article: Drosophila provides a powerful system for defining the complex genetic programs that drive organogenesis. Under control of the steroid hormone ecdysone, the adult heart in Drosophila forms during metamorphosis by a remodelling of the larval cardiac organ. Here, we evaluated the extent to which transcriptional signatures revealed by genomic approaches can provide new insights into the molecular pathways that underlie heart organogenesis. Whole-genome expression profiling at eight successive time-points covering adult heart formation revealed a highly dynamic temporal map of gene expression through 13 transcript clusters with distinct expression kinetics. A functional atlas of the transcriptome profile strikingly points to the genomic transcriptional response of the ecdysone cascade, and a sharp regulation of key components belonging to a few evolutionarily conserved signalling pathways. A reverse genetic analysis provided evidence that these specific signalling pathways are involved in discrete steps of adult heart formation. In particular, the Wnt signalling pathway is shown to participate in inflow tract and cardiomyocyte differentiation, while activation of the PDGF-VEGF pathway is required for cardiac valve formation. Thus, a detailed temporal map of gene expression can reveal signalling pathways responsible for specific developmental programs and provides here substantial grasp into heart formation.
  A traditional way of approaching organogenesis consists of focusing the analysis on discrete genes or simple gene networks, to evaluate their function in the development of particular cells within the organ. One would like, however, to draw a more global view of organogenesis in which the temporal and spatial cues are integrated in a unique picture. With the era of genomics, high-throughput expression analysis approaches supply complementary information to the single-gene approaches currently under way. Microarrays are currently the strongest technology platform for large-scale analysis of gene expression profiles. They provide an opportunity to simultaneously monitor the expression of thousands of genes in a single assay, thus providing genome-wide snapshots of transcriptional networks that are active in a particular tissue in a particular developmental context [1–3]. Here, we evaluated the relevance and the efficiency of a global genomic approach in one example of organogenesis: the formation of the adult heart in Drosophila melanogaster. The fruit fly is the simplest multicellular model organism with a heart, which is constituted of a linear tube that is certainly less complex than its vertebrate counterpart, but which forms and functions on a similar molecular and functional basis by acting as a myogenic muscular pump with automatic contractility. Formation of primitive cardiac tubes of fruit flies and vertebrates are well conserved, as are the molecular pathways responsible for their morphogenesis [4]. Choosing this system was dictated by its relative simplicity (the cardiac tube is formed by only 104 myocytes, which can be readily identified in vivo) and by the extensive knowledge that we have acquired of its developmental control [5]. The adult heart forms during metamorphosis by a remodelling of the larval cardiomyocytes without cell proliferation or cell migration. We have a detailed knowledge of the profound morphological and functional transformations that accompany the formation of the adult organ [5,6] (Figure 1A). These include, in particular, the destruction of a portion of the larval organ by programmed cell death (PCD), an important growth of the remaining myocytes, the formation of new inflow tracts and cardiac valves, and the acquisition of new physiological properties by most of the myocytes. In addition, the remodelling timetable is perfectly well defined [5,7]. Heart remodelling starts 30 h after puparation in response to the third rise of the steroid hormone ecdysone. Ecdysone acts as a temporal necessary cue to switch on heart remodelling, and blocking the Drosophila Ecdysone receptor (EcR) prevents all known cellular and molecular aspects of the remodelling process [5]. Even though we know that one important EcR output during heart remodelling consists of a modification of the expression and activity of Hox genes Ultrabithorax (Ubx) and abdominal-A (abd-A) [5], we still have a very poor knowledge of the genetic programs and the molecular pathways that are elicited to direct cardiac myocytes to adopt their final fates. We have undertaken a global systematic approach to this question. We show that transcriptional signatures identified from cardiac tubes dissected at carefully chosen time-points during the process provide an accurate and precise description of the main cellular events that occur, which fits very well with what we know of the process. From this observation, the expression modulation of genes encoding components of a few signalling pathways was taken as an indication of their potential implication in the process. We demonstrated, by a reverse genetic approach, that the fibroblast growth factor (FGF), Wnt, and the platelet-derived growth factor-vascular endothelial growth factor (PDGF-VEGF) signalling pathways induce specific developmental programs and that each of these are implicated in discrete events required for adult heart formation. Our study thus illustrates that integrating genomic and reverse-genetic approaches is an efficient way to provide comprehensive knowledge of an organogenesis process, and furnishes significant new insights into the signalling pathways involved in heart organogenesis.
  Cardiac tube remodelling coincides with the last ecdysone peak at 30 h after puparium formation (APF) [5]. Up to 27 h APF, the cardiac tube retains larval morphology and function and is morphologically and functionally divided into an anterior “aorta” and a posterior “heart” [5,8, 9] (Figure 1A). Heart beating stops between 27 h and 30 h APF. Then, most of the larval heart is eliminated by PCD and the adult heart progressively differentiates from the larval aorta. The larval aorta myocytes increase their size and the number of their myofibrils, and differentiate into working cardiomyocytes that also acquire a contractile automatic cardiac activity. Four pairs of inflow tracts (also referred to as “ostia”) differentiate from 16 cells of the larval aorta and three pairs of valves are newly formed. In addition, segment A5, which is part of the heart in the larva, transdifferentiates into a new structure, called the terminal chamber, that becomes innervated but loses its automatic contractile activity [5]. Finally, a ventral sheet of syncytial imaginal muscles develops beneath the cardiac tube. At 48 h APF, the first signs of adult cardiac activity are detectable. Based on this knowledge, we conducted a time-course analysis of the genome-wide expression dynamics of dissected cardiac tubes, with increased temporal precision around 30 h APF, corresponding to the maximum ecdysone rise [10]. The dissected material constitutes a highly enriched preparation of heart tissue, with a low level of noncardiac contaminants. In addition to the myocytes that constitute the cardiac tube, the whole preparation contained the attached pericardial cells [11] and the ventral layer of syncytial adult muscles that develop beneath the cardiac tube at metamorphosis [6]. Total RNAs were prepared from dissected cardiac tubes of staged pupae at eight successive time-points 21,24,27,30,33,36,42 and 48 h APF. PolyA+ RNAs were linearly amplified [12], labelled, and used for hybridization on Drosophila whole-genome microarrays. Given the number of time-points, a loop-design dedicated to time-course experiments [13] was chosen to perform our microarray study (Figure 1B). Each of the eight samples was hybridized twice in two different dye assignments, once with each of their two neighbour time-point samples in the loop. This resulted in 16 hybridizations with technical dye-swap replications (See Figure 1B and Materials and Methods). Four independent biological replicates were analysed to confer a high reproducibility and statistical significance of the expression data. The data were normalized, filtered, and plotted in scatter plots to estimate the quality of the normalized data. Data processing and normalization are described in details under Materials and Methods. Among 4,853 elements shown to be expressed in the pupal cardiac tube, we identified 2,394 genes that exhibited significant differential expression between time-points in using modified t-statistic significance analysis of microarrays (SAM) [14] with estimated q-values (false discovery rates) of ≤ 0. 05. By this procedure, we focused on further analysis of 1,660 genes that showed significant levels of differential expression at least 1. 8-fold in at least one condition through our time-course analysis (Table S1). Self-organizing map (SOM) clustering [15] of these significant genes demonstrated a temporal and progressive dynamic of gene expression with 13 distinct clusters showing diverse expression profiles (Figure 2). Sets of genes were defined as progressively repressed (clusters 1–5) or activated (clusters 8–12) during the remodelling process, or transiently activated (cluster 6 and 7) or repressed (cluster 13). The microarray expression data were validated by quantitative real-time reverse-transcriptase PCR (RQ-PCR). Seventeen genes with different levels of expression and different expression profiles were selected from each of the gene clusters and analysed for their expression by RQ-PCR. In all cases tested, the changes observed in the arrays were confirmed (Figure 3). The pattern of expression was very similar in both analyses, and the associated fold-change correlated closely. The temporal map of gene expression thus shows a highly dynamic profile of gene expression, suggesting that a complex network of transcriptional regulation underlies adult heart organogenesis. An important issue was to find out if we can deduce, from the functional characteristics of the genes found to be dynamically and timely coexpressed, the cellular and molecular events that are sequentially involved in cardiac remodelling. To this end, we searched for biased representation of gene function annotations within the individual expression clusters. As summarized below and detailed in Figure S1 and Table S2, the dynamic of overrepresented biological processes based on Gene Ontology (GO) annotations appropriately recapitulates the dynamic of adult heart formation and provides significant new insights into heart metamorphosis (Figure 4). Expression clusters 1 to 5 comprise progressively repressed genes. In cluster 2, overrepresentation of genes encoding ion channels or genes involved in muscle contractile function is likely to be linked to cessation of larval cardiac activity. Clusters 3 and 4 were enriched in genes annotated as involved in PCD (21 genes, p = 10−6), in agreement with the destruction of larval cardiac tube abdominal segments A6 and A7 as the first step of adult heart formation [5]. The main feature of transiently activated genes was the highly significant enrichment in signal transduction–related genes. Of 84 annotated genes in clusters 6 and 7,18 (p = 10−6) were annotated as functionally linked to cell surface receptor–mediated signal transduction. This strongly suggests that specific signalling pathways are activated in a timely fashion and required for cardiac remodelling; this was further analysed by reverse genetics (see below). Besides signal transduction, these clusters were characterized by an overrepresentation of genes involved in myogenesis that appears relevant to cardiomyocyte differentiation. A highly significant number of genes involved in energy metabolism (70 genes, p = 10−14) and muscle contraction (21 genes, p = 10−9) were found in clusters 8 to 12, as expected for growth and functional recovery of the organ. Moreover, genes annotated as involved in cell matrix adhesion were overrepresented in cluster 10, which may indicate an important remodelling of the extracellular matrix during adult heart formation (see associated batteries of gene expression in Figure S2). Finally, among the genes that are downregulated during remodelling but actively transcribed during periods of cardiac activity (cluster 13), the most salient feature was the overrepresentation of genes involved in carbohydrate metabolism, reflecting the dependence of myocyte contraction upon energy derived from sugar metabolism. In conclusion, global analysis of overrepresented biological functions within the coexpressed gene clusters provides an appropriate readout of the chronology of events occurring during adult heart formation and allowed us to gain significant insight into cardiac remodelling events. We subsequently focused our analysis on components of the ecdysone regulatory network and on the downstream signalling pathways, whose potential implication was first pointed out by this global analysis. Heart remodelling is prevented by cardiac tube–specific inactivation of ecdysone receptor function [5], indicating that adult heart formation is initiated by a cell autonomous response to ecdysone signalling. At metamorphosis, ecdysone induces a cascade of transcriptional activation, defining early and late target genes that are progressively activated and are intricately coordinated by changes in hormone titre. This signalling cascade has been mainly characterized at the first and second rise in ecdysone titre [16,17]. To date, no detailed expression data are available for the third and last ecdysone pulse, which drives cardiac tube remodelling. In addition, few microarray studies of ecdysone response at metamorphosis have been devoted to single tissues or organs [2,18,19]. We compared the genes differentially expressed during heart remodelling to data from three microarray studies that examined ecdysone-regulated processes: midgut metamorphosis, salivary gland cell death, and ecdysone-regulated genes at puparium formation [2,19,20] (Table S3). Of note, clusters 1 to 5 were highly enriched in genes that are also induced in the other processes, indicating that a population of genes is reused at distinct stages and in different tissues in response to ecdysone. The highest significant enrichment was observed for genes that are induced during salivary gland cell death: 18% of the genes induced during this steroid-dependent PCD (p = 10−40) were recovered in clusters 1 to 5 (Table S3). This result suggests that, in the cardiac tube as well, PCD may proceed by autophagy, very much like in the salivary glands. The significant enrichment of genes annotated for autophagic cell death in clusters 3 and 4 (11 genes, p = 10−6), and the recovery of a high proportion of autophagy-specific genes that change their expression during remodelling (Figure 5A) further support this assumption. The temporal expression map showed a clear dynamic expression profile of the annotated ecdysone-response genes recovered in our analysis (Figure 5B). Similarly to what occurs during the former ecdysone pulses in both salivary glands and midgut [21], the first activated genes encode EcR, Eip93F, broad (br), and Ecdysone-induced protein 74EF (Eip74EF), the characterized early response genes. Just downstream of this group of genes, Hormone receptor-like in 39 (Hr39) and Ecdysone-induced protein 78C (Eip78C) appeared to be transiently induced, suggesting that their function may be required for activation of a set of late response genes, including the nuclear receptors Hormone receptor-like in 46 (Hr46) and Ecdysone-induced protein 75B (Eip75B), and other ecdysone-related genes. Notably, the late upregulation of this set of genes, after occurrence of cell death and the onset of ecdysone titre decline, strongly suggests these late genes participate in differentiation of the adult heart rather than in PCD. As a whole, the ecdysone-induced transcriptional cascade in the cardiac tube appears to be similar to the ones observed in other ecdysone-dependent processes characterized so far [22]. Temporal and tissue specificity of the ecdysone-induced program is thus likely to be conferred by tissue-specific factors, the best candidates being transcription factors. Supporting this hypothesis, the Fork head transcription factor was recently shown to control the timing of ecdysone-induced cell death in the salivary glands [23]. A number of transcription factors have been identified in our transcriptome profiling (Figure S3) and future analysis of the function of these transcription factors in cardiac tube remodelling is expected to shed light on the mechanisms of ecdysone response specificity. The considerable overrepresentation of cell surface receptor–linked signal transduction annotated genes in clusters of transiently overexpressed genes (Figure 4) suggested that signal transduction processes play a central role in the adult organ formation. A list of genes encoding the core components of all known receptor-linked signalling pathways was generated from several gene annotation resources, and their temporal expression profiles in the transcriptome survey were further examined (see Table S4). From this dataset, we searched for pathways whose key components are overrepresented and display a timely ordered expression (see details in Materials and Methods). This selection procedure designated the FGF, Wnt, PDGF-VEGF, Notch, and Toll pathways as being potentially implicated (Figure 5C). Heart-specific targeted inhibition and/or activation of these pathways was used to evaluate their specific function. As detailed below, all except the Toll pathway are involved in cardiac tube remodelling, confirming the central role played by signalling pathways in this process and validating the procedure used for the selection of signalling pathways.
  An important challenge in understanding the mechanisms that govern the formation of a specific organ is to decipher the complex and dynamic genetic programs exhibited by the constituent cell types. Here, we integrated genomic and reverse genetic analysis to comprehensively determine the molecular pathways that participate in Drosophila adult heart formation. Importantly, many of our conclusions could only be drawn by examining the large datasets of heart-specific gene-expression changes that occur during heart metamorphosis. One of the major outcomes of our genome-wide transcriptome profiling approach is that changes in gene expression can be taken as indicative of the cellular events occurring during the process of interest. When applied with dense sampling of time-points during the complete organogenesis of a single tissue, the cardiac tube, this strategy led to the identification of many batteries of genes involved sequentially in this tissue-specific event. Substantial knowledge has been gained with respect to PCD, ecdysone signalling cascade, metabolism, and physiological pathways involved. Surprisingly, we showed here that signalling pathway components were subjected to transcriptional regulation, suggesting that activation and/or repression of these pathways could, at least in part, rely on the transcriptional control of some of their components. In this line, a recent transcriptome analysis has clearly demonstrated that transcriptional oscillation of a few signalling pathways underlies the vertebrate segmentation clock [36]. The oscillating genes were, however, found to be mainly targets of the signalling pathways instead of the integral components (receptors, ligands, nuclear effectors) of the pathways found in the present study. Candidate signalling pathways were therefore selected here on the basis of the timely ordered expression of key factors components. This strategy proved to be highly effective and pointed to specific signalling pathways whose implication during heart remodelling was subsequently genetically evaluated. Of note, the main features of adult heart organogenesis include segment A6 and A7 myocyte PCD, segment A5 myocyte trans-differentiation to form the adult terminal chamber, inflow tract and valve differentiation in segments A1 to A4, and development of a syncytial muscle sheet on the ventral side of the organ. Importantly, significant insights have been gained for each of these processes, emphasizing that our combination of positional (tissue specific) and temporal genome-wide expression survey allows for a substantial molecular understanding of heart organogenesis. Subsequent experiments will analyse the consequences of perturbations of the implicated signalling pathways upon the dynamics of gene expression profiling in order to identify potential targets of these pathways. Evolutionarily conserved transcription factors drive cardiac development in both Drosophila and vertebrates [37,38], suggesting that downstream genetic networks responsible for heart organogenesis might, at least partially, be conserved. Our results may as well designate conserved signalling pathways as playing similar functions in mammals. In support of this, the VEGF pathway is required for valve formation in mammals [32], and we demonstrated that the PDGF-VEGF fly' s pathway has analogous function. Valves are, however, formed by different cellular processes in flies and mammals, and it will be important to evaluate whether the immediate downstream events directed by this particular pathway are conserved in both phyla.
  UAS>PvrDN and UAS>Pvrλ were obtained from P. Rorth, dsRNA>Htl from K. VijayRaghavan, UAS>Dsh-Dix from J. Axelrod, UAS>Toll10B [35], Tll mutants (Tl r144, Tl 9QURE, Tl 1rxa, Tl r632) [34], TinCΔ5>LacZ [29]. The following lines were obtained from the Bloomington Drosophila Stock Centre: Nts, dsRNA>N, UAS>abd-A, UAS>armS10, UAS>HtlDN, and UAS>dTCFDN. GAL4 drivers were: 24B>Gal4 [39], NP5169>Gal4 (obtained from the Gal4 Enhancer Trap Insertion Database (http: //flymap. lab. nig. ac. jp/~dclust/getdb. html) and Hand>Gal4 (generous gift from A. Paululat). The P (tub-GAL80[ts]), was obtained from the Bloomington Drosophila Stock Center. Onset of pupal development corresponds to white pupae that were selected on the basis of spiracle eversion, absence of reaction following forceps contact, and absence of tanning. Individuals were kept for further development in an air incubator at 25 °C. Cardiac tubes were hand dissected from staged individuals. For each time-point sample, five cardiac tubes were dissected and stored at −80 °C in 300 μl of TRIzol solution prior to total RNA isolation. Four samples of five cardiac tubes each were generated for each time-point in order to generate the four biological replicates. Dissected cardiac tubes were collected in 300 μl of TRIzol and extracted according to Baugh et al [12]. Isolated total RNA (∼100 ng) was amplified with the Amino Allyl MessageAmp II aRNA Amplification Kit (Ambion) based on the RNA amplification protocol developed by Van Gelder et al [40]. The aRNA procedure begins with total RNA that is reverse transcribed using an oligo (dT) primer containing a T7 RNA polymerase promoter sequence. The reaction is treated with RNase H to cleave the mRNA into small fragments. These small RNA fragments serve as primers during the second-strand synthesis reaction, producing a double-stranded cDNA template for T7 in vitro transcription. This RNA was subjected to a second round of amplification with a second in vitro transcription reaction configured to incorporate the modified nucleotide (amino allyl UTP) into the aRNA during transcription for subsequent indirect labelling with fluorescent dyes Cy3 and Cy5. Dye-swap replications, in which each hybridization is done twice, with dye assignments reversed in the second hybridization, are used according to the experimental loop-design [41] shown in Figure 1B. In the case of eight sampling points in a time-series experiment [42], a simple loop-design is more efficient because it implies a small variance for log ratios and balancing varieties with dye-swapping. One of the main advantages of this design is to allow technical replicates, thereby eliminating variations that might result from differences in fluorescence dye intensities. In addition, this method allows direct comparisons of successive time-points via a chain of conditions, thereby removing the need for a reference sample of no intrinsic interest in our time-course analysis. To guarantee the significance of the expression variations, this loop-design microarray experiment was done four times with four independent biological replicates. Cy3- and Cy5-labelled aRNA samples were mixed in equal proportions and fragmented with the RNA Fragmentation Reagents (Ambion) to enhance aRNA hybridization, and hybridized on INDAC high-density oligonucleotide microarrays that contained 18,240 spots with long oligomers designed by the International Drosophila Array Consortium (http: //www. flychip. org. uk/services/core/FL002/) representing 14,444 different genes. After these competitive hybridizations (using Lucidea SlidePro Hybridizer), the slides are imaged using the scanner Axon Instruments 4200AL and fluorescence measurements are made separately for each dye at each spot on the arrays using Array Vision quantification software (Imaging Research Inc). 32 slides (eight for each biological replicate) were used in this study. Normalization of primary expression data was performed through two successive steps using both R software packages [43] SMA [44,45] and LIMMA [46]: Lowess normalization to normalize the M-values for each array separately (within-array normalization) without prior background correction, and quantile normalization to the A-values, making the density distributions the same across arrays to compare expression intensities between them (between-array normalization). Normalized expression values were averaged through Cy3 and Cy5 signal intensities according to dye-swap replications (see loop-design in Figure 1B) to assign only one expression value for each biological replicate. Microarray data were filtered for detectable expression level. Elements whose level of expression is lower or equal to the background control cut-off, defined as twice the average of the expression levels of negative controls spotted on the array, were excluded from further analysis. A total of 4,853 displayed expression above this cut-off. A modified t-statistic method SAM [14] in a multiclass response format was used to identify genes with statistically significant changes in gene expression, relative to the standard deviation of repeated measurements across the time-course stages. Predicted false discovery rate of 5% was used as the threshold for differential expression, leading to 2,394 genes that exhibited significant differential expression between time-points. The final dataset comprises 1,660 genes and was generated by using the median expression value for each time-point on biological replicates and by selecting only genes with at least 1. 8 fold-change in expression level in at least one condition through the expression kinetic analysis. Clustering analyses were performed by the SOM method [15] with an initial 8 × 8 geometry of nodes using EXPANDER 2. 0 software [47] from http: //acgt. cs. tau. ac. il/expander/ after gene standardization processing (mean = 0, variance = 1). By this procedure, we obtained 64 expression classes. These were further clustered by hierarchical clustering of predictor genes specific of each SOM class to get 13 significant distinct clusters. By this procedure, 99. 4% of the 1660 genes dataset were assigned to one cluster. The extracted datasets were visualized either by their expression profiles with EXCEL software or by their expression matrices with TreeView software [48] (Figure 2). The identification of statistically relevant over-represented GO terms in our gene clustering datasets was performed by using GOToolBox software [49] from http: //crfb. univ-mrs. fr/GOToolBox. All significant enriched GO terms in the whole BP hierarchy were analysed and their description was further restricted to BP annotation levels 4 to 6 to avoid the excessively detailed terms of the lower hierarchy levels as well as the poorly defined terms present in higher levels. In Figure 4, only cluster-enriched GO functions with a stringent p-value cut-off of 10−3 were considered. In the detailed Figure S1, the enrichment p-value cut-off was set to 5. 10−2 and the annotation levels considered extended to level 8 but only the GO terms hierarchically connected to the ones selected in Figure 4 were retained. Gene expression data comparisons were made between our microarray dataset and previously published microarray datasets using statistic package of R software. Each published gene list was split into genes that are either upregulated or downregulated, represented by up or down arrows in Table S3, and compared to expression clusters of genes with a 1. 8-fold cut-off from our microarray data analysis. Enrichment p-values were based on a test following the hypergeometric distribution. A list of genes encoding the most important components (receptor/ligand/nuclear effector) of all known receptor linked signalling pathways was established. A first gene list was generated from GO annotations of each particular signalling pathway. This gene list was then mainly pruned by the biochemical pathways described in The Interactive Fly (http: //flybase. bio. indiana. edu/) resource, and each gene was further analysed for its signalling function in using the Flybase website. KEGG (http: //www. genome. jp/kegg/) database was also used to check and complete the data. The final gene set was then implemented with the transcriptome data from the temporal map of gene expression and exposed in Table S4. For each signalling pathway, expression of the receptor was considered as an absolute prerequisite (EGF, Insulin, and Torso receptor signalling pathways were directly eliminated by this filtering step). However, if diffusible, the detection of ligand expression was not considered as absolute necessity. Then, in the remaining list, only signalling pathways that displayed dynamic and timely ordered expression of their regulated key genes, with at least two of the following components such as the receptor, the ligand or nuclear effectors, were selected. Decapentaplegic, Hedgehog, JNK and JAK/STAT pathways were eliminated at this last selection step. The final regulated components dataset of selected pathways, including FGF, Notch, Toll, PDGF-VEGF and Wnt pathways, were further analysed for their expression regulation during heart remodelling (an associated expression matrix was constructed and is presented in Figure 5C), and their potential involvement during cardiac tube metamorphosis was then analysed by reverse genetics. Microarray results were confirmed with RQ-PCR to verify the expression data results. For all the expression clusters, at least one differentially expressed gene has been tested in RQ-PCR analysis. cDNA was synthesized from 500 ng of amplified RNA from the first round of T7 linear RNA amplification from microarray experiments, using random hexamers and Superscript II reverse-transcriptase (Invitrogen). The design of primers for each gene was done using Primer Express software (ABI), and validated for their gene specificity by an agarose gel electrophoresis and by the associated derivative melting curve profile. RQ-PCR analyses for selected genes were performed using the qPCR Core kit for SYBR Green I (Eurogentech) and starting with 1 ng of cDNA in a 25-μl PCR on an ABI PRISM 7000 SDS (Applied Biosystems) according to the manufacturer' s instructions. For each gene-specific RQ-PCR experiment, serially diluted cDNA preparations (made by reverse-transcription of pooled aRNA samples representing all chosen stages of the expression kinetic) were used to construct a standard curve to quantify the eight test samples as well as the PCR efficiency according to the Relative Standard Curve Method for relative quantification. Ribosomal protein L32 (RP49) amplifications were used as endogenous control for normalization, and the first time-point (21 h APF) was chosen as calibrator for comparing results. The relative quantification for any given gene with respect of the calibrator was determined and compared with the normalized expression values resulting from microarray experiments. In order to prevent UAS activation before the pupal stage, we used the TARGET system to control GAL4 activity [50]. UAS and P (tub-GAL80[ts]) transgenes were combined in the same lines and then crossed with the 24B>Gal4 which is expressed in all myocytes [39] or with NP5169>Gal4 or Hand>Gal4 lines whose expression is restricted to cardiac myocytes [5]. Development was allowed to proceed at 22 °C until late third instar larval stage and individuals were then shifted to restrictive temperature (29 °C), thus inactivating GAL80 and consequently allowing Gal4 activity. Dissections and staining procedures were done as described in Monier et al, 2005 [5]. The following primary antibodies were used: mouse anti-β-galactosidase (Promega), 1: 50; rabbit anti-D-Mef2 [51], 1: 1000; mouse anti-Abd-A [52] (6A8. 12), 1: 500; anti-Pvr [53], 1: 500. Observations and photographs were done under either an Axiophot Zeiss microscope or a BioRad confocal microscope.
  The microarray data discussed in this manuscript have been deposited in The National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO, http: //www. ncbi. nlm. nih. gov/geo/) and are accessible through GEO Series accession number GSE7689. Flybase (http: //flybase. bio. indiana. edu/) ID numbers for genes cited in the text are abd-A, FBgn0000014; arm, FBgn0000117; bap, FBgn0004862; br, FBgn0000210; cact, FBgn0000250; dally, FBgn0011577; Dif, FBgn0011274; dl, FBgn0000462; Dl, FBgn0000463; dlp, FBgn0041604; Doc3, FBgn0035954; dsh, FBgn0000499; EcR, FBgn0000546; Eip74EF, FBgn0000567; Eip75B, FBgn0000568; Eip78C, FBgn0004865; Eip93F, FBgn0013948; fz, FBgn0001085; Gal4, FBgn0014445; Hr39, FBgn0010229; Hr46, FBgn0000448; htl, FBgn0010389; kuz, FBgn0015954; lacZ, FBgn0014447. ; mam, FBgn0002643; Mef2, FBgn0011656; mid, FBgn0005511; N, FBgn0004647; pan, FBgn0019664; pll, FBgn0010441; pnr, FBgn0003117; Pvf2, FBgn0031888; Pvr, FBgn0032006; pyr, FBgn0033649; RpL32, FBgn0002626; sty, FBgn0014388; Su (H), FBgn0004837; svp, FBgn0003651; ths, FBgn0033652; tin, FBgn0004110; Tl, FBgn0003717; tub, FBgn0003882; Ubx, FBgn0003944; wg, FBgn0004009; and Wnt4, FBgn0010453.
summary: The formation of specific organs depends on complex genetic programs that drive cell morphogenesis and growth to shape the mature organs, and functional differentiation to ensure their physiological function. Classical genetic studies in model organisms have shed light on some of the mechanisms that participate in organogenesis, but, given the complexness of these processes, drawing an integrated view is a long-lasting issue. Here, using high-throughput approaches for examining changes in gene expression at transcriptional level, we analyse the expression dynamics of genes as readouts of the molecular mechanisms that drive adult heart formation in the fruit fly Drosophila melanogaster. Whole-genome gene expression recording at several successive time-points during heart morphogenesis provides extensive insight into the mechanisms that lead to the formation of a mature adult heart. In particular, several evolutionarily conserved signalling pathways appear to be temporally regulated at the transcriptional level during the process, and subsequent genetic manipulation of these pathways shows they play important roles in heart formation. This study furnishes significant new insights into the signalling pathways involved in heart organogenesis and demonstrates that integrating genomic and genetic approaches is an efficient way to provide extensive knowledge of an organogenesis process.
keywords: developmental biology
  cell biology
  arthropods
  drosophila
  animals
  genetics and genomics
  insects
title: Signalling Pathways Involved in Adult Heart Formation Revealed by Gene Expression Profiling in Drosophila