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Retinal Cell Biology  |   November 2010
Transcriptional Profile Analysis of RPGRORF15 Frameshift Mutation Identifies Novel Genes Associated with Retinal Degeneration
Author Affiliations & Notes
  • Sem Genini
    From the Section of Ophthalmology, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
  • Barbara Zangerl
    From the Section of Ophthalmology, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
  • Julianna Slavik
    From the Section of Ophthalmology, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
  • Gregory M. Acland
    the Baker Institute, College of Veterinary Medicine, Cornell University, Ithaca, New York.
  • William A. Beltran
    From the Section of Ophthalmology, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
  • Gustavo D. Aguirre
    From the Section of Ophthalmology, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
  • Corresponding author: Gustavo D. Aguirre, School of Veterinary Medicine, University of Pennsylvania, 3900 Delancey Street, Philadelphia, PA, 19104; [email protected]
Investigative Ophthalmology & Visual Science November 2010, Vol.51, 6038-6050. doi:https://doi.org/10.1167/iovs.10-5443
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      Sem Genini, Barbara Zangerl, Julianna Slavik, Gregory M. Acland, William A. Beltran, Gustavo D. Aguirre; Transcriptional Profile Analysis of RPGRORF15 Frameshift Mutation Identifies Novel Genes Associated with Retinal Degeneration. Invest. Ophthalmol. Vis. Sci. 2010;51(11):6038-6050. https://doi.org/10.1167/iovs.10-5443.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To identify genes and molecular mechanisms associated with photoreceptor degeneration in a canine model of XLRP caused by an RPGR exon ORF15 microdeletion.

Methods.: Expression profiles of mutant and normal retinas were compared by using canine retinal custom cDNA microarrays. qRT-PCR, Western blot analysis, and immunohistochemistry (IHC) were applied to selected genes, to confirm and expand the microarray results.

Results.: At 7 and 16 weeks, respectively, 56 and 18 transcripts were downregulated in the mutant retinas, but none were differentially expressed (DE) at both ages, suggesting the involvement of temporally distinct pathways. Downregulated genes included the known retina-relevant genes PAX6, CHML, and RDH11 at 7 weeks and CRX and SAG at 16 weeks. Genes directly or indirectly active in apoptotic processes were altered at 7 weeks (CAMK2G, NTRK2, PRKCB, RALA, RBBP6, RNF41, SMYD3, SPP1, and TUBB2C) and 16 weeks (SLC25A5 and NKAP). Furthermore, the DE genes at 7 weeks (ELOVL6, GLOD4, NDUFS4, and REEP1) and 16 weeks (SLC25A5 and TARS2) are related to mitochondrial functions. qRT-PCR of 18 genes confirmed the microarray results and showed DE of additional genes not on the array. Only GFAP was DE at 3 weeks of age. Western blot and IHC analyses also confirmed the high reliability of the transcriptomic data.

Conclusions.: Several DE genes were identified in mutant retinas. At 7 weeks, a combination of nonclassic anti- and proapoptosis genes appear to be involved in photoreceptor degeneration, whereas at both 7 and 16 weeks, the expression of mitochondria-related genes indicates that they may play a relevant role in the disease process.

The term retinitis pigmentosa (RP) refers to a group of many different inherited retinal diseases characterized by progressive rod or rod–cone photoreceptor degeneration that causes subsequent visual impairment and blindness. Some of the causative genes have clear, well-identified roles (e.g., involvement in phototransduction, in maintaining photoreceptor structure, or in RPE retinoid metabolism; RetNet: http://www.sph.uth.tmc.edu/RetNet/ provided in the public domain by the University of Texas Houston Health Science Center, Houston, TX). However, there remain a large number of diseases caused by genes with poorly understood functions and for which the mechanism linking the genes and/or mutations with photoreceptor disease and degeneration is unknown. 
Among these is the RP3 form of X-linked RP (XLRP), a uniformly severe, early-onset retinal disease in humans that is caused by mutations in the RP GTPase regulator (RPGR) gene. 1 Although estimates vary depending on the sample population and methods of testing, it is generally accepted that mutations in RPGR account for >70% of XLRP cases. 2 4 Furthermore, the carboxyl-terminal exon open reading frame 15 (ORF15) of RPGR, a mutational hot spot, has been shown to be mutated in 22% to 60% of XLRP patients. 2,5,6  
RPGR is essential for the maintenance of photoreceptor viability. 7 The protein, which has a series of six RCC1-like domains (RLDs) characteristic of the highly conserved guanine nucleotide exchange factors, is found in the rod and cone photoreceptor connecting cilia. 8 RPGR has complex interactions with other proteins that have microtubular-based transport functions in the retina and that are presumed to function in the photoreceptor centrosome, inner and outer segments, and ciliary axoneme region. 9,10 Among these, the genes coding for nephrocystin-4, 11 -5, 12 and -6 9 ; PDE6D 13 ; RPGR interacting protein (RPGRIP1) 11 ; and RPGRIP1L 14 cause retinal disease when mutated, thus emphasizing the critical importance of this protein complex in maintaining photoreceptor structure, function, and viability. 
One approach to developing insights into the cell- or tissue-specific functions of genes or to examining the molecular mechanisms of disease is microarray-based global profiling of gene expression in combination with bioinformatic analysis. In several studies, the transcriptome of the mouse and human retinas has been analyzed by characterizing changes in expression profiles during development and aging. 15 17 More recently, transcriptomic data of distinct retinal cells 18 20 and a web-based platform containing numerous retinal gene expression studies have been made available (http://alnitak.u-strasbg.fr/RetinoBase/ provided in the public domain by University Louis Pasteur, Strasbourg, France). In addition, studies based on differential gene expression in mouse retinal disease models provide useful information to aid in discerning the role of disease-causing genes with respect to other genes and in evaluating their involvement in gene pathways and cascades. 21 23 These approaches have specific limitations in terms of human retinal diseases, not the least being the lack of adequate sample sizes at the appropriate disease stages. However, the constraints can be overcome by using animal models of homologous diseases. These models provide a powerful tool for translational studies, provided that the human disease modeled and the corresponding animal disease are comparable. 
Natural mutations in RPGRORF15 occur in humans and dogs, 2,24 and X-linked progressive retinal atrophy (XLPRA) is the dog homolog of human XLRP. In dogs, two different ORF15 microdeletions have been identified: XLPRA1 is a postdevelopmental, slowly progressive photoreceptor degeneration resulting from a 5-bp deletion in ORF15 that truncates the translated protein, whereas XLPRA2 is an early-onset, progressive rod and cone photoreceptor disease caused by a 2-bp deletion that creates a frameshift and premature stop in the translated protein. The deduced peptide sequence is changed by the inclusion of 34 additional basic residues that increase the isoelectric point of the truncated protein. 25 Beltran et al. 26,27 described in detail the course of retinal disease in canine XLPRA2, the phenotype of which replicates the salient features of RPGR-XLRP. 28,29  
The purpose of the present study was to identify the genes and molecular mechanisms associated with disease onset and progression in normal and XLPRA2 mutant canine retinas. We examined the global retinal gene expression profiles at 7 and 16 weeks, the most relevant disease-related ages. Kinetics of photoreceptor cell death show a burst of dying cells between 6 and 7 weeks, whereas at 16 weeks, when the retina has lost approximately 40% of its photoreceptors, there is a constant but decreased rate of cell death. 26 For this, we used a validated custom retinal cDNA microarray 30,31 and performed real-time quantitative reverse transcription-PCR (qRT-PCR), Western blot analysis, and immunohistochemistry, to confirm and expand the microarray results. We detected several genes that were differentially expressed (DE) at critical time points in the degenerating XLPRA2 retina and that are specific for the disease stages examined. The downregulation of rod-specific genes also suggests the differential and preferential damage of rods in the early stages of the disease. 
Material and Methods
Tissue Samples
Retinas were obtained from age-matched normal and mutant dogs with a common genetic background that were maintained at the Retinal Disease Studies Facility (RDSF; Kennett Square, PA) and housed in 12-hour cyclic light conditions. To avoid potential fluctuations in retinal gene expression with time of day, 32 we collected the eyes at a single time period (noon). Both eyes were enucleated after intravenous anesthesia with pentobarbital sodium, and the dogs were euthanatized after enucleation with a barbiturate overdose. The retinas were collected within 1 to 2 minutes after enucleation, flash frozen in liquid nitrogen, and stored at −80°C until use. The research was conducted in full compliance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. 
Analyses were performed at three critical time points in the disease: 3, 7, and 16 weeks of age. 26 The 3-week time point comes before the beginning of apoptosis, when the retina is comparable in structure to normal; we refer to this stage as the induction phase. The peak of cell death occurs at 7 weeks (execution phase) and decreases the number of photoreceptors by ∼10% to 15%. At 16 weeks, in the persistent execution–chronic cell death phase, the mutant retina shows a sustained, albeit reduced, cell death rate and loss of 40% of the photoreceptor layer. 
RNA Extraction
Total RNA from retinas was extracted by using standard procedures (TRIzol; Invitrogen-Life Technologies, Carlsbad, CA). RNA concentration was assessed with a spectrophotometer (model ND-1000; NanoDrop Technologies-Thermo Fisher Scientific, Wilmington, DE), and RNA quality was verified by microcapillary electrophoresis (model 2100 Bioanalyzer with RNA 6000 Nanochips; Agilent Technologies, Santa Clara, CA). Only high-quality RNA with an RIN greater than 7 and an A260/A280 ratio greater than 1.9 was used in both the microarray and the qRT-PCR analyses. 
Microarray Procedures and Statistical Analysis
Expression profiles of age-matched 7- and 16-week-old normal and XLPRA2 mutant retinas (three biological replicates for each time point and group) were compared by using a canine retinal custom cDNA microarray containing ∼4500 transcripts. Microarray construction and hybridization were performed as previously described. 30 Briefly, ∼4500 transcripts from a normalized canine retinal EST database, including positive controls, were selected and used to construct the microarray. 31 On the basis of initial validation studies, 30 pooled brain RNA, including equal amounts of total RNA from the occipital, temporal, and frontal regions collected from three 16-week-old beagles, was used as the reference sample. In each analysis, amplified and cleaned retinal RNA (RNeasy columns, Qiagen, Valencia, CA) was labeled with Cy5, and the amplified pooled brain reference RNA was labeled with Cy3. The two labeled samples were combined, and the mixture was hybridized to the slide microarray. Arrays were scanned (GenePix 4000B scanner; Molecular Devices Corp., Downingtown, PA), and the signal intensities were evaluated (GenePix Pro 6.0 software; Molecular Devices Corp.). Data normalization, using locally weighted linear regression (LOWESS) subgrid normalization, 33 which eliminates spatial- and intensity-dependent dye bias, and data filtering were performed (GeneSpring 7.3.1; Silicon Genetics-Agilent Technologies). 
Significant changes in expression were identified with Significance Analysis of Microarrays (SAM 1.15, available at http://www-stat.stanford.edu/∼tibs/SAM/, Stanford University, Palo Alto, CA). A two-class, unpaired t-statistic was applied to log 2-transformed expression data and ranked on the basis of 500 permutations, to identify significant gene expression differences between normal and mutant animals. For each gene, SAM calculated the q-value (in percent), which is the lowest false-discovery rate (FDR) at which an individual gene is called significant (calculated as the average of three biological replicates). 34 The false-negative rate (FNR) was also predicted by SAM for each comparison and resulted in 0.6% or less for all comparisons, indicating negligible type 1 error. DE genes were identified between XLPRA2 mutant versus control retinas at 7 and 16 weeks separately and between mutant and control retinas regardless of age (combined analysis). Only genes with q-values less than 10% and more than twofold change ratios were considered to be DE. 
Microarray Data Submission
The complete microarray data set presented in this publication has been deposited in the Gene Expression Omnibus 35 (National Center for Biotechnology Information [NCBI], Bethesda, MD), according to the guidelines of the rationale of minimum information about a microarray experiment (MIAME), 36 and is accessible through GEO Series accession number GSE19124 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19124). 
Bioinformatic Analyses
The Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://david.abcc.ncifcrf.gov/ National Institutes of Health, Bethesda, MD) was used to allocate DE genes with similar biological features in the different gene ontology (GO) categories (biological process, cellular component, and molecular function). A Fisher's exact test was applied to calculate the P-value (P ≤ 0.05 was considered statistically significant), which determined the probability that the association between the DE genes in the dataset and the category is explained by chance alone. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (http://www.genome.jp/kegg/kegg2.html/ developed by the Bioinformatics Center, Kyoto University, and the Human Genome Center, University of Tokyo) and the pathway analysis databases (IPA; http://www.ingenuity.com; Ingenuity Systems Inc., Redwood City, CA) were interrogated to determine biological processes, pathways, and networks with possible involvement of DE genes. For the latter, gene identifiers were mapped to networks available in the Ingenuity Systems database and ranked by score, indicating the statistical significance of genes that were linked to the same network at better than chance. Using a 99% confidence level, we considered scores of >3 to be significant, and only networks containing more than two genes were further analyzed. 
Quantitative Real-Time PCR
Eleven genes were selected for qRT-PCR to confirm expression patterns observed in the microarray data (BNIP3, CRX, NDUFS4, PAX6, PFDN5, PLAGL2, SAG, SLC25A5, SPP1, TPD52, and ZBTB4). To complement the microarray data and to evaluate crucial photoreceptor genes known to be involved in similar retinal diseases, we included seven additional genes not present in the microarray or that did not amplify in the brain pool reference tissue (CNGA3, CNGB3, GFAP, OPN1LW, OPN1SW, RHO, and RPGR). Either custom gene-specific assays (TaqMan; Applied Biosystems, Inc. [ABI], Foster City, CA) or gene-specific primers (Primer Express; ABI) were used (Supplementary Table S1). The primers for CNGA3, CNGB3, OPN1LW, OPN1SW, and RHO have been validated in ongoing studies of canine achromatopsia (András Komáromy, University of Pennsylvania, unpublished data, 2010). For RPGR, which is the gene mutated in XLPRA2 with a 2-bp microdeletion in exon ORF15, we used a probe in the junction between the 5′ untranslated region (UTR) and exon 1 that is common to all known isoforms and has been validated in a parallel study of canine XLPRA (Shana Gilbert-Gregory, University of Pennsylvania, unpublished data, 2010). 
To better understand the time course and early gene expression changes in the disease, we also performed qRT-PCR on 3-week-old mutant and normal retinas, in addition to the 7- and 16-week retinas. Three biological replicates were tested at each time point. In addition, at the 7- and 16-weeks time points, three technical replicates of one retina per group were tested, to control for technical errors. 
RNA samples were treated with RNase-free DNase (Ambion, Austin, TX) and then reverse-transcribed with random hexamers (High Capacity cDNA Reverse Transcription Kit; ABI) according to standard procedures of the manufacturers. The real-time reaction (total of 20 μL) included 20 ng of cDNA as a template, 1× PCR reaction master mix (TaqMan Universal PCR Master Mix; ABI), 1× custom gene-specific assay (TaqMan; ABI) or 900 nM of each forward and reverse primer, and 250 nM of probe (TaqMan; ABI). All the qRT-PCR reactions were performed in 96-well plates with a real-time PCR system (model 7500; ABI) and detection software (7500 ver 2.0.1; ABI). Four genes were initially selected as a reference: glyceraldehyde 3-phosphate dehydrogenase (GAPDH; Supplementary Table S1), 18S (TaqMan Gene Expression Assay Hs99999901_s1), HPRT1 (TaqMan Gene Expression Assay Cf02626256_m1), and ACTB (TaqMan Gene Expression Assay Hs03023880_g1; all from ABI). Ultimately, GAPDH was selected because, for this specific disease, it performed the most accurately and with the least variation between samples (data not shown). 
The CT values of the genes were normalized with those of GAPDH, and the ratio of mutant versus control was calculated by the ΔΔCT method. 37 An unpaired t-test was applied to each gene, to verify whether the differences between control and mutant samples at each time point were statistically significant, using thresholds previously described 38 (P ≤ 0.05, statistically significant; 0.05 < P < 0.1, trend toward statistical significance). 
Protein Extraction and Western Blot Analysis
Because of limited sample availability, Western blot analysis was performed at two ages (7 and 16 weeks), with one normal and one mutant retina used at each time point. Protein extraction and Western blot analysis were performed as described elsewhere, with minor modifications. 39 Briefly, normal and mutant retinas were homogenized and sonicated at 4°C in a buffer containing 50 mM Tris-HCl (pH 7.5), 100 mM NaCl, and protease inhibitor cocktail (Roche Diagnostics, Indianapolis, IN). The homogenate was centrifuged at 13,000g for 15 minutes at 4°C, and the supernatant containing the proteins was collected. Total protein levels were determined by the Bradford method (ABC protein assay; Bio-Rad, Hercules, CA). For Western blot analysis, 20 μg protein extract was boiled in SDS sample buffer (4% glycerol, 0.4% sodium dodecyl sulfate, 1% β-mercaptoethanol, and 0.005% bromophenol blue in 12.5 mM Tris-HCl buffer [pH 6.8]) and then separated, along with a biotinylated protein ladder (no. 7727, 1:1000; Cell Signaling Technology, Danvers, MA), by SDS-PAGE (4% stacking gel, 12% separating gel). The proteins were transferred to a polyvinylidene difluoride membrane (Trans-Blot Transfer Medium; Bio-Rad) in chilled transfer buffer (25 mM Tris base, 192 mM glycine, and 15% methanol). The membrane was blocked in 10% skim milk in Tris-buffered saline containing 0.5% Tween-20 overnight at 4°C and then was incubated for 1.5 hours with the primary antibodies. The antibodies included were NDUFS4 (ab55540, 1:1,000; Abcam, Cambridge, MA), SAG 40 (kindly provided by Igal Gery, 1:10,000), GFAP 27 (Z0334, 1:10,000; Dako Cytomation, Carpinteria, CA), and OPN1SW 27 (AB5407, 1:2,000; Chemicon, Temecula, CA). With the exception of NDUFS4 (specificity determined by the detection of the appropriate size product by Western blot analysis), the other antibodies had been validated and produced specific labeling in the canine retina using Western analysis and/or immunohistochemistry 27,40 (Kathleen Boesze-Battaglia, School of Dental Medicine, University of Pennsylvania, Philadelphia, personal communication, 2010). ACTB (MAB1501, 1:10,000, Chemicon) was used as the loading control. 
Signal was detected by incubating with the appropriate secondary antibody conjugated with horseradish peroxidase (1:2,000, Zymed, San Francisco, CA) and was visualized by the ECL method according to the manufacturer's recommendations (ECL Western Blot Detection Reagents Kit; Amersham, Piscataway, NJ). The blots were exposed on autoradiograph film (X-Omat; Eastman Kodak, Rochester, NY). 
Immunohistochemistry
Seven-micrometer-thick cryosections of OCT-embedded retinas from normal and mutant animals at 7 and 16 weeks of age were used for immunohistochemistry (IHC); the sections were cut along the superior retinal meridian, as previously described. 26 We used the same antibodies as described in the Western blot section, but at different concentrations: NDUFS4 (1:500), SAG (1:3000), GFAP (1:1000), and OPN1SW (1:50). 
Cryosections for NDUFS4 labeling were incubated with 5% H2O2/methanol for 30 minutes, blocked with 2% FBS/0.1 M Tris for 20 minutes, and incubated with the primary antibody overnight at 4°C. They were then incubated at room temperature for 30 minutes with secondary antibodies conjugated with biotin and for 30 minutes with avidin-biotin complex (Vector Laboratories, Burlingame, CA). Signals were detected with the HRP substrate 3, 3′-diaminobenzidine (DAB; Dako Cytomation). 
Cryosections were washed with 1× PBS and 0.25% Triton X-100, blocked for 20 minutes in 10% normal goat serum, 1× PBS-0.25% Triton X-100, and 0.05% sodium azide and incubated overnight at 4°C with the primary antibodies. The antigen–antibody complexes were visualized with fluorochrome-labeled secondary antibodies (Alexa Fluor, 1:200; Molecular Probes, Eugene, OR). 
Slides were examined (Axioplan microscope; Carl Zeiss Meditec, GmbH, Oberkochen, Germany) with transmitted light (NDUFS4) or epifluorescence (SAG, GFAP, and OPN1SW). Images were digitally captured (Spot 4.0 camera; Diagnostic Instruments, Sterling Heights) and displayed with a graphics program (Adobe Photoshop, Mountain View, CA). Negative control slides (normal retinas at 7 weeks) without primary antibodies did not label and did not show any labeling with the secondary antibody. 
Results
Differentially Expressed Genes
We used a canine retinal cDNA slide microarray hybridization technique to generate a comprehensive gene expression profile of normal and RPGR mutant retinas at 7 and 16 weeks of age—the relevant time points for detection of degeneration-related genes. Using high stringency in the normalization and filtering of data, we identified greater than 3500 high-quality transcripts for the comparative expression analysis. The sequences of the DE transcripts were blasted against the canine genome, and the most likely represented gene was identified. 
First, we characterized the gene expression changes during normal development by comparing the 7- and 16-week time points in normal retinas. At 7 weeks, the retina has just reached structural maturation, and at 16 weeks, it is considered developed. 41 When compared with the 16-week normal retinas, the 7-weeks retina showed 245 transcripts upregulated, and 15 downregulated, with at least a twofold change and an FDR of less than 10% (Supplementary Table S2). 
A total of 23 genes with an FDR of q = 0 were upregulated at 7 versus 16 weeks; of those, PAX6 has a major role in eye development. 42 With an increased q-value, some genes relevant to retinal transport (KIF3A, KIFAP3, and IFT88) and function (CHML) also showed increased expression at 7 versus 16 weeks (Supplementary Table S2). Eight DE genes at 7 versus 16 weeks are involved in retinal diseases in humans and, in some cases, in dogs and mice. Five were upregulated (BBS9, EYS, PRSS11, RP1, and TUB) and three were downregulated (PRCD, NPHP4, and UNC119). Among the 15 downregulated transcripts, 3 represented the same gene, SAG (S-arrestin, S-antigen, 48 kDa), indicating a high expression of this gene when the normal retina has matured. 
On the other hand, in the mutant retinas, 28 transcripts were upregulated at 7 compared with 16 weeks, but none were downregulated (Supplementary Table S2). Four of these (q = 0) were unknown genes that were represented by the clones DR010015B20A11, DR010023B10B08, DR010024B20F07, and DR010020A10F02. With the exception of two genes, VEZF1 and TPR, that were upregulated at 7 compared with 16 weeks in both the normal and mutant retinas, there was no commonality in the transcriptional profiles of the normal and mutant retinas at these two time points. 
Next, we compared the gene expression changes that occurred between the mutant and normal retinas. At the 7- and 16-week time points, 56 and 18 transcripts, respectively, were downregulated twofold or more in the mutant compared with the normal retinas, but no statistically significant upregulated transcripts were found at an FDR <10% (Supplementary Table S3). Overall, 65 of the 74 transcripts that were downregulated at either time point were annotated in comparison with the ortholog genes in humans. 
In general, although the total number of DE genes was lower at 16 weeks, significantly higher change ratios were observed when compared with those at 7 weeks. Of note, three transcripts with high change ratios (DR010015B20A11, DR010020A10F02, and DR010023B10B08), could not be associated with any known gene in the dog and other species. Furthermore, there was no overlap of DE genes at the two time points. 
Finally, to determine disease-specific changes that were not influenced by age, we also compared the mutant retinas to the normal ones, regardless of age (7 and 16 weeks: combined analysis). A total of 16 transcripts were DE, 7 upregulated and 9 downregulated, in the mutant retinas compared with the normal ones (Supplementary Table S3). Of these, PDE6A has a critical role in phototransduction and disease, and RDH11 in vision, particularly during dark adaptation. Five genes—NDUFS4, RDH11, RNF41, PCMT1, and SULT4A1—were significantly downregulated at 7 weeks and in the combined analysis. However, none of the genes downregulated at 16 weeks was also DE in the combined analysis. 
Functional Grouping and Assignment of the DE Genes to Biological Pathways
Using different approaches, we grouped the DE genes according to their functions and involvement in distinct pathways. We performed a literature screening with pathway analysis (IPA; Ingenuity Systems) of each DE gene and a formal functional clustering of the DE genes at each time point to the GO categories (biological processes, cellular compartments, and molecular functions) through the DAVID Bioinformatics resource at NIAID/NIH (National Institute of Allergy and Infections Diseases, National Institutes of Health). Also, we investigated the relationships and common regulatory pathways of the DE genes with both the KEGG and IPA pathway databases. 
Seven Weeks.
The mutant retina showed expression changes in nine genes—CAMK2G, NTRK2, PRKCB, RALA, RBBP6, RNF41, SMYD3, SPP1, and TUBB2C—that directly or indirectly are involved in the apoptosis and cell death processes. These are defined as part of the signaling pathways that activate apoptosis, attempt to block apoptosis, or attempt to down- or upregulate protective cell functions (Table 1). Four genes with mitochondrial function—ELOVL6, GLOD4, NDUFS4, and REEP1—were downregulated in the mutant retinas at the same age, as well as a few genes (CHML, PAX6, RDH11, and RBBP6) that are relevant for visual system development and function (Table 1). CHML and RDH11 are the paralogs of CHM and RDH12, two genes that, when mutated, cause X-linked choroideremia and RP, respectively. 
Table 1.
 
Selected DE Genes Related to Apoptotic/Cell Death Processes or to Mitochondria Functions or Having Relevant Vision Functions in Mutant Retinas Compared with Age-Matched Normal Retinas at 7 and 16 Weeks and in a Combined (7 and 16 Weeks) Analysis
Table 1.
 
Selected DE Genes Related to Apoptotic/Cell Death Processes or to Mitochondria Functions or Having Relevant Vision Functions in Mutant Retinas Compared with Age-Matched Normal Retinas at 7 and 16 Weeks and in a Combined (7 and 16 Weeks) Analysis
Gene Name Related Function GO q (%) Change Mutant vs. Normal
Seven Weeks
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4 Mitochondria Mitochondrial electron transport; oxygen and reactive oxygen species metabolic process 0.0 −47.2
PAX6 Paired box 6 Vision Eye development; protein and DNA binding; transcription regulator activity 0.0 −8.6
ELOVL6 ELOVL family member 6, elongation of long chain fatty acids Mitochondria Transferase activity; fatty acid elongation 0.0 −3.4
GLOD4 Glyoxalase domain containing 4 Mitochondria Lyase activity 0.0 −3.2
PRKCB Protein kinase C, beta Proapoptosis Protein kinase activity; nucleotide binding 7.0 −16.0
TUBB2C Tubulin, beta 2C Cell death Nucleotide, GTP and MHC class I protein binding; gtpase activity 7.0 −2.8
CHML Choroideremia-like (Rab escort protein 2) Vision Visual perception; regulation of gtpase activity 9.6 −12.6
SPPI Secreted phosphoprotein 1, osteopontin Antiapoptosis Protein binding; cytokine activity; inflammatory response 9.6 −9.0
CAMK2G Calcium/calmodulin-dependent protein kinase II gamma Cell death Protein kinase activity; nucleotide binding 9.6 −5.1
RBBP6 Retinoblastoma binding protein 6 Proapoptosis; vision Nucleic acid and protein binding; ubiquitin-protein ligase activity 9.6 −4.4
REEP1 Receptor accessory protein 1 Mitochondria; cell death Protein insertion into membrane 9.6 −4.3
SMYD3 SET and MYND domain containing 3 Antiapoptosis Protein binding; transferase activity 9.6 −3.4
RNF41 Ring finger protein 41 Proapoptosis Protein binding; ligase activity 9.6 −2.8
RALA V-ral simian leukemia viral oncogene homolog A (ras related) Cell death Gtpase activity; protein and nucleotide binding 9.6 −2.6
NTRK2 Neurotrophic tyrosine kinase, receptor, type 2 Prosurvival Protein kinase activity; nucleotide binding 9.6 −2.6
RDH11 Retinol dehydrogenase 11 Vision Retinol dehydrogenase activity; catalytic activity 9.6 −2.0
Sixteen Weeks
NKAP NFKB activating protein Prosurvival Transcriptional repressor 7.5 −68.6
TARS2 Threonyl-tRNA synthetase 2, mitochondrial Mitochondria Nucleotide and ATP binding; ligase activity 7.5 −58.3
SAG S-antigen; retina and pineal gland (arrestin) Vision Protein binding; signal transduction; visual perception 7.5 −5.7
CRX Cone-rod homeobox Vision DNA and protein binding; transcription factor activity; visual perception 7.5 −5.0
SLC25A5 Solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 5 Mitochondria; pro-survival Protein binding; transporter activity 7.5 −3.9
Combined Analysis
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4 Mitochondria Mitochondrial electron transport; oxygen and reactive oxygen species metabolic process 0.0 −37.0
ACSL1 Acyl-CoA synthetase long-chain family member 1 Mitochondria Nucleotide and ATP binding 0.0 2.3
PDE6A Phosphodiesterase 6A, cGMP-specific, rod, alpha Vision Catalytic activity; visual perception 8.0 −3.0
PPP3CA Protein phosphatase 3, catalytic subunit, alpha isoform Mitochondria; proapoptosis Protein serine/threonine phosphatase activity 8.0 −2.3
RNF41 Ring finger protein 41 Proapoptosis Protein binding; ligase activity 8.0 −2.3
ADC Arginine decarboxylase Mitochondria Protein binding; lyase activity 8.8 2.5
HSP90AA1 Heat shock protein 90kDa alpha, class A member 1 Antiapoptosis; mitochondrial transport Nucleotide binding; protein folding; response to stress 8.8 2.4
TFAM Transcription factor A, mitochondrial Mitochondria; antiapoptosis; vision DNA binding; regulation of transcription 8.8 2.3
ZBTB4 Zinc finger and BTB domain containing 4 Proapoptosis DNA and protein binding; regulation of transcription 8.8 2.0
The downregulated genes in the mutant retina that were DE were mainly associated with very general cellular functions such as secretion, cellular organization, homeostasis, protein modification, mRNA transcription, and different enzymatic functions (binding, deaminase, GTPase, glycosyltransferase, oxidoreductase, and nuclease). They were mainly localized in the cytoplasm, endoplasmic reticulum, and cellular membranes (Table 2). 
Table 2.
 
Functional Assignment
Table 2.
 
Functional Assignment
GO Category Term Genes (n) P
Seven Weeks
BP Secretion 5 0.01
Cellular component organization and biogenesis 13 0.014
Organelle organization and biogenesis 8 0.017
Posttranslational protein modification 9 0.019
Cellular monovalent inorganic cation homeostasis 2 0.036
Establishment of localization 12 0.041
Localization 13 0.042
Protein modification process 9 0.047
CC Organelle membrane 11 0.0007
Cytoplasmic part 17 0.004
Endoplasmic reticulum 7 0.01
Endoplasmic reticulum membrane 5 0.016
Nuclear envelope-endoplasmic reticulum network 5 0.018
Endomembrane system 7 0.019
Endoplasmic reticulum part 5 0.025
Cytoplasm 21 0.034
Intracellular organelle part 14 0.038
Organelle part 14 0.039
Membrane 23 0.047
MF Protein binding 24 0.003
GTP binding 4 0.047
Guanyl ribonucleotide binding 4 0.049
Sixteen Weeks
CC Intracellular part 11 0.043
MF Protein phosphatase regulator activity 2 0.031
Phosphatase regulator activity 2 0.032
Combined Analysis
BP Mitochondrion organization and biogenesis 3 0.004
Nitrogen compound metabolic process 4 0.011
Cellular metabolic process 13 0.035
Primary metabolic process 13 0.036
CC Cytoplasmic part 10 0.0005
Cytoplasm 11 0.006
Endoplasmic reticulum 4 0.027
MF Catalytic activity 10 0.044
To further characterize the DE genes, we interrogated the human KEGG pathways database. We found in the mutant retinas that several signaling (neurotrophin, ErbB, chemokine, and MAPK), focal adhesion, glioma, long-term potentiation, cancer, and metabolic pathways were significantly altered (Table 3). Relevant genes involved in several of these pathways included two kinases: CAMK2G and PRKCB. Together with RAP1B, these are part of the long-term potentiation pathway that is critical for neuronal synapses and interacts with the MAPK pathway. RAP1B and RALA also are part of, or are closely related to, the Ras signaling pathway, which affects many cellular functions, such as cell proliferation, apoptosis, migration, cell fate specification, and differentiation. Use of the IPA program showed networks that differed slightly from those in the KEGG analysis. The four networks of DE genes that were found with IPA at 7 weeks were (1) nervous system development and function, organ development, and cell morphology (12 DE genes); (2) amino acid metabolism, posttranslational modification, and small molecule biochemistry (11 DE genes); (3) infection mechanism, antimicrobial response, and gene expression (10 DE genes); and (4) cellular growth and proliferation, cellular development, and connective tissue development and function (9 DE genes). 
Table 3.
 
Significant Human KEGG Pathway
Table 3.
 
Significant Human KEGG Pathway
Seven Weeks
hsa04722 Neurotrophin signaling pathway
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    NTRK2; neurotrophic tyrosine kinase, receptor, type 2
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa04510 Focal adhesion
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
    SPP1; secreted phosphoprotein 1
hsa04012 ErbB signaling pathway
hsa05214 Glioma
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    PRKCB; protein kinase C, beta
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa04062 Chemokine signaling pathway
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa05200 Pathways in cancer
    PRKCB; protein kinase C, beta
    RALA; v-ral simian leukemia viral oncogene homolog A (ras related)
    TCEB1; transcription elongation factor B (SIII), polypeptide 1 (15kDa, elongin C)
hsa04010 MAPK signaling pathway
    NTRK2; neurotrophic tyrosine kinase, receptor, type 2
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
hsa04720 Long-term potentiation
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
hsa01100 Metabolic pathways
    ATP6V1H; ATPase, H+ transporting, lysosomal 50/57 kDa, V1 subunit H
    NDUFS4; NADH dehydrogenase (ubiquinone) Fe-S protein 4
    RDH11; retinol dehydrogenase 11
Combined Analysis
hsa01100 Metabolic pathways
    ACSL1; acyl-CoA synthetase long-chain family member 1
    ADC; arginine decarboxylase
    NDUFS4; NADH dehydrogenase (ubiquinone) Fe-S protein 4
    RDH11; retinol dehydrogenase 11
Sixteen Weeks.
The DE genes in the 16-week mutant retinas showed trends similar to those in the 7-week retinas. Some were also related to apoptosis (NKAP and SLC25A5), mitochondria (SLC25A5 and TARS2), and visual perception (CRX and SAG) (Table 1). They also grouped in a cluster related to the protein-modification processes (e.g., the protein phosphatase regulator activities) and were located in the intracellular domain (Table 2). Although none of the KEGG pathways was represented by more than two genes, the IPA Cell Cycle, Genetic Disorder, Neurologic Disease network was identified with seven of the DE genes (Supplementary Fig. S1). Of note, qRT-PCR at 16 weeks confirmed downregulation of OPN1SW (opsin 1 cone pigments, short-wave–sensitive) and RHO (rhodopsin), two photoreceptor-specific genes that also belong to this network (see the Validation and Expansion section, to follow, and Fig. 1A). 
Figure 1.
 
qRT-PCR results. The histograms represent the ratios of the changes in expression for the different genes analyzed. (Image not available) Genes not DE in the microarray analysis; (■) DE genes in the microarray analysis; (□) genes not on the microarray or that did not amplify in the brain reference tissue; (Image not available) genes that were only examined by qRT-PCR at 3 weeks, but not by microarray analysis. Values that significantly differ are indicated with asterisks (*P ≤ 0.05; **0.05<P < 0.1, indicating a trend toward statistical significance). Error bars: ranges of the maximum and minimum change differences calculated based on the standard deviation of biological triplicates, as previously shown.37 See Supplementary Tables S2 and S3 for the complete microarray results of the DE genes CRX, PAX6, NDUFS4, ZBTB4, SPP1, SAG, SLC25A5, and TPD52. (A) Comparison of expression for 18 selected genes between mutant and normal retinas at 3, 7, and 16 weeks of age. (B) Comparison of NDUFS4 and ZBTB4 expression between mutant and normal retinas in the combined analysis (7 and 16 weeks of age). (C) Expression comparison of eight genes between mutant and normal retinas at 7 and 16 weeks of age.
Figure 1.
 
qRT-PCR results. The histograms represent the ratios of the changes in expression for the different genes analyzed. (Image not available) Genes not DE in the microarray analysis; (■) DE genes in the microarray analysis; (□) genes not on the microarray or that did not amplify in the brain reference tissue; (Image not available) genes that were only examined by qRT-PCR at 3 weeks, but not by microarray analysis. Values that significantly differ are indicated with asterisks (*P ≤ 0.05; **0.05<P < 0.1, indicating a trend toward statistical significance). Error bars: ranges of the maximum and minimum change differences calculated based on the standard deviation of biological triplicates, as previously shown.37 See Supplementary Tables S2 and S3 for the complete microarray results of the DE genes CRX, PAX6, NDUFS4, ZBTB4, SPP1, SAG, SLC25A5, and TPD52. (A) Comparison of expression for 18 selected genes between mutant and normal retinas at 3, 7, and 16 weeks of age. (B) Comparison of NDUFS4 and ZBTB4 expression between mutant and normal retinas in the combined analysis (7 and 16 weeks of age). (C) Expression comparison of eight genes between mutant and normal retinas at 7 and 16 weeks of age.
Combined Analysis.
As expected, the results of the combined analysis of DE genes which excluded age as a factor were in accord with the overall picture observed when the two ages were analyzed separately. Apoptosis-related genes (downregulated: RNF41 and PPP3CA; upregulated: HSP90AA1, ZBTB4, and TFAM), mitochondria-related genes (downregulated: PPP3CA and NDUFS4; upregulated: ACSL1, ADC, HSP90AA1, and TFAM), and two genes shown to be relevant to visual processes (PDE6A and TFAM) were DE (Table 1). Furthermore, the DE genes play a relevant role in mitochondrial organization and biogenesis, in metabolic and catalytic processes, and in functions localized to the cytoplasm and the endoplasmic reticulum (Table 2). KEGG analysis identified the metabolic pathways as being represented with four DE genes: ACSL1, ADC, NDUFS4, and RDH11 (Table 3). This pathway was already significant at 7 weeks with the same DE genes NDUFS4 and RDH11, in addition to ATP6V1H. In contrast, IPA analysis identified Gene Expression, Cancer, Cellular Growth and Proliferation as the only significant network with 12 DE genes included. 
In conclusion, these functional analyses showed a consistent correlation of the DE genes with processes and pathways known to be essential for the correct maintenance and regulation of retinal function. Furthermore, they indicate that the function of the identified DE genes alters and modifies several metabolic and cellular activities, as well as signaling pathways, in the retina that were not previously known to be involved with this particular or other retinal degenerative diseases. 
Validation and Expansion of Selected DE Genes at the RNA Level
We performed qRT-PCR at 7 and 16 weeks on a subset of 11 genes, to validate the microarray results, and on seven additional genes, to better characterize the pathogenesis of XLPRA2. As well, we used qRT-PCR to compare the expression levels of all 18 genes between the normal and mutant retinas at 3 weeks, to identify possible early differences in gene expression that would provide additional insights into the disease (Fig. 1A). For this analysis, we examined three categories of genes:
  •  
    Genes not DE in the microarray analysis, but with a potential role in the disease based on the functional analyses just detailed. These included BNIP3 (a mitochondrial gene, hypoxia-responsive, and strong proapoptotic protein), PLAGL2 (a zinc-finger protein inducer of cell death and promoter of BNIP3 expression), 43 PFDN5 (a subunit of prefoldin, a chaperone complex that binds and stabilizes newly synthesized polypeptides), and TPD52 (a tumor protein with homodimerization activity present in the cytoplasm and the endoplasmic reticulum).
  •  
    Genes downregulated (7 weeks: PAX6, NDUFS4, and SPP1; 16 weeks: CRX, SAG, and SLC25A5; combined analysis: NDUFS4) or upregulated (combined analysis: ZBTB4) in the microarray analysis in the mutant retinas.
  •  
    Genes not contained in the microarray or not expressed in the brain reference tissue, but with a known role in photoreceptor function or retinal degenerative diseases (CNGA3, CNGB3, OPN1LW, OPN1SW, RHO, and RPGR) or that reflect an inner retinal glial response to outer retinal disease (GFAP).
High concordance between microarray and qRT-PCR results was found for all DE genes in the mutant retinas compared with the normal retinas at the corresponding ages (Fig. 1A). SPP1 could not be confirmed by qRT-PCR, although the general pattern of expression was similar for both analyses at the 7- and 16-week time points (Fig. 1A). A trend toward a decreased expression in the mutant retinas at 16 weeks of NDUFS4 (P < 0.1), identified by qRT-PCR but not by microarray, represented the only other difference between the two techniques in the mutant and normal retinas (Fig. 1A). We also confirmed the downregulation of NDUFS4 and upregulation of ZBTB4 (P < 0.1, trend toward statistical significance) identified in the combined microarray analysis (Fig. 1B). Furthermore, the qRT-PCR data confirmed the upregulation of TPD52 (P < 0.1, trend toward statistical significance) and PAX6, and the downregulation of SAG in normal retinas between 7 and 16 weeks (Fig. 1C). SAG and CRX expression, determined by qRT-PCR, showed a trend toward upregulation in the mutant retinas at 7 compared with 16 weeks (P < 0.1; Fig. 1C), but these changes were not observed with the microarray analysis. 
Regarding the analysis of genes not present on the array or not expressed in the brain reference tissue, we found that the expression of GFAP was increased in the mutant retinas at all three ages (Fig. 1A). Among the 18 genes tested, it was the only one altered at 3 weeks of age, and its expression was highly upregulated in the mutant retinas at 16 weeks compared with 7 weeks (Fig. 1C). The early increase in GFAP expression suggests that there is a response in the inner retina to the photoreceptor disease that occurs before the onset of overt degeneration. 
Analysis of RPGR with a probe common to all retinally expressed isoforms (located in the junction between the 5′ UTR and exon 1) showed increased expression in the mutant retinas compared with the normal retinas at 16 weeks, but no expression differences at 3 and 7 weeks (Fig. 1A). Similar results with a trend toward statistical significance (P < 0.1, results not shown) were found with an additional gene-specific assay (from ABI; Supplementary Table S1), which also identifies all known retinal isoforms but is located on the exon 3–4 junction. 
In contrast to the finding at 3 weeks, which showed no differences in photoreceptor-specific gene expression between normal and mutants, at 7 weeks the rod-specific gene RHO was downregulated, whereas the S-cone specific OPN1SW (P < 0.1, trend toward statistical significance) and the cone-specific CNGB3 genes were upregulated in the mutant retinas (Fig. 1A). At 16 weeks, RHO, OPN1SW, and SAG were downregulated in the mutant retinas (Fig. 1A) and also were downregulated in comparison to their levels in the mutant retinas at 7 weeks (Fig. 1C). On the other hand, the cone-specific genes CNGA3 and OPN1LW were equally expressed between the mutant and normal retinas at both 7 and 16 weeks. 
Of interest, all the hybridization-based microarray analyses indicated much greater ratios of change in expression compared with the amplification-based technology (qRT-PCR). This result is in line with those reported in other retina studies. 21,44  
Validation of Selected DE Genes at the Protein Level
To compare the differential RNA expression results at the protein level, we analyzed four DE genes (NDUFS4, SAG, GFAP, and OPN1SW) by Western blot analysis and IHC. For Western analysis, a single retina per status/time point was used. The results of Western analysis of NDUFS4 showed that a band of ∼21 kDa was found for all four retinas. When compared using ACTB as a loading control, expression levels were lower in the mutant retinas at both ages, particularly at 16 weeks (Fig. 2A). This result is in accordance with the findings at the RNA level (e.g., at 7 weeks) and in combined analysis (microarray and qRT-PCR) and 16 weeks (qRT-PCR), as well as with the IHC results (Fig. 3A). NDUFS4 showed positive staining in cell layers where mitochondria are abundant (e.g., in the RPE and the photoreceptor inner segments; Fig. 3A). Compared with the other retinas, the normal at 16 weeks showed intense staining in the inner nuclear layer and in the photoreceptor inner segments. The loss of photoreceptors and the subsequent misalignment, disorganization, and shortened inner and outer segments were observed in the mutant retinas at 16 weeks. 
Figure 2.
 
Western blot analysis of single samples from normal (16 and 7 weeks) and XLPRA2 mutant (16 and 7 weeks) retinas with four antibodies (NDUFS4, SAG, FAP, and OPN1SW) in addition to actin (ACTB), used as a loading control. Dashed line indicates that the gel was cut and ACTB placed below the protein of interest. The relevant molecular size markers are indicated. (A) NDUFS4 levels were lower in the mutant retina at both ages. (B) Lower protein levels of SAG were found in the mutant retina at 16 weeks compared with either the normal age-matched control or the 7-week mutant. (C) GFAP was upregulated in both the 7- and 16-week mutant retinas. (D) The mutant retina at 16 weeks showed a downregulation of OPN1SW. The specific ∼39 kDa band is absent, even though the quantity of the ACTB loading control was high.
Figure 2.
 
Western blot analysis of single samples from normal (16 and 7 weeks) and XLPRA2 mutant (16 and 7 weeks) retinas with four antibodies (NDUFS4, SAG, FAP, and OPN1SW) in addition to actin (ACTB), used as a loading control. Dashed line indicates that the gel was cut and ACTB placed below the protein of interest. The relevant molecular size markers are indicated. (A) NDUFS4 levels were lower in the mutant retina at both ages. (B) Lower protein levels of SAG were found in the mutant retina at 16 weeks compared with either the normal age-matched control or the 7-week mutant. (C) GFAP was upregulated in both the 7- and 16-week mutant retinas. (D) The mutant retina at 16 weeks showed a downregulation of OPN1SW. The specific ∼39 kDa band is absent, even though the quantity of the ACTB loading control was high.
Figure 3.
 
Immunolabeling of normal and XLPRA2 mutant 16- and 7-week retinas with the same four antibodies (NDUFS4, SAG, GFAP, and OPN1SW) as were used in Western analysis. Except for NDUFS4 (A), images were merged with DIC-transmitted light. (A) NDUFS4 was expressed in the mitochondrion inner membrane. Staining was observed in the retinal pigment epithelium (RPE), photoreceptor inner segment (IS), inner plexiform (IPL), and ganglion cell (GCL) layers. Lower NDUFS4 labeling was seen in the mutant retina at 16 weeks, particularly in the IS, owing to the loss of photoreceptors. Intense staining was found in the inner nuclear layer (INL) in the normal retinas at 16 weeks. (B) SAG was highly expressed in the photoreceptor outer segments (OS) and in the outer plexiform layer (OPL) in normal retinas. In the mutant, it mislocalized to the outer nuclear layer (ONL). (C) GFAP staining was weak and limited to astrocytes and Müller cell end feet in normal retinas at 7 weeks and was minimal at 16 weeks. In the mutant retinas, GFAP immunoreactivity was evidenced by intense GFAP labeling in Müller cells at both 7 and 16 weeks, and labeled radial processes extended from the inner retina into the ONL. (D) OPN1SW is exclusively expressed in the OS of S-cones, in the 16-week mutant retina OPN1SW were minimal to absent. Scale bar: 2.5 μm.
Figure 3.
 
Immunolabeling of normal and XLPRA2 mutant 16- and 7-week retinas with the same four antibodies (NDUFS4, SAG, GFAP, and OPN1SW) as were used in Western analysis. Except for NDUFS4 (A), images were merged with DIC-transmitted light. (A) NDUFS4 was expressed in the mitochondrion inner membrane. Staining was observed in the retinal pigment epithelium (RPE), photoreceptor inner segment (IS), inner plexiform (IPL), and ganglion cell (GCL) layers. Lower NDUFS4 labeling was seen in the mutant retina at 16 weeks, particularly in the IS, owing to the loss of photoreceptors. Intense staining was found in the inner nuclear layer (INL) in the normal retinas at 16 weeks. (B) SAG was highly expressed in the photoreceptor outer segments (OS) and in the outer plexiform layer (OPL) in normal retinas. In the mutant, it mislocalized to the outer nuclear layer (ONL). (C) GFAP staining was weak and limited to astrocytes and Müller cell end feet in normal retinas at 7 weeks and was minimal at 16 weeks. In the mutant retinas, GFAP immunoreactivity was evidenced by intense GFAP labeling in Müller cells at both 7 and 16 weeks, and labeled radial processes extended from the inner retina into the ONL. (D) OPN1SW is exclusively expressed in the OS of S-cones, in the 16-week mutant retina OPN1SW were minimal to absent. Scale bar: 2.5 μm.
Western blot analysis of the SAG protein showed a single band at the expected molecular weight of ∼48 kDa (Fig. 2B). Much lower SAG levels were found in the mutant retina at 16 weeks than in either the normal age-matched control or the younger mutant retina (Fig. 2B). On the other hand, Western analysis did not indicate an increase in this protein as a result of upregulation of SAG expression in the normal retinas at 16 weeks compared with 7 weeks. In the normal retinas, IHC showed high expression in the photoreceptor outer segment and in the synaptic terminals of the outer plexiform layer (Fig. 3B). In mutants, SAG was mislocalized to the outer nuclear layer, and loss of photoreceptors and outer nuclear layer at 16 weeks was reflected as a decrease in the label's intensity (Fig. 3B). 
We also assessed the protein expressions of GFAP and OPN1SW, two genes that were not on the microarray, but were DE in the qRT-PCR analysis. Western blot analysis of GFAP confirmed a band at ∼50 kDa and an upregulation of this protein in the mutant retinas compared with the age-matched normal retinas at both 7 and 16 weeks (Fig. 2C). Similar results were found by IHC: In the mutant retinas, GFAP labeled the radial processes of Müller cells, which form a heavily labeled network of fibers that extend from the internal limiting membrane to the outer nuclear layer (Fig. 3C). 
Western blot results of OPN1SW showed lower levels in the mutant retinas at 7 weeks, and no protein was detectable at 16 weeks, even though the quantity of the ACTB loading control was high (Fig. 2D). It appears that at the time the cones are degenerating and increasing OPN1SW expression at the mRNA level, the message is not translated or the protein degraded. Immunolabeling with OPN1SW antibody confirmed the localization and labeling of S-cone outer segments in the normal and 7-week mutant retinas (Fig. 3D). However, there was a marked decrease in the number of labeled S-cone outer segments at 16 weeks (Fig. 3D). 
Discussion
This study is the first report of a large-scale transcriptomic analysis at different critical ages in XLPRA2 mutant retinas and identifies the genes and pathways that are associated with photoreceptor degeneration in this relevant canine model of human RPGR/XLRP. In particular, our findings showed alteration, specifically downregulation, in mutant retinas of genes and several important cellular pathways (Tables 2, 3); these include mitochondria-related modifications, which might not be expected, based solely on the RPGR function. The alterations in the mutant retinas were specific for the disease stages examined, and no commonalities were found between the two ages. 
Furthermore, Table 1 provides a list of DE genes that are known to be involved in nonclassic anti- and proapoptotic pathways, but, with the exception of PAX6, SAG, and CRX, have not been associated with photoreceptor degenerative diseases. The list of novel genes associated with XLPRA2 disease can serve as a useful reference for other comparative studies and for inter- and intraspecies meta-analyses. 
The powerful tool of cDNA microarrays allows simultaneous analysis of thousands of genes, to look for those modified by a specific process (e.g., normal aging, disease, and disease stage). In this study, we applied this technology to expand our knowledge of the pathways and mechanisms involved in photoreceptor degeneration by examining the transcriptional profile of normal and XLPRA2 mutant retinas at 7 and 16 weeks of age. The two ages sampled represent key time points previously established for the disease. 26 At 7 weeks of age (execution phase), there is photoreceptor disorganization and disruption. The outer nuclear layer is 85% to 90% of its normal thickness, but cell death, assayed with the TUNEL method, is at its maximum. As nearly all photoreceptor cells present at this time are not dying, any detected alterations in gene expression are likely to represent early degenerative processes that are associated with or induce apoptosis. At 16 weeks (persistent execution/chronic cell death phase), there is loss of rod inner and outer segments, and narrowing of the outer nuclear layer to ∼60% of normal thickness; at this time, the number of TUNEL-positive cells is significantly reduced, but remains constant until close to 1 year of age. 26  
We used a custom canine cDNA microarray, derived from a normal retina library, that is the only canine and retina-specific array available. 30,31 This approach is similar to that taken in other studies that have used custom slide microarrays of eye/retina-expressed genes. 45 47 However, there are some limitations with the custom canine cDNA microarray, in that the number of genes that it contains is ∼4500, and many belonging to classic anti- and proapoptotic pathways are not represented. For example, not included in the microarray are some of the major classic proapoptosis genes such as BAX; the calpains; caspase-3, -4, -8, and -10; FADD; FAS/CD95; FASL; TNFSF10/TRAIL; TNFSF12/APO3L; TNFSF8 / CD30L; TNFA; TNFRSF1A; and TRADD. These genes, and others, are now being analyzed as part of an ongoing, focused study on the expression of cell death and survival genes. 
Changes in Normal and XLPRA2-Mutant Retinas during Development
With these caveats in mind, we identified genes that were DE. In the normal retinas, 5% of the total genes on the array were DE when the 7- and 16-week samples were compared. Even though at both time points the retinas are structurally and functionally comparable, the higher level of DE genes at 7 weeks, most of which were upregulated, suggests that molecular changes are taking place as the retina completes postnatal development (7 weeks) and reaches maturity (16 weeks). 41 In contrast, all the genes that were DE in the mutant retina were upregulated at 7 weeks when compared with 16 weeks. Moreover, in the mutants, we did not observe a similar pattern of change in gene expression with development, probably because disease-related molecular processes and pathways at this stage of development are altered secondary to the ongoing degenerative process. 
Mitochondrial and Nonclassic Pro- or Antiapoptosis Genes Altered during XLPRA2 Degeneration
One of the most important findings of this study highlighted a connection between mitochondria function and XLPRA2 degeneration, with a clear emphasis on either pro- or antiapoptosis genes that are related to the death of the photoreceptors, but that do not contribute to the classic cell death and survival events (Table 1). Mitochondria and their membrane integrity are critical for retinal cell function and survival. Dysfunctions, which can be caused by mutations in both mitochondrial and nuclear DNA, have been associated with the pathogenesis of hereditary neurodegenerative diseases 48 and with several outer retinal diseases, including age-related macular degeneration, 49 cone-rod dystrophy, 50 and light-induced retinopathy. 51 The nine DE genes related to mitochondria that were identified in this study are located on the nuclear DNA, indicating that the mitochondrial DNA itself is not affected and providing new avenues for future investigation. 
Age and Disease Stage Specificity of Gene Expression Profiles
A further relevant finding of this study indicated downregulation of genes in the mutant retinas compared with expression in the normal retinas at both ages. This result appears to be due to an overexpression of genes in normal versus mutant retinas at 7 weeks, and, at 16 weeks, probably reflects a general downregulation of gene expression in the mutant retina associated with ongoing photoreceptor degeneration and active cell death. These findings were further validated at the protein level, where downregulation of NDUFS4 at both ages, as well as SAG and OPN1SW at 16 weeks, was shown. 
It could be argued that the overall downregulation of gene expression in the mutant retinas was simply due to the loss of photoreceptors associated with the disease (i.e., ∼10% and 40%, respectively, at 7 and 16 weeks). However, in most cases, the magnitude of the decreased expression was much greater than could be accounted for by photoreceptor loss alone. This result suggests that downregulation of gene expression accompanies the disease at the time points examined and is not unique to the canine disease, as similar findings have been reported in other microarray studies of retinal degenerative disease: In rd1 mice during peak rod degeneration, 1 gene is upregulated and 69 downregulated 52 ; in Bbs4-null mice, 48 genes are upregulated and 306 downregulated 53 ; in R6/2 mice 81 transcripts are upregulated and 230 downregulated 54 ; and in R7E mice, 215 transcripts are upregulated and 324 downregulated. 54  
Similar to studies of RP1 knockout mice, 55 our results showed very specific age- and disease stage–dependent changes in gene expression profiles, which further suggests that mechanisms triggered during the execution phase of the disease are not only different, but also have a broader influence on the cells than those during the persistent execution/chronic cell death phase. This possibility is reflected by the higher number of DE genes at the earlier stage, but also by the increase in the change ratio expression in the later stage, which may reflect the ongoing degeneration. 
Important Cellular Pathways and Signaling Functions Altered by the RPGRORF15 Frameshift Mutant Retina
The functional and pathway analyses were used to further characterize the gene expression changes. These mainly indicated a general modification of signaling, binding (in particular protein and DNA binding; Table 2), and metabolic functions, as well as alteration of homeostasis, cellular organization, and biogenesis in the mutant retinal cells. This result was in agreement with those in previous studies of photoreceptor cell death in mice, in which similar functional categories of genes were found to be altered. 56 Of particular interest, the 7-week XLPRA2 mutant retina showed an alteration in the neurotrophin pathway with the downregulation of CAMK2G, NTRK2, RAP1B, and SHC3. This pathway, which is closely related to the MAPK signaling pathway, is initiated by neurotrophins that promote cell survival by preventing the initiation of programmed cell death. Studies demonstrate that specific neurotrophins (e.g., pigment epithelium–derived factor [PEDF] and glial cell line-derived neurotrophic factor [GDNF]), induce neuroprotection in animal models of RP. 57,58 Downregulation of the genes in this pathway may suggest that during the peak of photoreceptor loss, cell death can occur by both a lack of survival signaling and the induction of apoptosis cascades. The downregulation of another gene at 7 weeks, ELOVL6, confirms that a complex pattern of regulation occurs in mutant retinas. This gene belongs to the same family as ELOVL4, in which mutations have been shown to cause Stargardt disease-3 (STGD3), 59 and ELOVL2, a cone-specific gene that was upregulated in NR2E3−/− and rd7/rd7 mice. 60  
In the analysis, we also compared expression between normal and mutant retinas, regardless of age, to help identify genes that show a consistent change. Three of them, HSP90AA1, TFAM, and ZBTB4, are of particular interest with regard to apoptotic events, as they seem to have opposite functions. HSP90AA1 is an antiapoptosis molecule related to mitochondrial pathways, 61 whereas TFAM is involved in the maintenance of mitochondrial DNA and has been shown to attenuate apoptosis when upregulated. 62 Increased expression of both genes in mutant retinas may suggest an antiapoptotic role in the mitochondria. 
On the other hand, increased ZBTB4 expression may suggest a proapoptosis role in mutant retinas, as depletion, in response to p53 activation, suppresses apoptosis and promotes long-term cell survival. 63  
qRT-PCR Confirmation and Expansion of the Microarray Results
qRT-PCR results indicate high reliability of the microarray data at both ages, as the expression of almost all the genes tested was confirmed. The only exception at both ages was SPP1, which was downregulated in the mutant retinas at 7 weeks by microarray, but with qRT-PCR no statistically significant differences were found, because of an unusually high variation between samples. At 16 weeks, there was a 5.5-fold upregulation of SPP1 in the mutant retinas by qRT-PCR; however, although upregulation was also found with the microarray analysis, it was not statistically significant because of a high q-value (42.3%). 
The qRT-PCR analysis also identified DE genes that play a crucial role in the phenotype of the disease and that might have a bearing on photoreceptor degeneration. At 3 weeks (induction phase), when the mutant photoreceptors are developing, albeit abnormally, only GFAP, a marker of glial activation, was DE in the mutant retinas. Increased GFAP expression early indicates that signaling events from the outer retina to the Müller cells take place and suggests that early stress events in the photoreceptors may be transmitted to the Müller cells. GFAP expression was highly upregulated during the entire time course of the disease, as clearly confirmed at the proteomic level by Western and IHC analyses. Similar observations at different ages were also previously reported in mutant dogs. 26  
In an interesting result, we found an upregulation of the expression of the mutated gene RPGR in the mutant retinas at 16 weeks This result is in line with those in other studies of retinal degeneration caused by mutation in the NR2E3 gene 60,64,65 that also report an upregulated expression in mutant animals of the mutated gene and suggest that, in XLPRA2 mutants, the RPGR gene product is necessary for its own feedback mechanisms only during the persistent execution/chronic cell death phase
Alteration of Photoreceptor-Specific Gene Expression
As expected, the qRT-PCR findings show misregulation of cone and rod photoreceptor-specific gene expression. In mutants, we found at 7 weeks of upregulation of OPN1SW and CNGB3, downregulation of RHO, and no change in CNGA3. These results suggest that during the photoreceptor death peak, a differential decrease in the number of rods with respect to cones occurs and confirms the results obtained with morphologic evaluation. 26 At 16 weeks, there was decreased expression of SAG, RHO, and OPN1SW in the mutant retinas, but expression of OPN1LW, CNGA3, and CNGB3 did not change. These findings suggest a differential and preferential damage of rods and S-cones during this later phase of the disease. 
The decreased expression at 16 weeks of the rod-specific gene SAG that was identified at both the RNA and protein levels is in line with the results reported in two NR2E3 knockout mouse lines. 60 SAG encodes for one of the major soluble rod outer segment proteins; it binds as a cofactor to photoactivated-phosphorylated rhodopsin and interacts with CRX, a photoreceptor-specific protein. In the XLPRA2 retina at 16 weeks, both SAG and CRX showed comparable reductions in expression, a finding also reported in rd1 mice. 56 In general, downregulation of CRX, PAX, RHO, OPN1SW, and SAG have also been reported in other comparable retinal diseases. 52,53,54,60  
Unknown EST Sequences and Potential Splice Variations of the 3′ UTR Regions of Unidentified Genes
The identification of several DE transcripts that could not be assigned to any known gene suggests that some genes and/or pathways involved in the long-term regulation of disease are not yet known. 
These unknown ESTs did not show any commonalities, including conserved domains and/or sequence homologies to known genes and are located on different chromosomes. The library used to construct the arrays is slightly biased toward the 3′ UTR of the genes and the EST clones are unlikely to represent genomic contamination. 31 As the translational data did not give any evidence that these clones could be in coding regions, we speculate that the unknown ESTs may be splicing variants of 3′-UTRs of genes not yet identified. Characterization and elucidation of these clones would be of particular interest and may help to identify novel genes that play pivotal roles in retinal maintenance and development not only in the dog, but possibly in other species. For example, in a previous study we identified an unknown and uncharacterized gene that subsequently was found to be a novel gene that causes retinal degeneration in dogs and humans. 66  
Conclusions and Perspectives
In conclusion, DE of retina-expressed genes in XLPRA2 provides useful information to begin to determine at the molecular level the sequence of events that link a mutation in a retina-expressed gene with the ultimate degeneration and loss of the visual cells. These studies now can be expanded so that some of the identified pathways can be examined in greater detail to identify the key signaling molecules and pathways responsible for the death of the photoreceptors. 
Supplementary Materials
Footnotes
 Supported by National Eye Institute/National Institutes of Health (NEI/NIH) Grants EY13132, EY06855, EY17549, and P30 EY001583; The Foundation Fighting Blindness; a Fight For Sight Nowak Family Grant; The University of Pennsylvania Research Foundation (URF); Hope for Vision; The Van Sloun Fund for Canine Genetic Research; and unrestricted grants from Pfizer, Inc. and Merck & Co., Inc.
Footnotes
 Disclosure: S. Genini, None; B. Zangerl, None; J. Slavik, None; G.M. Acland, None; W.A. Beltran, None; G.D. Aguirre, None
The authors thank András M. Komáromy and Shana Gilbert-Gregory (University of Pennsylvania), for providing retina samples and primers for qRT-PCR; Igal Gery (NEI/NIH) and Nancy J. Mangini (Indiana University School of Medicine-Northwest, Gary, IN) for SAG antibodies; Gerardo Paez for performing the slide hybridizations; Mary Leonard for some of the illustrations; Giulia Pertica (University of Milan, Italy), Daniel Martinez (Children's Hospital of Philadelphia); Svetlana Savina for technical assistance; the staff of the Retinal Disease Studies Facility for animal care and John Tobias (Penn Bioinformatics Core, University of Pennsylvania) for help with the statistical analyses. 
References
Meindl A Dry K Herrmann K . A gene (RPGR) with homology to the RCC1 guanine nucleotide exchange factor is mutated in X-linked retinitis pigmentosa (RP3). Nat Genet. 1996;13:35–42. [CrossRef] [PubMed]
Vervoort R Lennon A Bird AC . Mutational hot spot within a new RPGR exon in X-linked retinitis pigmentosa. Nat Genet. 2000;25:462–466. [CrossRef] [PubMed]
Bader I Brandau O Achatz H . X-linked retinitis pigmentosa: RPGR mutations in most families with definite X linkage and clustering of mutations in a short sequence stretch of exon ORF15. Invest Ophthalmol Vis Sci. 2003;44:1458–1463. [CrossRef] [PubMed]
Sharon D Sandberg MA Rabe VW Stillberger M Dryja TP Berson EL . RP2 and RPGR mutations and clinical correlations in patients with X-linked retinitis pigmentosa. Am J Hum Genet. 2003;73:1131–1146. [CrossRef] [PubMed]
Breuer DK Yashar BM Filippova E . A comprehensive mutation analysis of RP2 and RPGR in a North American cohort of families with X-linked retinitis pigmentosa. Am J Hum Genet. 2002;70:1545–1554. [CrossRef] [PubMed]
Pusch CM Broghammer M Jurklies B Besch D Jacobi FK . Ten novel ORF15 mutations confirm mutational hot spot in the RPGR gene in European patients with X-linked retinitis pigmentosa. Hum Mutat. 2002;20:405. [CrossRef] [PubMed]
Hong DH Pawlyk BS Adamian M Sandberg MA Li T . A single, abbreviated RPGR-ORF15 variant reconstitutes RPGR function in vivo. Invest Ophthalmol Vis Sci. 2005;46:435–441. [CrossRef] [PubMed]
Hong DH Pawlyk B Sokolov M . RPGR isoforms in photoreceptor connecting cilia and the transitional zone of motile cilia. Invest Ophthalmol Vis Sci. 2003;44:2413–2421. [CrossRef] [PubMed]
Chang B Khanna H Hawes N . In-frame deletion in a novel centrosomal/ciliary protein CEP290/NPHP6 perturbs its interaction with RPGR and results in early-onset retinal degeneration in the rd16 mouse. Hum Mol Genet. 2006;15:1847–1857. [CrossRef] [PubMed]
Khanna H Hurd TW Lillo C . RPGR-ORF15, which is mutated in retinitis pigmentosa, associates with SMC1, SMC3, and microtubule transport proteins. J Biol Chem. 2005;280:33580–33587. [CrossRef] [PubMed]
Roepman R Letteboer SJ Arts HH . Interaction of nephrocystin-4 and RPGRIP1 is disrupted by nephronophthisis or Leber congenital amaurosis-associated mutations. Proc Natl Acad Sci U S A. 2005;102:18520–18525. [CrossRef] [PubMed]
Otto EA Loeys B Khanna H . Nephrocystin-5, a ciliary IQ domain protein, is mutated in Senior-Loken syndrome and interacts with RPGR and calmodulin. Nat Genet. 2005;37:282–288. [CrossRef] [PubMed]
Linari M Ueffing M Manson F Wright A Meitinger T Becker J . The retinitis pigmentosa GTPase regulator, RPGR, interacts with the delta subunit of rod cyclic GMP phosphodiesterase. Proc Natl Acad Sci U S A. 1999;96:1315–1320. [CrossRef] [PubMed]
Khanna H Davis EE Murga-Zamalloa CA . A common allele in RPGRIP1L is a modifier of retinal degeneration in ciliopathies. Nat Genet. 2009;41:739–745. [CrossRef] [PubMed]
Chowers I Liu D Farkas RH . Gene expression variation in the adult human retina. Hum Mol Genet. 2003;12:2881–2893. [CrossRef] [PubMed]
Yoshida S Yashar BM Hiriyanna S Swaroop A . Microarray analysis of gene expression in the aging human retina. Invest Ophthalmol Vis Sci. 2002;43:2554–2560. [PubMed]
Diaz E Yang YH Ferreira T . Analysis of gene expression in the developing mouse retina. Proc Natl Acad Sci U S A. 2003;100:5491–5496. [CrossRef] [PubMed]
Ivanov D Dvoriantchikova G Barakat DJ Nathanson L Shestopalov VI . Differential gene expression profiling of large and small retinal ganglion cells. J Neurosci Methods. 2008;174:10–17. [CrossRef] [PubMed]
Roesch K Jadhav AP Trimarchi JM . The transcriptome of retinal Muller glial cells. J Comp Neurol. 2008;509:225–238. [CrossRef] [PubMed]
Saghizadeh M Akhmedov NB Farber DB . Identification and characterization of genes expressed in cone photoreceptors. Adv Exp Med Biol. 2008;613:235–244. [PubMed]
Natoli R Provis J Valter K Stone J . Gene regulation induced in the C57BL/6J mouse retina by hyperoxia: a temporal microarray study. Mol Vis. 2008;14:1983–1994. [PubMed]
Krishnan J Chen J Shin KJ . Gene expression profiling of light-induced retinal degeneration in phototransduction gene knockout mice. Exp Mol Med. 2008;40:495–504. [CrossRef] [PubMed]
Punzo C Kornacker K Cepko CL . Stimulation of the insulin/mTOR pathway delays cone death in a mouse model of retinitis pigmentosa. Nat Neurosci. 2009;12:44–52. [CrossRef] [PubMed]
Zhang Q Acland GM Zangerl B . Fine mapping of canine XLPRA establishes homology of the human and canine RP3 intervals. Invest Ophthalmol Vis Sci. 2001;42:2466–2471. [PubMed]
Zhang Q Acland GM Wu WX . Different RPGR exon ORF15 mutations in canids provide insights into photoreceptor cell degeneration. Hum Mol Genet. 2002;11:993–1003. [CrossRef] [PubMed]
Beltran WA Hammond P Acland GM Aguirre GD . A frameshift mutation in RPGR exon ORF15 causes photoreceptor degeneration and inner retina remodeling in a model of X-linked retinitis pigmentosa. Invest Ophthalmol Vis Sci. 2006;47:1669–1681. [CrossRef] [PubMed]
Beltran WA Acland GM Aguirre GD . Age-dependent disease expression determines remodeling of the retinal mosaic in carriers of RPGR exon ORF15 mutations. Invest Ophthalmol Vis Sci. 2009;50:3985–3995. [CrossRef] [PubMed]
Aguirre GD Yashar BM John SK . Retinal histopathology of an XLRP carrier with a mutation in the RPGR exon ORF15. Exp Eye Res. 2002;75:431–443. [CrossRef] [PubMed]
Aleman TS Cideciyan AV Sumaroka A . Inner retinal abnormalities in X-linked retinitis pigmentosa with RPGR mutations. Invest Ophthalmol Vis Sci. 2007;48:4759–4765. [CrossRef] [PubMed]
Paez GL Sellers KF Band M Acland GM Zangerl B Aguirre GD . Characterization of gene expression profiles of normal canine retina and brain using a retinal cDNA microarray. Mol Vis. 2006;12:1048–1056. [PubMed]
Zangerl B Sun Q Pillardy J . Development and characterization of a normalized canine retinal cDNA library for genomic and expression studies. Invest Ophthalmol Vis Sci. 2006;47:2632–2638. [CrossRef] [PubMed]
Korenbrot JI Fernald RD . Circadian rhythm and light regulate opsin mRNA in rod photoreceptors. Nature. 1989;337:454–457. [CrossRef] [PubMed]
Yang YH Dudoit S Luu P . Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 2002;30:e15. [CrossRef] [PubMed]
Storey JD Tibshirani R . Statistical methods for identifying differentially expressed genes in DNA microarrays. Methods Mol Biol. 2003;224:149–157. [PubMed]
Edgar R Domrachev M Lash AE . Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30:207–210. [CrossRef] [PubMed]
Brazma A Hingamp P Quackenbush J . Minimum information about a microarray experiment (MIAME): toward standards for microarray data. Nat Genet. 2001;29:365–371. [CrossRef] [PubMed]
Livak KJ Schmittgen TD . Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method. Methods. 2001;25:402–408. [CrossRef] [PubMed]
Pfaffl MW Gerstmayer B Bosio A Windisch W . Effect of zinc deficiency on the mRNA expression pattern in liver and jejunum of adult rats: monitoring gene expression using cDNA microarrays combined with real-time RT-PCR. J Nutr Biochem. 2003;14:691–702. [CrossRef] [PubMed]
Guziewicz KE Zangerl B Lindauer SJ . Bestrophin gene mutations cause canine multifocal retinopathy: a novel animal model for best disease. Invest Ophthalmol Vis Sci. 2007;48:1959–1967. [CrossRef] [PubMed]
Long K Philp N Gery I Aguirre G . S-antigen in a hereditary visual cell disease. immunocytochemical and immunological studies. Invest Ophthalmol Vis Sci. 1988;29:1594–1607. [PubMed]
Acland GM Aguirre GD . Retinal degenerations in the dog: IV. Early retinal degeneration (erd) in Norwegian elkhounds. Exp Eye Res. 1987;44:491–521. [CrossRef] [PubMed]
Halder G Callaerts P Gehring WJ . New perspectives on eye evolution. Curr Opin Genet Dev. 1995;5:602–609. [CrossRef] [PubMed]
Mizutani A Furukawa T Adachi Y Ikehara S Taketani S . A zinc-finger protein, PLAGL2, induces the expression of a proapoptotic protein Nip3, leading to cellular apoptosis. J Biol Chem. 2002;277:15851–15858. [CrossRef] [PubMed]
Panagis L Zhao X Ge Y Ren L Mittag TW Danias J . Gene expression changes in areas of focal loss of retinal ganglion cells (RGC) in the retina of DBA/2J mice. Invest Ophthalmol Vis Sci. 2010;51:2024–2034. [CrossRef] [PubMed]
Blackshaw S Fraioli RE Furukawa T Cepko CL . Comprehensive analysis of photoreceptor gene expression and the identification of candidate retinal disease genes. Cell. 2001;107:579–589. [CrossRef] [PubMed]
Chowers I Gunatilaka TL Farkas RH . Identification of novel genes preferentially expressed in the retina using a custom human retina cDNA microarray. Invest Ophthalmol Vis Sci. 2003;44:3732–3741. [CrossRef] [PubMed]
Farjo R Yu J Othman MI . Mouse eye gene microarrays for investigating ocular development and disease. Vision Res. 2002;42:463–470. [CrossRef] [PubMed]
Kwong JQ Beal MF Manfredi G . The role of mitochondria in inherited neurodegenerative diseases. J Neurochem. 2006;97:1659–1675. [CrossRef] [PubMed]
Jarrett SG Lin H Godley BF Boulton ME . Mitochondrial DNA damage and its potential role in retinal degeneration. Prog Retin Eye Res. 2008;27:596–607. [CrossRef] [PubMed]
Porto FB Mack G Sterboul MJ . Isolated late-onset cone-rod dystrophy revealing a familial neurogenic muscle weakness, ataxia, and retinitis pigmentosa syndrome with the T8993G mitochondrial mutation. Am J Ophthalmol. 2001;132:935–937. [CrossRef] [PubMed]
Maeda A Maeda T Golczak M . Involvement of all-trans-retinal in acute light-induced retinopathy of mice. J Biol Chem. 2009;284:15173–15183. [CrossRef] [PubMed]
Hackam AS Strom R Liu D . Identification of gene expression changes associated with the progression of retinal degeneration in the rd1 mouse. Invest Ophthalmol Vis Sci. 2004;45:2929–2942. [CrossRef] [PubMed]
Swiderski RE Nishimura DY Mullins RF . Gene expression analysis of photoreceptor cell loss in bbs4-knockout mice reveals an early stress gene response and photoreceptor cell damage. Invest Ophthalmol Vis Sci. 2007;48:3329–3340. [CrossRef] [PubMed]
Abou-Sleymane G Chalmel F Helmlinger D . Polyglutamine expansion causes neurodegeneration by altering the neuronal differentiation program. Hum Mol Genet. 2006;15:691–703. [CrossRef] [PubMed]
Liu J Huang Q Higdon J . Distinct gene expression profiles and reduced JNK signaling in retinitis pigmentosa caused by RP1 mutations. Hum Mol Genet. 2005;14:2945–2958. [CrossRef] [PubMed]
Rohrer B Pinto FR Hulse KE Lohr HR Zhang L Almeida JS . Multidestructive pathways triggered in photoreceptor cell death of the rd mouse as determined through gene expression profiling. J Biol Chem. 2004;279:41903–41910. [CrossRef] [PubMed]
Murakami Y Ikeda Y Yonemitsu Y . Inhibition of nuclear translocation of apoptosis-inducing factor is an essential mechanism of the neuroprotective activity of pigment epithelium-derived factor in a rat model of retinal degeneration. Am J Pathol. 2008;173:1326–1338. [CrossRef] [PubMed]
Dong A Shen J Krause M Hackett SF Campochiaro PA . Increased expression of glial cell line-derived neurotrophic factor protects against oxidative damage-induced retinal degeneration. J Neurochem. 2007;103:1041–1052. [CrossRef] [PubMed]
McMahon A Jackson SN Woods AS Kedzierski W . A stargardt disease-3 mutation in the mouse Elovl4 gene causes retinal deficiency of C32–C36 acyl phosphatidylcholines. FEBS Lett. 2007;581:5459–5463. [CrossRef] [PubMed]
Webber AL Hodor P Thut CJ . Dual role of Nr2e3 in photoreceptor development and maintenance. Exp Eye Res. 2008;87:35–48. [CrossRef] [PubMed]
Lanneau D de Thonel A Maurel S Didelot C Garrido C . Apoptosis versus cell differentiation: role of heat shock proteins HSP90, HSP70 and HSP27. Prion. 2007;1:53–60. [CrossRef] [PubMed]
Xu S Zhong M Zhang L . Overexpression of tfam protects mitochondria against beta-amyloid-induced oxidative damage in SH-SY5Y cells. FEBS Lett. 2009;276:3800–3809. [CrossRef]
Weber A Marquardt J Elzi D . Zbtb4 represses transcription of P21CIP1 and controls the cellular response to p53 activation. EMBO J. 2008;27:1563–1574. [CrossRef] [PubMed]
Chen J Rattner A Nathans J . The rod photoreceptor-specific nuclear receptor Nr2e3 represses transcription of multiple cone-specific genes. J Neurosci. 2005;25:118–129. [CrossRef] [PubMed]
Corbo JC Cepko CL . A hybrid photoreceptor expressing both rod and cone genes in a mouse model of enhanced S-cone syndrome. PLoS Genet. 2005;1:e11. [CrossRef] [PubMed]
Zangerl B Goldstein O Philp AR . Identical mutation in a novel retinal gene causes progressive rod-cone degeneration in dogs and retinitis pigmentosa in humans. Genomics. 2006;88:551–563. [CrossRef] [PubMed]
Figure 1.
 
qRT-PCR results. The histograms represent the ratios of the changes in expression for the different genes analyzed. (Image not available) Genes not DE in the microarray analysis; (■) DE genes in the microarray analysis; (□) genes not on the microarray or that did not amplify in the brain reference tissue; (Image not available) genes that were only examined by qRT-PCR at 3 weeks, but not by microarray analysis. Values that significantly differ are indicated with asterisks (*P ≤ 0.05; **0.05<P < 0.1, indicating a trend toward statistical significance). Error bars: ranges of the maximum and minimum change differences calculated based on the standard deviation of biological triplicates, as previously shown.37 See Supplementary Tables S2 and S3 for the complete microarray results of the DE genes CRX, PAX6, NDUFS4, ZBTB4, SPP1, SAG, SLC25A5, and TPD52. (A) Comparison of expression for 18 selected genes between mutant and normal retinas at 3, 7, and 16 weeks of age. (B) Comparison of NDUFS4 and ZBTB4 expression between mutant and normal retinas in the combined analysis (7 and 16 weeks of age). (C) Expression comparison of eight genes between mutant and normal retinas at 7 and 16 weeks of age.
Figure 1.
 
qRT-PCR results. The histograms represent the ratios of the changes in expression for the different genes analyzed. (Image not available) Genes not DE in the microarray analysis; (■) DE genes in the microarray analysis; (□) genes not on the microarray or that did not amplify in the brain reference tissue; (Image not available) genes that were only examined by qRT-PCR at 3 weeks, but not by microarray analysis. Values that significantly differ are indicated with asterisks (*P ≤ 0.05; **0.05<P < 0.1, indicating a trend toward statistical significance). Error bars: ranges of the maximum and minimum change differences calculated based on the standard deviation of biological triplicates, as previously shown.37 See Supplementary Tables S2 and S3 for the complete microarray results of the DE genes CRX, PAX6, NDUFS4, ZBTB4, SPP1, SAG, SLC25A5, and TPD52. (A) Comparison of expression for 18 selected genes between mutant and normal retinas at 3, 7, and 16 weeks of age. (B) Comparison of NDUFS4 and ZBTB4 expression between mutant and normal retinas in the combined analysis (7 and 16 weeks of age). (C) Expression comparison of eight genes between mutant and normal retinas at 7 and 16 weeks of age.
Figure 2.
 
Western blot analysis of single samples from normal (16 and 7 weeks) and XLPRA2 mutant (16 and 7 weeks) retinas with four antibodies (NDUFS4, SAG, FAP, and OPN1SW) in addition to actin (ACTB), used as a loading control. Dashed line indicates that the gel was cut and ACTB placed below the protein of interest. The relevant molecular size markers are indicated. (A) NDUFS4 levels were lower in the mutant retina at both ages. (B) Lower protein levels of SAG were found in the mutant retina at 16 weeks compared with either the normal age-matched control or the 7-week mutant. (C) GFAP was upregulated in both the 7- and 16-week mutant retinas. (D) The mutant retina at 16 weeks showed a downregulation of OPN1SW. The specific ∼39 kDa band is absent, even though the quantity of the ACTB loading control was high.
Figure 2.
 
Western blot analysis of single samples from normal (16 and 7 weeks) and XLPRA2 mutant (16 and 7 weeks) retinas with four antibodies (NDUFS4, SAG, FAP, and OPN1SW) in addition to actin (ACTB), used as a loading control. Dashed line indicates that the gel was cut and ACTB placed below the protein of interest. The relevant molecular size markers are indicated. (A) NDUFS4 levels were lower in the mutant retina at both ages. (B) Lower protein levels of SAG were found in the mutant retina at 16 weeks compared with either the normal age-matched control or the 7-week mutant. (C) GFAP was upregulated in both the 7- and 16-week mutant retinas. (D) The mutant retina at 16 weeks showed a downregulation of OPN1SW. The specific ∼39 kDa band is absent, even though the quantity of the ACTB loading control was high.
Figure 3.
 
Immunolabeling of normal and XLPRA2 mutant 16- and 7-week retinas with the same four antibodies (NDUFS4, SAG, GFAP, and OPN1SW) as were used in Western analysis. Except for NDUFS4 (A), images were merged with DIC-transmitted light. (A) NDUFS4 was expressed in the mitochondrion inner membrane. Staining was observed in the retinal pigment epithelium (RPE), photoreceptor inner segment (IS), inner plexiform (IPL), and ganglion cell (GCL) layers. Lower NDUFS4 labeling was seen in the mutant retina at 16 weeks, particularly in the IS, owing to the loss of photoreceptors. Intense staining was found in the inner nuclear layer (INL) in the normal retinas at 16 weeks. (B) SAG was highly expressed in the photoreceptor outer segments (OS) and in the outer plexiform layer (OPL) in normal retinas. In the mutant, it mislocalized to the outer nuclear layer (ONL). (C) GFAP staining was weak and limited to astrocytes and Müller cell end feet in normal retinas at 7 weeks and was minimal at 16 weeks. In the mutant retinas, GFAP immunoreactivity was evidenced by intense GFAP labeling in Müller cells at both 7 and 16 weeks, and labeled radial processes extended from the inner retina into the ONL. (D) OPN1SW is exclusively expressed in the OS of S-cones, in the 16-week mutant retina OPN1SW were minimal to absent. Scale bar: 2.5 μm.
Figure 3.
 
Immunolabeling of normal and XLPRA2 mutant 16- and 7-week retinas with the same four antibodies (NDUFS4, SAG, GFAP, and OPN1SW) as were used in Western analysis. Except for NDUFS4 (A), images were merged with DIC-transmitted light. (A) NDUFS4 was expressed in the mitochondrion inner membrane. Staining was observed in the retinal pigment epithelium (RPE), photoreceptor inner segment (IS), inner plexiform (IPL), and ganglion cell (GCL) layers. Lower NDUFS4 labeling was seen in the mutant retina at 16 weeks, particularly in the IS, owing to the loss of photoreceptors. Intense staining was found in the inner nuclear layer (INL) in the normal retinas at 16 weeks. (B) SAG was highly expressed in the photoreceptor outer segments (OS) and in the outer plexiform layer (OPL) in normal retinas. In the mutant, it mislocalized to the outer nuclear layer (ONL). (C) GFAP staining was weak and limited to astrocytes and Müller cell end feet in normal retinas at 7 weeks and was minimal at 16 weeks. In the mutant retinas, GFAP immunoreactivity was evidenced by intense GFAP labeling in Müller cells at both 7 and 16 weeks, and labeled radial processes extended from the inner retina into the ONL. (D) OPN1SW is exclusively expressed in the OS of S-cones, in the 16-week mutant retina OPN1SW were minimal to absent. Scale bar: 2.5 μm.
Table 1.
 
Selected DE Genes Related to Apoptotic/Cell Death Processes or to Mitochondria Functions or Having Relevant Vision Functions in Mutant Retinas Compared with Age-Matched Normal Retinas at 7 and 16 Weeks and in a Combined (7 and 16 Weeks) Analysis
Table 1.
 
Selected DE Genes Related to Apoptotic/Cell Death Processes or to Mitochondria Functions or Having Relevant Vision Functions in Mutant Retinas Compared with Age-Matched Normal Retinas at 7 and 16 Weeks and in a Combined (7 and 16 Weeks) Analysis
Gene Name Related Function GO q (%) Change Mutant vs. Normal
Seven Weeks
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4 Mitochondria Mitochondrial electron transport; oxygen and reactive oxygen species metabolic process 0.0 −47.2
PAX6 Paired box 6 Vision Eye development; protein and DNA binding; transcription regulator activity 0.0 −8.6
ELOVL6 ELOVL family member 6, elongation of long chain fatty acids Mitochondria Transferase activity; fatty acid elongation 0.0 −3.4
GLOD4 Glyoxalase domain containing 4 Mitochondria Lyase activity 0.0 −3.2
PRKCB Protein kinase C, beta Proapoptosis Protein kinase activity; nucleotide binding 7.0 −16.0
TUBB2C Tubulin, beta 2C Cell death Nucleotide, GTP and MHC class I protein binding; gtpase activity 7.0 −2.8
CHML Choroideremia-like (Rab escort protein 2) Vision Visual perception; regulation of gtpase activity 9.6 −12.6
SPPI Secreted phosphoprotein 1, osteopontin Antiapoptosis Protein binding; cytokine activity; inflammatory response 9.6 −9.0
CAMK2G Calcium/calmodulin-dependent protein kinase II gamma Cell death Protein kinase activity; nucleotide binding 9.6 −5.1
RBBP6 Retinoblastoma binding protein 6 Proapoptosis; vision Nucleic acid and protein binding; ubiquitin-protein ligase activity 9.6 −4.4
REEP1 Receptor accessory protein 1 Mitochondria; cell death Protein insertion into membrane 9.6 −4.3
SMYD3 SET and MYND domain containing 3 Antiapoptosis Protein binding; transferase activity 9.6 −3.4
RNF41 Ring finger protein 41 Proapoptosis Protein binding; ligase activity 9.6 −2.8
RALA V-ral simian leukemia viral oncogene homolog A (ras related) Cell death Gtpase activity; protein and nucleotide binding 9.6 −2.6
NTRK2 Neurotrophic tyrosine kinase, receptor, type 2 Prosurvival Protein kinase activity; nucleotide binding 9.6 −2.6
RDH11 Retinol dehydrogenase 11 Vision Retinol dehydrogenase activity; catalytic activity 9.6 −2.0
Sixteen Weeks
NKAP NFKB activating protein Prosurvival Transcriptional repressor 7.5 −68.6
TARS2 Threonyl-tRNA synthetase 2, mitochondrial Mitochondria Nucleotide and ATP binding; ligase activity 7.5 −58.3
SAG S-antigen; retina and pineal gland (arrestin) Vision Protein binding; signal transduction; visual perception 7.5 −5.7
CRX Cone-rod homeobox Vision DNA and protein binding; transcription factor activity; visual perception 7.5 −5.0
SLC25A5 Solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 5 Mitochondria; pro-survival Protein binding; transporter activity 7.5 −3.9
Combined Analysis
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4 Mitochondria Mitochondrial electron transport; oxygen and reactive oxygen species metabolic process 0.0 −37.0
ACSL1 Acyl-CoA synthetase long-chain family member 1 Mitochondria Nucleotide and ATP binding 0.0 2.3
PDE6A Phosphodiesterase 6A, cGMP-specific, rod, alpha Vision Catalytic activity; visual perception 8.0 −3.0
PPP3CA Protein phosphatase 3, catalytic subunit, alpha isoform Mitochondria; proapoptosis Protein serine/threonine phosphatase activity 8.0 −2.3
RNF41 Ring finger protein 41 Proapoptosis Protein binding; ligase activity 8.0 −2.3
ADC Arginine decarboxylase Mitochondria Protein binding; lyase activity 8.8 2.5
HSP90AA1 Heat shock protein 90kDa alpha, class A member 1 Antiapoptosis; mitochondrial transport Nucleotide binding; protein folding; response to stress 8.8 2.4
TFAM Transcription factor A, mitochondrial Mitochondria; antiapoptosis; vision DNA binding; regulation of transcription 8.8 2.3
ZBTB4 Zinc finger and BTB domain containing 4 Proapoptosis DNA and protein binding; regulation of transcription 8.8 2.0
Table 2.
 
Functional Assignment
Table 2.
 
Functional Assignment
GO Category Term Genes (n) P
Seven Weeks
BP Secretion 5 0.01
Cellular component organization and biogenesis 13 0.014
Organelle organization and biogenesis 8 0.017
Posttranslational protein modification 9 0.019
Cellular monovalent inorganic cation homeostasis 2 0.036
Establishment of localization 12 0.041
Localization 13 0.042
Protein modification process 9 0.047
CC Organelle membrane 11 0.0007
Cytoplasmic part 17 0.004
Endoplasmic reticulum 7 0.01
Endoplasmic reticulum membrane 5 0.016
Nuclear envelope-endoplasmic reticulum network 5 0.018
Endomembrane system 7 0.019
Endoplasmic reticulum part 5 0.025
Cytoplasm 21 0.034
Intracellular organelle part 14 0.038
Organelle part 14 0.039
Membrane 23 0.047
MF Protein binding 24 0.003
GTP binding 4 0.047
Guanyl ribonucleotide binding 4 0.049
Sixteen Weeks
CC Intracellular part 11 0.043
MF Protein phosphatase regulator activity 2 0.031
Phosphatase regulator activity 2 0.032
Combined Analysis
BP Mitochondrion organization and biogenesis 3 0.004
Nitrogen compound metabolic process 4 0.011
Cellular metabolic process 13 0.035
Primary metabolic process 13 0.036
CC Cytoplasmic part 10 0.0005
Cytoplasm 11 0.006
Endoplasmic reticulum 4 0.027
MF Catalytic activity 10 0.044
Table 3.
 
Significant Human KEGG Pathway
Table 3.
 
Significant Human KEGG Pathway
Seven Weeks
hsa04722 Neurotrophin signaling pathway
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    NTRK2; neurotrophic tyrosine kinase, receptor, type 2
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa04510 Focal adhesion
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
    SPP1; secreted phosphoprotein 1
hsa04012 ErbB signaling pathway
hsa05214 Glioma
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    PRKCB; protein kinase C, beta
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa04062 Chemokine signaling pathway
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
    SHC3; SHC (Src homology 2 domain containing) transforming protein 3
hsa05200 Pathways in cancer
    PRKCB; protein kinase C, beta
    RALA; v-ral simian leukemia viral oncogene homolog A (ras related)
    TCEB1; transcription elongation factor B (SIII), polypeptide 1 (15kDa, elongin C)
hsa04010 MAPK signaling pathway
    NTRK2; neurotrophic tyrosine kinase, receptor, type 2
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
hsa04720 Long-term potentiation
    CAMK2G; calcium/calmodulin-dependent protein kinase II gamma
    PRKCB; protein kinase C, beta
    RAP1B; RAP1B, member of RAS oncogene family
hsa01100 Metabolic pathways
    ATP6V1H; ATPase, H+ transporting, lysosomal 50/57 kDa, V1 subunit H
    NDUFS4; NADH dehydrogenase (ubiquinone) Fe-S protein 4
    RDH11; retinol dehydrogenase 11
Combined Analysis
hsa01100 Metabolic pathways
    ACSL1; acyl-CoA synthetase long-chain family member 1
    ADC; arginine decarboxylase
    NDUFS4; NADH dehydrogenase (ubiquinone) Fe-S protein 4
    RDH11; retinol dehydrogenase 11
Supplementary Table S1
Supplementary Table S2
Supplementary Table S3
Supplementary Figure S1
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