|Molecular Vision 2007;
Received 30 October 2006 | Accepted 27 January 2007 | Published 8 February 2007
Transfer of lens-specific transcripts to retinal RNA samples may underlie observed changes in crystallin-gene transcript levels after ischemia
Frederike Dijk,1 Willem Kraan,1 Arthur A.B. Bergen1
1Department of Molecular Ophthalmogenetics, 2Department of Cellular Quality Control, Netherlands Institute for Neuroscience-KNAW, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands
Correspondence to: W. Kamphuis, Department of Ophthalmogenetics, Netherlands Institute of Neuroscience (NIN-KNAW), Meibergdreef 47, 1105 BA Amsterdam, The Netherlands; Phone: 31 20 5666101; FAX: 31 20 5665500; email: email@example.com
Purpose: Retinal ischemia appears to lead to alterations in retinal transcript levels of a group of genes known to be abundantly expressed in the lens. Our purpose is to study whether these alterations are truly the result of retinal ischemia or whether they could be caused by contamination of the retinal tissue with trace amounts of lens tissue.
Methods: Changes occurring in the retinal gene expression profile after induction of retinal ischemia were assessed by oligonucleotide microarrays and by real-time quantitative PCR.
Results: Microarray analysis of the retinal gene expression profile after 5 or 60 min ischemia showed altered transcript levels for a group of genes with functions related to "structural constituent of eye lens" (23 genes, predominantly crystallins). Subsequent qPCR assays for this set of genes showed extremely high variations in transcript levels between individual animals of both control and ischemia-treated groups. However, the relative transcript levels, or expression profile, of these genes was constant in all samples. The transcript levels of these genes were on average 2624-times higher in tissue samples isolated from the superficial layers of the total lens. Moreover, all 23 genes had high expression levels in lens compared to retina as was shown by microarray.
Conclusions: From these data, it appears plausible that during isolation of the retina, trace amounts of lens tissue may end up in the studied retinal samples. This would explain the high level of variability in transcript levels of genes, the strong correlation of relative levels between samples, and the link with lens-specific function of the "altered" genes. Changes in crystallin gene expression in other models of retinal degeneration have been reported and a careful examination of the transcript level of other lens-specific genes is essential to rule out a possible confounding effect of lens-material transfer.
The gradual and selective loss of retinal ganglion cells via apoptosis underlies the progression of glaucoma. A variety of causal factors leading to ganglion cell apoptosis has been put forward, but the relative contribution of these factors to the initiation and progression of glaucoma remains unknown. One of the factors implicated in glaucoma as well as in diabetic retinopathy and central retinal artery occlusion, is hypoxia/ischemia [1-4]. The preferential loss of retinal ganglion cells in the glaucomatous retina corresponds to the pattern of neuronal degeneration through apoptosis after experimental ischemia [5,6]. We have initiated a series of experiments in order to study the alterations in gene expression patterns after 60 min of ischemia and after ischemic preconditioning (IPC). The latter refers to the effect that a short period of ischemia, 5 min, does not lead to cell loss but instead provides a transient protection against the degenerative effects of a subsequent full ischemic insult [7,8].
The results of these studies will be published elsewhere . In the present report we focus on the profound changes observed in a set of genes including members of the crystallin gene family and other genes associated with the lens. At first alterations in the expression of crystallin genes seemed to be in line with reports on altered crystallin transcript levels resulting from chronic elevation of intraocular eye pressure [10,11], light injury , mechanical injury , and genetic retinal degeneration . However, subsequent evaluation of our microarray findings by quantitative PCR assays performed on individual samples revealed an exceptional large inter-individual variation in the expression level of this set of genes, in both control and experimental groups.
The focus of this report was to investigate the possibility that a transfer of tissue from the lens to the retinal sample may occur and corrupt the expression data for genes that are abundantly expressed in the lens compared to the retina.
Animals and anesthetics
Animal handling and experimental procedures were reviewed and approved by the ethical committee for animal care and use of the Royal Netherlands Academy for Sciences, acting in accordance with the European Community Council directive of 24 November 1986 (86/609/EEC) and the ARVO statement for the use of animals in Ophthalmic and Vision Research. Transient retinal ischemia was induced by means of raising the pressure in the anterior chamber of the rat eye via an inserted needle as described in detail previously [15-18]. For ischemic preconditioning (IPC) 5 min of ischemia was applied and retinas were isolated 1, 3, 6, 12, 24, 48 h, and 7 days later (n=5-6, each condition). For ischemia/reperfusion (I/R), 60 min of ischemia was applied and the retinas were studied after the following reperfusion times: 1, 2, 6, and 12 h (n=5/condition). To study the changes in gene expression after 60 min of ischemia in preconditioned animals (IPC-I/R), animals were first subjected to 5 min ischemia followed, after an interval of 24 h, by 60 min of ischemia. Retinas were studied after the following reperfusion times: 1, 2, 6, and 12 h (n=6-7 each time point). Animals were killed by an overdose of sodium-pentobarbital (0.8 ml; 60 mg/ml) intraperitoneally. Sham-operations were performed by inserting a needle into the anterior chamber without elevating the pressure.
The eyes were enucleated and washed in cold phosphate buffered saline. A circumferential cut was made along the ora serrata. The cornea, ciliary body, lens and adhering vitreous were carefully removed from the eyecup using a pair of brushes. The retina was separated from the sclera, frozen on dry ice, and stored at -80 °C until use. Frozen retina was thawed in Trizol (Invitrogen) and homogenized. Total RNA was isolated following the manufacturer's instructions. The total RNA yield was 8-10 μg/retina and quality checks showed sharp ribosomal RNA bands with RNA Integrity Numbers (RIN) >8.7 (Agilent Technologies 2100 Bioanalyzer).
Four eye lenses were isolated, placed in Trizol and shaken for 5-10 min. The total RNA sample obtained was used for microarray probe generation and for qPCR assays.
Microarrays and analysis of microarray data
Of each animal, 1 μg of isolated total RNA was used to make pooled samples for each of the groups and one for all contralateral control retinas (n=36). From these pooled samples amino allyl-UTP labeled aRNA was prepared (Amino Allyl MessageAmp aRNA kit, Ambion) and coupled to Cy3 or Cy5 monoreactive dyes (Amersham). For details see Kamphuis et al. .
For microarray hybridization, a common reference design was used. aRNA of the control-group (30 μg) was labeled with Cy3. An aliquot of 1 μg of this sample served as the identical common reference sample present on each array and was hybridized together with 1 μg of Cy5-labeled aRNA from one of the experimental groups. Hybridization and washing was carried out according to the protocols described by Agilent. For details see: "Agilent" 60-mer oligo microarray processing protocol v2.1 (SSPE/SureHyb)® at Agilent. After normalization, the resulting dye ratio represents the transcript ratio between the two hybridized samples.
Oligonucleotide arrays were obtained from Agilent (22K catalog rat array, 60-mer oligonucleotides, product number G4130A; detailed information on all oligonucleotide probes can be found at Agilent or Geo).
The array images were acquired using an Agilent microarray scanner set at 5 μm resolution and were processed with Feature Extraction software v8.1 (Agilent) using default settings for all parameters. The Feature Extraction output shows the sequence identification and description of all chip oligonucleotide probes, the signal strength of the treatment (Cy5) and control (Cy3) channels, the relationship between the two channels in terms of log10 ratio, the estimated log ratio error and associated p-value. Images and data files were uploaded to the Rosetta Biosoftware Resolver® system, v5.0. Detailed information on the Rosetta Resolver system can be found at Rosettabiosoftware, and in several published papers [19-21].
Gene annotation of the genes on the array was updated using web-based annotation tools DAVID and Source. Of the 20,280 features representing expressed sequences 18,690 were linked to a UniGene Cluster ID (92%). Gene Ontology (GO) analysis was performed with GOstat (GOstat) . Searches for regulatory elements in the crystallin genes were conducted with the Genomatix Suite (Genomatix) , and with Match 1.0 (Generegulation).
Real-time quantitative polymerase chain reaction
For qPCR, 2 μg of total RNA from each individual retina was DNaseI treated, reverse transcribed into cDNA with 100 U Superscript III Reverse Transcriptase (Invitrogen) and 50 ng random hexamer primers. The resulting cDNA sample served as a template for SYBR green RT-qPCR analysis (ABI 7300 real-time system). The amplification efficiencies were close to 100% for all primer combinations. The resulting Ct values were converted to absolute amounts of transcript present in the sample (E-Ct) in arbitrary units, multiplied by 1010 for presentation purposes .
To correct for differences in cDNA load between the different samples, we normalized the target PCR to a set of four reference PCRs. For this purpose, qPCR data for a selection of candidate reference genes on experimental and control samples was used as input for a geNorm analysis [24,25]. Rho (rhodopsin), Hprt (hypoxanthine phosphoribosyl transferase), Pde6b (phosphodiesterase 6B), and Prkca (protein kinase C alpha) were identified as most stable and were used for normalization. All presented transcript levels, including crystallin levels, are normalized against the transcript levels of these reference genes.
Three different conditions of retinal ischemia were studied: ischemic preconditioning (IPC), ischemia-reperfusion (I/R), and IPC followed by ischemia-reperfusion 24 h later (IPC-I/R). Applying a feature extraction assigned p value <0.001 cutoff on the microarray-derived changes showed that several members of the crystallin-gene family were highly regulated under all three conditions with 2- to 10 fold changes. Gene ontology (GO) analysis , revealed a statistically significant overrepresentation of the GO-term Structural constituent of eye lens (GO id: 0005212) for most of the experimental conditions (Table 1).
Clustering was carried out on the changes observed in the three different experimental conditions separately and on the combined total data set. Various clustering algorithms consistently identified a set of 25 features, representing 23 different genes, with a parallel response to the different ischemic conditions (Figure 1). This set included 10 different crystallin genes (Cryaa, Cryab, Cryba1/ba3, Cryba2, Cryba4, Crybb1, Crybb2, Crybb3, Crygd, Crygn) and six genes with a known lens-association: Bfsp1 (Beaded filament structural protein 1, also known as filensin), Bfsp2 (Beaded filament structural protein 2, also known as phakinin or CP49), Gluld1 (Glutamate-ammonia ligase domain containing 1/lens glutamine synthase-like (lengsin)), Grifin (Galectin-related inter-fiber protein), Lenep (lens epithelial protein), and Lim2 (Lens intrinsic membrane protein 2). The transcript levels of these genes were transiently upregulated after IPC by 4- to 7 fold at 1, 3 and 6 h. Following I/R in naive animals, transcript levels were decreased 3- to 10 fold. In contrast, in preconditioned animals, ischemia resulted in a persistent increase of 2- to 6 fold compared to controls. The crystallin features Crym, Cryac, and Cryz were not associated with the cluster.
The transcript levels of the 14 crystallin genes were investigated by qPCR assays on all individual RNA-samples that contributed to the sample pools. Linear regression analysis of the fold change as measured on microarray against the average change derived from the qPCR results showed a significant correlation (R2=0.61; Figure 2). qPCR data were also obtained for a different group of 16 other transcripts, including the reference genes (Gapd, Hprt, Pde6b, Prkca), genes known to give an early response to ischemia (c-fos, c-jun) and genes known to show a more delayed response (Hmox1, Gfap, Vim, Gria1, Gria2, Pvalb, Thy1, nestin, VIP, Thy1). The correlation coefficient R2 for this group was at 0.73 similar to the set of crystallin genes. However, the two groups of genes differed in the level of variance among the individual samples. For the crystallins the variance was 120% (SD/mean * 100%), while the variance for the second group of genes was around 40% comparable to our earlier findings [18,24]. The difference in variance was consistent in groups of non-treated animals, sham-operated animals, and in all three experimental groups. As a consequence of this high variance, most changes depicted in Figure 1 were not found to be statistical significant whereas ischemia-induced alterations of c-fos, c-jun, Hmox1, Gfap, Vim, Gria1, Gria2, Pvalb, Thy1, nestin, VIP, and Thy1 were all highly significant [18,24]. The only significant changes found in the group of crystallin genes were the increased Cryab and Cryac expression levels at 2, 6, and 12 h after I/R and after IPC+I/R (range 4- to 8 fold; p<0.001; Student's t-test).
In contrast to the high inter-individual variance, the transcript levels between different cluster genes showed strong correlations. An example showing the close correlation between Cryaa and Cryba1/3 is presented in Figure 3. This implies that the expression levels of the different cluster genes are linked and that transcript levels have a consistent expression profile, differing between individual samples only by a scaling factor. The transcript levels of crystallins not assigned to the cluster (Crym, Cryac, and Cryz) did not show this correlation.
These findings may indicate a co-regulation for the expression of this set of genes. However, genes in the cluster are located on different chromosomes thus ruling out a tandem arrangement of these genes under the control of a single promotor region. Expression could also be united by a common transcription factor simultaneously acting on all genes. Pax6, one of the transcription factors inferred in the regulation of crystallin gene expression may be a candidate for such a role , however changes in Pax6 transcript levels were not in line with the pattern presented in Figure 1. Other transcription factors implicated in the regulation of crystallin gene expression were either not altered (c-Maf, Sox-2, Six3, Hsf2, Ap1, Foxd3, Foxj2, Hsf, Oct1, v-Maf), or were not represented on the array (MafB, Sox1, Ror, Prox1). Searches for transcription binding sites in the crystallin genes in rat and mouse genome yielded potential regulation sites for large families of transcription factors ETSF, HOXF, EVE1, GATA, and CREB. Attempts to find a common framework of multiple transcription factor binding sites did not lead to results.
Another explanation for the correlated transcript levels could be the unintentional transfer of lens tissue during the isolation of the retina. Genes that are abundantly expressed in lens and with a low expression level in the retina would display highly correlated levels. To test this hypothesis, 2 μg RNA samples from the lens and retina (n=4 each) were analyzed by qPCR. The results are presented in Table 2. Of the set of 24 genes identified by clustering, 17 were studied by qPCR and 16 were found to much more abundant in the lens with an average lens/retina ratio of 2,624; ranging from 215 (S100a4) up to 12,700 (Crybb2). In addition Crygb, a crystallin gene not represented on the array, had a lens/retina ratio of 3273, and the Crygb levels were found to be correlated to the transcript levels found for the cluster genes. Moreover, the crystallins Cryac, Cryz, Crym not assigned to the cluster, had ratios of 0.32, 0.09, and 0.006, respectively, showing a higher expression in the retina compared to expression in the lens.
We investigated the possibility that transfer of vitreous could be implicated because it is difficult to remove all overlying vitreous from the retina during isolation. The amount of RNA in all of the vitreous obtained from a single rat eye is low (50-125 ng; n=4). qPCR assays were performed for Gapd, Hprt, 28S and Bfsp1, Lim2, Grifin, Crym, Cryaa, Crybb3. The profile of transcript levels was comparable to that of the retinal samples. However, Rho, Pde6b and Thy1 transcripts were detected in the vitreous samples, indicating a contamination with retinal tissue. The normalized transcript levels of Rho, Pde6b and Thy1 were comparable to those found in retinal samples.
Microarray of lens versus retina
In order to verify whether the set of 25 genes of the cluster are all genes with a high lens to retina expression ratio, we performed a microarray hybridization of the lens samples against retinal control samples. All 25 features found in the cluster had high expression levels in the lens compared to the retina; the PMT-settings of the scanner had to be reduced to 2% to prevent saturation of these features. The resulting MA-plot is shown in Figure 4.
We conducted a series of microarray experiments on rat retina to study alterations in the gene expression profiles after transient ischemia in order to gain insight in molecular pathways that lead to neurodegeneration and neuroprotection [7,8,27-30]. The results of these studies will be published elsewhere; here we focus on the marked changes detected in a cluster of 23 genes, including crystallins and other lens-specific genes Bfsp1, -2, Gluld1, Grifin, Lenep, and Lim2. These genes showed parallel changes after IPC, I/R, and after IPC-I/R. These findings are based on microarray data of pooled samples. The pooling strategy was prompted by the high cost of the arrays. It must be emphasized that pooling is less favorable from a statistical point of view, in particular for genes with higher variability in expression level, making validation by qPCR on individual samples a necessity . Nevertheless, previously reported alterations in gene expression were confirmed by the microarray results [18,24], and changes detected by microarrays were validated by qPCR . The qPCR validation of the cluster genes revealed a higher variability of inter-individual transcript levels compared to a set of other genes [18,24,32,33], and consequently, the ischemia-related changes in expression were not statistically significant. Only the increase of Cryab and Cryac transcript levels was confirmed. This may be of physiological relevance since Cryab confers a cytoprotective effect on various cell types and has been implicated in several neurological diseases like multiple sclerosis, Alzheimer, Parkinson disease [34,35], and myocardial ischemia . qPCR results also showed that the transcript levels between the different cluster genes were tightly coupled over the wide range of absolute levels. A common framework of transcription factor binding at the gene level could not be identified, which makes a biological regulatory mechanism to explain this observation unlikely.
We therefore explored the possibility that a transfer of lens material into the isolated retinal tissue underlies the coupling in transcript levels of these genes. In accordance with this hypothesis we found that: (i) the transcript levels of the cluster genes were between 215-times and 12,700-times more abundant in RNA isolated from the total lens as compared RNA from the retina, (ii) when comparing equal amounts of lens and retinal mRNA by microarray, the cluster genes had the highest lens/retina ratio. The same cluster genes were not abundantly expressed in samples of the vitreous. In conclusion, a transfer of lens tissue into the isolated retinal sample offers a plausible explanation of our observations.
The most likely moment of transfer to take place is during isolation of the retina. The rat lens is relatively large and the lens may be damaged when the circumferential cut along the ora serrata is made. The cornea, ciliary body, lens, and vitreous were removed using a pair of brushes. These brushes were cleaned in buffer and then used to pick up the retina from the eyecup and transfer it to a vial for storage. Following this method, small amounts of lens tissue may contaminate the isolated retinal sample. We tested an alternative method for isolation of the retina on a separate series of 59 eyes; opening the eye with a cut through the cornea and taking out the lens, vitreous and retina simultaneously, to avoid damaging the lens, followed by dissection of the retina in buffer. However, this method also resulted in crystallin transcript levels with a variation coefficient of 133%, indicating that transfer may be difficult to avoid completely. RNA isolation by laser dissection from retinal cryosections may be effective in preventing contamination but this method is labor-intensive and may compromise the quality of RNA (unpublished observations N.Y.).
The lens contains lens epithelium, stem cells, and lens fiber cells in the transition zone undergoing terminal differentiation into secondary lens fibers. The superficial lens fiber cells are nucleated and have the standard complement of intracellular membrane compartments. Crystallins α, β, and γ are ubiquitously expressed in the more superficial cortical fiber cells positioned at the equatorial region [36-38], together with Bfsp1, Bfsp2  and Gja3 . Aqp0 also known as Lim1, another major lens protein, was not represented on our array . Recently, Hawse et al. compared the gene expression profile of human lens epithelial cells and lens cortical fiber cells by microarray analysis, and found an enhanced expression of several crystallins (Cryba1, -ba2, -ba4, -bb1, -bb3, -gA, -gB, -gC, and -gD), Bfsp1, Bfsp2, Lim2, Lenep, Clic5, and Cd24 in fiber cells compared to epithelial cells. These results support our hypothesis that lens fiber cells from the superficial layers of the lens is most likely source of inadvertently transferred material.
Our data show that the transcript levels of the genes of the cluster are low in the retina. In contrast, expression of the Crym, Cryz and Cryac, which were not in the cluster, are more abundant in the retina. Localization studies on crystallins have confirmed strong Crym-immunostaining in photoreceptors but not in the lens . In mouse retina, expression of all of the 20 studied crystallin genes was detected by qPCR but similar to our findings with highly variable levels . Moreover, immunoblotting showed a high variation for Cryaa, Cryab, Crybb2, and Cryg (b, c, d) protein levels of more than 5- to 10 fold compared to tubulin levels.
To gain insight into retinal transcript levels in samples not corrupted by lens material, we analyzed microarray data collected from human photoreceptor RNA isolated by laser dissection from cryosections (unpublished observations NY). Detectable hybridization was found for all cluster members but the signal strength was lower than 4% of the maximum intensity on the array, indicating low transcript levels. The hybridization signals for Gryab, Cryz, Crym, and Crygs were strongest, which is in good agreement with our findings in the rat. In conclusion, there is ample evidence for retinal gene expression of crystallins but transcript levels are low. For that reason, due to high transcript levels found in the lens, contamination of retinal tissue with traces of lens tissue will greatly bias these transcript levels.
An intriguing question is whether our findings have any relevance for the changes in retinal crystallin gene expression that have been reported for several experimental models involving retinal injury or degeneration. As can be concluded from our data, a proper statistical analysis is essential to evaluate the observed changes. For instance, light-induced retinal damage was claimed to lead to a 2- to 3 fold increase in spot intensity of all identified crystallins in 2D-gels, however statistical information was not given . A microarray study on retinal ischemia reported an upregulation of Cryaa, Cryab, Cryba1/3, Crybb2, Crygc, and Grifin transcript levels after 12 h of reperfusion, but no qPCR validation was presented . Chronic elevation of intra-ocular pressure in rats resulted in decreased levels of Cryaa, Crybb2, and Cryab at 8 days after episcleral vein injection but the effect disappeared after 35 days and was not confirmed by qPCR . Two studies showed evidence for changes of crystallin expression in the retina and were validated by qPCR [11,13]. Local mechanical injury of the rat retina was found to be accompanied by an enhanced expression for all crystallins on the microarray and of Lim2, Bfsp1, and Grifin . The upregulation for Cryab and Crygd was confirmed by qPCR and the injury was accompanied by an increased immunoreactivity for crystallin-β,-α, and γ near the scar . A microarray study on the glaucomatous DBA/2J mouse identified a loss of Cryaa, Cryba1, Cryba2, Cryba4, Crybb1, Crybb3, Crygb, Cryd, Cryn, Cd24, Grifin, Lim2, and Mip (Lim1), of which Cryba4 and Mip were confirmed by qPCR .
In conclusion, studies on changes in the retinal transcriptome have often reported alterations of crystallins and several other lens-associated genes. Our observations show that the data on these genes have the risk of being corrupted by transfer of lens material into the isolated retinal tissue. Avoiding pooling strategies in microarray designs, a careful statistical evaluation of individual samples, and the use of comparative lens cDNA samples as controls, is essential to draw any conclusions on gene expression changes in the retina of genes with an abundant expression in the lens relative to the retina.
This study was supported by grants from: Rotterdamse Vereniging Blindenbelangen (RVBB), Stichting Blinden-Penning, Landelijke Stichting voor Blinden en Slechtzienden (LSBS), Algemene Nederlandse Vereniging ter Voorkoming van Blindheid (ANVVB), and Stichting OOG
We like to thank Natalya Yeremenko for providing the micorarray data on the photoreceptors of human retina. Koen Bossers and Judith Booy for their helpful comments.
1. Piltz-seymour JR, Grunwald JE, Hariprasad SM, Dupont J. Optic nerve blood flow is diminished in eyes of primary open-angle glaucoma suspects. Am J Ophthalmol 2001; 132:63-9.
2. Quigley HA, Nickells RW, Kerrigan LA, Pease ME, Thibault DJ, Zack DJ. Retinal ganglion cell death in experimental glaucoma and after axotomy occurs by apoptosis. Invest Ophthalmol Vis Sci 1995; 36:774-86.
3. Osborne NN, Melena J, Chidlow G, Wood JP. A hypothesis to explain ganglion cell death caused by vascular insults at the optic nerve head: possible implication for the treatment of glaucoma. Br J Ophthalmol 2001; 85:1252-9.
4. Sommer A, Katz J, Quigley HA, Miller NR, Robin AL, Richter RC, Witt KA. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss. Arch Ophthalmol 1991; 109:77-83.
5. Lam TT, Abler AS, Tso MO. Apoptosis and caspases after ischemia-reperfusion injury in rat retina. Invest Ophthalmol Vis Sci 1999; 40:967-75.
6. Nickells RW. Apoptosis of retinal ganglion cells in glaucoma: an update of the molecular pathways involved in cell death. Surv Ophthalmol 1999; 43 Suppl 1:S151-61.
7. Roth S. Endogenous neuroprotection in the retina. Brain Res Bull 2004; 62:461-6.
8. Roth S, Li B, Rosenbaum PS, Gupta H, Goldstein IM, Maxwell KM, Gidday JM. Preconditioning provides complete protection against retinal ischemic injury in rats. Invest Ophthalmol Vis Sci 1998; 39:777-85.
9. Kamphuis W, Dijk F, Van Soest S, Bergen AAB. Changes in gene expression profiles in the rat retina after ischemic preconditioning. Molecular Vision. In press 2007.
10. Ahmed F, Brown KM, Stephan DA, Morrison JC, Johnson EC, Tomarev SI. Microarray analysis of changes in mRNA levels in the rat retina after experimental elevation of intraocular pressure. Invest Ophthalmol Vis Sci 2004; 45:1247-58.
11. Steele MR, Inman DM, Calkins DJ, Horner PJ, Vetter ML. Microarray analysis of retinal gene expression in the DBA/2J model of glaucoma. Invest Ophthalmol Vis Sci 2006; 47:977-85.
12. Sakaguchi H, Miyagi M, Darrow RM, Crabb JS, Hollyfield JG, Organisciak DT, Crabb JW. Intense light exposure changes the crystallin content in retina. Exp Eye Res 2003; 76:131-3. Erratum in: Exp Eye Res 2003; 77:121-2.
13. Vazquez-Chona F, Song BK, Geisert EE Jr. Temporal changes in gene expression after injury in the rat retina. Invest Ophthalmol Vis Sci 2004; 45:2737-46.
14. Jones SE, Jomary C, Grist J, Thomas MR, Neal MJ. Expression of alphaB-crystallin in a mouse model of inherited retinal degeneration. Neuroreport 1998; 9:4161-5.
15. Osborne NN, Larsen AK. Antigens associated with specific retinal cells are affected by ischaemia caused by raised intraocular pressure: effect of glutamate antagonists. Neurochem Int 1996; 29:263-70.
16. Dijk F, Kamphuis W. Ischemia-induced alterations of AMPA-type glutamate receptor subunit. Expression patterns in the rat retina--an immunocytochemical study. Brain Res 2004; 997:207-21.
17. Osborne NN. Neuroprotection to the retina: relevance in glaucoma. In: Drance SM, editor. Vascular risk factors and neuroprotection in glaucoma: update 1996. New York: Kugler; 1997. p. 139-155.
18. Dijk F, van Leeuwen S, Kamphuis W. Differential effects of ischemia/reperfusion on amacrine cell subtype-specific transcript levels in the rat retina. Brain Res 2004; 1026:194-204.
19. Hughes TR, Marton MJ, Jones AR, Roberts CJ, Stoughton R, Armour CD, Bennett HA, Coffey E, Dai H, He YD, Kidd MJ, King AM, Meyer MR, Slade D, Lum PY, Stepaniants SB, Shoemaker DD, Gachotte D, Chakraburtty K, Simon J, Bard M, Friend SH. Functional discovery via a compendium of expression profiles. Cell 2000; 102:109-26.
20. Weng L, Dai H, Zhan Y, He Y, Stepaniants SB, Bassett DE. Rosetta error model for gene expression analysis. Bioinformatics 2006; 22:1111-21.
21. Roberts CJ, Nelson B, Marton MJ, Stoughton R, Meyer MR, Bennett HA, He YD, Dai H, Walker WL, Hughes TR, Tyers M, Boone C, Friend SH. Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles. Science 2000; 287:873-80.
22. Beissbarth T, Speed TP. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 2004; 20:1464-5.
23. Seifert M, Scherf M, Epple A, Werner T. Multievidence microarray mining. Trends Genet 2005; 21:553-8.
24. Dijk F, Kraal-Muller E, Kamphuis W. Ischemia-induced changes of AMPA-type glutamate receptor subunit expression pattern in the rat retina: a real-time quantitative PCR study. Invest Ophthalmol Vis Sci 2004; 45:330-41.
25. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002; 3:RESEARCH0034.
26. Cvekl A, Yang Y, Chauhan BK, Cveklova K. Regulation of gene expression by Pax6 in ocular cells: a case of tissue-preferred expression of crystallins in lens. Int J Dev Biol 2004; 48:829-44.
27. Whitlock NA, Lindsey K, Agarwal N, Crosson CE, Ma JX. Heat shock protein 27 delays Ca2+-induced cell death in a caspase-dependent and -independent manner in rat retinal ganglion cells. Invest Ophthalmol Vis Sci 2005; 46:1085-91.
28. Li B, Roth S. Retinal ischemic preconditioning in the rat: requirement for adenosine and repetitive induction. Invest Ophthalmol Vis Sci 1999; 40:1200-16.
29. Li B, Yang C, Rosenbaum DM, Roth S. Signal transduction mechanisms involved in ischemic preconditioning in the rat retina in vivo. Exp Eye Res 2000; 70:755-65.
30. Nonaka A, Kiryu J, Tsujikawa A, Yamashiro K, Nishijima K, Miyamoto K, Nishiwaki H, Honda Y, Ogura Y. Inhibitory effect of ischemic preconditioning on leukocyte participation in retinal ischemia-reperfusion injury. Invest Ophthalmol Vis Sci 2001; 42:2380-5.
31. Dobbin K, Simon R. Sample size determination in microarray experiments for class comparison and prognostic classification. Biostatistics 2005; 6:27-38. Erratum in: Biostatistics 2005; 6:348.
32. Xi J, Farjo R, Yoshida S, Kern TS, Swaroop A, Andley UP. A comprehensive analysis of the expression of crystallins in mouse retina. Mol Vis 2003; 9:410-9 <http://www.molvis.org/molvis/v9/a53/>.
33. Chowers I, Liu D, Farkas RH, Gunatilaka TL, Hackam AS, Bernstein SL, Campochiaro PA, Parmigiani G, Zack DJ. Gene expression variation in the adult human retina. Hum Mol Genet 2003; 12:2881-93.
34. Sun Y, MacRae TH. The small heat shock proteins and their role in human disease. FEBS J 2005; 272:2613-27.
35. Tezel G, Yang J, Wax MB. Heat shock proteins, immunity and glaucoma. Brain Res Bull 2004; 62:473-80.
36. Treton JA, Jacquemin E, Courtois Y, Jeanny JC. Differential localization by in situ hybridization of specific crystallin transcripts during mouse lens development. Differentiation 1991; 47:143-7.
37. Ong MD, Payne DM, Garner MH. Differential protein expression in lens epithelial whole-mounts and lens epithelial cell cultures. Exp Eye Res 2003; 77:35-49.
38. Alcala J, Katar M, Rudner G, Maisel H. Human beta crystallins: regional and age related changes. Curr Eye Res 1988; 7:353-9.
39. Merdes A, Gounari F, Georgatos SD. The 47-kD lens-specific protein phakinin is a tailless intermediate filament protein and an assembly partner of filensin. J Cell Biol 1993; 123:1507-16.
40. Tenbroek E, Arneson M, Jarvis L, Louis C. The distribution of the fiber cell intrinsic membrane proteins MP20 and connexin46 in the bovine lens. J Cell Sci 1992; 103:245-57.
41. Hawse JR, DeAmicis-Tress C, Cowell TL, Kantorow M. Identification of global gene expression differences between human lens epithelial and cortical fiber cells reveals specific genes and their associated pathways important for specialized lens cell functions. Mol Vis 2005; 11:274-83 <http://www.molvis.org/molvis/v11/a32/>.
42. Segovia L, Horwitz J, Gasser R, Wistow G. Two roles for mu-crystallin: a lens structural protein in diurnal marsupials and a possible enzyme in mammalian retinas. Mol Vis 1997; 3:9 <http://www.molvis.org/molvis/v3/a9/>.
43. Yoshimura N, Kikuchi T, Kuroiwa S, Gaun S. Differential temporal and spatial expression of immediate early genes in retinal neurons after ischemia-reperfusion injury. Invest Ophthalmol Vis Sci 2003; 44:2211-20.