Molecular Human Reproduction, Vol. 8, No. 2, 149-166,
February 2002
© 2002 European Society of Human Reproduction and Embryology
Embryology |
A set of 1542 mouse blastocyst and pre-blastocyst genes with well-matched human homologues
Department of Anatomy and Structural Biology, University of Otago Medical School, P.O. Box 913, Dunedin, New Zealand
Abstract
GenBank contains 57 151 Expressed Sequence Tags (EST) derived from 11 preimplantation embryo mouse cDNA libraries ranging from the 2-cell embryo to the blastocyst. EST were matched to UniGene clusters to identify a composite set of 11 291 UniGenes. These 11 291 UniGenes were screened using HomoloGene to identify a subset of 3467 mouse UniGenes with matches in at least two other species, one of which was human. Of the 3467 matches, 1542 are for named human proteins. Four of the 11 preimplantation embryo libraries were for blastocysts and contain 22 307 EST. These blastocyst EST generate 5762 UniGenes, of which 2246 have matches in at least two other species. Of the 2246 matches, 1170 are for named human proteins. Comparison of the expression profile of the blastocyst set with a similarly derived set from the mouse oocyte identified a number of transcripts that are significantly up-regulated during preimplantation development. The set of named blastocyst and pre-blastocyst genes complements the similar set published recently for the mouse oocyte. They provide a database for identifying signalling pathways that may play a role in determining cell fate in preimplantation embryo development.
blastocysts/HomoloGene/human homologues/mouse/UniGene
Introduction
Preimplantation embryo development is initiated by fertilization of the oocyte and terminates with implantation of the blastocyst into the uterine wall. This period of development is associated with two cell lineage decisions. The first results in differentiation of the embryo into the trophectoderm and inner cell mass. The second prefigures development of the endoderm after implantation. In mammals, little is known of the gene expression that accompanies these lineage decisions.
One way of approaching this question is to undertake large-scale DNA sequencing of cDNA libraries constructed from preimplantation embryos. GenBank contains a set of 71 825 Expressed Sequence Tags (EST) derived from 15 non-normalized mouse preimplantation cDNA libraries. Seven of these libraries are derived from embryos ranging from 2- to 16-cell embryos. These account for 34 844 EST. A further four libraries are derived from blastocysts and contain 22 307 EST. The balance of the EST from this set of 15 libraries are derived from four oocyte libraries that have already been analysed (Stanton and Green, 2001a
,b).
The majority (80%) of the 71 825 preimplantation EST can be mapped to UniGene clusters. This allows construction of gene expression catalogues, either for individual cDNA libraries or combinations of libraries. The expression catalogues can be screened using HomoloGene to identify the homologue of each UniGene in other species, principally human, but increasingly cow, rat, fruit fly, zebra fish and Xenopus. Homology screening provides a powerful strategy for bootstrapping gene expression data from the tissue of one species into data sets in other species, with the potential for synergies in ascription of function, annotation, etc.
This paper describes the analysis of the 57 151 EST generated from mouse cDNA libraries ranging from the 2-cell embryo to the blastocyst.
Methods
The 57 151 EST used in this analysis were downloaded as UniGene libraries from www.ncbi.nlm.nih.gov/UniGene/Mm_DATA/lib_report.html. The catalogue numbers of the UniGene libraries in this analysis were: 2-cell embryo, 88 (14 813 EST), 149 (3688 EST), 414 (6596 EST); 4-cell embryo, 175 (3011 EST); 8-cell embryo, 91 (98 EST), 150 (3443 EST); 16-cell embryo, 176 (3195 EST); blastocyst, 85 (12 955 EST), 94 (2499 EST), 102 (5692 EST) and 134 (1161 EST). Detailed descriptions of cDNA library construction are available from the UniGene website. The cDNA libraries were non-normalized.
UniGene libraries were imported into FileMaker Pro (FileMaker Inc., Santa Clara, CA, USA) for construction of 14 EST databases, one for each of the 11 separate cDNA libraries, a combined set of the seven libraries spanning the 2-cell to the 16-cell embryo, a combined set of blastocyst libraries and finally, a complete aggregate set for the 11 libraries spanning the 2-cell embryo to the blastocyst. UniGene Cluster Numbers were identified for each EST GenBank Accession Number. Digital gene expression profiles for the blastocyst sets were generated by summing UniGene cluster abundances. Profiles for individual blastocyst libraries were compared using Fisher's exact test. The HomoloGene database (found at ftp://ftp.ncbi.nlm.nih.gov/pub/HomoloGene) was imported into FileMaker Pro to screen for UniGene homologues in other species. We used the non-redundant homology sets in the hmlg.trip.ftp file. These sets are reciprocal best matches that are mutually consistent between at least three organisms. We identified the subset of mouse embryo UniGenes in this file with human UniGenes as one of the matches. The version of the HomoloGene database used was released in January, 2001. It was constructed from UniGene build #13 for Danio rero (zebra fish), #86 for Mus musculus (mouse), #83 for Rattus norvegicus (rat), and #129 for Homo sapiens (human). Additional information on mouse UniGenes was obtained using Locus Link (www.ncbi.nlm.nih.gov/LocusLink/) and Online Mendelian Inheritance in Man (OMIM) (www.ncbi.nlm.nih.gov).
Results
The work described in this paper is an analysis of 57 151 EST derived from cDNA libraries spanning the development of mouse preimplantation embryos from the 2-cell embryo to the blastocyst. These EST were derived from random sequencing of 11 mouse cDNA libraries. All 11 cDNA libraries used in this study were non-normalized. It was not possible to include an analysis of an earlier study (Sasaki et al., 1998) because of restricted access to the relevant data.
The 57 151 EST mapped to 11 291 UniGene clusters. These UniGenes were screened against HomoloGene and classified into one of three groups, as previously described for the mouse oocyte (Stanton and Green, 2001a): group A is composed of UniGene clusters that have homologues in at least two other species, one of which is human; group B is a small group of mouse UniGenes that have a UniGene homologue only in human and not in any other species; and group C constitutes the remainder. The analysis in this paper is restricted to the 3467 UniGenes in group A. Each UniGene in group A is further classified into one of three categories: (i) a matched gene with an official symbol and name (1542 UniGenes), (ii) a gene encoding a hypothetical protein or (iii) a set of overlapping EST.
Each of the 1542 named UniGenes in group A(i) above was assigned to one of 17 tables (also available at http://anatomy.otago.ac.nz/green_egg_database). The first 16 tables represent distinct functions, and Table XVII represents the balance of unassigned genes. Each entry contains a mouse UniGene number, the corresponding human UniGene number as identified by HomoloGene, and the official gene symbol currently employed by the National Institutes of Health (NIH). Abundances are given for blastocyst UniGene entries. These abundances represent the number of EST in the set of 22 307 EST that derive from blastocysts. Entries marked in bold type represent UniGenes that are also present in the oocyte (Stanton and Green, 2001a). Each entry also contains the official description of the gene as given by the NIH. Entries without abundances are transcripts that are not present in either mouse oocytes or blastocysts, but instead derive from one or more of the intermediate cDNA libraries. Genes were assigned to one of the 17 tables denoting functional categories after an investigation of their database entry that included, where possible, an evaluation of their OMIM entry, their domain structure in Locus Link, and Basic Local Assignment Search Tool (BLAST) searches. Each gene is entered into one table only. In the majority of cases, genes have a single, dominant function that makes assignment straightforward. However, in some cases, a gene has more than one putative function. Placement of these genes in the tables was based on the function currently perceived as the most important.
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The number of EST for each UniGene catalogue and the total number of EST derived from the preimplantation libraries differs slightly from those used previously (Stanton and Green, 2001a
,b). These differences reflect changes to the databases over the past 6 months. They include deposition of additional cDNA sequences for some of the libraries, removal of some existing clones, and reclustering of EST in the UniGene database. (An example is the reclustering of EST for eukaryotic translation elongation factor 
1, which is discussed later.) As a result, the 71 346 EST from 15 preimplantation cDNA libraries used previously (Stanton and Green, 2001b) has now risen to 71 825 EST. The number of UniGene clusters identified for this set has risen from 11 483 to 13 518 (Stanton and Green, 2001b).
In addition to the identification of genes expressed between the 2-cell embryo and blastocyst stage, we also undertook a separate analysis of the four blastocyst cDNA libraries. There were no significant changes from our previous study (Stanton and Green, 2001b). We have analysed the four libraries again in the light of the changes to the databases and find that the number of genes showing differences in expression has fallen to two. These are haemoglobin beta adult major chain (Hbb-b1, mm.142368) and RIKEN cDNA 2810026E11 gene (2810026E11Rik, mm.29859). The libraries remain remarkably concordant. All blastocyst EST were therefore amalgamated into a single set and this set was taken as representative of mouse blastocyst expression. A gene expression profile was established by counting the number of EST for each UniGene cluster (Stanton and Green, 2001b). This number is entered in Tables I–XVII
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The gene expression profile of the amalgamated blastocyst set of UniGenes was compared using Fisher's exact test to that of the mouse oocyte profile derived previously (Stanton and Green, 2001a
). There were no significant changes between the oocyte and the blastocyst. A total of 87 genes were differentially expressed in this pair-wise comparison, 34 of which were up-regulated and 53 down-regulated. These 87 genes are a subset of the 109 genes identified previously (Stanton and Green, 2001b). The 22 genes making up the balance show significant differences in the expression at one of the intervening stages. The up-regulated genes identified previously (Stanton and Green, 2001b) include ribosomal genes, keratins 8 and 18, eukaryotic translation elongation factor 11, and actins. Discussion
The mammalian blastocyst consists of a spherical layer of epithelial cells (trophectoderm) surrounding an inner cell mass (ICM) of pluripotential stem cells. Differentiation of blastomeres into trophectoderm represents the first lineage decision of the developing embryo. The first cytoskeletal genes that are differentially expressed include those encoding keratins 8* and 18, desmoplakin* (= dystonin), plakoglobin, E-cadherin*, -catenin* and ß-catenin* (Brulet et al., 1980; Jackson et al., 1980; Paulin et al., 1980; Oshima et al., 1983). (An asterisk indicates that the transcript for the protein was identified in the present study). Keratins 8 and 18 are found in simple epithelia where they heterodimerize to form intermediate filaments. Transcripts for both keratins rise progressively from the 2-cell embryo to the blastocyst, paralleling development of the trophectoderm, and targeted deletion of keratin 18 in the mouse leads to trophoblast fragility and early embryonic lethality (Hesse et al., 2000). Keratin 18 does not have a calculated ortholog in human and is therefore not included in the tables. However, there were 35 transcripts for keratin 18 (mm.22479, krt1-18) in the initial set of 22307 blastocyst EST.
There are also transcripts in the blastocyst for the recently-identified DnaJ/Hsp40 family protein, Mrj. Mrj binds specifically to keratin 18 and may play a role in K8/18 filament organization (Izawa et al., 2000). Also identified in the present study are other transcripts associated with epithelial differentiation and morphogenesis, including those which encode ELF3, EVA, TGFBI, TLE1, MMP7, TIEG, EPIM and STEAP. Although formal evidence is lacking, expression of these transcripts may be restricted to trophectoderm and reflect its differentiation. Transcripts that reflect gene expression in ICM cells are less easy to identify and may be largely absent in the tables (which only contain entries if there are human homologues) because of the lack of deposited DNA sequence from human embryonic cDNA libraries. For example, the mouse embryonal stem cell specific gene 1 (mm.139314) is highly expressed in the mouse blastocyst but has no human homologue. Its expression is significantly up-regulated in blastocysts when compared with the oocyte [normalized transcript abundances for unfertilized oocyte, fertilized oocyte, 2-cell, 4-cell, 8-cell, 16-cell embryos and blastocyst per 10 000 transcripts are 0, 0, 3, 0, 0, 6 and 41 respectively (Stanton and Green, unpublished data)]. The gene encodes a hypothetical RNA-binding protein and may be involved in suppression of differentiation and maintenance of pluripotency.
Gene expression profiles and their associated gene identities provide a wealth of data that, in principle, should be capable of identifying key features of cells such as signalling pathways. The challenge is to move from the merely speculative analysis of these large data sets to realistic candidates that warrant further investigation. One approach is to use information from gene knock-outs and gene traps to identify candidate pathways. We discuss here two examples of this approach, both based on homozygous null mutants that show embryonic lethality during preimplantation development or immediately following implantation.
The first signalling pathway involves epidermal growth factor* (EGF), epidermal growth factor receptor* (EGFR), the gene product of survival motor neuron* (SMN1), survival motor neuron binding protein* (SIP1), and a recently identified intermediary protein, ZPR1* (Gangwani et al., 2001; Matera and Hebert, 2001). ZPR1 (Official Gene Symbol and Name = ZNF259; zinc finger protein 259) is a highly conserved zinc finger protein that binds to the cytoplasmic domain of tyrosine kinase receptors such as EGFR and platelet-derived growth factor (PDGFR) in their inactive states (Matera and Hebert, 2001). Phosphorylation of the receptor releases ZPR1 which, in proliferating cells, interacts with eukaryotic translation elongation factor 1* (eEF-1). Expression of eEF-1 transcripts is relatively low at the 1- and 2-cell embryo stage but rises markedly from the 4-cell stage through to the blastocyst, paralleling cell proliferation in the preimplantation embryo. The rise in expression of eEF-1 mRNA is shown in Table I of Stanton and Green as UniGene number 16317 (Stanton and Green, 2001b). (This UniGene number has since been retired and the current UniGene cluster number for eEF-1 is 196614). Recent evidence suggests that ZPR1 immunoprecipitates with SMN1 (Gangwani et al., 2001; ). SMN1 plays roles in the biogenesis of small nuclear ribonucleoprotein (snRNP) particles and pre-mRNA splicing and its homozygous deletion is lethal at the peri-implantation stage (Schrank et al., 1997). It has been suggested that there is a potential signalling pathway connecting cellular proliferation signals such as EGF with SMN1 action (Matera and Hebert, 2001). Although mutations in SMN1 are associated with spinal atrophy (and therefore must allow the development of a functional blastocyst), homozygous null SMN1 mutants in mice show extensive degeneration of the trophectoderm and ICM (Hsieh-Li et al., 2000). The timing of the degeneration suggests that the limited embryonic development in homozygous null mutants reflects the duration of maternal transcripts and their gene products. The embryonic lethality associated with SMN1–/– mutants does not, by itself, implicate the EGF signalling pathway since homozygous EGFR-null mutants are viable. However, ZPR1 is bound by other receptor tyrosine kinases which may also be present in preimplantation embryos (for example, PDGFR*).
The second example of a potential signalling pathway identified by gene knock-outs is provided by E-cadherin*. Homozygous deletion of E-cadherin* prevents development of trophectoderm (Larue et al., 1994). Although the defect may be purely adhesive at the preimplantation stage, there is a rapidly growing body of data that indicates that E-cadherin is part of a large multimeric complex that also includes presenilins 1* and 2, *- and ß*-catenin and nicastrin* (Baki et al., 2001). Presenilin 1 is a membrane protein that interacts with both E-cadherin and ß-catenin and anchors the complex to the actin cytoskeleton through -catenin. Recent evidence suggests that presenilin 1 is involved in regulating at least two signal cascades, intramembranous proteolytic cleavage of APP* and Notch, and degradation of ß-catenin in the Wnt signalling pathway (De Strooper and Annaert, 2001). Simultaneous knock-outs of both presenilins in mice causes death at 9.5 d.p.c., with many indications of prior abnormal development (Donoviel et al., 1999). The Notch knock-out also produces similar defects at 9.5 d.p.c. (Swiatex et al., 1994; Conlan et al., 1995). The evidence suggests that signalling pathways involving these proteins are important in early embryonic development, but it is unclear whether E-cadherin initially has a simpler role in trophectoderm formation that is restricted to intercellular adhesion.
The transcripts identified in this study also include those for the membrane protein BACE (which contains ß-secretase activity), two amyloid precursor protein binding proteins and amyloid precursor-like protein 2 (APLP2), a member of a family of amyloid precursor-like proteins that includes APP. APLP2 shares a large ectodomain with APP that can be cleaved by BACE. There are conflicting reports on the effects of knocking out APLP2, with one report indicating preimplantation embryonic lethality (Rassoulzadegan et al., 1998) and the other not reporting such an effect (Heber et al., 2000). These differences may reflect the size of the deletion or the genetic background.
A number of additional functions have been identified recently for nicastrin, presenilin 1 and APLP2 (Sester et al., 2000; Yu et al., 2000; De Strooper and Annaert, 2001; Fagan et al., 2001; Kim et al., 2001; Soriano et al., 2001), potentially placing these, and related proteins, at the hub of a number of key developmental pathways.
The existence of signalling pathways involving Wnt signalling in early embryonic development is strengthened by the presence of transcripts in the set of mouse blastocyst EST for the Wnt receptors Frizzled 3, 4 and 7 (Fzd3, Fzd4, Fzd7), although the genes are not included in the tables in this paper because they do not satisfy the criterion of a three-way homology match. Other components of the Wnt signalling pathways whose transcripts are present in the preimplantation set of EST include glycogen synthase kinase 3ß (GSK3 ß), axin and adenomatous polyposis coli (APC). APC is a significant transcript because of the widescale functions of this protein (Fearnhead et al., 2001). These include signal transduction in Wnt signalling, mediation of intercellular adhesion, stabilization of the cytoskeleton and possibly regulation of the cell cycle. Recent evidence suggests that Fzd7 is implicated in mediating APC/ß-catenin signalling (Tanaka et al., 1998).
This discussion has focused on exploring the utility of embryonic lethal gene knock-outs as a means of identifying key signalling pathways in large EST data sets. These provide a powerful tool in sifting large bodies of gene expression data to identify pathways of functional significance. A related method that may be effective is the use of gene trapping in embryonic stem cells (Mitchell et al., 2001). However, conventional knock-out technology is relatively slow and expensive and there are now opportunities for higher throughput methods to test the large number of candidate pathways that are emerging from the data. Recent work on RNA interference (RNAi) has shown it to be capable of ablating transcripts in mouse preimplantation embryos (Svoboda et al., 2000; Wianny and Zernicka-Goetz, 2000) and it has the great benefit of speed. Comparative data derived from the use of RNAi in C.elegans (Zipperlen et al., 2001) may also contribute as homologous mammalian genes are identified. We see considerable potential in integrating RNAi, bioinformatics and DNA microarrays to provide rapid progress in elucidating mechanisms of preimplantation embryonic development and differentiation.
Appendix to Stanton and Green
Information in the following tables is available at http://anatomy.otago.ac.nz/green_egg_database
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Acknowledgements
We wish to thank Andrew Macgregor for his invaluable assistance in helping to construct databases in FileMaker Pro. This work was supported by grants from the New Zealand Marsden Fund and the New Zealand New Economy Research Fund.
Notes
1 To whom correspondence should be addressed. E-mail: david.green{at}stonebow.otago.ac.nz 
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Submitted on June 18, 2001; accepted on November 12, 2001.
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