Expression profiling of Drosophilaimaginal discs
© Klebes et al., licensee BioMed Central Ltd 2002
Received: 10 May 2002
Accepted: 7 June 2002
Published: 24 July 2002
In the Drosophila larva, imaginal discs are programmed to produce adult structures at metamorphosis. Although their fate is precisely determined, these organs remain largely undifferentiated in the larva. To identify genes that establish and express the different states of determination in discs and larval tissues, we used DNA microarrays to analyze mRNAs isolated from single imaginal discs.
Linear amplification protocols were used to generate hybridization probes for microarray analysis from poly(A)+ RNA from single imaginal discs containing between 10,000 and 60,000 cells. Probe reproducibility and degree of representation were tested using microarrays with approximately 6,000 different cDNAs. Hybridizations with probes that had been prepared separately from the same starting RNA pool had a correlation coefficient of 0.97. Expression-profile comparisons of the left and right wing imaginal discs from the same larva correlated with a coefficient of 0.99, indicating a high degree of reproducibility of independent amplifications. Using this method, we identified genes with preferential expression in the different imaginal discs using pairwise comparisons of discs and larval organs. Whereas disc-to-disc comparisons revealed only moderate differences, profiles differed substantially between imaginal discs and larval tissues, such as larval endodermal midgut and mesodermal fat body.
The combination of linear RNA amplification and DNA microarray hybridization allowed us to determine the expression profiles of individual imaginal discs and larval tissues and to identify genes expressed in tissue-specific patterns. These methods should be widely applicable to comparisons of expression profiles for tissues or parts of tissues that are available only in small amounts.
During the development of multicellular organisms, complexity builds sequentially in discrete steps as cells proliferate and their descendants choose between alternative developmental fates. Much of our understanding of these processes in Drosophila has come from mutants that have developmental defects. There are many examples. For instance, mutations in the homeodomain protein genes of the Antennapedia and Bithorax complexes provide evidence for the role of transcription factors in making developmental decisions. Flies with gain-of-function mutations in the Antennapedia (Antp) gene cannot grow normal antennae, but instead make extra legs with their antennal cells. Conversely, loss of Antp function causes transformation of the second leg to antenna-like structures . Another example is the glass gene, which encodes a zinc-finger transcription factor that is expressed in many of the cell types in the eye imaginal disc and is required for photoreceptor development . The common functions of these and many other genes in regulating gene expression suggest that developmental fates are manifested in part in the transcripts that different cell types produce.
Although the number of Drosophila mutants with interesting developmental phenotypes is large, we cannot assume that the genetic screens that have been carried out identified all the relevant genes. Many Drosophila genes have been refractory to genetic analysis, either because they are duplicated and may code for redundant functions, or because they have mutant phenotypes that are difficult to recognize. In addition, genetic and biochemical approaches have yielded few downstream genes that the key transcription factors regulate. The recent release of the Drosophila genome sequence  and the demonstration that cDNA microarrays can be used to catalog the transcriptome of both unicellular and multicellular organisms [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20] opens up a new approach. Hybridization of mRNA pools to DNA microarrays can potentially identify the differences in gene activity that define every developmental state. Thus, transcriptional regulators and their downstream targets can be identified simultaneously.
The Drosophila larva contains two developmentally distinct sets of organs. One set comprises the vital organs of the larva - the epidermis and musculature, the central and peripheral nervous systems, and the organs of the digestive tract. Most of these tissues will be destroyed at metamorphosis and will be replaced by imaginal (adult) cells. The imaginal precursor cells have no functional role in the larva. For some adult structures such as the eyes, antennae, legs, wings, halteres and genitalia, the imaginal precursors are sequestered as physically distinct primordia - the imaginal discs. The different discs are determined as to disc type, but do not differentiate until the late larval and subsequent pupal stages when they form the adult structures. The distinct developmental phases of the imaginal discs, their easy accessibility, along with the numerous advantages of Drosophila as a model genetic and developmental organism make imaginal disc development an ideal system to explore the feasibility and usefulness of such an analysis at a genomic scale.
We applied linear RNA amplification methods that were first introduced by Eberwine and co-workers [21,22] and have been refined by Baugh et al. . We used two rounds of reverse transcription (RT) and in vitro transcription (IVT), and achieved as much as 1-5 × 105-fold amplification. The amplified RNA (aRNA) from different tissues of single larva was used to perform pairwise comparisons and to identify sets of genes with preferential expression. The preferential expression of many of the genes in these sets had been previously shown by genetic or molecular analysis. We also confirmed the preferential expression of ten genes that had not been previously characterized by in situ hybridization to imaginal discs. Several of these genes had particularly interesting patterns of expression. Our findings show that this method can be applied to determine the expression profile of individual tissues and to identify candidate genes with specific expression patterns.
Results and discussion
Principle of amplification
The amplification procedure we used is based on protocols described by Eberwine [21,22,24], Wang et al. , and Baugh et al. , and details are given in Materials and methods. Briefly, double-stranded cDNA was synthesized either from total RNA isolated from imaginal discs or from poly(A)+-purified embryonic RNA. The cDNA was used as a template for in vitro transcription, routinely generating an RNA product that represented an amplification of approximately 1,000 fold. This RNA was subjected to a second round of RT and IVT. The yield from the second round represented an approximately 100-fold amplification, resulting in an overall amplification of 1-5 × 105. Probes for hybridization were synthesized by RT and labeled with either Cy5 (red) or Cy3 (green). Arrays were hybridized simultaneously with Cy5- and Cy3-labeled probes, and the intensities and ratios of bound fluor were measured for each spot. Because of inherent variability in the hybridization efficiency of individual microarrays, only the ratios of the red and green fluorescence were interpreted to indicate relative transcript abundance in the starting pool of poly(A)+ RNA.
A known drawback of linear amplification is that sequences at the 5' end of transcripts can be preferentially lost. This reduction in sequence complexity can probably be attributed to incomplete RT, to priming from subterminal locations, and to incomplete IVT. To overcome this problem, we supplemented the random hexanucleotides that were used to prime the second RT reaction with a template-switch (TS) primer . This primer includes a guanosine triplet that is designed to pair with a 3' cytidine overhang created by the reverse transcriptase (Clontech ). Control amplifications with the TS primer alone or random hexanucleotides alone yielded similar quantities of aRNA. When these aRNA preparations were used for microarray hybridizations, many spots had significantly different signal intensities (data not shown). The 25 cDNAs with the most intense signals for the probe amplified with the TS primer alone had an average length of 1.6 kilobases (kb). In contrast, after amplification with hexanucleotides alone, the 25 cDNAs with the most intense signals had an average length of 1.1 kb. We interpret the bias towards long transcripts in TS-primer amplified probes as indicating better preservation of 5'-complexity.
Representation of transcripts in amplified probes
Comparisons between amplified and unamplified RNA indicated that essentially no transcripts were lost during amplificaton. Of the spots that hybridized to probes generated from amplified and unamplified embryonic poly(A)+ RNA 99% (5,514 out of 5,574) did so with both probes. Differences in intensities were, nevertheless, significant (CC 0.53 and SD 1.13, data not shown). We do not know whether these differences in intensities were a result of changes in relative abundance or in transcript length, both of which will affect hybridization signals. Nevertheless, the good correspondence of the hybridizing spots shows that the aRNA is an essentially complete representation of the population of transcripts present in the initial pool. We conclude that comparisons of two different probes on microarrays are valid if the RNA pools have been amplified in the same way.
Pairwise comparisons of imaginal discs and larval organs
Overview of the comparisons
Number of experiments
Wing : wing
Wing : eye-antenna
Wing : leg1
Leg1 : leg2
Leg1 : leg3
Leg2 : leg3
Haltere : genital
Wing : fat body
Leg1 : fat body
Haltere : fat body
Wing : brain/optic lobe
Wing : salivary gland
Wing : midgut
Hybridizations that were carried out were of two types: with probes generated from different imaginal discs; and with probes from imaginal discs and larval organs. Comparisons between imaginal disc probes revealed a high degree of similarity, but comparisons between imaginal disc and larval organ probes identified many differentially expressed genes. We now give a general description of these results, starting with those tissues that were most alike. It should be noted that these results were obtained with microarrays that represent a pool of cDNAs obtained from the Berkeley Drosophila Genome Project (BDGP) containing approximately 44% (6,000/13,600) of the transcription units predicted to be in the Drosophila genome. As this pool may not be a truly random subset, extrapolations to the whole genome may be of limited value. Indeed, a preliminary comparison of our cDNA arrays with microarrays that contain short cDNA sequences for all annotated genes suggests that the total number of genes that produce a signal with these probes is similar. It is possible that the set of 6,000 cDNAs distributed by the BDGP is biased toward genes expressed in the tissues we analyzed.
Expression profiles of imaginal discs
Left and right wing discs
We first asked whether microarray hybridization could detect differences in expression profiles between left and right wing discs. Although few differences might be expected, previous studies have revealed a left/right difference in wing size, suggesting that the respective developmental programs are not identical . When probes were prepared independently from the poly(A)+ RNA isolated from left and right wing discs of a third instar larva, only minor differences in the intensities were observed (CC 0.99 and SD 0.14) (Figure 2c). This tight correlation again shows the reproducibility of the amplification procedure.
Leg and wing discs
Wing and eye-antennal imaginal discs
In addition to the genes whose tissue-specific expression was confirmed by this array analysis, many have not been characterized previously. One of these novel genes, CG9335, was notable for its 16-fold relative induction in eye-antennal discs (Figure 5). We also single out Gliolectin (glec) in the eye-antennal cluster, as this is not consistent with previous studies. glec is expressed in midline glia cells, but previous in situ hybridization and immunohistochemistry failed to detect it in discs . We did not characterize glec further and cannot therefore distinguish whether this discrepancy should be attributed to greater sensitivity of the array analysis or to possible contamination by glial cell RNA in the eye-antennal RNA.
Haltere and genital imaginal discs
In five direct comparisons of haltere and genital imaginal discs, 130 genes were found to be preferentially expressed in the haltere disc and 54 in the genital disc (see Additional data files). As with the wing/eye-antennal analysis, known genes clustered as predicted from previous studies. For example, caudal, a homeobox domain transcription factor, partitioned into the genital-disc cluster. caudal is expressed in the genital disc but not in more anterior tissues such as the haltere disc . abdominal B, which would be predicted to show preferential expression in the genital disc, was not represented on the arrays. These 184 differentially expressed genes correspond to 3% of the entire set of 6,000 and represent the largest cluster we obtained in all pairwise comparisons of imaginal discs.
Expression profiles of larval organs
In order to compare and contrast the expression profiles of larval organs and imaginal discs, we made probes from the poly(A)+ RNA isolated from several larval organs. We directly compared probes from the wing imaginal disc with: the salivary gland, an anterior fraction of the midgut, parts of the fat body and the brain hemisphere, including the optic lobe primordium. For each experiment, probes prepared from a single larva were compared. With the exception of the comparisons between the first leg disc and fat body which was carried out once, each of the other comparisons was repeated at least three times.
The only exceptions to emerge in this analysis were the cells of the optic lobe/brain hemisphere. Comparisons of these neuronal tissues with wing discs revealed only a small number of differentially expressed genes (Figure 8a) and had low standard deviations that were in the range of disc-to-disc comparisons (Figure 8b). The optic lobe primordium and brain of late third instar larvae have only limited functions in larval photoreception and contain only a small number of mature neurons. The larval brain is populated with clusters of immature neurons, neuroblasts and ganglion mother cells whose descendants will generate the neuronal and glial populations of the adult optic neuropil and the brain hemisphere. The brain hemisphere also differs from other larval tissues by not degenerating during metamorphosis. Instead, most neurons of the larva join with newly formed adult-specific neurons to build the CNS of the adult ( and references therein). We interpret the high degree of similarity in the expression profiles of imaginal discs and the brain/optic lobe preparations as a manifestation of the apparent commonalities of their developmental programs.
The number of genes that were found to be induced in the larval organs is significantly greater than the number of genes in the sets defined by the disc-to-disc comparisons. Most of the genes in these sets have not been characterized previously and therefore have no known function, but the known genes in these clusters illustrate the predictive power of the method; we mention three examples.
Many of the genes that are preferentially expressed in the optic lobe/brain hemisphere have predicted or described expression and/or function in neurons or glial cells (data not shown). One of these is lola, which encodes a transcription factor involved in axon guidance and is expressed in the embryonic optic lobe placodes as well as other tissues . Another is beta amyloid protein precursor-like (Appl), with known expression in the larval optic lobe .
Experimental design and data analysis
Two methods for comparative hybridizations to DNA microarrays have been used in previous studies. Most commonly, experimental samples have been compared to a common reference sample that contains an appropriate diversity of cell types and states. An alternative method, which we have used in this study, is to directly compare probes generated from two experimental samples. This second method should be the more sensitive. The amplification technique we used was such that product generated from a single imaginal disc was sufficient to make several probes and to carry out multiple array hybridizations. By comparing samples that had been isolated from a single animal, this method minimized differences due to biological variability. By repeating experiments several times and by reversing the label (dye-flip) for experimental samples in repeat hybridizations, we also attempted to minimize experimental noise.
In addition to these design aspects of the experimental protocols, we applied a number of filters to the data analysis. We selected only those genes with hybridization signals over background in 80% of all experiments and with a 1.74-fold difference between the two channels in at least 45%. Applying this method to 11 arrays that compared wing and eye-antennal discs, we found two subclusters representing genes preferentially expressed in either disc. These lists of genes are largely validated by the previously described expression pattern in either tissue and by in situ hybridization analysis. We understand that the use of any such threshold settings is likely to filter out biologically relevant genes. For example, when less stringent settings were used (for example, a 1.6-fold intensity difference increased the gene sets by 20%), additional genes such as twin of eyeless were included in the eye-antennal cluster and Antp and CG6680 (Figure 6e) in the wing cluster. Relaxing the requirement to produce a ratio in at least 80% of all experiments to 70% identifies yet another group of genes, and includes LD11162 (Figure 6j). Conversely, setting a more stringent threshold to 1.9-fold intensity difference decreased the gene sets by 25% and removed genes such as Arrestin2 and CG11798 (Figure 6d,6f).
Setting a threshold level for the clusters is arbitrary, and as some candidate genes may be expressed by only a small subset of cells in the experimental sample, each analysis must be evaluated separately. Nevertheless, we interpret the good correlation between the array analysis and expression patterns we have described as indicating that the method is both efficient and reliable. Subsequent to the analyses described above, we carried out single-disc comparisons with microarrays that represent a nearly complete set of the approximately 14,000 annotated Drosophila genes. The short cDNAs spotted on these arrays were produced with specific primer pairs obtained from Incyte Genomics, Inc. Use of these arrays for disc-to-disc comparisons also identified only a relatively small number of differentially expressed genes (data not shown). The list of induced genes was apparently more complete, however, and included, for example, vestigal in the wing-to-leg disc comparisons (A.K., G. Schubiger and T.B.K., unpublished observations).
Although the absolute number of genes included in the lists of tissue-specific genes is not meaningful, the relatively small number of genes that differ between imaginal tissues and the significantly greater number of genes that differ between imaginal and larval tissues certainly is.
We have shown that linear RNA amplification is reproducible and can be used to generate probes for microarray experiments with limited quantities of starting material. We used this technique to determine the expression profiles of imaginal and larval tissues by pairwise comparisons of tissues dissected from single larvae. Our approach was validated by the presence of characterized genes in the appropriate cluster and by confirmation of expression patterns by direct analysis. Applying stringent threshold criteria, we found that less than 3% of the genes represented on the arrays were preferentially expressed when discs were compared to each other. Many of these genes have either not been characterized previously or lack obvious similarity to known coding domains. Those that have been previously characterized or share sequence similarities represent a broad array of cellular functions. These include basic metabolic and transporting functions, structural, cell-adhesive and signaling functions, as well as transcriptional regulation. We lack sufficient understanding of the specific processes in most cell types to interpret the significance of the genes that they specifically express. Future studies will be required to identify the functional networks that the identified candidate genes describe and to establish how they contribute to the execution of specific developmental programs.
We anticipate that the methods we describe here can be applied to determine and compare the expression profiles of small cell groups in Drosophila tissues. We look forward to a further enhancement in resolution that can be achieved by combining cell-sorting techniques with this type of array analysis. We found that starting with as little as 10 pg poly(A)+ RNA yields enough aRNA for one hybridization. This amount roughly corresponds to 300 cells of the third instar wing imaginal disc.
Materials and methods
Microarray production and labeling
Spotted cDNA microarrays were produced essentially as described at . In brief, the Drosophila Gene Collection (DGC 1.0, kindly provided by the Berkeley Drosophila Genome Project) of 5,849 nonredundant cDNAs was amplified using universal primers essentially as described at . The amplification products were purified with 96-well format Qiagen PCR purification columns. All PCR products were analyzed on agarose gels, and reactions with no detectable product, multiple bands or bands of unexpected size were repeated using Herculase (Amersham) or Expand polymerase (Roche). One hundred and seventy-five cDNAs from our lab collection were amplified and added to the set, resulting in a total of 6,024 cDNAs. Reactions were arrayed into 384-well plates and printed on poly-L-lysine-coated glass slides using a linear servo arrayer and ArrayMaker Version 2 control software. To minimize background caused by oxidation of the polylysine coating, slides were pretreated by a protocol suggested by Paul Ebert. Before post-processing, slides were incubated for 5 min in 3× SSC; 0.2% SDS at 65°C, washed first in water and then in 95% ethanol, followed by centrifugation to dry the slides. Slides were then treated, and the hybridization reaction was carried out as described at . We indirectly labeled the hybridization probes by incorporation of amino-allyl modified nucleotides in a first-strand cDNA RT reaction. Monofunctional Cy5 or Cy3 dye (Amersham) was subsequently coupled to the reactive residues. Multiple hybridizations were carried out for most experiments, and dye labeling was reversed to avoid systematic bias.
Larval dissections, RNA isolation and in situhybridization
Third instar wandering larvae were dissected and washed several times in Ringer solution (130 mM NaCl, 5 mM KCl, 2 mM Na2HPO4, 1.5 mM CaCl2, 0.37 mM KH2PO4). Fat-body fragments were mainly anterior plates. Midgut was the anterior portion just posterior to the gastric caeca. Brain/optic lobe consisted of one brain hemisphere including the optic lobe primordium.
Total RNA from larval tissues was extracted using the Mini RNA Isolation Kit (Zymo Research, Orange, CA) and was eluted with RNase-free water. Total RNA from embryos was extracted with Trizol reagent (Invitrogen). Embryonic poly(A)+ RNA was purified using the Oligotex mRNA Mini Kit (Qiagen). Poly(A)+ RNA was not purified before amplification of disc RNA because of the small amounts (see Figure 1).
In situ hybridizations were carried out as described in O'Neill and Bier . The plasmids used to generate in situ probes were derived by subcloning an aliquot of the PCR product that was printed onto the microarray with Topo TA cloning (Invitrogen). All cloned products were sequenced and separate hybridizations were carried out for sense and antisense probes.
Methods for amplification were adapted from Wang et al.  and Baugh et al. . Total RNA isolated from dissected larval tissues or poly(A)+ RNA purified from embryos was incubated with 100 ng oligo(dT)24 -T7 primer (GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCG-GTTTTTTTTTTTTTTTTTTTTTTTT) and 125 ng TS primer (AAGCAGTGGTAACAACGCAGAGTACGCGGG) in 5 μl at 65°C for 10 min and cooled on ice. Six microliters first-strand premix were added and incubated at 42°C for 2 h (6 μl mix was made up with 2 μl 5× first-strand buffer, 1 μl 0.1 M DTT, 1 μl dNTPs (10 mM each), 0.3 μl T4gp32 (USB, 13.82 mg/ml), 0.5 μl RNasin (Promega), 1 μl Superscript II (Invitrogen)). The reaction was incubated at 65°C for 10 min and cooled on ice. Cold second-strand premix (64.5 μl prepared on ice: 45 μl RNase-free water, 15 μl 5× second-strand buffer (Invitrogen), 1.5 μl dNTPs (10 mM each), 0.5 μl E. coli ligase (10 U/μl), 2 μl E. coli polymerase (10 U/μl), 0.5 μl E. coli RNaseH (2 U/μl)). Enzymes for the second-strand premix (Invitrogen) were added and incubated at 16°C for 2 h, followed by the addition of 2 units T4 DNA polymerase (Promega) and incubation at 16°C for 15 min before heat inactivation at 70°C for 10 min. Clean-up was performed with DNA clean and concentrator-5 (Zymo Research), eluting twice with 8 μl RNase-free water. The total volume was adjusted to 8 μl in a Speed Vac. The first IVT was performed with Megascript T7 (Ambion) in a 20 μl volume for 5-6 h, followed by DNA digestion. aRNA was purified using Mini RNA Isolation Kit or RNA Clean-up kit (Zymo Research), eluting in 2 × 8 μl RNase-free water. Random hexanucleotides (250 ng) and TS primer (1 μg) were added and the volume adjusted to 5 μl. The mix was incubated at 65°C for 10 min before 5 μl first-strand premix was added followed by incubation at 42°C for 2 h. Before the second-strand synthesis, 200-500 ng oligo(dT)24 -T7 primer was added and denatured at 65°C for 10 min. The second-round second-strand synthesis, clean-up and IVT were carried out as for the first round, except that no ligase was added to the second-strand premix. One-quarter to one-third of the total aRNA was applied to the clean-up columns after the second IVT to avoid overloading. All reactions were carried out in a thermocycler with heated lid or air incubator to avoid evaporation.
Hybridized microarrays were scanned with a GenePix 4000 A Microarray Scanner (Axon Instruments, Union City, CA). Data were analyzed and displayed with Cluster and Treeview , AMAD , Genepix PRO (Axon Instruments), and Microsoft Excel. Normalization for cluster analysis and calculation of standard deviations were done with AMAD. Only genes that qualified with a combined median intensity > 300 above background in both channels in at least 80% of the repeated experiments were included in the analysis. A threshold of > 1.74 (= 0.8 of the log2-transformed ratios) was chosen for all comparisons. A requirement to show induction above threshold in 100% of the arrays was applied for experiments that were repeated three times or less. For experiments that were repeated more than three times this requirement was relaxed to 45%. Standard deviations were calculated on the log2-transformed normalized R/G ratios using the 'nonbiased' method. To calculate the correlation coefficients, the intensities of both channels were normalized to equalize the sums of the intensities.
Additional data files
A comparison of expression profiles of genital and haltere discs is available. Five comparisons between the haltere (H) and genital (G) disc were carried out. Four of the G discs were female (nos 48, 149, 150, 224) and one was male (no. 148). To control for contaminating fat body (FB) cells in the disc preparations, one direct comparison between haltere disc and FB (no. 129) was included. The columns indicate the subclusters with consistent induction in one channel (H, green; G, red), the gene identification numbers (ID), the average fold induction of the five H:G comparisons, the gene name and function as published on . 130 and 54 genes were induced in the H and G subclusters, respectively, using the same threshold settings as in Figure 3. Note the 2.5-fold induction of caudal (CG1759) in the G subcluster.
We thank Ken Burtis, Sarah Meadows, Gerold Schubiger, Mike Eisen and Joe DeRisi for technical help and advice, and Paul Ebert for suggesting the pretreatment protocol. We thank the Merck and the Ellison Foundation for financial support.
- Struhl G: A homoeotic mutation transforming leg to antenna in Drosophila. Nature. 1981, 292: 635-638.PubMedView ArticleGoogle Scholar
- Moses K, Ellis MC, Rubin GM: The glass gene encodes a zinc-finger protein required by Drosophila photoreceptor cells. Nature. 1989, 340: 531-536. 10.1038/340531a0.PubMedView ArticleGoogle Scholar
- Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, Amanatides PG, Scherer SE, Li PW, Hoskins RA, Galle RF, et al: The genome sequence of Drosophila melanogaster. Science. 2000, 287: 2185-2195. 10.1126/science.287.5461.2185.PubMedView ArticleGoogle Scholar
- Andrews J, Bouffard GG, Cheadle C, Lu J, Becker KG, Oliver B: Gene discovery using computational and microarray analysis of transcription in the Drosophila melanogaster testis. Genome Res. 2000, 10: 2030-2043. 10.1101/gr.10.12.2030.PubMedPubMed CentralView ArticleGoogle Scholar
- Brown V, Jin P, Ceman S, Darnell JC, O'Donnell WT, Tenenbaum SA, Jin X, Feng Y, Wilkinson KD, Keene JD, et al: Microarray identification of FMRP-associated brain mRNAs and altered mRNA translational profiles in fragile X syndrome. Cell. 2001, 107: 477-487.PubMedView ArticleGoogle Scholar
- Bryant Z, Subrahmanyan L, Tworoger M, LaTray L, Liu CR, Li MJ, van den Engh G, Ruohola-Baker H: Characterization of differentially expressed genes in purified Drosophila follicle cells: toward a general strategy for cell type-specific developmental analysis. Proc Natl Acad Sci USA. 1999, 96: 5559-5564. 10.1073/pnas.96.10.5559.PubMedPubMed CentralView ArticleGoogle Scholar
- Chu S, DeRisi J, Eisen M, Mulholland J, Botstein D, Brown PO, Herskowitz I: The transcriptional program of sporulation in budding yeast. Science. 1998, 282: 699-705. 10.1006/jmbi.1998.2134.PubMedView ArticleGoogle Scholar
- DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA, Trent JM: Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nat Genet. 1996, 14: 457-460.PubMedView ArticleGoogle Scholar
- Furlong EE, Andersen EC, Null B, White KP, Scott MP: Patterns of gene expression during Drosophila mesoderm development. Science. 2001, 293: 1629-1633. 10.1126/science.1062660.PubMedView ArticleGoogle Scholar
- Hayward RE, Derisi JL, Alfadhli S, Kaslow DC, Brown PO, Rathod PK: Shotgun DNA microarrays and stage-specific gene expression in Plasmodium falciparum malaria. Mol Microbiol. 2000, 35: 6-14. 10.1046/j.1365-2958.2000.01730.x.PubMedView ArticleGoogle Scholar
- Hill AA, Hunter CP, Tsung BT, Tucker-Kellogg G, Brown EL: Genomic analysis of gene expression in C. elegans. Science. 2000, 290: 809-812. 10.1126/science.290.5492.809.PubMedView ArticleGoogle Scholar
- Irving P, Troxler L, Heuer TS, Belvin M, Kopczynski C, Reichhart JM, Hoffmann JA, Hetru C: A genome-wide analysis of immune responses in Drosophila. Proc Natl Acad Sci USA. 2001, 98: 15119-15124. 10.1073/pnas.261573998.PubMedPubMed CentralView ArticleGoogle Scholar
- Lashkari DA, DeRisi JL, McCusker JH, Namath AF, Gentile C, Hwang SY, Brown PO, Davis RW: Yeast microarrays for genome wide parallel genetic and gene expression analysis. Proc Natl Acad Sci USA. 1997, 94: 13057-13062. 10.1073/pnas.94.24.13057.PubMedPubMed CentralView ArticleGoogle Scholar
- McDonald MJ, Rosbash M: Microarray analysis and organization of circadian gene expression in Drosophila. Cell. 2001, 107: 567-578.PubMedView ArticleGoogle Scholar
- Miki R, Kadota K, Bono H, Mizuno Y, Tomaru Y, Carninci P, Itoh M, Shibata K, Kawai J, Konno H, et al: Delineating developmental and metabolic pathways in vivo by expression profiling using the RIKEN set of 18,816 full-length enriched mouse cDNA arrays. Proc Natl Acad Sci USA. 2001, 98: 2199-2204. 10.1073/pnas.041605498.PubMedPubMed CentralView ArticleGoogle Scholar
- Schena M, Shalon D, Heller R, Chai A, Brown PO, Davis RW: Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. Proc Natl Acad Sci USA. 1996, 93: 10614-10619. 10.1073/pnas.93.20.10614.PubMedPubMed CentralView ArticleGoogle Scholar
- Shalon D, Smith SJ, Brown PO: A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. Genome Res. 1996, 6: 639-645.PubMedView ArticleGoogle Scholar
- White KP, Rifkin SA, Hurban P, Hogness DS: Microarray analysis of Drosophila development during metamorphosis. Science. 1999, 286: 2179-2184. 10.1126/science.286.5447.2179.PubMedView ArticleGoogle Scholar
- Wilson M, DeRisi J, Kristensen HH, Imboden P, Rane S, Brown PO, Schoolnik GK: Exploring drug-induced alterations in gene expression in Mycobacterium tuberculosis by microarray hybridization. Proc Natl Acad Sci USA. 1999, 96: 12833-12838. 10.1073/pnas.96.22.12833.PubMedPubMed CentralView ArticleGoogle Scholar
- Zou S, Meadows S, Sharp L, Jan LY, Jan YN: Genome-wide study of aging and oxidative stress response in Drosophila melanogaster. Proc Natl Acad Sci USA. 2000, 97: 13726-13731. 10.1073/pnas.260496697.PubMedPubMed CentralView ArticleGoogle Scholar
- Eberwine J, Yeh H, Miyashiro K, Cao Y, Nair S, Finnell R, Zettel M, Coleman P: Analysis of gene expression in single live neurons. Proc Natl Acad Sci USA. 1992, 89: 3010-3014.PubMedPubMed CentralView ArticleGoogle Scholar
- Van Gelder RN, von Zastrow ME, Yool A, Dement WC, Barchas JD, Eberwine JH: Amplified RNA synthesized from limited quantities of heterogeneous cDNA. Proc Natl Acad Sci USA. 1990, 87: 1663-1667.PubMedPubMed CentralView ArticleGoogle Scholar
- Baugh LR, Hill AA, Brown EL, Hunter CP: Quantitative analysis of mRNA amplification by in vitro transcription. Nucleic Acids Res. 2001, 29: e29-10.1093/nar/29.5.e29.PubMedPubMed CentralView ArticleGoogle Scholar
- Eberwine J: Amplification of mRNA populations using aRNA generated from immobilized oligo(dT)-T7 primed cDNA. Biotechniques. 1996, 20: 584-591.PubMedGoogle Scholar
- Wang E, Miller LD, Ohnmacht GA, Liu ET, Marincola FM: High-fidelity mRNA amplification for gene profiling. Nat Biotechnol. 2000, 18: 457-459. 10.1038/74546.PubMedView ArticleGoogle Scholar
- Klingenberg CP, McIntyre GS, Zaklan SD: Left-right asymmetry of fly wings and the evolution of body axes. Proc R Soc Lond B Biol Sci. 1998, 265: 1255-1259. 10.1098/rspb.1998.0427.View ArticleGoogle Scholar
- White RA, Wilcox M: Protein products of the bithorax complex in Drosophila. Cell. 1984, 39: 163-171.PubMedView ArticleGoogle Scholar
- Wirz J, Fessler LI, Gehring WJ: Localization of the Antennapedia protein in Drosophila embryos and imaginal discs. EMBO J. 1986, 5: 3327-3334.PubMedPubMed CentralGoogle Scholar
- Glicksman MA, Brower DL: Expression of the Sex combs reduced protein in Drosophila larvae. Dev Biol. 1988, 127: 113-118.PubMedView ArticleGoogle Scholar
- Pattatucci AM, Kaufman TC: The homeotic gene Sex combs reduced of Drosophila melanogaster is differentially regulated in the embryonic and imaginal stages of development. Genetics. 1991, 129: 443-461.PubMedPubMed CentralGoogle Scholar
- Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA. 1998, 95: 14863-14868. 10.1073/pnas.95.25.14863.PubMedPubMed CentralView ArticleGoogle Scholar
- Kiss I, Beaton AH, Tardiff J, Fristrom D, Fristrom JW: Interactions and developmental effects of mutations in the Broad-Complex of Drosophila melanogaster. Genetics. 1988, 118: 247-259.PubMedPubMed CentralGoogle Scholar
- Williams JA, Paddock SW, Carroll SB: Pattern formation in a secondary field: a hierarchy of regulatory genes subdivides the developing Drosophila wing disc into discrete subregions. Development. 1993, 117: 571-584.PubMedGoogle Scholar
- Tiemeyer M, Goodman CS: Gliolectin is a novel carbohydrate-binding protein expressed by a subset of glia in the embryonic Drosophila nervous system. Development. 1996, 122: 925-936.PubMedGoogle Scholar
- Freeland DE, Kuhn DT: Expression patterns of developmental genes reveal segment and parasegment organization of D. melanogaster genital discs. Mech Dev. 1996, 56: 61-72. 10.1016/0925-4773(96)00511-4.PubMedView ArticleGoogle Scholar
- Ceron J, González C, Tejedor FJ: Patterns of cell division and expression of asymmetric cell fate determinants in postembryonic neuroblast lineages of Drosophila. Dev Biol. 2001, 230: 125-138. 10.1006/dbio.2000.0110.PubMedView ArticleGoogle Scholar
- Giniger E, Tietje K, Jan LY, Jan YN: lola encodes a putative transcription factor required for axon growth and guidance in Drosophila. Development. 1994, 120: 1385-1398.PubMedGoogle Scholar
- Torroja L, Luo L, White K: APPL, the Drosophila member of the APP-family, exhibits differential trafficking and processing in CNS neurons. J Neurosci. 1996, 16: 4638-4650.PubMedGoogle Scholar
- Hayashi S: A Cdc2 dependent checkpoint maintains diploidy in Drosophila. Development. 1996, 122: 1051-1058.PubMedGoogle Scholar
- Edgar BA, Orr-Weaver TL: Endoreplication cell cycles: more for less. Cell. 2001, 105: 297-306.PubMedView ArticleGoogle Scholar
- Microarrays.org - a public source for microarray protocols and software. [http://www.microarrays.org/]
- Berkeley Drosophila Genome Project resources. [http://www.fruitfly.org/about/methods/ampUniGene.html]
- O'Neill JW, Bier E: Double-label in situ hybridization using biotin and digoxigenin-tagged RNA probes. Biotechniques. 1994, 17: 874-875.Google Scholar
- FlyBase. [http://flybase.bio.indiana.edu/]