![]() | ![]() |
Formats:
|
||||||||||||||||||||||||||
Copyright © 2008 Krens et al; licensee BioMed Central Ltd. ERK1 and ERK2 MAPK are key regulators of distinct gene sets in zebrafish embryogenesis 1Institute of Biology, Leiden University, Wassenaarseweg 64, 2333 AL Leiden, The Netherlands Corresponding author.SF Gabby Krens: S.F.G.Krens/at/biology.leidenuniv.nl; Maximiliano Corredor-Adámez: M.Corredor/at/biology.leidenuniv.nl; Shuning He: S.He/at/biology.leidenuniv.nl; B Ewa Snaar-Jagalska: B.E.Snaar-Jagalska/at/biology.leidenuniv.nl; Herman P Spaink: H.P.Spaink/at/biology.leidenuniv.nl Received December 20, 2007; Accepted April 28, 2008. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background The MAPK signaling proteins are involved in many eukaryotic cellular processes and signaling networks. However, specific functions of most of these proteins in vertebrate development remain elusive because of potential redundancies. For instance, the upstream activation pathways for ERK1 and ERK2 are highly similar, and also many of their known downstream targets are common. In contrast, mice and zebrafish studies indicate distinct roles for both ERKs in cellular proliferation, oncogenic transformation and development. A major bottleneck for further studies is that relatively little is known of in vivo downstream signaling specific for these kinases. Results Microarray based gene expression profiling of ERK1 and ERK2 knockdown zebrafish embryos at various stages of early embryogenesis resulted in specific gene expression signature sets that showed pronounced differences in gene ontology analyses. In order to predict functions of these genes, zebrafish specific in silico signaling pathways involved in early embryogenesis were constructed using the GenMAPP program. The obtained transcriptome signatures were analyzed in the BMP, FGF, Nodal and Wnt pathways. Predicted downstream effects of ERK1 and ERK2 knockdown treatments on key pathways responsible for mesendoderm development were confirmed by whole mount in situ hybridization experiments. Conclusion The gene ontology analyses showed that ERK1 and ERK2 target common and distinct gene sets, confirming the difference in knockdown phenotypes and diverse roles for these kinases during embryogenesis. For ERK1 we identified specific genes involved in dorsal-ventral patterning and subsequent embryonic cell migration. For ERK2 we identified genes involved in cell-migration, mesendoderm differentiation and patterning. The specific function of ERK2 in the initiation, maintenance and patterning of mesoderm and endoderm formation was biologically confirmed. Background ERK1 and ERK2 (Extra-cellular signal Regulated protein Kinases) are most likely the best studied members of the mitogen activated protein kinase (MAPK) proteins. Despite much effort and their biological and medical importance, still relatively few in vivo downstream targets of these kinases have been identified conclusively, especially when considering the numerous cellular events and signaling networks they are involved in [1]. Most of the target proteins and downstream genes have been identified by in vitro studies using cell culture systems. Specific roles for both ERKs are described for cellular proliferation, as mouse embryos fibroblasts (MEF) isolated from erk1-/- mice grew faster than wild type cells. The tumorgenicity of transplanted NIH 3T3 cells stably expressing an oncogenic form of Ras in nude mice was largely inhibited by co-transfection of ERK1, but not by ERK2 or p38 [2]. In diseases, ERK1 and ERK2 can display distinct cellular functions, as has been shown for the formation of cancer [3]. The upstream activators MEK1 and MEK2 have also been shown to play a role in human diseases such as Cardio-Facio-Cutaneous (CFC) syndrome [4]. In addition, divergent roles for ERK1 and ERK2 were already shown by the different effect of the knockout studies performed in mice since erk1-/- mice are viable and fertile [5], while erk2-/- mice die in utero before embryonic day (E) 8.5 [6]. To study and compare the developmental roles of ERK1 and ERK2 we used specific morpholino antisense oligonucleotides (MO), to block translation of ERK1 and ERK2. We previously showed that saturated knockdown conditions of ERK2 led to severe phenotype, as ERK2MO morphants did not go into epiboly, whereas ERK1MO morphants still developed further and entered gastrulation stages. In addition, immuno-histochemical studies showed that ERK phosphorylation was completely abolished in the blastula margin of ERK2 morphants, indicating that ERK2 is the active ERK MAPK in the margin and essential for epiboly initiation and further progression of the developmental program (Krens et al., manuscript in preparation). Possibly ERK2 also functions in mesendodermal differentiation processes in the blastula margin, as FGF is known to activate the canonical MAPK pathway in a Ras dependent manner (reviewed by Gotoh and Bottcher [7,8]). The severe phenotype of ERK2 morphants indicate that ERK2 has a more dominant role than ERK1 during early developmental processes, as also suggested by the mice knockout phenotypes. Here we aim to further determine specific downstream gene targets of ERK1 and ERK2 during vertebrate development, by performing expression profiling analysis using a microarray approach. We compared the expression profiles of ERK1 and ERK2 knockdown embryos, using specific morpholino antisense oligonucleotides (MO), which specifically block the translation of a gene of interest into a functional protein [9]. Recently developed software programs and web-based analysis tools, e.g. Rosetta Resolver, GenMAPP and GeneTOOLS eGOn were used for the processing and comparisons of large expression datasets and biological interpretation of the data and to facilitate the prediction of interconnections between developmental signaling pathways that were tested by biological assays (qPCR and in situ hybridizations). Analysis of the obtained data revealed that ERK1MO and ERK2MO knockdown affect signature sets of common target genes, as well as signature sets of specific genes. Surprisingly, we also identified gene sets in which the expression patterns were anti-correlated. Several signature marker genes identified in this study were confirmed by quantitative real time PCR and in situ hybridization. We performed signaling pathway analysis on the obtained ERK1 and ERK2 transcriptome signatures, using the GenMAPP software program [10,11] for the analysis of important signaling cascades during early vertebrate development. These include BMP, FGF, Nodal and Wnt signaling pathways [12]. For ERK1 knockdown we identified a connection with genes involved in dorsal-ventral patterning and subsequent embryonic cell migration. For ERK2 knockdown we identified a connection with genes involved in mesoderm and endoderm initiation, differentiation and patterning. Many of these genes also play a role in morphogenic cell migration processes during later stages of development. The outcomes of the predictions for ERK2 knockdown on developmental signaling were confirmed by in situ hybridization experiments indicating that ERK2 controls mesoderm and endoderm initiation, maintenance and patterning. Results Distinct gene expression signature sets of ERK1 and ERK2 knockdown embryos A morpholino knockdown approach was used to block translation of either ERK1 or ERK2 by injection of 0.4 mM (= 3.4 ng/embryo) morpholinos (MO) targeting ERK1 (ERK1MO) or ERK2 (ERK2MO). The knockdown embryos, also referred to as morphants, showed severe phenotypes after depletion of ERK2. These embryos did not enter epiboly at 4.5 hpf and the blastula cells remained on top of the yolk, preventing further development of the embryo (Fig. (Fig.1C).1C
The specificity of ERK1 and ERK2 knockdown phenotypes was rescued by co-injection of synthetic mRNA (data not shown, manuscript in preparation), western blot analysis (Fig. (Fig.1J)1J Addition of different MEK specific inhibitors (U0126 or PD98059, Cell Signaling technologies), did not result in the same phenotypes as obtained by the ERK2MO mediated knockdown. The inhibiting effects of these drugs were confirmed by Western blot analysis, but apparently these effects were not efficient enough to block epiboly (data not shown). Because it is not possible to address the specific functions of either ERK1 or ERK2 using these chemical inhibitors, we did not proceed with these experiments. These data prove the functionality of the morpholino-mediated knockdown of either ERK1 or ERK2. In addition, the severe phenotype of ERK2 morphants indicate defects in crucial early developmental processes and most likely affects the expression levels of a larger number of genes than knockdown of ERK1. Distinct ERK-knockdown gene expression profiles in time To identify specific gene pools affected by the knockdown of ERK1 or ERK2, and to identify possible downstream targets, microarray based transcriptome analysis was performed using Agilent zebrafish microarrays. As a control for aspecific morpholino effects, a standard control morpholino (GeneTools Philomath, OR, USA) was injected in the same concentration. This did not result in any phenotypes during zebrafish development. The RNA from these standard control MO injected embryos was used as a reference to compare the transcriptomes of both ERK1MO and ERK2MO injected embryos. We annotated the Agilent 22K-zebrafish microarray chip by BLAST searches with all oligonucleotide sequences in the zebrafish genome. From the complete number of 21495 oligonucleotides from the Agilent 22K zebrafish chip, 16675 oligonucleotides were assigned a Unigene ID (build #105). The phenotypic effect of ERK2 depletion was observed at 30% epiboly indicating an altered gene expression profile at earlier stages. Therefore we analyzed the gene-expression profile of ERK2 morphants at more time points than ERK1 morphants (Fig. 2A,B
Comparison of the gene expression profiles of ERK1 and ERK2 morphants at various stages showed a larger number of Unigene identifiers with significant changes (p < 10-5) in ERK2 compare to ERK1 morphants in time, as illustrated in a Venn-diagram (Fig. (Fig.2A2A Comparing the effect of ERK1 and ERK2 knockdown, we found distinct gene expression signature sets during embryonic development. (Fig. 2E,F Because we observed a strong activated ERK signal in the margin at the onset of epiboly, we compared the expression levels of a selection of genes that are described to be expressed in the margin at the onset of epiboly in time. To do so, a gene-expression trend-line of the selected margin genes for ERK1 and ERK2 morphants was constructed (Fig. 3A,B
The identified gene-sets of correlated and anti-correlated regulated genes by knockdown of either ERK1 or ERK2 at 30% epiboly are listed and annotated [see Additional file 1, tables 1 and 4]. To identify the ERK1MO and ERK2MO specific genes, we focused on the genes that were most significantly affected. Therefore we used the following criteria: the absolute fold change must be at least 1.5 in each independent replicate and the common p-value provided by the error-model taking into account all hybridizations must be smaller than 10-5. The genes that were only found in either ERK1MO or ERK2MO gene-pools were manually annotated and assigned gene designations [see Additional file 1, tables 5 and 6]. Quantitative real time PCR analyses confirm the different ERK1- and ERK2- knockdown gene expression profiles To confirm the results of the microarrays experiments, quantitative reverse transcriptase PCR analysis was performed on seven regulated genes at 4.5 hpf (30% epiboly) that were chosen as hallmarks of the differences between the ERK1 and ERK2 morphant expression profiles. The expression levels were tested on the same RNA samples as used for the microarray analysis for cdh2 (cadherin 2, neuronal, NM_131081), mycn (v-myc, myelocytomatosis viral related oncogene, neuroblastoma derived, NM_212614), erm (ets related protein erm, NM_131205), cfos (FBJ murine osteosarcoma viral oncogene homolog, NM_205569), mos (moloney murine sarcoma viral oncogene homolog, NM_205580), snai1a (snail homolog 1a Drosophila, NM_131066) and vegf (vascular endothelial growth factor A, NM_131408) (Fig. (Fig.4).4
In summary, the qPCR data confirmed the change in expression levels of the selected genes as observed by microarray analysis for all genes tested, thereby confirming the unique gene expression profiles for ERK1MO and ERK2MO mediated knockdown in early zebrafish development at 4.5 hpf (30% epiboly). Gene Ontology (GO) analysis The gene expression signatures of the ERK1 and ERK2 morphants were used to perform gene ontology (GO) analysis. This provides an unbiased biological gene enrichment analysis based on biological properties (GO-terms) assigned per gene. Gene ontologies describe gene products in terms of their associated biological processes (GO:0008150), cellular components (GO:0005575) and molecular functions (GO:0003674) in a species-independent manner. The results of this analysis showed a significant relative over- or under-representation of the number of Unigene IDs in ERK1 versus ERK2 morphants within the GO categories (Fig. (Fig.5).5
Comparing the ERK1 and ERK2 knockdown signature sets various particular differences in over- or under-represented GO-terms were found. For example, both the GO-terms cell cycle (GO:0007049) and apoptosis (GO:0006915) are significantly enriched upon ERK2 knockdown. However, looking at the gene-lists in more detail inhibitory factors of apoptosis are mostly down-regulated, whereas positive regulators of cell cycle were up-regulated, indicating that apoptosis was not induced by the depletion of ERK2 at 30% epiboly (also see Fig. Fig.2D)2D The GO-enrichment analysis showed that the number of genes within the GO-cluster 'development' (GO:0007275) were significantly under-represented for both ERK1 (19 genes) and ERK2 (136 genes) morphants. From the 19 development-related genes whose expression was affected by ERK1 knockdown, 12 genes (63%) were not found in the ERK2 knockdown signature set. This supports the notion that ERK1 and ERK2 may have distinct functions during embryogenesis by affecting the gene-expression of common and distinct genes sets during vertebrate development. GenMAPP Pathways for zebrafish To further analyze putative down stream targets of ERK1 and ERK2 involved in early development, we focused on essential signaling pathways that are involved in early embryonic differentiation and patterning; Nodal, FGF, Wnt and BMP-signaling pathways (Fig. (Fig.11)11
Pathway Analysis of ERK1MO and ERK2MO mediated knockdown expression profiles The Unigene ID linked ERK1MO and ERK2MO signature sets that were used for GeneMAPP analysis were not limited by fold change but instead we used all genes that had a combined p-value for changed expression, compared to the standard control morpholino treated embryos, smaller than 10-5. As previously mentioned, the number of genes that showed a changed expression in ERK2MO compared to ERK1MO injected embryos was far larger. Therefore, as expected, more genes with changed expression levels were found in the in silico GenMAPPs signaling pathways for ERK2MO, than for ERK1MO. Knockdown of ERK1 did show only one gene (smurf1) with a significantly changed expression level within our BMP signaling GenMAPP (Fig. (Fig.9).9 The effect of depletion of ERK2 was far more severe in most of the analyzed signaling processes (Fig. (Fig.66 The Wnt ligand Wnt11 and receptors (frz7a, 7b, 8a, 9 and 10) and the central mediator β-catenin1 were down-regulated in ERK2 morphants, suggesting a severe inhibitory effect or even complete block of these pathways at this level (Fig. (Fig.8).8 The effect of ERK2 knockdown on BMP signaling is also complex, as bmp4 is up-regulated whereas bmp1a/tolloid and bmp6 are down-regulated (Fig. (Fig.9).9 Biological confirmation of Pathway Analysis based prediction To confirm predicted effects of the GenMAPP pathway analysis experimentally and to add information on the localization of expression, we performed whole mount in situ hybridization on ERK1 and ERK2 morphants at 30% epiboly with marker genes regulated by Nodal, BMP, Wnt and FGF (Fig. (Fig.6,6
The lefty 1 (lft1, antivin1) gene is a member of the TGF-beta super-family that regulates left-right axis formation during embryogenesis via antagonistic activity against nodal, another TGF-beta super-family member. Expression starts at blastula stage, immediately after initiation of zygotic transcription, and is localized in the whole blastula margin at late blastula – 30% epiboly stage [21]. Whole mount in situ hybridization with lefty1 probe (Fig. 10D–F In zebrafish, vox and vent interact with bozozok (boz), which is the earliest expressed dorsal-specific gene, and studies of boz embryos and the effects of ectopic boz expression indicate that it functions at the top of a hierarchy. Vox and vent are proposed to be repressors of boz expression since ectopic vox and vent eliminated the appearance of boz to establish the dorsal organize [15]. The expression signatures from the ERK1 and ERK2 morphants revealed that vox expression was not significantly changed in ERK1 morphants, but was down-regulated in ERK2 morphants., whereas for vent -expression this seemed to be opposite, as its expression was down-regulated in ERK1 morphants, but not significantly changed in ERK2 morphants (Fig. (Fig.6).6 The zebrafish ntl gene is, like the tbx6 gene, a member of the Brachyury-related T-box family of genes. Notail (ntl/brachyury) is involved in mesoderm development, as described in the legend to figure figure11.11 Tbx6 is exclusively expressed in the ventral mesendoderm and its expression is linked to ventral mesoderm specification [25]. In ERK1 morphants the in situ hybridization experiment showed that tbx6 expression was not extended as far dorsally as in wild type embryos, as tbx6 expression at the putative dorsal side of these embryos was severely reduced (Fig. 10P,Q The obtained results by whole mount in situ hybridization using gsc, lft, vox, vent, ntl and tbx6, confirm or support the predictions made by the GenMAPP analysis, as the changes in their expression levels are in agreement with the predictions obtained by the signaling pathway analysis of the microarray data. Discussion Specific functions of most proteins in vertebrate development remain elusive because of potential redundancies. In this manuscript we present a case study that indicates that the combination of micro-array analysis and targeted knockdown of essential embryonic genes in zebrafish can provide new insights in the specific targets of key regulators of development. For this study we have chosen the mitogen activated protein kinase members ERK1 and ERK2 because they are involved in virtually all eukaryotic cellular processes and signaling networks but still little is known of their specific functions in development. The proteins show high amino acids identity and have redundancy potential; however this does not exclude specific target genes. These archetypal signaling proteins are good examples for showing the power of this approach since the upstream activation pathways for ERK1 and ERK2 are highly similar, and many of their known downstream targets are common. In contrast to this, mice and zebrafish studies indicate distinct roles for both ERKs in cellular proliferation, oncogenic transformation and development. A major bottleneck for further studies is that relatively few in vivo downstream targets of these kinases and upstream activators such as MEK1 and MEK2 have been identified conclusively. Our manuscript uses microarray technology and bioinformatics to document the functional differences between the ERK1 and ERK2 proteins at the transcriptome level at different time points during zebrafish development. The obtained data is projected on a model of our current knowledge of several developmental signaling pathways. This gives new mechanistic insights in how ERK signaling is functioning and integrates with other known effectors of vertebrate embryogenesis. ERK1 and ERK2 target distinct genes during early zebrafish development Comparison of the gene expression profiles of the ERK1 and ERK2 morphants during early embryogenesis, with standard control MO injected embryos as a shared reference, showed specific gene expression profiles. Distinct gene expression signatures were obtained for ERK1 and ERK2 knockdown embryos, proving that both ERK1 and ERK2 target specific gene pools during zebrafish embryogenesis (Fig. (Fig.2).2 The higher number of genes affected by the knockdown of ERK2 is in agreement with the severe phenotype of ERK2 knockdown embryos (Fig. (Fig.11 ERK1 and ERK2 are involved in different developmental processes For biological interpretation of the obtained expression profiles, analysis of gene ontology (GO) was used to indicate processes that are likely to be affected. Different gene ontology clusters showed a relative enrichment in ERK1 versus ERK2 knockdown gene expression signatures. Since the annotation of the zebrafish genome is the limiting factor in assigning biological functions we have focused on gene ontologies that are relatively well known and have further supported the analyses by manual annotation of our signature sets. This led for instance to the observation that the Biological GO-clusters "development" was significant under-represented for both ERK1 and ERK2 knockdown. More detailed analysis was performed using the signaling-pathway based GenMAPP gene map annotator and pathway profiler program. By performing complete gene expression profiles (p < 10-5) without a fold-change cut-off in pathway analyses, we address both primary and secondary effects related to ERK knockdown from a morphogenetic perspective. Our observations led us to propose a model for distinct effects of ERK1 and ERK2 knockdown in developmental signaling processes, by effecting common as well as distinct genes (Fig. (Fig.2G).2G Stringent knockdown conditions, as applied in this array-based study, showed that in ERK1 morphants the ventrally expressed patterning gene vent was down-regulated, but also the BMP inhibitory gene smurf1 was up-regulated, possibly responsible for inhibition of BMP signaling on the ventral side (Fig. 11B,D ERK2 signaling is essential for the maintenance of the mesendodermal cell fates In ERK2 morphants no active MAPK was detected at the margin at 4,5hpf (data not show) suggesting that Ras-Raf-MEK-ERK dependent FGF signaling and subsequent downstream signaling was blocked. FGF signaling acts as a competence factor for cells to respond to Nodal mediated mesoderm induction. As our data show that ERK2 morphants are severely impaired in both FGF and Wnt signaling it is likely that mesoderm progenitor cells in the margin are affected in the maintenance of the mesodermal cell fates (Fig. (Fig.1111 Drosophila, FGF-dependent ERK activation was shown to be required for proper mesoderm dispersal [38-40]. In Xenopus, ERK2 was shown to be required for mesoderm differentiation [41]. Mouse erk2-/- embryos also fail to form mesoderm at E6.5 and E7.5 based on histological criteria, but erk2-/- embryonic stem cells were still capable of forming mesoderm. However, treatment of these ES cells with the MAPK inhibitor PD184352 decreased total ERK activity in these cells and expression of the mesoderm marker brachyury/ntl (essential for posterior mesoderm and axis formation) [26]. Our gene expression profiling shows that ERK2 plays a role in mesoderm development based on additional mesoderm markers (e.g. spt/tbx16, tbx6), but importantly also by addressing the upstream signaling mechanisms involved in mesoderm initiation and maintenance. It should be noted that ERK-activation is not only mediated by FGF signaling, but also influenced by other growth factors (PDGF, VEGF), G-protein coupled receptor signaling and hormone- and Ca2+ signaling pathways. A nice example that demonstrates the complexity of interconnections, redundancy and crosstalk between the different pathways is the work of Poulain et al, (2006) showing that combinatorial Nodal, FGF and BMP signaling regulates endoderm formation in zebrafish. These authors also reported that activation of FGF-signaling or injection of constitutive active (rat) ERK2 lead to phosphorylation of SOX32 and repression of the endoderm marker sox17. However, in our study, ERK2 morphants showed a reduced expression of the upstream Nodal responsive genes gata5, sox32 and sox17. These genes are normally expressed in presumptive endoderm progenitor cells in the margin at 4,5 hpf [42]. This suggests that depletion of ERK2 also affects endoderm differentiation (Fig. (Fig.11).11 Conclusion Our analysis of the gene expression microarray data revealed that ERK1 and ERK2 knockdown affected a set of common, as well as specific downstream genes. Interestingly, we also discovered a set of genes with anti-correlated expression. The gene ontology analyses show that ERK1 and ERK2 have specific roles in embryogenesis and target distinct gene sets involved in vertebrate development, confirming the embryonic knockdown phenotypes. These gene sets are large and considering the early embryonic time points of analyses, most likely include many direct transcriptional targets at least at the oblong stage. At later stages we expect to have identified also several secondary effects that are due to phenotypic changes. The signaling pathway analysis on the ERK1 and ERK2 transcriptome signatures using the GenMAPP software program for analysis of BMP, FGF, Nodal and Wnt signaling pathways indicated distinct roles for these MAP kinases. For ERK1 knockdown we identified a connection with genes involved in dorsal-ventral patterning and subsequent embryonic cell migration. For ERK2 knockdown we identified a connection with genes involved in mesoderm and endoderm initiation, differentiation and patterning. The outcome of the predictions for ERK2 knockdown on developmental signaling were confirmed by the observed effects on mesoderm and endoderm patterning and subsequent whole mount in situ hybridization experiments. Our results demonstrate the strength of gene expression profiling of morpholino knockdown embryos in combination with versatile bioinformatics tools in order to show common functions as well as distinct functions for highly related signaling proteins such as ERK1 and ERK2. Methods Zebrafish Morpholino knockdown experiments Zebrafish embryos were injected at the one-cell stage with 1 nl of the solubilized compounds in 1× Danieau's buffer [58 mM NaCl, 0.7 mM KCl, 0.4 mM MgSO4, 0.6 mM Ca(NO3)2, 5.0 mM HEPES; pH 7.6] containing 1% Phenol red solution (Sigma). Definition of stages was according to Kimmel et al. At 1K-stage (3hpf), embryos with a red animal pole were selected as positive-injected embryos. To block translation of the ERK1 or ERK2 protein, 0.4 mM (3.4 ng) morpholinos (MOs) were injected per embryo. MOs were targeted against the 5'-UTR of the respective mRNAs (GeneTools Philomath, OR, USA): ERK1-MO, 5'-TCTGTCCGCAAATCGTCGCCTTCGC; ERK2-MO, 5'-CACCCAAAAGCACCAGG AAAAGCTC. As a control, the standard control morpholino standard control MO 5'-CCTCTTACCTCAGTTACAATTTATA was used at the same concentration. Injected embryos were kept at 28°C until desired stages, until sacrifice. RNA isolation from zebrafish embryos The zebrafish embryos were homogenized in liquid nitrogen and total RNA was extracted using Trizol reagent (Invitrogen) according to the manufacturer's instructions. To remove genomic DNA, RNA samples were incubated at 37°C for 15 min with 10 units of DNaseI (Roche). The RNA samples were purified using the RNeasy kit (Qiagen) according to the RNA Cleanup protocol. Total RNA concentrations were determined spectrophotometrically using a Nanodrop ND-1000 (Isogen Life science). Optical density A260/A280 ratios of all samples ranged from 1.8–1.9, indicating high purity. Experimental design, Labeling and Hybridization of Agilent 22K-microarrays A total of 19 Agilent 22K-microarray hybridizations were performed for this gene expression profiling study of ERK1 versus ERK2 knockdown during development. A minimum of 2 independent biological replicates were analyzed for each biological sample In the case of ERK1 at 80% epiboly and ERK2 at 30%- and 80% epiboly, additional technical replicate were hybridized for each biological replicate, including dye swaps. For each biological sample, a number of 70–100 morpholino injected embryos were collected. The RNA from standard control MO injected embryos was labeled with Cy3 and those of ERK1MO and ERK2MO injected embryos were labeled with Cy5, using the Agilent Low RNA input linear amplification kit. Hybridization and scanning were performed according to standard Agilent protocol by Service XS (Leiden, the Netherlands). Data analysis of Agilent 22K-microarrays Feature Extraction also performed by Service XS using Agilent FE 8.5 software. Our data has successfully completed the curration protocol by MIAMExpress in the EBI public Array-express database [43]. Subsequent analysis was performed using the default settings implemented in Rosetta Resolver v 7.0 for an error modeling-based normalization. For the analysis and detailed annotation shown in the Venn diagrams and bar-graphs, the combine p-value per gene had to be 10e-5. For the annotated tables we focused on the genes that were most significantly affected. For that selection we used the following criteria: the absolute fold change should be at least 1.5 in each independent replicate; and the p-value provided by the error-model taking into account all hybridizations combined must be smaller than 10-5 to compensate for multiple testing false positives. For Gene Ontology analysis, the Unigene ID-linked gene expression signature sets of the ERK1 and ERK2 morphants were uploaded into the GeneTools eGOn V2.0 web-based gene ontology analysis software (explore Gene Ontology, database build #97) [44]. These signature sets comprised 575 Unigene IDs in the case of ERK1 morphants and 2987 Unigene IDs in the case of ERK2 morphants were compared to the complete set of 21485 Unigene IDs linked probes from the Agilent 22K zebrafish microarray chip (Biological Process; 6036 Unigene IDs, Molecular Function; 6322 Unigene IDs and Cellular Component; 5606 Unigene IDs). We determined the significantly over- or under represented Gene Ontology clusters in the ERK1MO and ERK2MO Unigene ID linked signature sets (p-value < 0.05 or 0.02). The number of GO-terms was reduced by excluding GO clusters with high similarity in representative genes. To ensure statistical relevance, also the GO-clusters that contained less than 10 Unigene IDs were also removed. The relative fold of gene-enrichment within the ERK1- and ERK2-morphant signature sets was calculated for the selected GO-terms. For the tables used for GeneMAPP analysis we took a less stringent approach not limiting the number of genes by fold change, therefore using all genes that had a combined p-value smaller than 10-5. In this approach we focus on transcriptional effects that can be linked to the phenotypic changes as a result of pathway blocking by ERK knockdown. cDNA synthesis and Quantitative PCR cDNA synthesis was performed using a TGradient Thermocycler 96 (Whatman Biometra) according to the manufacturer's instructions. RNA samples were identical to those used for microarray hybridization. Reactions were performed in a 20 μl mixture of 150 ng RNA, 4 μl of 5× iScript Reaction mix (Bio-Rad) and 1 μl of iScript Reverse Transcriptase (Bio-Rad). The reaction mixtures were incubated at 25°C for 5 min, 42°C for 30 min, and 85°C for 5 min. Quantitative real-time PCR was performed using the Chromo4 Four-color Real-time PCR detection system (Bio-Rad laboratories, Hercules, CA) according to the manufacturers' instructions. Gene-specific primers for quantitative real-time PCR were designed, using Beacon Designer software, to generate single gene-specific amplicons of 75–150 nucleotides. Reactions were performed in a 25 μl volume comprised of 1 μl cDNA, 12.5 μl of 2× iQ SYBR Green Supermix (Bio-Rad) and 10 pmol of each primer. Cycling parameters were 94°C for 3 min to activate the polymerase, followed by 40 cycles of 94°C for 15 sec and 59°C for 45 sec. Fluorescence measurements were taken at the end of each cycle. Melting curve analysis was performed to verify that no primer dimers were amplified. All reactions were done in duplicate or triplicate and the threshold cycle CT values were plotted against the base 10 log of the amount of cDNA by using Opticon Monitor 3.1 (Bio-Rad) according to the manufacturer's instructions. For evaluation of PCR efficiencies of all primers sets standard curves were generated using serial diluted cDNA samples (dilution factors of 1, 5, 25, 125 and 625) and strong linear correlations between the CT values and the log of input cDNA amount were obtained, indicating correlation coefficiencies ranging from 98% to 101%. Data were normalized using the Genex macro provided by Bio-Rad. The expression level were tested for cdh2 (NM_131081), mycn (NM_212614), erm (NM_131205), cfos (NM_205569), mos (NM_205580), snai1a (NM_131066) and vegf (NM_131408) on the same RNA samples used for the array analysis: 0.4 mM (= 3.4 ng/embryo) ERK1MO, ERK2MO and standard control MO injected embryos, collected at 30% epiboly. α-actin was taken as reference and it showed unchanged expression level between standard control MO injected and ERK1MO or ERK2MO injected embryos. Sequences of forward and reverse primers were 5'-CGAGCAGGAGATGGGAACC-3' and 5'-CAACGGAAACGCTCATTGC-3' for β-actin (accession no. AF057040). Cdh2; qP1fw 5'-ACAAGAAGCAGAAGTGTGTGAGC-3' and qP2rv AGCGTAGGGTCCAGCGTTG-3', Mycn; qP1fw 5'-GAGGATGATGAGGAAGATGATGAAG-3', qP2rv 5'-CCTGCCTGAGAGTTGGAGAC-3', erm; qP3fw, 5'-TCCACCAACTCTCAATCAAACAGG-3' and qP4rv 5'-AGATGGGCTTCTCCGTCATACC-3', cfos; (NM_205569) qP1Fw 5'-TGACCTGGAGCCGCTTTGC-3' and qP2rv 5'-GGTAGGTGAACATGAAGGAAGACG-3', mos; (NM_205580) qP1fw 5'-CCCTCACCAATCCCCGTCAC-3' and qP2rv 5'-GAGCCTGTGTGCGACTTTACC-3', snai1a; qP3fw 5'-TCCTGCCCACACTGTAACCG-3' and qP4rv 5'-GCGACTAAAGGTGCGAGAGC-3', vegf; qP1fw 5'-GCGGCTCTCCTCCATCTG-3' and qP2rv 5'-ACATCCATGAAGGGAATCACATC-3'. Whole mount in situ hybridization Embryos were fixed overnight in 4% paraformaldehyde in PBS at 4°C and in situ hybridization was performed as described previously [45] using described probes for gsc, lft1/antivin, vox, vent, ntl and tbx6. Authors' contributions GK Was involved in all experiments, experimental design and bioinformatics analyses. He co-drafted the manuscript, made revisions critically for important intellectual content and submitted the data to the Miamexpress database. MC uploaded data in the Rosetta Resolver database and assisted in bioinformatics analyses. SH carried out the labeling reactions for micro-array analyses and performed Q-PCR experiments. ES-J performed the western blot analyses, co-drafted the manuscript, made revisions critically for important intellectual content and participated in design and coordination. HS co-drafted the manuscript, made revisions critically for important intellectual content and gave final approval for the final version to be published and participated in design and coordination. Additional file 1 Additional data is submitted as tables S1 to S6 consists of the ERK1 and ERK2 knockdown commonly and anti-correlated regulated probes (table S1 to S4), containing the assigned gene designations (Unigene, accession number and sequence name), the fold of the changed expression and p-value (smaller than 10-5 to compensate for multiple testing false positives) for these genes. The tables S5 and S6 contain genes selected by a stringent selected that were only found in either ERK1MO or ERK2MO gene-pools were manually annotated and assigned gene designations as listed in. Table S1 – Anti-correlated regulated genes1: ERK1MO up-regulated, ERK2MO down-regulated. Table S2 – Anti-correlated regulated genes2: ERK1MO down-regulated, ERK2MO up-regulated. Table S3 – Commonly down-regulated genes by ERK1or ERK2 knockdown at 30% epiboly. Table S4 – Commonly up-regulated genes by ERK1or ERK2 knockdown at 30% epiboly. Table S5 – ERK1 knockdown specific genes at 30% epiboly, filtered by a 1.5 fold up- or down- regulation per experiment and a common P-value of 10-5 . Table S6 – ERK2 knockdown specific genes at 30% epiboly, filtered by a 1.5 fold up- or down- regulation per experiment and a common P-value of 10-5 Click here for file(1.7M, doc) Additional file 2 ERK1 knockdown phenotype at 24 and 48hpf. Images show representative examples of surviving ERK1 morpholino injected embryos with a tailless phenotype at 24 and 48hpf. Click here for file(234K, pdf) Acknowledgements We gratefully acknowledge Zoltan Hegedus for the help with the annotation of the complete 22K Agilent zebrafish microarray chips. We thank Carl Philipp Heisenberg for providing us with probe constructs, Professor David Kimelman for providing the vox and vent probe constructs and Eric Schmidt from the Robert Ho-lab., for providing the tbx6-probe construct In addition, we thank Annemarie Meijer and Enrique Salas-Vidal for stimulating discussions. This work was financially supported by the European Commission 6th Framework Program (LSHG-CT-2003-503496, ZF-MODELS). References
|
PubMed related articles
Your browsing activity is empty. Activity recording is turned off. |
|||||||||||||||||||||||||
Curr Opin Chem Biol. 2005 Jun; 9(3):325-31.
[Curr Opin Chem Biol. 2005]J Biol. 2006; 5(5):14.
[J Biol. 2006]J Biol. 2006; 5(5):13.
[J Biol. 2006]Dev Cell. 2007 Apr; 12(4):615-29.
[Dev Cell. 2007]Science. 1999 Nov 12; 286(5443):1374-7.
[Science. 1999]Biochim Biophys Acta. 1996 Aug 8; 1288(1):F1-7.
[Biochim Biophys Acta. 1996]Endocr Rev. 2005 Feb; 26(1):63-77.
[Endocr Rev. 2005]Nat Genet. 2000 Oct; 26(2):216-20.
[Nat Genet. 2000]Nat Genet. 2002 May; 31(1):19-20.
[Nat Genet. 2002]Annu Rev Genet. 2005; 39():561-613.
[Annu Rev Genet. 2005]Dev Dyn. 1995 Jul; 203(3):253-310.
[Dev Dyn. 1995]Annu Rev Genet. 2005; 39():561-613.
[Annu Rev Genet. 2005]Nat Genet. 2002 May; 31(1):19-20.
[Nat Genet. 2002]Dev Biol. 2000 Aug 15; 224(2):275-85.
[Dev Biol. 2000]Curr Biol. 2004 Sep 21; 14(18):1632-8.
[Curr Biol. 2004]Dev Biol. 2003 Sep 15; 261(2):391-411.
[Dev Biol. 2003]Development. 2006 Aug; 133(16):3265-76.
[Development. 2006]Science. 1998 Apr 24; 280(5363):596-9.
[Science. 1998]Development. 1993 Apr; 117(4):1261-74.
[Development. 1993]Development. 1999 Jan; 126(2):229-40.
[Development. 1999]Dev Biol. 2000 Aug 15; 224(2):275-85.
[Dev Biol. 2000]Development. 1992 Dec; 116(4):1021-32.
[Development. 1992]Development. 2003 Oct; 130(19):4639-54.
[Development. 2003]Dev Biol. 2003 Dec 15; 264(2):456-66.
[Dev Biol. 2003]Dev Biol. 1997 Mar 1; 183(1):61-73.
[Dev Biol. 1997]J Biol. 2006; 5(5):13.
[J Biol. 2006]J Biol. 2006; 5(5):14.
[J Biol. 2006]Science. 1999 Nov 12; 286(5443):1374-7.
[Science. 1999]EMBO Rep. 2003 Oct; 4(10):964-8.
[EMBO Rep. 2003]Proc Natl Acad Sci U S A. 2003 Oct 28; 100(22):12759-64.
[Proc Natl Acad Sci U S A. 2003]Nat Rev Genet. 2006 May; 7(5):360-72.
[Nat Rev Genet. 2006]Nature. 2003 Jul 24; 424(6947):448-52.
[Nature. 2003]Curr Biol. 2004 Sep 21; 14(18):1632-8.
[Curr Biol. 2004]Development. 1996 Dec; 123():143-51.
[Development. 1996]Development. 2004 Feb; 131(3):629-41.
[Development. 2004]Dev Biol. 2006 Dec 15; 300(2):612-22.
[Dev Biol. 2006]Development. 1997 Sep; 124(18):3535-41.
[Development. 1997]Genes Dev. 2004 Mar 15; 18(6):687-99.
[Genes Dev. 2004]EMBO J. 1995 Jun 1; 14(11):2491-8.
[EMBO J. 1995]Proc Natl Acad Sci U S A. 2003 Oct 28; 100(22):12759-64.
[Proc Natl Acad Sci U S A. 2003]Development. 2002 Jan; 129(2):275-86.
[Development. 2002]BMC Bioinformatics. 2006 Oct 24; 7():470.
[BMC Bioinformatics. 2006]Development. 1993 Dec; 119(4):1203-15.
[Development. 1993]