Functional annotation of the human retinal pigment epithelium transcriptome
© Booij et al; licensee BioMed Central Ltd. 2009
Received: 10 July 2008
Accepted: 20 April 2009
Published: 20 April 2009
To determine level, variability and functional annotation of gene expression of the human retinal pigment epithelium (RPE), the key tissue involved in retinal diseases like age-related macular degeneration and retinitis pigmentosa. Macular RPE cells from six selected healthy human donor eyes (aged 63–78 years) were laser dissected and used for 22k microarray studies (Agilent technologies). Data were analyzed with Rosetta Resolver, the web tool DAVID and Ingenuity software.
In total, we identified 19,746 array entries with significant expression in the RPE. Gene expression was analyzed according to expression levels, interindividual variability and functionality. A group of highly (n = 2,194) expressed RPE genes showed an overrepresentation of genes of the oxidative phosphorylation, ATP synthesis and ribosome pathways. In the group of moderately expressed genes (n = 8,776) genes of the phosphatidylinositol signaling system and aminosugars metabolism were overrepresented. As expected, the top 10 percent (n = 2,194) of genes with the highest interindividual differences in expression showed functional overrepresentation of the complement cascade, essential in inflammation in age-related macular degeneration, and other signaling pathways. Surprisingly, this same category also includes the genes involved in Bruch's membrane (BM) composition. Among the top 10 percent of genes with low interindividual differences, there was an overrepresentation of genes involved in local glycosaminoglycan turnover.
Our study expands current knowledge of the RPE transcriptome by assigning new genes, and adding data about expression level and interindividual variation. Functional annotation suggests that the RPE has high levels of protein synthesis, strong energy demands, and is exposed to high levels of oxidative stress and a variable degree of inflammation. Our data sheds new light on the molecular composition of BM, adjacent to the RPE, and is useful for candidate retinal disease gene identification or gene dose-dependent therapeutic studies.
The retinal pigment epithelium (RPE) is a multifunctional neural-crest derived cell layer, flanked by the photoreceptor cells on the apical side and the Bruch's membrane (BM)/choroid complex on the basolateral side. Among others, the RPE supplies the photoreceptors with nutrients, regulates the ion balance in the subretinal space and recycles retinal from the photoreceptor cells, which is necessary for the continuation of the visual cycle. It also phagocytoses and degrades photoreceptor outer segments and absorbs light that is projected onto the retina. Finally, the RPE secretes a number of growth factors that maintain the structure and cellular differentiation of the adjacent tissues.
The importance of the RPE in vision is illustrated by the major involvement of this monolayer of cells in genetically determined retinal diseases like age related macular degeneration (AMD) and retinitis pigmentosa (RP). Since the great majority of genes implicated in AMD or RP are expressed in either the RPE or the photoreceptors, the identification of additional genes highly expressed in the RPE may provide valuable clues in the search for new genes involved in retinal disease. [2–6]
Obviously, the functional properties of RPE cells are determined by the genes they express and the proteins they encode. Although the RPE cell is one of the best studied neural cell types, [3–12] large scale assignment of expressed genes to the RPE has been largely dependent on RNA based studies. Assignment of proteins to the RPE has been hampered by its autofluorescence and melanin content. Large-scale RPE related expression studies were performed using cDNA arrays, serial analysis of gene expression (SAGE), expressed sequence tag (EST) analysis, and multiple RT-PCRs. The number of eyes used in these studies ranged from one to fifteen, and the number of genes under investigation from 29 to 30,000. [8–12] While these studies provided valuable information, they were limited in either the number of genes or the number of eyes under investigation, or they lacked specificity due to the tissue sampling method used. Moreover, most or all of these studies focused on the mean gene expression profile of all samples together, rather than documenting potential interindividual differences. [8–12] A robust and specific dataset on RPE expression levels from a substantial number of individuals is lacking and a great deal remains unknown with regard to the interindividual expression differences.
A number of biological processes and cellular functions of genes expressed in the RPE were described in three of the above mentioned studies.[8, 10, 12] All three identified protein metabolism and signal transduction as an important functional class of genes expressed by the RPE.[8, 10, 12] Similarly, cell structure,[8, 10] cell proliferation,[8, 10] gene transcription[10, 11] and energy metabolism were described in two out of three studies. Finally, individual studies also identified overrepresentation of membrane proteins, transport or channel proteins, heat shock proteins and vitamin A metabolism. In a recent microarray study we compared RPE gene expression in the macula with the retinal periphery and demonstrated, among other things, consistent differential expression of extracellular matrix genes corresponding with proteins in BM.
The aim of the current study is to describe the gene expression levels and the interindividual variation in gene expression of native human macular RPE cells in a systematic fashion. In addition, we annotate the functions and biological pathways associated with RPE expressed (disease) genes.
To our knowledge this is the first study to present data on (interindividual differences in) human macular RPE gene expression and interindividual differences on a large scale of 22,000 genes, resulting in a further detailed description of the RPE transcriptome.
RNA from six selected human macular RPE samples was hybridized to six custom made 22 k microarrays enriched for neural transcripts. We functionally annotated and analyzed the data using Rosetta Resolver, the web tool DAVID and Ingenuity software, with regard to gene expression level and variability as well as functional annotation. Furthermore, we specifically looked at the expression levels and variability of retinal disease genes.
Analysis of gene expression levels (μint)
Overrepresented Kegg pathways in macular RPE expressed genes with high, moderate and low expression levels and high or low levels of interindividual variability (coefficient of variation, CV).
all expression levels
high (> 90th perc)
moderate (50th–90th perc)
low (10th–50th perc)
ecm-receptor interaction (E)
oxidative phosphorylation (B,E)
ATP synthesis (B,E)
phosphatidylinositol signaling system (B,E)
aminosugars metabolism (E)
neuroactive ligand receptor interaction (B,E)
long-term depression (E)
o-glycan biosynthesis (E)
calcium signaling pathway (E)
type I diabetes mellitus (B,E)
focal adhesion (B,E)
cytokine-cytokine receptor interaction (E)
complement and coagulation cascades (E)
antigen processing and presentation (E)
ecm-receptor interaction (E)
antigen processing and presentation (B,E)
complement and coagulation cascades (E)
focal adhesion (E)
cytokine-cytokine receptor interaction (E)
type I diabetes mellitus (E)
glycosaminoglycan degradation (E)
Genes with high expression levels (μint > 90th percentile, n = 2,194)
The thirty most highly expressed genes in macular RPE identified in six different human donors, sorted by intensity in descending order.
mean intensity μint perc
protection against reactive oxygen species
Solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 7
Tumor protein p53
protection against reactive oxygen species
E74-like factor 2 (ets domain transcription factor)
Serpin peptidase inhibitor, clade B, member 5
minichromosome maintenance deficient 7
Solute carrier family 1 member 2
Prostaglandin D2 synthase 21 kDa
Eukaryotic translation elongation factor 1 alpha 1
Transthyretin (prealbumin, amyloidosis type I)
Zinc finger protein 503
Heat shock protein 90 kDa beta (Grp94), member 1
Guanine nucleotide binding protein (G protein), gamma transducing activity polypeptide 1
Ribosomal protein L3
Ribosomal protein L41
Proprotein convertase subtilisin/kexin type 7
member of complement system 
Genes with moderate expression levels (μint 50th–90th percentile)
Upon analyzing this group of 8,776 genes, we found a statistically significant overrepresentation of the Kegg pathways phosphatidylinositol signaling and aminosugars metabolism (Benjamini-Hochberg p value < 0.001) (Table 1).
Genes with low expression levels (μint 10th–50th percentile)
Among the 8,776 genes with low expression levels there was a statistically significant overrepresentation of the neuroactive ligand-receptor interaction (Benjamini-Hochberg p value 0.001), long-term depression, O-glycan biosynthesis and calcium signaling pathways (Ease score p value < 0.001) (Table 1).
Analysis of gene expression variability (CV)
The top thirty genes with the highest interindividual variation in expression levels (CV) between six healthy human donors, sorted descending by coefficient of variation (CV).
mean intensity μint perc
Hydroxysteroid (17-beta) dehydrogenase 2
Myocilin, trabecular meshwork inducible glucocorticoid response
Osteoglycin (osteoinductive factor, mimecan)
Secreted frizzled-related protein 4
Amine oxidase, copper containing 2 (retina-specific)
Deiodinase, iodothyronine, type III
Solute carrier family 2 (facilitated glucose/fructose transporter), member 5
X (inactive)-specific transcript
Tissue factor pathway inhibitor 2
Cysteine-rich, angiogenic inducer, 61
EGF-like-domain, multiple 6
Microfibrillar-associated protein 4
Chemokine (C-C motif) ligand 2
Zinc family member 1 (odd-paired homolog, Drosophila)
Collagen, type IX, alpha 1
Chemokine (C-C motif) ligand 26
Paired-like homeodomain transcription factor 2
Aldehyde dehydrogenase 1 family, member A1
Hemoglobin, gamma A
S100 calcium binding protein A6
Interleukin 6 (interferon, beta 2)
Hemoglobin, gamma G
Chromosome 13 open reading frame 33
RNA binding motif (RNP1, RRM) protein 3
Complement factor B
Early growth response 1
Pentraxin-related gene, rapidly induced by IL-1 beta
Genes with high interindividual variability (CV > 90th percentile)
Among the 390 genes with both a high CV and high μint there was an overrepresentation of genes involved in antigen processing as well as the complement and coagulation cascades. The 824 genes with a high CV and moderate μint showed an overrepresentation of genes involved in focal adhesion and cytokine-cytokine receptor interaction, and the 762 genes with high CV and low μint showed an overrepresentation of genes involved in type I diabetes mellitus. The latter group contains mainly major histocompatibility complex genes and interleukin 1α [genbank: NM_000575].
Genes with low interindividual variability (CV < 10th percentile)
The thirty genes with the least interindividual variation in macular RPE gene expression levels among six healthy human donors, sorted ascending by coefficient of variation (CV).
mean intensity μint perc
Exocyst complex component 3
Pyridoxal (pyridoxine, vitamin B6) kinase
Synovial sarcoma translocation gene on chromosome 18-like 1
FOS-like antigen 1
Formyl peptide receptor-like 2
Cleavage and polyadenylation specific factor 4, 30 kDa
Chromosome 8 open reading frame 72
Chromodomain helicase DNA binding protein 2
Fetal and adult testis expressed 1
C-type lectin domain family 4, member E
Poly(A)-specific ribonuclease (deadenylation nuclease)
Transmembrane protein 156
Casein kinase 2, alpha 1 polypeptide
MYST histone acetyltransferase (monocytic leukemia) 3
Protein kinase C binding protein 1
Chromosome 20 open reading frame 11
Cyclin G associated kinase
hypothetical protein FLJ10159
Zinc finger protein 665
Olfactory receptor, family 2, subfamily A, member 7
Protein kinase C, epsilon
Ring finger protein 14
Selenium binding protein 1
Gene expression analysis of known retinal disease genes
Known macular disease genes
Expression levels and interindividual differences of currently known macular disease genes with RPE expression.
mean intensity μint (perc)
high interindividual variation (CV > 10 th perc)
intermediate interindividual variation (CV 10 th – 90 th perc)
low interindividual variation (CV < 90 th perc)
A number of genes currently known or suggested to be associated with AMD, showed high (C3 [genbank: NM_000064], CFB [genbank: NM_001710], CFH [genbank: NM_000186], HTRA1 [genbank: NM_002775], and CST3 [genbank: NM_000099]) or moderate (FBLN5 [genbank: NM_006329]) expression levels in the RPE. With the exception of HTRA1 [genbank: NM_002775], all these genes also showed high interindividual variation.
Known peripheral retinal disease genes
Expression levels and interindividual differences of currently known peripheral disease genes with RPE expression.
mean intensity (μint) (percentile)
high interindividual variation (CV > 90 th percentile)
intermediate interindividual variation (CV 10 th – 90 th percentile)
low interindividual variation (CV < 10 th percentile)
Of this group, 32 percent were found in the 10 percent of genes with high expression levels in the macular RPE. Eleven percent of the known peripheral disease genes were found in the 10 percent of genes with high interindividual variation in expression in the macular RPE.
This study presents the first comprehensive analysis of the macular RPE transcriptome, with a focus on interindividual differences in RPE gene expression levels. We based our analyses on microarray data from six healthy human donor eyes. In addition, we performed a Kegg pathway analysis on genes with high, moderate and low expression levels and on genes with high and low interindividual variation in expression.
Only five genes from our top 30 most highly expressed RPE genes were previously known to be expressed in the human RPE in vivo: SLC17A7 [genbank: NM_020309], CST3 [genbank: NM_000099]), PTGDS [genbank: NM_000954], TTR [genbank: NM_000371]and HSP90B1 [genbank: NM_003299]) illustrating the lack of knowledge on the RPE transcriptome.
Strengths and limitations of the study design
A recent statistical review suggested that a microarray study investigating a single tissue type, requires 6 biological replicate samples to draw statistically significant conclusions. Consequently, we used the RPE gene expression from 6 different individuals. Previous RPE gene expression studies were based on less than six eyes, with the exception of a single cDNA microarray study limited to 4,325 genes that was based on 15 individuals. [8–12]
One of the methodological limitations of our study was the limited number of eyes that met our selection criteria. The availability of a larger number of eyes would render more robust results with regard to interindividual variation. Nonetheless, our data give a good first impression of variability in gene expression levels in the RPE. An additional limitation is that a small amount of photoreceptor contamination was inevitably present in our RPE sample, see also table 2.[8, 13, 30] Furthermore, we cannot distinguish possible transient from permanent gene expression level differences. Our study is also limited by the fact that the measurement of gene expression of individual genes by microarray is inevitably influenced by a number of factors, like oligo design and the continuous updates of the human genome sequence. To correct for this last limitation, we focused our analysis on groups of genes with a wide range of expression levels, rather than on individual gene expression levels. Finally, our cut off criteria for high and low expression levels and interindividual differences are arbitrary. While this may indeed have consequences for individual genes, the impact on our functional analysis, which is based on large numbers of genes, will be minimal.
Despite these limitations, our data, combined with data from other retinal gene expression studies (which use a range of techniques, like SAGE and RT-PCR, that bear their own limitations),[13, 31] contributes significantly to the currently expanding knowledge of the RPE transcriptome.
Functional assessment of native gene expression in the macular RPE
The notion that the identity of a cell type is determined by the genes it expresses, prompted us to analyze the native macular RPE transcriptome. In the following section we describe the overrepresented functional groups that we identified in the RPE.
Highly expressed RPE genes and oxidative stress
Both functional annotation with DAVID and Ingenuity analysis independently indicate a statistically significant overrepresentation of genes associated with oxidative phosphorylation and ATP synthesis in our dataset. This is in line with the fact that the RPE has a high metabolic activity and energy demand. The down side of this high activity is that the RPE has to deal with large amounts of oxidative stress. The oxidative stress in the RPE is further augmented by the light projected onto the retina combined with the rich oxygen supply and lipid peroxidation in phagocytosed rod outer segments.[1, 32] Given the high level of oxidative stress, the expression of genes contributing to the defense of the RPE cell against oxidative stress is essential for cell survival. Our data confirm this notion, which is highlighted by the expression of the MT1A [genbank: K01383] gene, a metallothionein, and the TP53 [genbank: NM_000546] gene in the top 30 most highly expressed RPE genes. Metallothioneins are thought to play a role in protection against oxidative stress; addition of TP53 [genbank: NM_000546] to human cell lines leads to a 50 percent decrease in reactive oxygen species.[22, 23]
RPE and the immune system
Our data show an overrepresentation of genes with highly variable expression in a number of pathways related to the immune system. We identified the following four pathways, the complement and coagulation cascades (high expression levels), the antigen processing and presentation pathway (high expression levels) and the cytokine-cytokine receptor interaction pathway (moderate expression levels). Both the antigen processing and presentation pathway and the type 1 diabetes mellitus pathway contain MHC genes responsible for antigen presentation. Cytokine production is highly sensitive to inflammation in the RPE. The cytokine-cytokine receptor pathway contains a number of chemokines, small secreted proteins involved in the chemotaxic attraction of monocytes and neutrophils. The highly variable expression of genes involved in the immune system is most likely explained by both genetic differences and a variable degree of subclinical inflammation (local or systemic) among our donors.
RPE genes and the extracellular matrix (Bruch's membrane)
The close interaction of the RPE with Bruch's membrane (BM) is exemplified by the overrepresentation of genes in two pathways. The first pathway contains genes involved in extracellular matrix (ECM) receptor interaction. The ECM receptor interaction pathway, part of the focal adhesion pathway, contains collagens type I, III and IV, thrombospondin, laminin beta 1 [genbank: NM_002291], fibronectin 1 [genbank: NM_002291], reelin [genbank: NM_005045], and cd44 antigen [genbank: NM_000610]. Collagen type IV, laminin and fibronectin are all main components of basement membranes, such as BM. Surprisingly, the genes in this group showed highly variable expression, which may indicate that the molecular composition of BM is different among individuals. Alternatively, it has been described that with age, the solubility of collagens in BM decreases significantly. Thus, the high variability in expression levels of collagen genes between our samples can perhaps be explained by differences in the physiological donor age.
A second pathway that connects RPE expressed genes to BM is the glycosaminoglycan (GAG) degradation pathway. There was an overrepresentation of genes with stable and high expression in this pathway. GAG synthesis has been shown in cultured RPE and GAG's are secreted into the extracellular matrix and BM. Interestingly, GAG's are rapidly turned over in the RPE, and the composition of GAG in BM changes with age. [35–37] Our data suggest there is a strict regulation of GAG turnover in the RPE, even in donors of different ages.
Additional RPE gene functions
In addition to the involvement of the RPE genes in oxidative stress, BM and the immune system, analysis of our data revealed the following two functional categories: protein synthesis and glutamate transport.
A high level of protein synthesis is essential for the RPE to maintain its multiple functions. This is exemplified by the overrepresentation of genes with high expression in the ribosomal protein activity pathway.
Glutamate transport is an important process in the RPE. The top 30 most highly expressed RPE genes contained two glutamate transporters SLC1A2 [genbank: AF131756] and SLC17A 7 [genbank: AF131756]. The latter transporter was already known to be expressed in the human RPE in vivo.[14, 38] Glutamate is an important neurotransmitter that is released from the photoreceptors both in a light influenced fashion, and upon apoptosis. Since high concentrations of glutamate are neurotoxic, re-uptake and transport of glutamate are essential for the normal retinal homeostasis.
Finally, in the overlap between previous RPE studies and genes with high expression in our RPE transcriptome, we identified the cell-cell signaling and interaction network. This network contains several genes involved in signal transduction, like SLC7A2 [genbank: AL512749] and NCK2 [genbank: BC007195] further emphasizing the important role of the RPE in interaction with other cell types.[39, 40]
Comparison with literature
Comparison of our most highly expressed RPE genes to the literature revealed a distinct overlap. Schulz and coworkers recently combined different analyses of the retina/RPE/choroid transcriptome, and described 13,000 retina/RPE genes found in at least two studies. Out of these 13,000, we currently assign 7,231 genes to be expressed by the RPE, 1,407 of which are highly expressed. (see Additional file 2: overlap between highly expressed RPE genes and retina/RPE genes in at least two studies) In addition, the same review suggested that 246 genes were expressed only in RPE studies. We assign 137 of these 246 genes to the RPE as well; 17 out of these 137 genes have high expression levels in our RPE transcriptome analysis. (see Additional file 3: overlap between highly expressed RPE genes and genes found only in RPE studies)
Finally, of the genes previously described to be specifically expressed either in the retina or the RPE in individual studies, 39 genes are also present in our RPE transcriptome analysis. Twenty two of these 39 genes had high expression levels. (see Additional file 4: overlap between highly expressed RPE genes and retina/RPE genes in single studies)
While data on interindividual variation in RPE gene expression are lacking, functional properties of RPE genes have been investigated previously.
The combined functional annotation from three studies resemble our functional annotation in the following areas: gene regulation, transcription, protein metabolism, cell proliferation, survival and signaling, energy metabolism, cytoskeleton and inflammation.[8, 10, 11] The current study adds the following more specific functional categories, oxidative phosphorylation, ATP synthesis, ribosome, phosphatidylinositol signaling and aminosugars metabolism. Among the highly expressed RPE genes we identified an overrepresentation of the complement cascade and genes involved in the composition of BM.
Gene expression analysis of known retinal disease genes
In our macular RPE sample we observed that 63 percent of genes involved in macular disorders according to the literature, had high expression levels. In contrast, only 32 percent of the peripheral retinal disease genes were highly expressed in our sample. These figures may be biased, since the search for candidate genes has been focused on cell-specific highly expressed genes in the first place. The figures probably reflect the fact that RPE gene expression differences exist between the retinal macula and the periphery. However, our data probably also imply that the mean expression level of a gene in the RPE is informative in the search for new candidate disease genes.
With respect to the variability in gene expression, we found that the interindividual differences of currently known macular retinal disease genes were somewhat higher than the overall pattern of variation seen in the entire array. Whether or not this finding is coincidental remains to be elucidated.
In conclusion, we present comprehensive data on (interindividual differences of the) gene expression profile of the RPE based on 22,000 genes from six different healthy human donors. This is the first study to describe the interindividual variability in gene expression levels from a microarray analysis of the RPE transcriptome.
There was no correlation between the height of gene expression (μint) and the interindividual variability (CV) (data not shown). We noted a more than hundred fold difference in CV between genes with stable expression and genes with variable expression levels.
Our data show that the RPE most likely has high levels of protein synthesis, a high energy demand and is subject to high levels of oxidative stress as well as a variable degree of inflammation. Finally, our data show high interindividual variability in expression of ECM genes and indicate a high and constant level of glycosaminoglycan (GAG) turnover, two functions related to BM.
The fact that large interindividual differences exist in the expression of a number of known retinal disease genes has not only functional implications, but is also relevant for new candidate disease gene identification and the development of dose-dependent (gene) therapeutic strategies.
Human donor eyes
This study was performed in agreement with the declaration of Helsinki on the use of human material for research. Material used in this study was provided to us by the Corneabank Amsterdam. In order to minimize genetic heterogeneity, we selected six eyes from a total of 200 human donor eyes using strict selection criteria, (see Figure 3). In summary, donors were excluded when their age was not between 60 and 80 years, when they had an eye disease or any form of malignancy and when the time between death and enucleation of the eye was more than 30 hours. Furthermore, eyes were excluded when they showed any abnormalities upon visual or histological examination: more specifically, when more than one druse was seen in 10 histological sections, or when retinal morphology was poor. All donors were Caucasian, five were male, one was female. The donors died of cardiovascular or cerebrovascular causes or of chronic obstructive pulmonary disease. Donors did not have a known ophthalmic disorder or malignancy. Globes were enucleated between 14 and 27 hours post mortem and frozen several hours later according to a standard protocol. Donors were aged 63 to 78 years at the time of death. We chose old donors in order to minimize the likelihood of the presence of yet undiagnosed monogenic eye diseases. This does not rule out the presence of the most common retinal disease in the old eye, age related macular degeneration (AMD). Therefore the donor retinas were thoroughly screened for early signs of AMD by histological examination (the presence of more than 1 druse in 10 sections). Visual examination and histological examination, including periodic acid Schiff (PAS) staining, indicated no retinal pathology in any of the donor eyes.
RPE cell sampling
Globes were snap-frozen and stored at -80°C until use. A macular fragment of 16 mm2 with the fovea in its center was cut from each of the retinas, as described previously. In summary, for each eye, 10 cryosections, 8 μm thick, spaced no more than 220 μm apart were stained with periodic-acid Schiff and microscopically examined for abnormalities, such as drusen indicative of early-AMD.
Twenty μm sections from the macular areas were used for the isolation of RPE cells. These sections were dehydrated with ethanol and air-dried before microdissection with a Laser Microdissection System (PALM, Bernried, Germany) using a pulsed laser. A total of up to 10,000 RPE cells per eye were microdissected and stored at -80° Celsius.
RNA isolation and (single) amplification
Total RNA was isolated and the mRNA component was amplified essentially as described previously. Next, the amplified RNA (aRNA) samples were quantified with a nanodrop (Isogen Life Science B.V., The Netherlands) and the quality was checked on a BioAnalyzer (Agilent Technologies, Amstelveen, The Netherlands). Subsequently, aRNA samples were labeled with either a Cy3 or a Cy5 fluorescent probe.
A common reference design was applied in our microarray hybridizations using the common reference sample described in the study of van Soest et al (2007). In summary, the common reference sample consists of aRNA from a pool of RPE/choroid isolated from 10 donor eyes (mean age 60 years). aRNA from all six donors and the common reference sample was labeled. Subsequently, labeled aRNA from the donors was hybridized against the common reference sample to six 22 k custom arrays. Initially, a dye swap experiment was performed for three of the six donor samples in order to assess potential variability introduced by dye-bias for methodological reasons (see discussion). Dye swaps were disregarded in the final analysis. Arrays were enriched for sequences expressed in RPE, neural retina and brain (Agilent Technologies, Amstelveen, The Netherlands), (see Additional file 1: Expression level and interindividual variation in all genes on the custom microarray). Hybridization, washing and scanning were performed as described previously.
In order to describe the interindividual differences in gene expression levels between all six eyes systematically, we calculated the coefficient of variation (CV), defined as the standard deviation divided by the mean (σ/μint), for each gene. We considered genes with a CV above the 90th percentile to have "high" interindividual variation in expression and genes with a CV below the 10th percentile to have "low" interindividual variation, or stable expression. Obviously, the categories for intensity and variability of expression were chosen somewhat arbitrarily, but they were essential to facilitate systematic analysis and to minimize the number of false positive results.
A functional analysis of Kegg pathways (Kyoto Encyclopedia of Genes and Genomes) was performed on genes with high, moderate and low expression levels and on genes with high and low interindividual variation using the DAVID online software. Cut off criteria used were a p-value of less than 0.001 using either a Benjamini-Hochberg correction or an Ease score, which is a modified Fisher's exact test[41, 42].
We compared our RPE transcriptome to a compilation of the mammalian retina/RPE transcriptome, which is based on multiple independent gene expression studies of combinations of the neural retina/RPE/choroid in the literature. Overlap between the two datasets was analyzed using Ingenuity Pathways Analysis (Ingenuity® Systems) resulting in a connectivity network describing the underlying biology of RPE cells at the genomic and proteomic level.
We thank Dr. L. Pels and co-workers of the Corneabank, Amsterdam, for providing donor eyes. This study was supported by grants from the Foundation Fighting Blindness (T-GE-0101-0172), The Netherlands Organization for Scientific Research (NWO; project 948-00-013), The Royal Netherlands Academy of Arts and Sciences (KNAW), de Algemene Nederlandse Vereniging ter Voorkoming van Blindheid (ANVVB) and het Edward en Marianne Blaauwfonds van het Amsterdams Universiteitsfonds.
- Strauss O: The retinal pigment epithelium in visual function. Physiol Rev. 2005, 85: 845-881. 10.1152/physrev.00021.2004.View ArticlePubMedGoogle Scholar
- van Soest S, Westerveld A, de Jong PT, Bleeker-Wagemakers EM, Bergen AA: Retinitis pigmentosa: defined from a molecular point of view. Surv Ophthalmol. 1999, 43: 321-334. 10.1016/S0039-6257(98)00046-0.View ArticlePubMedGoogle Scholar
- Hageman GS, Zhu XL, Waheed A, Sly WS: Localization of carbonic anhydrase IV in a specific capillary bed of the human eye. Proc Natl Acad Sci USA. 1991, 88: 2716-2720. 10.1073/pnas.88.7.2716.PubMed CentralView ArticlePubMedGoogle Scholar
- Sugiura M, Kono K, Liu H, Shimizugawa T, Minekura H, Spiegel S, Kohama T: Ceramide kinase, a novel lipid kinase. Molecular cloning and functional characterization. J Biol Chem. 2002, 277: 23294-23300. 10.1074/jbc.M201535200.View ArticlePubMedGoogle Scholar
- Surguchov A, Bronson JD, Banerjee P, Knowles JA, Ruiz C, Subbaraya I, Palczewski K, Baehr W: The human GCAP1 and GCAP2 genes are arranged in a tail-to-tail array on the short arm of chromosome 6 (p21.1). Genomics. 1997, 39: 312-322. 10.1006/geno.1996.4513.View ArticlePubMedGoogle Scholar
- Rice DS, Huang W, Jones HA, Hansen G, Ye GL, Xu N, Wilson EA, Troughton K, Vaddi K, Newton RC, et al: Severe retinal degeneration associated with disruption of semaphorin 4A. Invest Ophthalmol Vis Sci. 2004, 45: 2767-2777. 10.1167/iovs.04-0020.View ArticlePubMedGoogle Scholar
- Wang Q, Chen Q, Zhao K, Wang L, Wang L, Traboulsi EI: Update on the molecular genetics of retinitis pigmentosa. Ophthalmic Genet. 2001, 22: 133-154. 10.1076/opge.22.214.171.1244.View ArticlePubMedGoogle Scholar
- Ishibashi K, Tian J, Handa JT: Similarity of mRNA phenotypes of morphologically normal macular and peripheral retinal pigment epithelial cells in older human eyes. Invest Ophthalmol Vis Sci. 2004, 45: 3291-3301. 10.1167/iovs.04-0168.View ArticlePubMedGoogle Scholar
- Kociok N, Joussen AM: Varied expression of functionally important genes of RPE and choroid in the macula and in the periphery of normal human eyes. Graefes Arch Clin Exp Ophthalmol. 2007, 245: 101-113. 10.1007/s00417-006-0266-x.View ArticlePubMedGoogle Scholar
- Buraczynska M, Mears AJ, Zareparsi S, Farjo R, Filippova E, Yuan Y, MacNee SP, Hughes B, Swaroop A: Gene expression profile of native human retinal pigment epithelium. Invest Ophthalmol Vis Sci. 2002, 43: 603-607.PubMedGoogle Scholar
- Sharon D, Blackshaw S, Cepko CL, Dryja TP: Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE). Proc Natl Acad Sci USA. 2002, 99: 315-320. 10.1073/pnas.012582799.PubMed CentralView ArticlePubMedGoogle Scholar
- Bowes Rickman C, Ebright JN, Zavodni ZJ, Yu L, Wang T, Daiger SP, Wistow G, Boon K, Hauser MA: Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE. Invest Ophthalmol Vis Sci. 2006, 47: 2305-2316. 10.1167/iovs.05-1437.View ArticlePubMedGoogle Scholar
- van Soest S, de Wit GM, Essing AH, ten Brink JB, Kamphuis W, de Jong PT, Bergen AA: Comparison of human retinal pigment epithelium gene expression in macula and periphery highlights potential topographic differences in Bruch's membrane. Mol Vis. 2007, 13: 1608-1617.PubMedGoogle Scholar
- Schulz HL, Goetz T, Kaschkoetoe J, Weber BH: The Retinome – defining a reference transcriptome of the adult mammalian retina/retinal pigment epithelium. BMC Genomics. 2004, 5: 50-10.1186/1471-2164-5-50.PubMed CentralView ArticlePubMedGoogle Scholar
- Bellocchio EE, Reimer RJ, Fremeau RT, Edwards RH: Uptake of glutamate into synaptic vesicles by an inorganic phosphate transporter. Science. 2000, 289: 957-960. 10.1126/science.289.5481.957.View ArticlePubMedGoogle Scholar
- Zurdel J, Finckh U, Menzer G, Nitsch RM, Richard G: CST3 genotype associated with exudative age related macular degeneration. Br J Ophthalmol. 2002, 86: 214-219. 10.1136/bjo.86.2.214.PubMed CentralView ArticlePubMedGoogle Scholar
- Beuckmann CT, Gordon WC, Kanaoka Y, Eguchi N, Marcheselli VL, Gerashchenko DY, Urade Y, Hayaishi O, Bazan NG: Lipocalin-type prostaglandin D synthase (beta-trace) is located in pigment epithelial cells of rat retina and accumulates within interphotoreceptor matrix. J Neurosci. 1996, 16: 6119-6124.PubMedGoogle Scholar
- Wasselius J, Hakansson K, Johansson K, Abrahamson M, Ehinger B: Identification and localization of retinal cystatin C. Invest Ophthalmol Vis Sci. 2001, 42: 1901-1906.PubMedGoogle Scholar
- Ershov AV, Parkins N, Lukiw WJ, Bazan NG: Modulation of early response gene expression by prostaglandins in cultured rat retinal pigment epithelium cells. Curr Eye Res. 2000, 21: 968-974. 10.1076/ceyr.21.6.968.6987.View ArticlePubMedGoogle Scholar
- Episkopou V, Maeda S, Nishiguchi S, Shimada K, Gaitanaris GA, Gottesman ME, Robertson EJ: Disruption of the transthyretin gene results in mice with depressed levels of plasma retinol and thyroid hormone. Proc Natl Acad Sci USA. 1993, 90: 2375-2379. 10.1073/pnas.90.6.2375.PubMed CentralView ArticlePubMedGoogle Scholar
- Wu WC, Kao YH, Hu PS, Chen JH: Geldanamycin, a HSP90 inhibitor, attenuates the hypoxia-induced vascular endothelial growth factor expression in retinal pigment epithelium cells in vitro. Exp Eye Res. 2007, 85: 721-731. 10.1016/j.exer.2007.08.005.View ArticlePubMedGoogle Scholar
- Bremner I, Beattie JH: Metallothionein and the trace minerals. Annu Rev Nutr. 1990, 10: 63-83. 10.1146/annurev.nu.10.070190.000431.View ArticlePubMedGoogle Scholar
- Sablina AA, Budanov AV, Ilyinskaya GV, Agapova LS, Kravchenko JE, Chumakov PM: The antioxidant function of the p53 tumor suppressor. Nat Med. 2005, 11: 1306-1313. 10.1038/nm1320.PubMed CentralView ArticlePubMedGoogle Scholar
- Trougakos IP, Gonos ES: Clusterin/apolipoprotein J in human aging and cancer. Int J Biochem Cell Biol. 2002, 34: 1430-1448. 10.1016/S1357-2725(02)00041-9.View ArticlePubMedGoogle Scholar
- Genecards. [http://www.genecards.org/index.shtml]
- Retnet. [http://www.sph.uth.tmc.edu/Retnet/]
- Lee NH, Saeed AI: Microarrays: an overview. Methods Mol Biol. 2007, 353: 265-300.PubMedGoogle Scholar
- Dobbin K, Shih JH, Simon R: Statistical design of reverse dye microarrays. Bioinformatics. 2003, 19: 803-810. 10.1093/bioinformatics/btg076.View ArticlePubMedGoogle Scholar
- Simon RM, Dobbin K: Experimental design of DNA microarray experiments. Biotechniques. 2003, 16-21. Suppl
- Peng YW, Robishaw JD, Levine MA, Yau KW: Retinal rods and cones have distinct G protein beta and gamma subunits. Proc Natl Acad Sci USA. 1992, 89: 10882-10886. 10.1073/pnas.89.22.10882.PubMed CentralView ArticlePubMedGoogle Scholar
- Skern R, Frost P, Nilsen F: Relative transcript quantification by quantitative PCR: roughly right or precisely wrong?. BMC Mol Biol. 2005, 6: 10-10.1186/1471-2199-6-10.PubMed CentralView ArticlePubMedGoogle Scholar
- Cai J, Nelson KC, Wu M, Sternberg P, Jones DP: Oxidative damage and protection of the RPE. Prog Retin Eye Res. 2000, 19: 205-221. 10.1016/S1350-9462(99)00009-9.View ArticlePubMedGoogle Scholar
- Holtkamp GM, Kijlstra A, Peek R, de Vos AF: Retinal pigment epithelium-immune system interactions: cytokine production and cytokine-induced changes. Prog Retin Eye Res. 2001, 20: 29-48. 10.1016/S1350-9462(00)00017-3.View ArticlePubMedGoogle Scholar
- Karwatowski WS, Jeffries TE, Duance VC, Albon J, Bailey AJ, Easty DL: Preparation of Bruch's membrane and analysis of the age-related changes in the structural collagens. Br J Ophthalmol. 1995, 79: 944-952. 10.1136/bjo.79.10.944.PubMed CentralView ArticlePubMedGoogle Scholar
- Stramm LE, Haskins ME, Aguirre GD: Retinal pigment epithelial glycosaminoglycan metabolism: intracellular versus extracellular pathways. In vitro studies in normal and diseased cells. Invest Ophthalmol Vis Sci. 1989, 30: 2118-2131.PubMedGoogle Scholar
- Kliffen M, Mooy CM, Luider TM, Huijmans JG, Kerkvliet S, de Jong PT: Identification of glycosaminoglycans in age-related macular deposits. Arch Ophthalmol. 1996, 114: 1009-1014.View ArticlePubMedGoogle Scholar
- Tate DJ, Oliver PD, Miceli MV, Stern R, Shuster S, Newsome DA: Age-dependent change in the hyaluronic acid content of the human chorioretinal complex. Arch Ophthalmol. 1993, 111: 963-967.View ArticlePubMedGoogle Scholar
- Miyamoto Y, Del Monte MA: Na(+)-dependent glutamate transporter in human retinal pigment epithelial cells. Invest Ophthalmol Vis Sci. 1994, 35: 3589-3598.PubMedGoogle Scholar
- Hoshide R, Ikeda Y, Karashima S, Matsuura T, Komaki S, Kishino T, Niikawa N, Endo F, Matsuda I: Molecular cloning, tissue distribution, and chromosomal localization of human cationic amino acid transporter 2 (HCAT2). Genomics. 1996, 38: 174-178. 10.1006/geno.1996.0613.View ArticlePubMedGoogle Scholar
- Chen M, She H, Davis EM, Spicer CM, Kim L, Ren R, Le Beau MM, Li W: Identification of Nck family genes, chromosomal localization, expression, and signaling specificity. J Biol Chem. 1998, 273: 25171-25178. 10.1074/jbc.273.39.25171.View ArticlePubMedGoogle Scholar
- Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA: DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003, 4: 3-10.1186/gb-2003-4-5-p3.View ArticleGoogle Scholar
- Hosack DA, Dennis G, Sherman BT, Lane HC, Lempicki RA: Identifying biological themes within lists of genes with EASE. Genome Biol. 2003, 4: R70-10.1186/gb-2003-4-10-r70.PubMed CentralView ArticlePubMedGoogle Scholar
- Ingenuity. [http://www.ingenuity.com]