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Human Molecular Genetics, 2003, Vol. 12, No. 11 1261-1272
DOI: 10.1093/hmg/ddg150
© 2003 Oxford University Press

Gene expression differences in quiescent versus regenerating hair cells of avian sensory epithelia: implications for human hearing and balance disorders

R. David Hawkins1, Stavros Bashiardes1, Cynthia A. Helms1, Lydia Hu2, Nancy Lim Saccone1, Mark E. Warchol2 and Michael Lovett1,*

1Division of Human Genetics, Department of Genetics, Washington University School of Medicine, 4566 Scott Avenue, St Louis, MO 63110, USA and 2Central Institute for the Deaf, 4560 Clayton Avenue, St Louis, MO 63110, USA

Received January 10, 2003; Revised March 25, 2003; Accepted March 31, 2003


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The sensory receptors for hearing and balance are the hair cells of the cochlea and vestibular organs of the inner ear. Permanent hearing and balance deficits can be triggered by genetic susceptibilities or environmental factors such as infection. Unlike mammalian hair cells that have a limited capacity for regeneration, the vestibular organ of the avian ear is constantly undergoing hair cell regeneration, whereas the avian cochlea undergoes regeneration only when hair cells are damaged. In order to gain insights into the genetic programs that govern the regenerative capacity of hair cells, we interrogated custom human cDNA microarrays with sensory epithelial cell targets from avian inner ears. The arrays contained probes from conserved regions of ~400 genes expressed primarily in the inner ear and ~1500 transcription factors (TF). Highly significant differences were observed for 20 inner-ear genes and more than 80 TFs. Genes up-regulated in the cochlea included BMP4, GATA3, GSN, FOXF1 and PRDM7. Genes up-regulated in the utricle included SMAD2, KIT, ß-AMYLOID, LOC51637, HMG20B and CRIP2. Many of the highly significant changes were validated by Q-PCR and in situ methods. Some of the observed changes implicated a number of known biochemical pathways including the c-kit pathway previously observed in melanogenesis. Twenty differentially expressed TFs map to chromosomal regions harboring uncloned human deafness loci, and represent novel candidates for hearing loss. The approach described here also illustrates the power of utilizing conserved human cDNA probes for cross-species comparisons.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The sensory hair cells of the inner ear detect sound and head movements. In mammals, hair cells are formed during a limited period of embryonic development and can be lost later in life as a consequence of acoustic trauma, treatment with ototoxic drugs, infections or autoimmune pathologies, or as part of the aging process. The loss of hair cells from the human cochlea and vestibular organs is a leading cause of permanent hearing and balance deficits. In contrast, the ears of most non-mammalian vertebrates (fish, amphibians and birds) can regenerate hair cells after injury. The process of hair cell regeneration has been characterized most completely in the avian inner ear, where lost sensory cells are quickly replaced via a process of regenerative cell proliferation (1–3). The precursors to regenerated hair cells are epithelial supporting cells, which re-enter the cell cycle after hair cell injury (4–8). A more limited regenerative response also occurs in the vestibular organs of mammals (9–11), but sensory regeneration does not occur in the normal mammalian cochlea (12). Thus, the factors that permit sensory regeneration in the ears of non-mammals but inhibit such regeneration in mammals are of great biological and clinical interest.

Many of the anatomical events that occur during regeneration in the avian ear have been described, but the precise signaling events that initiate regenerative proliferation are not known. Regenerative proliferation is confined to areas within or near (<200 µm) the lesion site, suggesting that hair cell death triggers the release of a diffusible mitogen or other local signal (7). The specific signaling pathways that trigger regenerative proliferation have not been identified, but recent studies have suggested that the PI3 kinase pathway (13,14), cAMP signaling (15,16), the JNK pathway (17), FGF signaling (18,19), and N-cadherin binding and interactions with extracellular matrix molecules (20) all play a role in the regulation of supporting cell proliferation and sensory regeneration. Only a few studies have examined changes in gene expression during hair cell regeneration. Differential display of mRNA following acoustic trauma revealed 70 novel cDNA bands within 48 h in the avian cochlea after injury (21,22). These include genes for parathyroid hormone-related protein, a neuron-specific CaM-kinase, the GTPase Cdc42 and UBE3B (a ubiquitin ligase), but most correspond to unknown genes. From a clinical basis it is important to identify these changes since the signaling pathways that are responsible for sensory regeneration in the avian ear may lead to methods for the activation of these same pathways in the injured human ear.

In addition to its robust regenerative capabilities, the avian inner ear also displays a unique pattern of sensory cell loss and turnover. Hair cells in the avian cochlea have long life spans and are not normally replaced unless they are lost by injury. As a result, the normal (undamaged) cochlea in mature birds contains very few proliferative cells (23). In contrast, hair cells in the vestibular organs have a relatively short life span (estimated at 2–6 weeks) (24–27) and then undergo spontaneous apoptosis. Those cells are then quickly replaced by new sensory cells which are produced by ongoing proliferation of epithelial supporting cells (24,25,27–29). Thus, the avian vestibular organs, but not the cochlea, are in a constant state of ongoing sensory regeneration.

In the present study, we combined two molecular technologies to investigate differences in gene expression between constantly regenerating chick utricle and the mitotically quiescent cochlea. The first was a micro-cDNA method that enabled us to construct representative cDNA libraries and microarray targets from the small number of cells in each sensory epithelium. The second was a set of custom microarrays. One contained probes for a collection of known inner ear-specific genes. The other contained probes for the vast majority of human transcription factors. Many of our significant findings were validated by quantitative PCR (Q-PCR) and in some cases by in situ detection methods.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Feasibility and design
We wished to characterize differences in gene expression between chick cochlear sensory epithelia that are normally quiescent and utricle epithelia that are in a constant process of apoptosis and regeneration. However, only a limited set of chicken (Gallus gallus) cDNAs and ESTs are available in public sequence databases. We therefore investigated the feasibility of using microarrays of human cDNAs to interrogate comprehensive sets of genes across species. To assess the feasibility of this approach with chicken versus human genes we examined one of the few available chicken EST databases (www.tigr.org/tdb/tgi/gggi/). A set of 500 randomly chosen ESTs from this collection were compared by BLASTN to the unique set of human gene-oriented clusters from Unigene (Hs.seq.uniq). Of the 500 queried ESTs, 10% did not exhibit significant homology with human sequence. Further analysis of these ESTs suggested that they were derived from chicken 3' untranslated region sequences. The percentage identities for the remaining 90% of this set of chicken ESTs ranged from 52 to 100% with a mean of 69%. These findings prompted us to build microarrays that comprised only human coding regions and to hybridize them under stringencies appropriate for a 69% overall nucleotide homology (see Materials and Methods). Two custom microarrays were designed and built and are discussed in detail below.

Inner ear array
The first cDNA microarray constructed for the current study contained cDNA probes to 426 genes that have been shown to affect hearing or to be expressed in the inner ear (a complete list is available at http://hg.wustl.edu). These human cDNA probes were prepared with PCR primers that would amplify several hundred base pairs of a unique segment of coding region. These arrays also contained probes for a number of control tags (see Materials and Methods).

Preparation of target
Comparative expression profiles of the chick cochlea and utricle were generated from the pseudostratified sensory epithelia. This is comprised entirely of sensory hair cells and supporting cells from the proliferative utricle and quiescent cochlea cells (see Materials and Methods). By implementing a micro-cDNA amplification scheme we were able to generate enough labeled targets from these small samples for multiple microarray hybridizations.

Targets were synthesized from an entire cDNA library or from primary cDNAs. In all cases we used multiple samples for our analyses to avoid any biases that might be introduced by genotypic variation or by sample preparations. All of the experimental hybridizations involved comparisons of multiple independent utricular or cochlear samples. In addition to these comparative hybridizations we conducted multiple self-to-self hybridizations (e.g. one utricle sample versus another) to test for sample variation and spurious dye effects. Encouragingly, these self-to-self hybridizations yielded no significant differences. For the comparative studies we conducted at least eight separate hybridizations. At least three of these were experiments where the fluorescent dye was switched to compensate for any effect of dye intensity. To assess statistically significant differences in gene expression, we applied the mixed model method recently described by Wolfinger et al. (30).

Table 1 shows a summary of the top 20 most significant gene expression changes detected between chick cochlea and utricle epithelia when the inner ear array was interrogated. In the table the samples are ranked according to P-values. Only samples with a fold change of 1.26 or greater are shown (see below for more on this). The two artificial control tags that were introduced into cochlea and utricle targets at different concentrations were detected with significant P-values, validating the quantitative changes we observed.


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  		Table 1. Genes from the inner-ear array showing the most significant changes in expression ranked by P-values
 
One might argue that fold-change could be misleading for cross-species hybridizations. However, if we used a P-value of less than 1x10-4 as a cut-off, then the number of genes showing differences in expression was 50, corresponding to 12% of those monitored. We therefore conclude in this case that our use of fold change as a cut-off value is the more conservative approach.

Quantitative-PCR (Q-PCR)
Q-PCR (31) was used as one independent method to validate our microarray-based observations. These results are also shown in Table 1. All of the Q-PCR assays agree with the trends observed from the microarrays and we were able to validate apparent microarray fold changes as low as 1.26-fold (see SPARC in Table 1). This array fold change is the average of eight hybridizations (ranging from a 1.10 to 1.55-fold increase). However, the exact fold changes in the Q-PCR did not always agree with the microarray observations. This is again illustrated by SPARC in Table 1, which had an average Q-PCR fold change of 2.25. This is not surprising given that microarrays of human cDNAs were used to detect changes in chick gene expression. It is expected that some compression of dynamic range will occur in cross-species hybridizations. By contrast, the Q-PCR primers were designed from chick cDNA sequences. It is therefore likely to be a better reflection of the expression level in each sample.

In situ hybridization and immunohistochemistry
In addition to the Q-PCR validation steps we also conducted a limited number of RNA in situ hybridizations with single-stranded probes to BMP4, GATA3, GELSOLIN and c-KIT. Figure 1 shows the differential expression of these genes in sensory epithelia of the cochlea and utricle. Consistent with previous observations (32) and our microarray and Q-PCR findings, expression of BMP-4 was observed only in the cochlea (Fig. 1A), providing an internal validation of our observations. GATA3 was expressed in both organs, but was present throughout the sensory epithelium of the cochlea and restricted to the striolar region of the utricle (Fig. 1A). Gelsolin was only detectable in the cochlea and was localized to a region near the superior edge of the sensory epithelium (Fig. 1A). Finally, we observed expression of c-KIT in the utricle (Fig. 1B). Notably, mutation of c-KIT in mice leads to dominant white spotting and ear abnormalities (33), and c-KIT is also mutated in one human deafness pedigree (34).



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  		Figure 1. In situ hybridizations confirm the differential expression of four genes from our microarray data. (A) RNA in situ hybridizations with antisense probes to BMP4, GATA3 and GELSOLIN on whole mount chick cochleae and utricles. Arrows indicate the areas of highest expression (sense probes are not shown but were uniformly negative). (B) Sense and antisense RNA in situ hybridizations of a c-KIT probe in the chick utricle.

 
In other experiments, we used immunocytochemical techniques to examine the distribution of GATA3 protein in the cochlea and utricle (Fig. 2). Consistent with our in situ results (above), we observed GATA3-labeled cell nuclei throughout the sensory region of the cochlea. In the utricle, however, GATA3 was present in only a six to eight cell-wide region in the center of the striola. This region corresponds to the zone of specialized type II hair cells that is located in the center of the striola in the avian utricle (35). The orientation of hair cell stereocilia undergoes an abrupt 180° shift at this region, and it is tempting to speculate that GATA3 may play a role in defining the polarity of this interesting group of cells (36). This gene has already been implicated in inner ear development (37,38).

The transcription factor microarray
Our second microarray was targeted at interrogating the majority of transcription factor genes. Our rationale in choosing transcription factors for this second line of investigation was that changes in these potent control molecules might reveal important switches in the genetic programs (apoptosis, quiescence or regeneration) that occur in the two sensory epithelia. We also reasoned that changes in transcription factor mRNAs might be less likely to be derived from non-specific variation. The design of this array is described elsewhere (Materials and Methods and Glasscock et al., in preparation). The version of the transcription factor (TF) array used in the current study consisted of probes for 1422 TFs plus a few transcriptional co-activators. This array also contained numerous 50mer control probes (see Materials and Methods).

Interrogation with the TF array revealed a large number of differences in expression profiles in the chick utricle and cochlea. The top 78 changes ranked according to P-value are shown in Table 2. This is a somewhat arbitrary cut-off, but, as is noted below, we independently validated a gene at position 74 on this list and therefore took that approximate P-value as a cut-off value. Array fold changes were averaged across six hybridizations with duplicate spots and two dye switch experiments. It should be noted that the P-values in this data set are higher because the Bonferroni correction (a multiple comparison correction of the data) depends on the number of spots on the array and is expected to be somewhat conservative as it does not account for potential correlations and unknown relationships among the genes on the array. Since our TF array measures changes in ~1500 genes, this results in more modest P-values. For example, the changes in GATA3 and SMAD2 that were observed with the inner ear array had P-values of less than 1x10-7, while on the TF array these changes have P-values of 3.5x10-4. It should also be noted that the detectable fold differences are different between the two arrays, presumably reflecting differences in degrees of homology between the chick cDNAs and the arrayed probes. However, while the values may differ slightly, the data are completely consistent in the trends they reflect between the two array types. Table 3 shows the top 50 TF changes in utricle and cochlea ranked by microarray fold change rather than by P-values.


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  		Table 2. The 78 most significant changes in TF gene expression ranked by P-values
 

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  		Table 3. The 50 highest changes in TF gene expression ranked by microarray fold changes
 
We again employed Q-PCR to independently validate this dataset and chose a range of fold changes to check. The lowest of these was TBX2, which had a fold change of 1.72. This change was associated with a highly significant P-value of 1.60x10-5. As shown in Table 2, the Q-PCR assays confirmed that this relatively low fold change reflected a real change in expression between the two epithelia. Interestingly, the trends shown by genes such as EYA3, which had a fold change of 1.83, but a much less significant P-value of 9.24x10-3 (placing it at 74th on the rank order of P-values), were also confirmed in multiple Q-PCR experiments.

We also used this dataset to obtain an estimate of how many TFs are on or off in each sensory epithelia. Again, the cut-off is somewhat arbitrary, but the internal controls in our experiments allowed us to set a sensitivity of detection threshold to guide our estimates. Based upon those calculations we estimate that approximately 600 TFs (out of 1422 assayed) are on in both epithelia. Of these TFs, we estimate that approximately 40 TFs in each epithelia are on in one and below the threshold of detection (presumably off) in the other (data not shown).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
This study had three distinct objectives. The first was the development of new molecular markers to investigate the development and regeneration of the cochlea and utricle epithelia. It is interesting to note that, among the changes we observed, several were in genes previously shown to play important roles in inner ear development. These include GATA3 and TBX2 (37,39–41). We also observed changes in additional inner ear transcription factors such as MATH1 and BRN3C, which showed 1.17- and 1.52-fold changes respectively. However, these genes did not meet the criteria for inclusion in Table 2 (ranked by P-values) or in Table 3 (ranked by fold change). It is likely that these slight observed changes in gene expression reflect the expression of these genes in the hair cells of both sensory epithelia (42,43). We expect that many of the other genes that were identified in this study will prove useful as markers of inner ear development. Of particular interest are transcription factors such as LOC51637 and HMG20B, about which little is know, but which are both up-regulated in the sensory epithelium of the utricle. Another novel TF is the cysteine-rich protein CRIP2/CRP2. It is widely expressed and localized to actin filaments, leading to its implication in assembly and organization of the cytoskeletal components (44,45), but its precise function is unknown. Tables 1 and 2 contain many additional interesting genes that should prove useful as markers and as clues to inner ear genetic pathways in the future. The set of 78 transcription factors in Table 2 should also provide potential markers for the study of the mature cochlea and utricle and for the molecular embryology of these structures. They may also point to pathways, activators or downstream genes that might make interesting targets for future disruption.

Our second aim in performing this study was to identify candidate deafness disease loci. A similar strategy has recently proved useful in the search for retinal degeneration loci (46). Our identification of several known ‘deafness’ loci within our dataset (e.g. GATA3, KIT and PAX3), suggests that further investigation of these genes as candidate disease loci might be productive. Figure 3 shows human chromosome ideograms with the mapped locations of as yet uncloned deafness loci and the localizations of 20 TFs from our list superimposed upon them. While some of these are likely to be coincidental colocalizations, these genes provide readily testable candidates for the various disease loci shown in Figure 3.



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  		Figure 3. Differentially expressed TFs as candidate deafness loci. A set of human ideograms are shown with the bars at the right indicating the localization of various as yet uncloned deafness loci. At the left of each ideogram are shown the genomic locations of various TF genes that show differential expression in cochlea/utricle epithelia from our microarray analyses.

 
Our final aim was to identify the signaling pathways that are responsible for sensory regeneration in the avian ear by analyzing changes in gene expression between the cochlea and the utricle. This is a complex problem and is further complicated by the dynamic nature of the processes that are occurring in the utricle sensory epithelia. At any given moment some utricular hair cells are undergoing apoptosis, and some supporting cells are quiescent while other are proliferating. Despite these complications it is possible to identify certain signaling pathways within our data set. For example, several stress response genes exhibit differential expression. This includes enolase 1 (ENO1) that is elevated in the utricle sensory epithelia. It acts as both a transcription factor and a glycolytic enzyme (47) and is involved in multiple events from hypoxia stress response and tumor progression (48), to a structural function in the lens (49). Its expression in the utricle has not been previously described. Another group of stress response genes are MAFs, (50–52). These form homo- and heterodimers and act as both transcriptional activators and repressors (53–55), but have not previously been shown to be expressed in the inner ear. Our data suggest that MAFG is up-regulated in the utricle.

One particularly intriguing result of the present study is the differing expression pattern of the zinc finger transcription factor GATA3 in the cochlea and utricle. Results of both in situ hybridization and immunohistochemical labeling indicate that GATA3 is expressed throughout the sensory epithelium of the cochlea, but is limited to the striolar region of the utricle (Figs 1 and 2). Prior studies have indicated that GATA3 plays several distinct roles in vertebrate development, including the differentiation of T-lymphocytes and selected populations of neural crest-derived and CNS neurons (56). GATA3 also appears to be involved in the patterning of the developing ear and in pathfinding of the auditory neurons. During the embryonic development of the mammalian ear, GATA3 is expressed in selected regions of the otocyst as well as in developing cochlea and in the striolar region of the utricle (37,38,40). GATA3 is also expressed in a cell line derived from the mammalian organ of Corti, and is associated with genes that are implicated in neuronal guidance (57). The expression of GATA3 in the mammalian ear appears to be limited to embryonic development and GATA3 expression is down-regulated following hair cell differentiation (38). It is also deleted in DiGeorge Syndrome and hypoparathyroidism, sensorineural deafness and renal displasia syndrome (HDR; MIM no. 131320-GATA3). Data from the present study indicate that GATA3 expression is maintained in the mature avian ear. The observation that GATA3 is expressed in the striolar region of the mature utricle is of particular interest, since the striola defines a narrow boundary where hair cell phenotype, orientation and innervation undergo abrupt changes (35). Since the mature avian utricle is constantly producing new hair cells, it is likely that the developmental cue(s) that specify the striola remain expressed throughout life. The present results, along with more recent observations (58) suggest that GATA3 may serve as a ‘marker’ for the position of the striola during sensory regeneration in the utricle.



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  		Figure 2. Immunohistochemical staining with a GATA3 antibody. The top two panels show GATA3 immunoreactivity in utricle hair cells and its localization to the nuclei of a strip of cells (the striola) in the utricle. The lower two panels show a more diffuse GATA3 staining in the cochlea.

 
In the current study the tyrosine kinase receptor cKIT was transcriptionally up-regulated in the utricular sensory epithelia. Mutations in c-KIT cause piebaldism, a skin pigmentation defect, but mutations in the mouse c-kit gene cause ear abnormalities (33) and a mutation at R796G in the intracellular kinase domain leads to deafness in one human pedigree (34). Several other genes that have been implicated in human deafness and pigmentation disorders are also up-regulated in the avian utricle. These include PAX3 (implicated in Waardenburg Syndrome, WS) and TBX2, a known downstream target of MITF (59,60) (also implicated in WS) and regulator of Tyrosinase Related Protein 1 (61). TBX2 has previously been shown to be expressed in the chick otic vesicle from stages 11 to 27 (41) and slight overexpression of this gene has been shown to repress the cell cycle checkpoint gene Cdkn2 and lead to cell immortalization (62,63). Interestingly, both melanogenesis and sensory hair cell proliferation can be stimulated by the addition of forskolin, which initiates cyclic AMP(cAMP) synthesis (15,16,64). Both processes are also stimulated by insulin, insulin growth factor and by beta-catenin (11,20,65,66). The inner ear contains melanocyte populations (67), but these were not present in the sensory epithelia used in this study. It is tempting to speculate that the cKIT pathway plays a role in utricle hair cell proliferation independent of its known role in melanocyte differentiation. Further experiments are underway to directly test this. Despite these few tantalizing clues, most of the changes we have observed do not fall into discernible pathways or networks at this time. It is clear that synchronized regenerating hair cell populations will be important in determining which of these changes are important in the turnover and regeneration of sensory hair cells.

We believe this is the first report of the successful use of human microarrays to interrogate chick gene expression. This is also the first time that gene expression changes in such a large number of transcription factor genes have been simultaneously measured. By monitoring over 1800 genes, we identified approximately 100 significant differences in gene expression between the proliferative chick utricle epithelium and the quiescent sensory epithelium of the chick cochlea. By conducting multiple hybridizations, incorporating numerous controls and using statistical analysis tools we were able derive a robust set of observations. The changes in gene expression that we have observed in this study should provide a diverse set of new reagents for investigating the molecular embryology of the inner ear as well as insights into the genetic pathways of hair cell turnover and regeneration.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Sensory epithelia isolation
White Leghorn chicks (10–21 days post-hatch) were euthanized by CO2 asphyxiation and decapitated. Cochleae and utricles were quickly removed and placed in chilled Medium 199 with Hanks salts (Invitrogen). The tegmentum vasculosum and lagena were removed from each cochlea and the otolithic membrane and associated otoconia were removed from the utricles. Sheets of isolated sensory epithelia were then obtained from these specimens following published methods (20,68). Briefly, sensory organs were incubated for 60 min in 500 µg/ml thermolysin (Sigma, dissolved in Medium 199 with Earles salts) at 37°C. Specimens were then returned to chilled Medium 199 with Hanks salts, and a fine needle was used to remove individual sensory epithelia from their native basement membranes and connective tissue. Sensory epithelia from individual cochleae or utricles were then pooled together in 100 µl Medium 199 (8–10 samples in each experiment).

RNA isolation, cDNA synthesis and amplification
Approximately 50 000 sensory epithelial cells from either the utricle or cochlea were suspended in Trizol (Invitrogen) and total RNA was isolated as per the manufacturer's protocol. Polyadenylated RNAs were isolated using 10 µl of oligo dT25 streptavidin-coated paramagnetic beads (Dynal) and these were introduced into a cDNA synthesis and PCR amplification [described in detail elsewhere (Korshunova et al., in preparation)]. Briefly, total RNA was combined with beads and an equal volume of binding buffer (20 mM Tris–HCl, pH 7.5, 1.0 M LiCl, 2 mM EDTA) at room temperature for 20 min. Beads were then washed with wash buffer (10 mM Tris–HCl pH 7.5, 0.15 M LiCl, 1 mM EDTA). An initial cDNA synthesis was conducted on the beads using Superscript RT (Invitrogen) in a 10 µl reaction at 42°C for 1 h in the presence of a modified 5' SMART linker (69) (Korshunova et al., in preparation), the sequence of which was 5'-GCGGCCGCTAATACGACTCACT ATAGGG-3'. The beads with cDNA attached were washed twice with wash buffer as above, followed by two washes with 1x digestion buffer (50 mM Tris–HCl, 10 mM MgCl2, 100 mM NaCl, 1 mM dithiothreitol). cDNAs were then digested with NotI to remove concatenated linkers. Beads/cDNA were washed twice with 50 µl of water. This cDNA was then subjected to three cycles of PCR amplification using the following two primers: 5'-CATGCTAATACGACTCACTAT AG-3', and 5'-AAGCAGTGGTAACAACGCAGAGTAC TTTTTTTTTTTTTTTVN-3'. Beads were then magnetically captured and the cDNA in the supernatant was removed. The entire cDNA supernatant was then amplified in twice the original reaction volume for an additional seven cycles with primers 5'-CATGCTAATACGACTCACTATAG-3', and 5'-AGTGGTAACAACGCAGAGTAC-3'. Amplified cDNA was desalted on a Sephadex G50 minicolumn, and one-third of the reaction was used in a tertiary PCR to add linkers for UDG cloning into the pAMP1 vector (Invitrogen). These linkers were: 5'-CAUCAUCAUCAUGCTAATACGACTCAC TATAG-3', and 5'-CUACUACUACUAGTGGTAACAACC AGAGTAC-3'. More than 106 primary transformants were constructed by chemical transformation of UltraMax DH5{alpha}-FT competent cells (Invitrogen). Two libraries (one from utricle and one from cochlea sensory epithelia) were constructed by these methods. Other samples were converted (as above) by PCR into double-stranded cDNAs that contained a T7 RNA polymerase binding site. These uncloned cDNAs were used in independent labeling and hybridization experiments (see below), but they were not converted into actual libraries of molecular clones.

In vitro transcription; RNA run-offs
RNA templates were generated from purified plasmid DNAs. These were produced from each entire cloned library by first growing the library (>106 clones) on plates, scraping off all these colonies and purifying plasmid DNAs (70). Pooled purified plasmids were linearized by digestion with NotI and gel purified. One microgram of linearized (library) plasmid DNAs was added to an Ambion T7 Megascript reaction and in vitro run-off transcripts were generated as per the manufacturer's instructions. Run-off RNAs were LiCl precipitated, washed with 75% ethanol, and resuspended in water at a concentration of 0.5–1.0 µg/µl. For run-off production from uncloned samples the PCR products after Sephadex G-50 desalting (above) were ethanol-precipitated, resuspended and directly added to an Ambion T7 Megascript reaction. The overall yield and quality of run-off products were assessed by gel electrophoresis.

Target labeling and microarray hybridizations
Bulk run-off RNAs from each library were used as templates in an oligo dT12–15 primed cDNA synthesis reaction that included amino-allyl dUTP (Sigma, 0.2 mM). The cDNA was then either coupled to Cy3 or Cy5 mono ester dyes (Amersham Pharmacia) and purified as described elsewhere (71). Labeled cDNA populations were precipitated and resuspended in 20 µl hybridization buffer (50% formamide, 6x SSPE, 5x Denhardt's, 0.5% SDS, 10% dextran sulfate). Microarray slides were hybridized at 42°C for 12 h. TF oligonucleotide slides were hybridized at 37°C for 12 h. Slides were washed 5 min each in 0.2x SSC followed by 0.05x SSC and dried. Slides were scanned using a GMS 418 scanner at gains ranging from 25 to 35 scanner units. Microarray targets included spiked control RNAs. Each of these three controls consisted of a few hundred base pairs of specific C. elegans cDNA sequence with a polyA tract inserted at its 3' end. The short sequence was directionally cloned adjacent to a T7 promoter. A T7 polymerase RNA run-off from each cloned Ce tag produced a short polyadenylated RNA that did not share significant sequence homology with any human, mouse or chick sequences (by BLAST search). These RNAs were then seeded into the two targets (at different concentrations) prior to cDNA synthesis. These controls are listed at http://hg.wustl.edu/lovett/projects/nohr/intlctrl.html.

Microarray slide processing and printing
Slides for printing were pre-treated by washing for 2 h in a 10% (w/v) NaOH, 57% (v/v) ethanol solution. Slides were then rinsed four times in water. They were coated in a solution of 10% poly-L-lysine, 10% PBS for 1 h at room temperature, rinsed in water and dried. PCR amplicons and oligonucleotides were resuspended in printing buffer (50% DMSO, 1.5 M Betaine for PCR products, and 6% DMSO, 1.5 M Betaine for oligonucleotides). Microarrays were printed on a GMS 417 arrayer within the Washington University Division of Human Genetics. After printing, slides were baked at 80°C for 2 h.

Design of custom cDNA and oligonucleotide microarrays
We designed and built two microarrays for this study. Both of these are listed at http://hg.wustl.edu/lovett/projects/nohr/hair-cell.html. The inner ear cDNA array interrogated a collection of 426 genes known to either affect hearing or to be expressed in the inner ear. Many of these were derived from three web sites (http://dnalab-www.uia.ac.be/dnalab/hhh/, http://www.ihr.mrc.ac.uk/hereditary/genetable/index.shtml and http://hearing.bwh.harvard.edu/estinfo.HTM). Primers for this array were designed using primer3 (http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi) to generate amplicons 150–300 bp in length. Each primer was designed to be 20–22 bp in length with an average annealing temperature of 58°C with 50% GC content, and a GC clamp. Amplicons were generated from a pool of human libraries including HeLa cells, thymus, fetal brain, testis and pancreas. PCR products were gel purified and ethanol precipitated. Following verification by DNA sequencing they were resuspended in printing buffer (50% DMSO, 1.5 M Betaine) at a concentration of 300 ng/µl. In all cases every gene or control was spotted in triplicate. The Ce tags mentioned above were also spotted onto this array. These artificial control tags were also introduced at various concentrations into the cochlea and utricle targets, and served as normalization factors and measures of detection sensitivity.

The TF array is listed at http://hg.wustl.edu/lovett/projects/nohr/TFarray.html and contains 50mer oligonucleotide probes to the majority of known human transcription factor genes, plus some anonymous ESTs that contain transcription factor motifs and a few transcriptional co-activators. The seed set for the array covered all orthologs of TFs in Flybase and TRANSFAC as well as TFs in REFSEQ. A complete list of the TFs that this array interrogates is available at http://hg.wustl.edu/lovett/projects/nohr/TFarray.html. The number of genes interrogated by this array was 1422. It should be noted that, while this is a very large set, our informatics analysis indicates that it does not comprise the entire set of TFs encoded by the human genome (Glasscock et al., in preparation). It is well known that many transcription factors contain highly related sequence motifs (for example zinc finger motifs). We therefore carried out a detailed analysis (Glasscock et al., in preparation) to derive a set of oligonucleotides from outside these shared motifs so that each transcription factor could be individually interrogated. In building these probes we were also particularly careful to avoid picking 3' untranslated regions (UTRs) as the specific probes, since this would render them useless for monitoring gene expression in different species (e.g. interrogating the chick samples in this study). For a discussion of the degree of sequence conservation on average between human and chick see above. All of the 50mers were Tm-matched. All were precipitated and resuspended at a concentration of 60 µM in 6% DMS0 and 1.5 M Betaine. The TF array also contained within it individual 50mers to interrogate each Ce control tag. All TF probes were spotted in duplicate on each printed slide.

Quantitative PCR
Total RNA was extracted from additional chicken utricular and cochlear sensory epithelia as described above. Approximately 50 ng of total RNA was used to generate cDNA using a Qiagen Sensiscript cDNA Synthesis Kit. The resulting cDNA (~0.72 ng) was diluted to 50 µl and 2 µl were used in each Q-PCR reaction. PCRs were set up using Applied Biosystem's SYBR Green PCR Master Mix in 25 µl reactions. Primers were designed using the ABI Primer Express software. Melting curves and PCRs were run on an ABI 7700 machine and results analyzed using ABI Sequence Detector software. To identify chick orthologs and design chick primers for each tested gene we BLASTed the corresponding human gene against the TIGR Gallus gallus EST database (http://tigrblast.tigr.org/tgi/). Relative fold changes were calculated based on differences between a user defined cycle threshold between the two populations of interest, after normalization based on 18S RNA levels in each population (72). Each gene was run at least six times on at least two biological samples. Cycle threshold values differing by a standard deviation greater than 0.5 were removed from the analysis, before being averaged to calculate the relative fold change.

In situ hybridizations and Immunocytochemistry
PCR amplicons were generated with primers designed to amplify chick sequences. A second round of amplifications was used to add T7 and T3 promoter sequences to the 5' and 3' ends, respectively. PCR products were gel purified and an aliquot was DNA sequenced to verify the identity of the product. Amplicons of 200–300 bp were used as templates to generate DIG-labeled in vitro transcripts (Ambion Maxi-script kit). Sense (T7) and anti-sense (T3) probes were separately generated from the respective promoters. Cochleae and utricles were harvested from chicks (10–21 days post-hatch) and processed for whole mount in situ hybridization following a published protocol (73). Labeled specimens were mounted in glycerol/PBS (9 : 1) and viewed with conventional brightfield microscopy (Nikon Eclipse 2000). Images were obtained using a monochrome CCD camera (Q-Imaging).

Other specimens were processed for immunohistochemical labeling of GATA3. Cochleae and utricles were fixed in chilled 4% paraformaldehyde (in PBS) for 20 min. Non-specific antibody binding was blocked by incubation for 2 h in 2% NHS, 1% BSA, and 0.2% Triton X-100 (in PBS). Specimens were then incubated overnight in anti-GATA3 (Santa Cruz Biotechnology, mouse IgG), diluted 1 : 200 in PBS, with 2% NHS and 0.2% Triton X-100. Following thorough rinsing in PBS, specimens were incubated in biotinylated anti-mouse IgG (Vector) followed by strepavidin-conjugated Alexa 594 (Molecular Probes). Specimens were counter-stained with Alexa 488-labeled phalloidin (Molecular Probes) and bisbenzimide (Sigma) and were viewed with epifluorescence microscopy (Nikon Eclipse 2000).

Data analysis
Microarray images were analyzed with the BioDiscovery ImaGene and GeneSite-Lite programs. The Cy3 and Cy5 images were computationally overlaid, aligned and gridded. The intensity of each spot was measured by laser scanning (as described above). The Imagene program uses the signal mean ratio of the log10 intensity values to determine fold expression changes. These values (over at least four different experiments and with at least two dye labeling switches) were then analyzed as described by Wolfinger et al. (30). This method uses two steps, a normalization step and a model fitting step, to obtain statistical significance levels that take into account experimental variability. SAS (SAS Institute, Cary, NC, USA) code from Wolfinger et al. (http://statgen.ncsu.edu/ggibson/Manual.htm) was adapted to our data. In the normalization step we included fixed effects for tissue, dye and spot repetition (the last to account for the triple or double-spotting of each probe onto the slide) as well as interaction terms; random effects were included to model variability among the experiments and the four pins of the arrayer, and interactions between random and fixed effects. The subsequent t-tests were corrected using a Bonferroni correction for the number of genes on the array.


   ACKNOWLEDGEMENTS
 
We thank Dr Jeffrey Gordon and his group for valuable assistance with Q-PCR, and Dr Anne Bowcock for critical comments on the manuscript. We are particularly grateful to the National Organization for Hearing Research Foundation for their financial support of this research. Additional support was provided by NIH/NIDCD grant DC03576 (M.E.W.).


   FOOTNOTES
 
* To whom correspondence should be addressed. Fax: +1 3147472489; Email: lovett{at}genetics.wustl.edu Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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