm the presence of corpora lutea. The uterine horns were placed directly into 0.5% dispase (Boehringer Ingelheim Ltd, Bracknell, UK; neutral protease, grade II from Bacillus polymyxa EC 3.4.24.4
[EC]
, catalogue no. 165859) in calcium- and magnesium-free Hanks’ balanced salt solution (HBSS; Invitrogen Ltd, Paisley, UK, catalogue no. 14170) for 2–3 h at room temperature. The LE was dissected cleanly from the underlying S + GE in PBS (Oxoid Ltd, Basingstoke, UK, catalogue no. BR0014G) under a low-power microscope, washed thoroughly through several drops of excess PBS and examined for purity microscopically (Sidhu and Kimber, 1999). The purified LE and the combined S + GE were placed in separate tubes containing 100 µl of Trizol (Invitrogen Ltd, catalogue no. 15596-026) for storage at –80°C. The LE preparation has been previously validated functionally (Catalano et al., 2005). Histological analysis was also undertaken on sample tissues after fixation in 1 ml of a 50 : 50 mix of Bouin’s and 70% ethanol, wax embedding and haematoxylin and eosin staining.
RNA extraction
Samples in Trizol were thawed and a further 250 µl of Trizol was added, before vortexing and standing at room temperature for 5 min. Tubes were spun at 8000 g (5 min), and the supernatant was taken to a clean tube, to which were added 70 µl of chloroform before vortexing and spinning at room temperature (8000 g for 5 min). The aqueous layer was taken to a fresh tube containing 2.5 µl of 5 mg/ml linear acrylamide (Ambion Inc., Austin, TX, USA, catalogue no. 9520), vortexed, an equal volume of 70% ethanol added and total RNA was isolated using a Qiagen column according to the manufacturer’s instructions (Qiagen Ltd, Crawley, UK; Rneasy Micro Kit, catalogue no. 74004). RNA concentration and integrity were assessed spectrophotometrically and on an Agilent Bioanalyzer 2100 (Agilent Technologies UK Ltd, Stockport, UK).
Microarrays
Microarrays (Mouse_Mm_SGC_Av2) containing 7524 oligonucleotides, which represent 7445 sequence clusters plus 79 controls, were obtained from the MRC RFCGR Microarray Programme (Hinxton, UK). All the oligo probes were printed in duplicate, together with controls representing ubiquitously expressed genes and tissue-specific genes. For a full description of the array, see the EBI ArrayExpress record: A-MEXP-54.
We used Cy3–Cy5 two-channel microarray analysis in which the samples were Cy3 labelled and the reference was Cy5 labelled. Reference preparations for LE and S + GE consisted of pooled RNA taken from all individual time-point samples across the LE and S + GE, respectively. This referencing strategy was used to maximize the detection of temporal changes within each tissue.
Sample labelling
Amplified double-stranded complementary DNA (cDNA) was prepared using the SMART cDNA synthesis kit (BD Bioscience Clontech UK, Cowley, UK) as follows. Total RNA (500 ng) was mixed with 10 pmol 3' SMART CDS primer IIA (5'-AAG CAG TGG TAT CAA CGC AGA GTA CT(30)N(–1)N-3'; synthesized by Sigma-Genosys, http://www.sigma-genosys.com) and 10 pmol template-switching primer [5'-d(AAG CAG TGG TAT CAA CGC AGA GTA CGC)r(GGG)-3'] in a volume of 5 µl; the reaction mixture was incubated at 72°C for 2 min and then quenched on ice for 2 min. The following reagents were then added: 2 µl of 5x first-strand buffer, 1 µl of 100 mM dNTPs and 1 µl of PowerScript RT (BD Bioscience Clontech UK, catalogue no. 8460-1), and the reaction was incubated at 42°C for 1 h. A 2-µl aliquot of the first-strand cDNA was then used as template for the second-strand amplification reaction. The following reagents were added: 75 µl of dH2O, 10 µl of 10x PCR buffer II (Applied Biosystems, Warrington, UK, catalogue no. N808-0161), 2 µl of 10 mM stock PCR primer (5'-AAG CAG TGG TAT CAA CGC AGA GT-3') and 2 µl of AmpliTaq polymerase (5 U/µl, Applied Biosystems), and amplified as follows: at 95°C for 1 min and then 15 cycles at 95°C for 10 s, at 65°C for 10 s and at 68°C for 6 min. Labelled target was prepared as follows: 21 µl of amplified cDNA was mixed with 20 µl of 2.5x random prime reaction buffer (Invitrogen Ltd; BioPrime DNA Labelling System, catalogue no. 18094-011), incubated at 95°C for 5 min and placed on ice. The following reagents were added: 5 µl of Low-C dNTP mix (5 mM dATP, 5 mM dGTP, 5 mM dTTP and 2 mM dCTP), 2 µl of Cy3 or Cy5-dCTP (Amersham Bioscience, Little Chalfont, UK, catalogue nos. PA53021 and PA55021) and 40 U of Klenow polymerase, and the reaction was incubated at 37°C for 2 h in the dark. The reaction was terminated with the addition of 5 µl of stop buffer (Invitrogen Ltd). Labelled cDNA was purified on an AutoSeq G-50 column (Amersham Bioscience, catalogue no. 275340). The Cy5 and Cy3 samples were measured for CyDye incorporation and amounts of cDNA using a Nanodrop spectrophotometer (http://www.labtech.co.uk/) and then pooled. Five micrograms of mouse cot-1 DNA (Invitrogen Ltd, catalogue no. 18440-016) was added and the cDNA precipitated with EtOH. This protocol has been validated previously for use in microarray analyses (Petalidis et al., 2003).
Hybridization to microarrays
Labelled targets were resuspended in 50 µl of hybridization buffer made up of 40% formamide, 5x saline sodium citrate (SSC) (20x SSC is 175.3 g sodium chloride + 88.2 g trisodium citrate per litre, autoclaved), 5x Denhardt’s solution (Sigma-Aldrich, Poole, Dorset, UK, catalogue no. D2532), 1 mM sodium pyrophosphate, 50 mM Tris pH 7.4, 0.1% sodium dodecyl sulphate (SDS) plus 2 µl of mouse cot-1 (1 µg/µl) and 1 µl of polyA (8 µg/µl) (Amersham Bioscience, catalogue no. 27-7988), denatured at 95°C for 5 min, incubated at 50°C for 5 min and then centrifuged at 8000 g for 5 min before being applied to an array. Hybridizations were performed under a coverslip at 50°C in a humidified chamber for 16 h. Following hybridization, slides were washed at room temperature twice in 2x SSC for 5 min, twice in 0.1x SSC/0.1% SDS for 5 min and finally twice in 0.1x SSC for 5 min. After washing, the slides were dried by centrifugation at 150 g for 2 min and then scanned on an Axon scanner. Raw image data were extracted using Bluefuse software (http://www.cambridgebluegnome.com).
Data analysis
Data from Bluefuse were imported into GeneSpring version 7.2 (Agilent Technologies UK Ltd). Initially all the data were viewed pre-normalized by tree clustering to remove outlying microarray data, leaving three arrays per time point. Normalization was performed using the per-spot, per-chip intensity-dependent Loess algorithm. Flagged data with confidence levels <50% were removed, as were any remaining genes in which the raw data did not exceed 250 in at least one of the five time points (3442/7485 genes passed). A one-way analysis of variance (ANOVA) (on five groups of three replicates) was performed on the remaining data, using the parametric test that does not assume variances equal, a false discovery rate of 0.06 and the multiple testing correction Benjamini and Hochberg False Discovery Rate test. This analysis identified 895 transcripts that were reliably detectable in LE and which altered over the study period. This subset was reduced to 447 genes by imposing a required change of 2-fold in expression level (see Results). These 895 transcripts were grouped (clustered) based on their expression profile across the time points sampled using the K-means clustering algorithm.
Use of two-colour comparison of LE samples with an LE reference precludes the reliable quantification of relative expression levels of these transcripts between LE and S + GE compartments. Expression level of the genes in the two tissues was therefore compared by first normalizing for each tissue and array the Cy3 raw data for each gene of interest against the Cy3 data for the L3 ribosomal gene on the same array. L3 is a ubiquitously expressed housekeeping gene, present in multiple copies on each array, and so this normalizing procedure takes account of different labelling and hybridization conditions in each tissue sample and array. We then compared the expression levels in LE and S + GE at the time point of maximal gene expression in each set (set 2 D4:09.00, set 3 D3:09.00, set 4 D3:09.00, set 5 D5:21.00, set 6 D4:21.00 and set 7 D5:21.00) and identified those genes where LE expression exceeded that in the S at the same time point by more than 15-fold, indicating relative LE specificity of expression at that time point.
TaqMan analysis
To verify selected microarray results, real-time PCR was performed on the MJ Research Opticon 2 (GRI, Braintree, UK) using first-strand cDNA from the above preparations. Primers and probes specific for Jub and Ptger2 transcripts were designed using Beacon Designer software (http://www.premierbiosoft.com). All other probes and primers were designed using Primer Express (http://www.appliedbiosystems.com), and all were manufactured by Sigma-Genosys. The probes were labelled with 5'-FAM and 3'-TAMRA. PCR was performed using mastermix buffers from Abgene (Epsom, UK). Sequences used are shown in Table I.
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Primer and probe optimization were performed using the manufacturer’s recommended conditions. Expression values were obtained for each transcript relative to its level in an arbitrary reference RNA sample and were normalized using the endogenous control 18S ribosomal RNA to account for varying amounts of starting material (Applied Biosystems, catalogue no. 4310893E).
Identification of potential gene targets for activated E2 and progesterone receptors and for stat3 in silico
The partial sequence of Mouse Genome (MouseGenome9999) version 1.1 was downloaded and installed from the GeneSpring website (http://www.chem.agilent.com), and homology tables were built between this list and the gene list for the microarrays used here. The array gene list shared 6017 of 7485 genes with MouseGenome9999 (80.4% match), representing 23.8% of the MouseGenome genes, and of the 895 and 447 genes identified as being of interest in this experiment, 816 and 416 respectively were represented. Among the 6017 genes, 620, 489 and 483 were identified as having potential binding sites for the estrogen receptor (ER), the progesterone receptor (PR) and the transcription factor Stat3, respectively. These translated lists were then used in the GeneSpring programme ‘Find Potential Regulatory Sequences’ by entering specified DNA-binding sequences for ER (argnnannntgaccy), PR (agaacannntgttct) and Stat3 (gnnatttccsggaartg) and searching between 10 and 3500 bases upstream of either the 816 or the 416 mapped gene sequences, not allowing for Ns other than those contained in the specific sequence. The following results were obtained for the 816 list: 79 genes had ER-binding sites, 64 genes had PR sites and 63 genes had Stat3 sites. For the 416 list, the following gene numbers were retrieved: 43 for ER, 35 for PR and 34 for Stat3.
Bioinformatics approach to comparing microarray data sets from different sources
Gene lists were prepared from selected publications using the descriptive names of the genes; these data were copied into the GeneListEditor window of GeneSpring, and those represented in this experiment were retained. The 895 and 447 subsets of changing LE genes were matched to these gene lists using the gene name, unigene ID or genbank ID.
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Results |
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The LE tissue samples are pure
Assessment of LE purity was made visually at dissection (Figure 1) and also by comparing 12 of the 15 LE samples with their corresponding S + GE samples using real-time PCR to determine the relative expression levels of three known tissue-specific markers. Each transcript level was normalized internally to 18S RNA to control for variable RNA recovery (Dolatshad et al., 2006
). Tnc (tenascin C) expression acts as a stromal marker (Noda et al., 2000), and its LE : S + GE ratio was 0.02 ± 0.02. Ptger2 [prostaglandin (PG) E receptor 2, subtype EP2] expression marks LE (Katsuyama et al., 1997; Lim and Dey, 1997) and gave a ratio of 1955 ± 611.06. Ptger3 (PGE receptor 2, subtype EP3) marks myometrium and pregnant S (Katsuyama et al., 1997) and was not detected in LE, although highly expressed in S. These results show that LE is indeed highly enriched for Ptger2 but expresses almost none of the stromal or the myometrial/stromal markers, thereby confirming the relative purity of the LE preparations.
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LE gene-expression patterns classify into seven broad temporal patterns
Of the 7445 mouse genes represented on the microarray, 895 (12%) were reliably detected in the LE and also appeared to change significantly by ANOVA during the study period. When this selected set of expressed genes was run through a K-means cluster algorithm (n = 10), seven main expression patterns resulted (Figure 2). The data show that the complexity of temporal-specific expression profiles can be broadly resolved into genes whose expression rises over the period of study (set 7; 238 genes), falls over the same period (sets 2 and 3; 277 genes), rises transiently during receptivity (sets 5 and 6; 204 genes) and falls transiently over the receptive period (set 4; 56 genes). A subset of 120 genes (set 1) shows little obvious consistent change in expression over the period of implantation. This result means that the changing receptivity of the LE to the embryo is characterized by distinctive transcriptional patterns.
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The temporal changes observed in LE are not seen in S + GE
To determine whether the temporal expression profiles were characteristic of LE specifically or a general feature of the uterus, the single-colour microarray data sets for these 895 genes in the individual S + GE and LE samples from the same uteri were normalized to allow the expression level of each transcript in LE and S + GE to be compared. The normalized data sets were then compared for their temporal profiles by K-means clustering. Representative examples of two K-means cluster plots (sets 3 and 7) are shown in Figure 3a and indicate that expression levels of the genes in these clusters in the S + GE compartment are relatively stable over time compared with their changing expression in LE samples. The same data can be viewed for individual genes of interest, as illustrated for Areg (amphiregulin), Igfbp3 (insulin-like growth factor-binding protein 3) and Coch (cochlin) in Figure 3b. These data show that the dynamic temporal patterns observed for genes in LE are not mirrored in the underlying S + GE tissue and thus indicate tissue specificity of the temporal change.
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Taken together with our earlier validation of the isolated LE preparation for descriptive and functional studies (Catalano et al., 2005
), all this evidence suggests that the LE gene set identified is indeed representative of LE and that the temporal patterns of their expression are largely restricted to the LE.
Half of the gene set shows large changes in expression over the implantation window: the core gene set
To focus functional analysis on genes showing the largest changes over the period of interest, the genes in sets 2–7 were further filtered to exclude those which did not show a change of at least 2-fold (up or down) during the course of the experiment as follows:
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A total of 447 (50%) genes resulted, which we call the core gene set (CGS, see Supplementary data, file 1, for full list organized by pattern of change in the sets listed above, each set subsorted by fold change during the period of study). Further detailed analysis reported here was confined to this CGS.
Many of the genes with changing expression profiles appear to be LE specific
In Figure 3, we showed that the changing profile of the LE gene expression was limited to that tissue. However, this did not show which of the changing genes are also expressed selectively in LE compared to S + GE, that is, are relatively tissue specific. We therefore interrogated the CGS data to uncover which of the 447 CGS genes were expressed more than 15- and 20-fold higher in LE compared with S + GE at the time of their maximal expression in LE. Transcripts fulfilling this requirement therefore represent potential LE-specific markers. Some interesting examples of these genes are shown in Table II (full data in Supplementary data, file 2). We found that of the 447 genes, 23% (101) and 31% (140) had LE expression levels more than 20- or 15-fold higher, respectively, than in the underlying S + GE and thus seem good candidates for LE markers. Encouragingly, these genes include the well-established LE-specific transcript PG receptor Ptger2 (Katsuyama et al., 1997; Lim and Dey, 1997), already shown by RT–PCR to be expressed 1955-fold more in our LE samples than in S + GE (see earlier). Interestingly, set 6 has the highest proportion (46%) of LE-specific transcripts, and these transcripts are the ones that increase expression transiently in LE over the whole of the receptive period (Supplementary data, file 2).
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General functional categorization of genes
A broad functional description of the 447 CGS gene profile was obtained by classifying them using the GO classification system (but grouping some categories; Supplementary data, file 3). It is striking, given the transduction role of the LE, that of the 447 genes, 120 (27%) are associated with cell signalling, indicating that the changes in preparation for blastocyst signalling are considerable. Additionally, large-scale changes of gene expression are indicated by the 39 changes associated with transcription factors and chromatin, consistent with the large profile of changing transcripts found in this study. A large group of genes (77; 17%) are associated with metabolism and mitochondria. A high representation of immune function-related genes (3.6%) was also noted by Reese et al. (2001)
in their microarray study of implantation, which employed the whole uterus (see also Lobo et al., 2004).
Some general tests of the plausibility of the LE CGS
Several genes, implicated in the change in endometrial receptivity leading up to attachment and implantation, have been identified from genetic and biochemical studies. Using only those genes known to be represented on our microarrays, we interrogated the CGS for evidence of the expression pattern of these genes.
- First, we performed ‘negative control’ searches by scanning for genes that would not be expected to change in LE during this experiment (Table III, lines 1–3). Several genes are induced in the LE in response to blastocyst attachment, and none was represented in the CGS as would be expected for the pseudo-pregnant uterus. Other genes do change their endometrial expression under hormonal influence but not in LE over the period under study or only in other endometrial tissues (S and/or GE). Likewise, none of these was represented. Finally, some genes are reportedly expressed invariantly in the LE over the period of study and were not significantly variable in our study.
- Certain genes are reported as being expressed in the LE at some point during the receptive period, but detailed temporal time courses for them are not available. We report data on six such genes (Marks et al., 1998; Fujiwara et al., 2002; Orchard and Murphy, 2002; Matsumoto et al., 2004), which appeared as expected in the CGS (Table III, line 4). Two signalling molecules, Efnb2 (ephrin B2) and Rdx (radixin), rose transiently over the period of maximum receptivity, whereas two cytoskeletal-associated molecules, Avil (advillin) and Cldn1 (claudin 1), behaved reciprocally. The more detailed expression profiles of Ptger2 and Ptgs1 (cyclo-oxygenase 1) that we have defined are consistent with those reported previously (Chakraborty et al., 1996; Lim and Dey, 1997).
- Finally, we have compared our data set with some of those obtained through different types of microarray studies, three on the mouse (Reese et al., 2001; Cheon et al., 2002; Hong et al., 2004) and one on the human (Mirkin et al., 2005), although none of these studies match closely our experimental design.
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The microarray used here shared 50–70% of those genes described in the other mouse microarray papers as being differentially regulated, and these were thus potentially available for comparison. However, of those shared genes reported previously as changing in microarray studies, the numbers that also changed in our study were not large, absolutely or proportionately (
10%; Table IV). Among the reported E2-stimulated genes (Hong et al., 2004), only polo-like kinase 2 (Snk) behaved in our study as that study predicts (Hong et al., 2004). Similarly, among the reported progesterone-regulated genes, it is not possible to see a corresponding predicted pattern in our data (Cheon et al., 2002). However, perhaps the closest study design to ours was the comparison by Reese et al. (2001) of delayed versus E2-activated uteri, although even this study is complicated by the presence of an embryo, potentially initiating responses downstream of receptivity in the activated uteri. Inspecting the 18 genes that changed after E2 injection and which also appear in our CGS, 9/10 that rose after E2 were in our sets 5 and 7 (rising at or during receptivity), whereas 5/8 that fell after E2 were in sets 2, 3 and 4 (falling at or during receptivity). Therefore, 14/18 transcripts behaved in a similar manner in both these studies.
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We also undertook a single comparison with a human microarray experiment (Mirkin et al., 2005
; Table V). Mirkin et al. compared human endometrial biopsies taken at two time points (day 16 pre-receptive with day 21 receptive) for genes showing 2-fold or more up- or down-regulation. The exact mouse : human gene homologies are often unclear, but of the mouse genes we identified as being homologous to those reported as altered over the implantation period in the human endometrial study, 23 were represented in our 447 CGS. Six of these 23 genes (marked as superscript ‘c’ in Table V) have also been reported to change in other human microarray studies (Table III of Mirkin et al., 2005). Most of these 23 showed changes in the same direction in mouse and human, but 9 moved in the opposite direction.
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Among those genes identified in all these cross-study comparisons, several appeared in more than one of the compared microarray studies (marked as superscript ‘b’ in Tables IV and V), and several were LE specific (marked as superscript ‘a’ in Tables IV and V). Overall, the results reported above give confidence that the CGS does indeed represent a changing profile of LE genes over the receptive period, because many of the genes were found to change in previous mouse studies. Our study also localizes to the LE many genes identified simply as endometrial in previous studies. Finally, our study identifies a number of candidate transcripts that may be expressed in both mouse and human LE.
Analysis of expressed genes by specific and implantation-relevant function
We then conducted a preliminary analysis of the CGS by examining specific implantation-associated functions. We selected three relevant functional categories for investigation based on previous studies of receptivity.
(i) The LIF pathway is a critical component of receptivity initiation, because binding of LIF to LE cells sensitizes them to blastocysts (Bhatt et al., 1991; Stewart et al., 1992). The LE response uses the Jak/stat3 signalling pathway to activate directly and indirectly a set of gene expression changes in the LE (Cheng et al., 2001; Ernst et al., 2001; Catalano et al., 2005). Several genes associated with the LIF pathway were represented in the CGS (Table VI, group 1). The LIF receptor (Lifr; known to be expressed in LE) (Cheng et al., 2001) was up-regulated as the LE moved to refractoriness. Interleukin 1 receptor (Il1r), through which leptin and IL1 mediate their stimulatory effect on both LIF and LIF-R production in the GE/LE (Gonzalez et al., 2004), was up-regulated over the time of maximum receptivity, appropriately in advance of the rise in LIF-R. IL1-R is also reported to mediate the 3 integrin increase, a marker of increased LE receptivity (Simon et al., 1994, 1997), although we found no rise in 3 integrin expression. The expression of oncostatin M receptor (Osmr), to which LIF does not bind but which other growth factors in the same family do bind to suppress stromal cell proliferation (Ohata et al., 2001), was also up-regulated, which may indicate a role for it in LE proliferative control. The expression of Stat3 itself (but not of the Jak kinases) was transiently elevated in LE over the receptive period itself, paralleling the reported transient rise in stat3 protein at this time (Cheng et al., 2001).
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Several downstream genes previously shown to be activated by the LIF-stat3 signalling pathway all rose as expected but did so with distinctive time courses (Cheon et al., 2002
, 2003; Rodriguez et al., 2004; Sherwin et al., 2004). Three of these were confirmed here by real-time PCR analysis (Figure 4). Thus, amphiregulin (Areg) expression rose transiently over the period of maximum sensitivity, whereas cochlin (Coch) showed a later rise and shallower fall, and Igbpf3 rose only as the LE moved to refractoriness. Interestingly, schlafen 3 (Slfn3) expression, which has not previously been implicated in uterine responses, showed a similar expression profile. Members of the Schlafen gene family have recently been implicated in LIF-driven terminal differentiation of myeloblastic cells, and our analysis suggests that this may also be regulated by LIF in the LE during this time (Geserick et al., 2004).
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(ii) PGs play important intrauterine signalling roles in the implantation period, and several genes involved in PG function or in related eicosanoid function were also identified (Table VI). We provide detailed temporal LE expression profiles for four genes previously implicated in the PG pathway at implantation (Edg7, Cox1, Plag4a and Alox15) (Cheon et al. 2002
; Song et al., 2002; Li et al., 2004; Wang et al., 2004; Ye et al., 2005) and show that their changing profiles were entirely consistent with a time-limited role in LE receptivity. Moreover, three of these are likely to be LE specific in their action, because they are expressed 66-fold (Plag4a), 88-fold (Edg7) and 39-fold (Alox15) higher in LE than in S + GE. Platelet-activating factor (PAF) acetylhydrolase (Pafah1b3) was reported as having elevated expression on day 5/6 in the pseudo-pregnant mouse (Chami and O’Neill, 2001), and we confirm and refine that timing. We have also identified the potential involvement of several associated genes, which are considered in more detail in Discussion. (iii) Finally, E2 and progesterone are key players in implantation, so we used two strategies to find sex steroid-regulated genes in the CGS. Searching for consensus DNA-binding sequences for activated E2 receptor and PR produced a list of 27 genes in the CGS with both E2 receptor and PR consensus sequences (Table VII). Remarkably, all of these also had stat3 consensus-binding sequences. Most showed late changes, 3 falling and 15 rising as receptivity declined (sets 3 and 7), but 9 showed transient rises over the receptive period (sets 2 and 5). Seven and one genes, respectively, were found with consensus-binding sequences for either the E2 receptor or the PR sequence alone (Table VII). Among the set 7 genes, we identified a cluster of 15 transcripts related to the intracellular signalling Ajuba (Jub) family pathway, and these are recorded separately in Table VII (see Discussion).
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In addition, several other genes that were not recovered in the above promoter search were identified from literature searches as being directly or indirectly E2/progesterone regulated (Table VII). Two of these fall progressively: Ebag9 is an E2-responsive gene that suppresses cell growth (Tsuchiya et al., 2001
), whereas Ctsk (Cathepsin K) is reported as showing lower expression in human secretory phase LE (Jokimaa et al., 2001). The expression of Ltf (Lactotransferrin) has previously been reported as reduced on day 4 and elevated on day 5 (Chen et al., 2000) and is shown here also to dip coincident with the E2 surge. The expression of FYN-binding protein (Fyb) and Flotillin 1 (Flot1) was reported as varying across the human cycle (Ponnampalam et al., 2004; Punyadeera et al., 2005), and here we provide more precise timings for the mouse. The flotillins (both 1 and 2) are interesting candidates for further study, because they are integral membrane proteins involved in lipid rafts and cell adhesion. Some of the genes in Tables VI and VII are discussed in more detail in Discussion. Here we make three main points. First, amongst the genes identified in these three functional pathways were many expected from previously published work (e.g. Ptger2, Stat3 and Calb3). These genes further validate the panel’s authenticity. Second, for many of these genes, we now provide detailed spatiotemporal descriptions of their expression profiles (e.g. Edg7, Cox1, Plag4a and Alox12/15), thereby enhancing our understanding of their potential roles and regulation. Third, a whole series of new genes not previously implicated in receptivity changes have been identified that warrant further study (e.g. Jub, Podx1 and Flot1 and 2). Many of these transcripts, which change over this period and which have both E2 receptor and PR consensus sequences, may turn out to be novel steroid-regulated genes.
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Discussion |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionSupplementary materialsAcknowledgementsReferences |
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Implantation is difficult to study for several reasons. First, continuous temporal changes occur under the influence of changing ratios of E2 and progesterone. Second, acute changes occur induced by the embryo itself. Third, the uterus is an anatomically complex tissue in which different subcomponents have different but inter-related responses to external signals, signals between compartments and signals from the embryo, and these responses also change with time. We have attempted in this study to simplify analysis by (i) excluding the embryo so as to focus exclusively on the nature of changes in primary receptivity and to avoid the complications of events downstream of embryo attachment and (ii) focusing on the epithelium, as the primary receptive tissue at which the embryo–uterine interaction initiates physically. We have also undertaken a time course study across the receptive period in an attempt to capture a more realistic picture of the dynamic changes occurring than can be achieved by the pair-wise microarray comparisons undertaken previously. Our study is, we believe, the first to describe the temporal molecular profile of the mouse LE over the pre-receptive to refractory phase of pseudo-pregnancy. Three important general findings emerge from our study.
First, a high number (447) of statistically significant changes occur to the transcript profile over the implantation window. We are confident that the data set represents a real picture, given the demonstrated purity of the LE and the tissue specificity of the pattern of change observed.
Second, the period of receptivity is characterized by a complex pattern of transcriptional changes. Far fewer genes show reversible transient changes in expression over the period of receptivity (106 genes—24%: 77 up and 29 down) than show a progressive rise or fall during passage from pre-receptive to post-receptive state (341 genes—76%: 163 rising and 178 falling). This novel finding indicates that the two non-receptive states we compared (D3, 21:00 and D5, 21:00) have distinctive transcript expression profiles even if they appear functionally equivalent. The transition from a pre-receptive to a receptive state does not simply involve the temporary up- or down-regulation of a set of ‘receptivity genes’, which then return to their pre-receptive levels as receptivity ends. Instead, the transitions from pre-receptive to receptive and then to post-receptive are characterized by changes in different gene sets. Even during the receptive period itself, we found rapid changes in expression. Thus, 150 transcripts changed more than 2-fold between D4, 21:00 and D5, 9:00. Clearly, the LE enters the receptive state by one door but leaves by another. It is important to note the suggestion by Shiotani et al. (1993) that the presence of embryos may also affect the time course of LE receptivity, because it is possible that additional ‘receptivity genes’ would be activated in their presence.
Third, we have identified 140 potential (mostly new) markers of LE, the relatively high expression of which distinguishes them from the underlying S + GE at key points in the implantation process. Although the absolute quantification of gene expression levels by the two-channel array methodology used here needs independent confirmation, this list of potential markers of LE should be a useful guide for future implantation studies.
Comparison of our data with previously published uterine microarray studies is difficult to make because of their fundamentally different designs. Thus, almost all were on whole uterus (mouse) or endometrium (primate), and of those using non-pathological non-pregnant tissues, almost all have used paired comparisons, not timed serial sampling. Three types of comparisons have been made. The first type compared two different uterine cycle stages [pair-wise comparison of mouse estrous uterus with diestrous (Tan et al., 2003), comparisons of proliferative and secretory phase human and rhesus endometrial biopsies (Kao et al., 2002; Borthwick et al., 2003; Ace and Okulicz, 2004; Ponnampalam et al., 2004) and of early and mid-secretory phase human endometrial biopsies (Martin et al., 2002; Riesewijk et al., 2003; Mirkin et al., 2005)]. The second type of study compared two distinct experimental conditions in mice [± estrogen in ovariectomized non-pregnant mice (Watanabe et al., 2002; Hong et al., 2004), ± estrogen in ovariectomized pregnant mice to simulate termination of delayed implantation (Reese et al., 2001) and early pregnant uterus ± the progesterone antagonist RU486 (Cheon et al., 2002)]. The third type of study compared implantation sites (ISs) with inter-ISs in the mouse (Reese et al., 2001; another study did the same using differential display: Salamonsen et al., 2002). These studies have provided useful gene lists (reviewed in Giudice, 2004; Horcajadas et al., 2004). Only one study, on the rhesus monkey endometrium and using differential display, has sampled at intervals over the implantation period of an artificial menstrual cycle (Okulicz and Ace, 2003), and only two have attempted analysis of tissue-component expression profiles, both using laser capture in non-pregnant mice (Hong et al., 2004) and mid-proliferative phase humans (Yanaihara et al., 2005). Despite these differences in study design, we nonetheless selected four of the studies, identified the genes present on the microarrays of both our and their studies and compared outcomes.
Unsurprisingly, our CGS for the purified LE included only a subset of those genes identified from previous endometrial studies. However, it was most encouraging that 14/18 of the genes shared with the study by Reese et al. (2001), which compared pre- and post-E2-pregnant uteri in delay, showed cross-study consistency in their direction of change. That these 14 genes included many that were also identified in other implantation studies is also encouraging. What our study achieves is to unambiguously identify these genes as being involved specifically in LE receptivity changes induced by nidatory E2, rather than in events and tissues downstream of embryo attachment.
Our analysis of three signalling pathways involved in implantation further validated the authenticity of the CGS because it confirmed known changes in several genes, providing for them more detailed localization and expression time courses. Finally, for many transcripts associated with these pathways, this is the first time changes in the LE at implantation have been described.
The LIF pathway is a critical component of receptivity initiation. LIF is produced transiently in the GE early on day 4 under the influence of E2 and binds to LE cells to sensitize them to blastocysts via the Jak/Stat3 pathway (Bhatt et al., 1991; Stewart et al., 1992; Cheng et al., 2001; Ernst et al., 2001; Catalano et al., 2005). As would be expected, we did not observe changes in Lif, a GE product. However, we did confirm changes in the expression of some genes previously believed to be LIF regulated, for example, amphiregulin (Areg), calbindin (Calb3), cochlin (Coch) and Igbpf3 (Table VI), and provided more detailed time courses. These suggest quite complex downstream transcriptional kinetics and distinct roles for each of the expressed proteins in relation to receptivity changes. We confirmed the localization of the LIF receptor (Lifr) in LE, as reported previously, but have now shown that the RNA transcripts for Lifr, the closely related oncostatin M receptor (Osmr) and Stat3, which is essential for transducing signals from these receptors, are all up-regulated during the receptive period (Cheng et al., 2001). This co-ordinated up-regulation may be due to the action of IL-1, which is also known to up-regulate the LIF receptor in human endometrium via the IL-1 receptor type (1Il1r1) (Gonzalez et al., 2004). The fact that 1Il1r1 is also up-regulated suggests a regulatory network in the LE, which can now be tested functionally.
PGs play an essential, if complex, role in receptivity and implantation as well as in luteolytic signalling. The rate-limiting step in PG synthesis is PGH2 synthesis from arachidonic acid by cyclo-oxygenases 1 and 2. Cox1 and 2 (also known as Ptgs1 and 2) are reportedly expressed in the LE (Chakraborty et al., 1996); Cox1 expression declining on day 4, whereas Cox2 becomes expressed solely at the site of blastocyst attachment, where it may be essential for implantation (Lim et al., 1997, 1999). It has been suggested that Cox2 expression may be blastocyst induced (Lin et al., 2005) but that the general decline in Cox1 expression is due to E2. Cox2 did not feature in our CGS, which is consistent with the absence of a blastocyst, but the transcript for an upstream regulator of its activity, namely Edg7, rises transiently over the receptive period (Table VI), possibly anticipating a potential embryonic signal? Null mutants of Edg7 show reduced implantation rates and defective embryo spacing (Ye et al., 2005). Cox1 was represented in the CGS, declining transiently over the period of receptivity (Table VI), consistent with down-regulation by nidatory E2. Cox1-null females are not infertile but can salvage fertility in Cox2-null females (Wang et al., 2004). PGD2 synthase (Ptgds) declined steadily across the implantation window.
Phospholipase A2 (Pla2g4a) is a major supplier of arachidonic acid for the cyclo-oxygenases, and its null mutation delays implantation (Song et al., 2002). We find that transcripts for both it and Pla2g10 increase transiently over the receptive window (followed by a later rise in Pla2g7), whereas Annexins 3 and 8 (Anxa3/8, inhibitors of Pla2) rise later as receptivity declines. However, the phospholipase A2 family has functions additional to PG synthesis. Thus, arachidonic acid is also a major cellular substrate for the synthesis of eicosanoids by the lipoxygenases (LOX) (Needleman et al., 1986), 5-LOX forming mainly the leukotrienes and lipoxines and 12- and 15-LOXes forming hydroxyeicosatetraenoic acids (HETEs) (Brash, 1999). Lipoxygenases feature prominently in the LE CGS (Table VI), 5-Lox declining but 12-15-Lox rising transiently over the period of maximal receptivity in parallel with Pla2g4a and 10, supporting a role for HETEs in receptivity, as has been suggested previously (Li et al., 2004). This study now localizes spatially and temporally their likely role. Their endogenous ligand (peroxisome proliferator-activated receptor, PPAR
) was not in the CGS despite being represented on the microarray, indicating that its level does not change significantly. Phospholipase A2 family members also generate lysophospholipids, membrane-derived bioactive lipid mediator, such as lysophosphatidic acid (LPA) and sphingosine1-phosphate. Pla2g7 and Pafah1b3 are involved in degrading PAF, and PAF degradation is known to rise as the implantation window closes (O’Neill, 1995). Lyso-phospholipids are known to rise in embryonic fluids around the time of implantation, and they may therefore play a role via LPA receptors such as Edg7 (see above) (Morin et al., 1992).
Steroids are key regulators of implantation, some but not all of their functions being exerted through sex steroid receptors (Dey et al., 2004). There is also no simple linear path linking the steroid : receptor complex through a consensus DNA-binding promoter sequence to a distinct set of steroid-sensitive genes (Das et al., 1997b; McKenna and O’Malley, 2000, 2002; Hewitt et al., 2005). Nonetheless, we identified 36 genes in the CGS that may be steroid regulated by searching for consensus DNA-binding sequences for activated E2 receptor and PR. Of the 27 genes with both E2 receptor and PR consensus sequences (Table VII), all also had Stat3 consensus-binding sequences. This strongly supports our previous suggestion that steroid receptors and Stat3 may co-operate to regulate the expression of some of these genes, as we showed for amphiregulin (Areg), cochlin (Coch) and Igfbp3 (Catalano et al., 2005). A further one and seven genes, respectively, were identified as having exclusively PR- or E2-binding sequences. Of these 36 potentially steroid-regulated genes, 14 rose or fell transiently over the receptive period, suggesting regulation by nidatory estrogen, either directly or via LIF/Stat3. Interestingly, our data suggest that Stat3 transcription itself may be directly stimulated by E2, and Usp18 (expression of which also rises transiently) has been reported to be downstream of Stat regulation (Wang and Campbell, 2005).
A major goal of this project was to identify novel genes in the LE, which might play a role in implantation. We draw attention to a few of the many potentially interesting candidates. Thus, Podx1 (set 3, expression falls during receptivity) encodes an anti-adhesive surface molecule (Takeda et al., 2000), which has also been identified as one of the earliest markers of the apical domain of epithelial cells (Meder et al., 2005). Its declining expression from D3 (21.00) might indicate a role in the increased LE adhesion occurring during the receptive phase. A second epithelial cell apical surface marker is encoded by Prominin1 (Prom1; expression elevated transiently), a transmembrane progenitor cell marker lost on cyto-differentiation, and is a potential mediator of surface adhesivity changes (Kania et al., 2005; Marzesco et al., 2005). A third epithelial cell-surface protein in the collectin family, surfactant protein D (Sftpd or SP-D; rises as receptivity ends), has been detected previously in uterine epithelial cells (Madsen et al., 2000; Oberley et al., 2004). It plays a protective role by binding bacterial carbohydrates and may affect the restoration of mucosal integrity after the receptive phase.
Hey1 and Gata-2 are interacting transcription factors (Ishiko et al., 2005), Hey1 mediating Notch signalling and implicated in steroid-mediated transcriptional control (Belandia et al., 2005), whereas Gata2 is regulated by progesterone (Jeong et al., 2005). The expression of both rises transiently during the receptive period. Mif (set 7) has been detected in human LE and GE, increasing in early secretory phases, stabilizing over the receptive period and rising as it ended (Kats et al., 2005), consistent with our finding. Mif release (but interestingly not its mRNA levels) from bovine LE and superficial GE is stimulated by IFN-
as part of its anti-luteolytic effect attenuating PGF2 secretion (Wang and Goff, 2003). Might the accumulation of Mif RNA towards the end of the receptive period be anticipating this embryo-mediated release?
A striking finding was the co-regulation of several members of the LIM protein family including ajuba (Jub) and zyxin (Zyx; Table VII). LIM proteins shuttle between the cell surface and nucleus and, through protein–protein interactions, contribute to the regulation of cytoskeletal organization and cell adhesion. They thereby play a role in several intracellular signalling pathways (Bach, 2000; Ostendorff et al., 2002; Marie et al., 2003; Feng and Longmore, 2005), one of which (the IL1/TNF/Toll receptor pathway) leads to the induction of many cytokines already implicated in post-adhesive uterine responses (Dunne and O’Neill, 2005; Smith et al., 2005). Some protein components/outputs of this pathway were reported previously from semi-quantitative studies to change in the mid-secretory phase LE cells of the human endometrium (Laird et al., 1994; Page et al., 2002). The TNF-stimulated pathway has been associated in mouse LE cells with apoptosis induction, which has led to the suggestion that it may be involved in terminating the luteal phase (Okazaki et al., 2005). It is of interest that the expression of both Jub and Zyx rises to a maximum towards the end of the receptive phase, raising the possibility of their involvement in the termination of this phase. Significantly, 15 other genes potentially associated with (or closely related to genes associated with) LIM protein activity have been identified in the changing LE profile, 7 of these with a possible role in the activation of NF-
B (marked as superscript ‘a’ in Table VII). Included among these are Toll-like receptors, which share pathways downstream of IL1 receptors (Dunne and O’Neill, 2005). These pathways are complex and can have a number of consequences including the induction of cell differentiation and cell apoptosis (Bach, 2000) and the production of pro-inflammatory cytokines (such as IL-1, cyclo-oxygenase, nitric oxide, adhesion molecules and chemokines) as well as interferons (Dunne and O’Neill, 2005), many of which are already implicated in the post-adhesion transduction activity of the LE. Jub-null mice grow into adults, show no obvious phenotype and are fertile (Pratt et al., 2005), but there is considerable gene redundancy in the LIM protein family. Further work on the functional importance of this signalling pathway is warranted to test its identity as a potential player in the receptive state of the LE.
This analysis of the LE transcription patterns has shown that the transition to a receptive state is accompanied by major changes in gene expression. It has shown that the pre- and post-receptive LE exhibit very different transcriptomes and has allowed us to identify many new candidates that may play important roles in the preparation for embryo attachment. This productive outcome has focused on just a small subset of the CGS, and it is already clear to us that many other genes of interest show interesting changes, many in functional clusters. This rich data set will prove very useful in further elucidating the molecular mechanisms responsible for implantation by providing candidates for further functional studies in the mouse. We also hope that it will prove useful in guiding investigations of the human LE and assist the detection of markers for both fertile and implantation-defective uteri that may be of value clinically.
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Supplementary materials |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionSupplementary materialsAcknowledgementsReferences |
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Supplementary data are available at http://humrep.oxfordjournals.org/.
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Acknowledgements |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionSupplementary materialsAcknowledgementsReferences |
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We thank Sue Kimber and Sam Saidi for their valuable advice. This study was supported by a grant from the Wellcome Trust to M.H.J. and M.H. Hastings.
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Submitted on February 6, 2006; resubmitted on April 3, 2006; accepted on April 13, 2006.
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