The vertebrate retina is comprised of seven major cell types that are generated in overlapping but well-defined intervals. To identify genes that might regulate retinal development, gene expression in the developing retina was profiled at multiple time points using serial analysis of gene expression (SAGE). The expression patterns of 1,051 genes that showed developmentally dynamic expression by SAGE were investigated using in situ hybridization. A molecular atlas of gene expression in the developing and mature retina was thereby constructed, along with a taxonomic classification of developmental gene expression patterns. Genes were identified that label both temporal and spatial subsets of mitotic progenitor cells. For each developing and mature major retinal cell type, genes selectively expressed in that cell type were identified. The gene expression profiles of retinal Müller glia and mitotic progenitor cells were found to be highly similar, suggesting that Müller glia might serve to produce multiple retinal cell types under the right conditions. In addition, multiple transcripts that were evolutionarily conserved that did not appear to encode open reading frames of more than 100 amino acids in length (“noncoding RNAs”) were found to be dynamically and specifically expressed in developing and mature retinal cell types. Finally, many photoreceptor-enriched genes that mapped to chromosomal intervals containing retinal disease genes were identified. These data serve as a starting point for functional investigations of the roles of these genes in retinal development and physiology.
Spatial and temporal patterns of expression for over 1000 genes in identified retinal cells invites functional investigations into the role of these genes in development and physiology
The rd1 mouse retina is a well-studied model of retinal degeneration where rod photoreceptors undergo cell death beginning at postnatal day (P) 10 until P21. This period coincides with photoreceptor terminal differentiation in a normal retina. We have used the rd1 retina as a model to investigate early molecular defects in developing rod photoreceptors prior to the onset of degeneration.
Using a microarray approach, we performed gene profiling comparing rd1 and wild type (wt) retinas at four time points starting at P2, prior to any obvious biochemical or morphological differences, and concluding at P8, prior to the initiation of cell death. Of the 143 identified differentially expressed genes, we focused on Rab acceptor 1 (Rabac1), which codes for the protein Prenylated rab acceptor 1 (PRA1) and plays an important role in vesicular trafficking. Quantitative RT-PCR analysis confirmed reduced expression of PRA1 in rd1 retina at all time points examined. Immunohistochemical observation showed that PRA1-like immunoreactivity (LIR) co-localized with the cis-Golgi marker GM-130 in the photoreceptor as the Golgi translocated from the perikarya to the inner segment during photoreceptor differentiation in wt retinas. Diffuse PRA1-LIR, distinct from the Golgi marker, was seen in the distal inner segment of wt photoreceptors starting at P8. Both plexiform layers contained PRA1 positive punctae independent of GM-130 staining during postnatal development. In the inner retina, PRA1-LIR also colocalized with the Golgi marker in the perinuclear region of most cells. A similar pattern was seen in the rd1 mouse inner retina. However, punctate and significantly reduced PRA1-LIR was present throughout the developing rd1 inner segment, consistent with delayed photoreceptor development and abnormalities in Golgi sorting and vesicular trafficking.
We have identified genes that are differentially regulated in the rd1 retina at early time points, which may give insights into developmental defects that precede photoreceptor cell death. This is the first report of PRA1 expression in the retina. Our data support the hypothesis that PRA1 plays an important role in vesicular trafficking between the Golgi and cilia in differentiating and mature rod photoreceptors.
Retina; Photoreceptor; Mouse; Retinal degeneration; Photoreceptor development; Rabac1; Prenylated Rab Acceptor 1; Rab6; Vesicular trafficking
Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seed-network of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development.
Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina.
We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses.
In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors.
This report presents an analysis of the retinal gene expression profile in a transgenic strain of zebrafish that experiences a continuous cycle of rod photoreceptor development and regeneration.
XOPS-mCFP transgenic zebrafish experience a continual cycle of rod photoreceptor development and degeneration throughout life, making them a useful model for investigating the molecular determinants of rod photoreceptor regeneration. The purpose of this study was to compare the gene expression profiles of wild-type and XOPS-mCFP retinas and identify genes that may contribute to the regeneration of the rods.
Adult wild-type and XOPS-mCFP retinal mRNA was subjected to microarray analysis. Pathway analysis was used to identify biologically relevant processes that were significantly represented in the dataset. Expression changes were verified by RT-PCR. Selected genes were further examined during retinal development and in adult retinas by in situ hybridization and immunohistochemistry and in a transgenic fluorescent reporter line.
More than 600 genes displayed significant expression changes in XOPS-mCFP retinas compared with expression in wild-type controls. Many of the downregulated genes were associated with phototransduction, whereas upregulated genes were associated with several biological functions, including cell cycle, DNA replication and repair, and cell development and death. RT-PCR analysis of a subset of these genes confirmed the microarray results. Three transcription factors (sox11b, insm1a, and c-myb), displaying increased expression in XOPS-mCFP retinas, were also expressed throughout retinal development and in the persistently neurogenic ciliary marginal zone.
This study identified numerous gene expression changes in response to rod degeneration in zebrafish and further suggests a role for the transcriptional regulators sox11b, insm1a, and c-myb in both retinal development and rod photoreceptor regeneration.
The mammalian retina is a tractable model system for analyzing transcriptional networks that guide neural development. Spalt family zinc-finger transcription factors play a crucial role in photoreceptor specification in Drosophila, but their role in mammalian retinal development has not been investigated. In this study, we show that that the spalt homolog Sall3 is prominently expressed in developing cone photoreceptors and horizontal interneurons of the mouse retina and in a subset of cone bipolar cells. We find that Sall3 is both necessary and sufficient to activate the expression of multiple cone-specific genes, and that Sall3 protein is selectively bound to the promoter regions of these genes. Notably, Sall3 shows more prominent expression in short wavelength-sensitive cones than in medium wavelength-sensitive cones, and that Sall3 selectively activates expression of the short but not the medium wavelength-sensitive cone opsin gene. We further observe that Sall3 regulates the differentiation of horizontal interneurons, which form direct synaptic contacts with cone photoreceptors. Loss of function of Sall3 eliminates expression of the horizontal cell-specific transcription factor Lhx1, resulting in a radial displacement of horizontal cells that partially phenocopies the loss of function of Lhx1. These findings not only demonstrate that Spalt family transcription factors play a conserved role in regulating photoreceptor development in insects and mammals, but also identify Sall3 as a factor that regulates terminal differentiation of both cone photoreceptors and their postsynaptic partners.
Cell fate; Evolution; Neural development; Photoreceptor; Transcription factor; Mouse
To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE).
Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR.
Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified.
The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.
Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data.
Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE), this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model) performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re-sampling techniques were studied. A random over-sampling method supported the implementation of the most powerful prediction models. The KStar model was also able to achieve higher predictive sensitivities and specificities using random over-sampling techniques.
The approaches assessed in this paper represent an efficient and relatively inexpensive in silico methodology for supporting large-scale analysis of photoreceptor gene expression by SAGE. They may be applied as complementary methodologies to support functional predictions before implementing more comprehensive, experimental prediction and validation methods. They may also be combined with other large-scale, data-driven methods to facilitate the inference of transcriptional regulatory networks in the developing retina. Furthermore, the methodology assessed may be applied to other data domains.
Photoreceptors in the vertebrate retina are light-sensitive neurons, and their degeneration results in irreversible visual loss. Understanding how photoreceptor fate is determined is a prerequisite for developing photoreceptor replacement therapies. Previous studies identified two basic helix-loop-helix genes, neurogenin2 (ngn2) and neuroD, participating in a genetic pathway leading to photoreceptor genesis. Here we present experimental data suggesting that ath5, which is known for its critical role in retinal ganglion cell development, may also lead to photoreceptor production. In the developing retina, ath5 expression was detected in two zones of cells, and coexpression with neuroD was observed in the zone adjacent to young photoreceptor cells accumulating on the retinal pigment epithelial side. Retroviral-driven misexpression of ath5 in retinal cells increased the population of photoreceptor cells, as well as ganglion cells, in a developmental stage-dependent manner that is consistent with ath5 being involved in the development of multiple types of retinal neurons. Ectopic ath5 expression in cultures of non-neural retinal pigment epithelial cells elicited transdifferentiation into cells that expressed photoreceptor-specific genes and displayed photoreceptor-like morphologies. Gene expression analysis showed that ngn2 did not induce ath5, and ath5 did not induce ngn2, but both induced neuroD and RaxL. These data suggest a pathway of “ath5 → neuroD → photoreceptor genes” separate from yet convergent with the ngn2 pathway.
gene; transcription; differentiation; regeneration; photoreceptor; retina
Identification of tissue-specific gene regulatory networks can yield insights into the molecular basis of a tissue's development, function and pathology. Here, we present a computational approach designed to identify potential regulatory target genes of photoreceptor cell-specific transcription factors (TFs). The approach is based on the hypothesis that genes related to the retina in terms of expression, disease and/or function are more likely to be the targets of retina-specific TFs than other genes. A list of genes that are preferentially expressed in retina was obtained by integrating expressed sequence tag, SAGE and microarray datasets. The regulatory targets of retina-specific TFs are enriched in this set of retina-related genes. A Bayesian approach was employed to integrate information about binding site location relative to a gene's transcription start site. Our method was applied to three retina-specific TFs, CRX, NRL and NR2E3, and a number of potential targets were predicted. To experimentally assess the validity of the bioinformatic predictions, mobility shift, transient transfection and chromatin immunoprecipitation assays were performed with five predicted CRX targets, and the results were suggestive of CRX regulation in 5/5, 3/5 and 4/5 cases, respectively. Together, these experiments strongly suggest that RP1, GUCY2D, ABCA4 are novel targets of CRX.
The majority of diseases in the retina are caused by genetic mutations affecting the development and function of photoreceptor cells. The transcriptional networks directing these processes are regulated by genes such as nuclear hormone receptors. The nuclear hormone receptor gene Rev-erb alpha/Nr1d1 has been widely studied for its role in the circadian cycle and cell metabolism, however its role in the retina is unknown. In order to understand the role of Rev-erb alpha/Nr1d1 in the retina, we evaluated the effects of loss of Nr1d1 to the developing retina and its co-regulation with the photoreceptor-specific nuclear receptor gene Nr2e3 in the developing and mature retina. Knock-down of Nr1d1 expression in the developing retina results in pan-retinal spotting and reduced retinal function by electroretinogram. Our studies show that NR1D1 protein is co-expressed with NR2E3 in the outer neuroblastic layer of the developing mouse retina. In the adult retina, NR1D1 is expressed in the ganglion cell layer and is co-expressed with NR2E3 in the outer nuclear layer, within rods and cones. Several genes co-targeted by NR2E3 and NR1D1 were identified that include: Nr2c1, Recoverin, Rgr, Rarres2, Pde8a, and Nupr1. We examined the cyclic expression of Nr1d1 and Nr2e3 over a twenty-four hour period and observed that both nuclear receptors cycle in a similar manner. Taken together, these studies reveal a novel role for Nr1d1, in conjunction with its cofactor Nr2e3, in regulating transcriptional networks critical for photoreceptor development and function.
Animals have evolved specialized photoreceptors in the retina and in extraocular tissues that allow them to measure light changes in their environment. In mammals, the retina is the only structure that detects light and relays this information to the brain. The classical photoreceptors, rods and cones, are responsible for vision through activation of rhodopsin and cone opsins. Melanopsin, another photopigment first discovered in Xenopus melanophores (Opn4x), is expressed in a small subset of retinal ganglion cells (RGCs) in the mammalian retina, where it mediates non-image forming functions such as circadian photoentrainment and sleep. While mammals have a single melanopsin gene (opn4), zebrafish show remarkable diversity with two opn4x-related and three opn4-related genes expressed in distinct patterns in multiple neuronal cell types of the developing retina, including bipolar interneurons. The intronless opn4.1 gene is transcribed in photoreceptors as well as in horizontal cells and produces functional photopigment. Four genes are also expressed in the zebrafish embryonic brain, but not in the photoreceptive pineal gland. We discovered that photoperiod length influences expression of two of the opn4-related genes in retinal layers involved in signaling light information to RGCs. Moreover, both genes are expressed in a robust diurnal rhythm but with different phases in relation to the light-dark cycle. The results suggest that melanopsin has an expanded role in modulating the retinal circuitry of fish.
Retinal neuron degeneration and survival are often regulated by the same trophic factors that are required for embryonic development and are usually expressed in multiple cell-types. Therefore, the conditional gene targeting approach is necessary to investigate the cell-specific function of widely expressed and developmentally regulated genes in retinal degeneration. The discussion in this review will be focused on the use of Cre/lox-based conditional gene targeting approach in mechanistic studies for retinal degeneration. In addition to the basic experimental designs, this article addresses various factors influencing the outcomes of conditional gene targeting studies, limitations of current technologies, availability of Cre-drive lines for various retinal cells, and issues related to the generation of Cre-expressing mice. Finally, this review will update the current status on the use of Cre/lox-based gene targeting approach in mechanistic studies for retinal degeneration, which includes rod photoreceptor survival under photo-oxidative stress and protein trafficking in photoreceptors.
We previously reported that Otx2 is essential for photoreceptor cell fate determination; however, the functional role of Otx2 in postnatal retinal development is still unclear although it has been reported to be expressed in retinal bipolar cells and photoreceptors at postnatal stages. In this study, we first examined the roles of Otx2 in the terminal differentiation of photoreceptors by analyzing Otx2; Crx double-knockout mice. In Otx2+/−; Crx−/− retinas, photoreceptor degeneration and downregulation of photoreceptor-specific genes were much more prominent than in Crx−/− retinas, suggesting that Otx2 has a role in the terminal differentiation of the photoreceptors. Moreover, bipolar cells decreased in the Otx2+/−; Crx−/− retina, suggesting that Otx2 is also involved in retinal bipolar-cell development. To further investigate the role of Otx2 in bipolar-cell development, we generated a postnatal bipolar-cell-specific Otx2 conditional-knockout mouse line. Immunohistochemical analysis of this line showed that the expression of protein kinase C, a marker of mature bipolar cells, was significantly downregulated in the retina. Electroretinograms revealed that the electrophysiological function of retinal bipolar cells was impaired as a result of Otx2 ablation. These data suggest that Otx2 plays a functional role in the maturation of retinal photoreceptor and bipolar cells.
Retinitis pigmentosa (RP) is a progressive retinal degeneration in which the retina loses nearly all of its photoreceptor cells and undergoes major structural changes. Little is known regarding the role the resident glia, the Müller glia, play in the progression of the disease. In this article, we define gene expression changes in Müller glial cells (MGCs) from two different mouse models of RP, the retinal degeneration 1 (rd1) and rhodopsin knockout (Rhod-ko) models. The RNA repertoire of single MGCs was comprehensively profiled, and a comparison was made between MGCs from wild-type (WT) and mutant retinas. Two time points were chosen for analysis, one at the peak of rod photoreceptor death and one during the period of cone photoreceptor death.
Retinas were dissociated, and single MGCs were chosen under a dissecting microscope using a micropipette. Single cell cDNAs were generated and genome-wide profiles were obtained by hybridization to Affymetrix arrays. A comparison was made among all samples to discover the changes in gene expression during the periods of rod and cone photoreceptor death.
MGCs respond to retinal degeneration by undergoing gliosis, a process marked by the upregulation of glial fibrillary acidic protein (Gfap). Many additional transcripts were found to change. These can be placed into functional clusters, such as retinal remodeling, stress response, and immune-related response.
A high degree of heterogeneity among the individual cells was observed, possibly due to their different spatial proximities to dying cells and/or inherent heterogeneity among MGCs.
The photoreceptor cells of the retina are subject to a greater number of genetic diseases than any other cell type in the human body. The majority of more than 120 cloned human blindness genes are highly expressed in photoreceptors. In order to establish an integrative framework in which to understand these diseases, we have undertaken an experimental and computational analysis of the network controlled by the mammalian photoreceptor transcription factors, Crx, Nrl, and Nr2e3. Using microarray and in situ hybridization datasets we have produced a model of this network which contains over 600 genes, including numerous retinal disease loci as well as previously uncharacterized photoreceptor transcription factors. To elucidate the connectivity of this network, we devised a computational algorithm to identify the photoreceptor-specific cis-regulatory elements (CREs) mediating the interactions between these transcription factors and their target genes. In vivo validation of our computational predictions resulted in the discovery of 19 novel photoreceptor-specific CREs near retinal disease genes. Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression. To test the generality of this rule, we used an expanded form of it as a selection filter to evolve photoreceptor CREs from random DNA sequences in silico. When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo. This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.
Development of therapies to treat visual system dystrophies resulting from the degeneration of rod and cone photoreceptors may directly benefit from studies of animal models, such as the zebrafish, that display continuous retinal neurogenesis and the capacity for injury-induced regeneration. Previous studies of retinal regeneration in fish have been conducted on adult animals and have relied on methods that cause acute damage to both rods and cones, as well as other retinal cell types. We report here the use of a genetic approach to study progenitor cell responses to photoreceptor degeneration in the larval and adult zebrafish retina. We have compared the responses to selective rod or cone degeneration using, respectively, the XOPS-mCFP transgenic line and zebrafish with a null mutation in the pde6c gene. Notably, rod degeneration induces increased proliferation of progenitors in the outer nuclear layer (ONL) and is not associated with proliferation or reactive gliosis in the inner nuclear layer (INL). Molecular characterization of the rod progenitor cells demonstrated that they are committed to the rod photoreceptor fate while they are still mitotic. In contrast, cone degeneration induces both Müller cell proliferation and reactive gliosis, with little change in proliferation in the ONL. We found that in both lines, proliferative responses to photoreceptor degeneration can be observed as 7 days post fertilization (dpf). These two genetic models therefore offer new opportunities for investigating the molecular mechanisms of selective degeneration and regeneration of rods and cones.
genetics; zebrafish; retina; photoreceptors; regeneration
Degeneration of the neural retina is the leading cause of untreatable blindness in the developed world. Stem cell replacement therapy offers a novel strategy for retinal repair. Postmitotic photoreceptor precursors derived from the early postnatal (P) retina are able to migrate and integrate into the adult mouse retina following transplantation into the subretinal space, but it is likely that a large number of these cells would be required to restore vision. The adult recipient retina presents a very different environment to that from which photoreceptor precursor donor cells isolated from the developing postnatal retina are derived. Here we considered the possibility that modulation of the recipient environment by ectopic expression of developmentally regulated growth factors, normally present during photoreceptor development, might enhance the migration and integration of transplanted cells into the adult neural retina. Adeno-associated viral (AAV) vectors were used to introduce three growth factors previously reported to play a role in photoreceptor development, IGF1, FGF2, and CNTF, into the adult retina, prior to transplantation of P4 cells derived from the Nrl.GFP+ve neural retina. At 3 weeks posttransplantation the number of integrated, differentiated photoreceptor cells present in AAV-mediated neurotrophic factor-treated eyes was assessed and compared to control treated contralateral eyes. We show, firstly, that it is possible to manipulate the recipient retinal microenvironment via rAAV-mediated gene transfer with respect to these developmentally relevant growth factors. Moreover, when combined with cell transplantation, AAV-mediated expression of IGF1 led to significantly increased levels of cell integration, while overexpression of FGF2 had no significant effect on integrated cell number. Conversely, expression of CNTF led to a significant decrease in cell integration and an exacerbated glial response that led to glial scarring. Together, these findings demonstrate the importance of the extrinsic environment of the recipient retina for photoreceptor cell transplantation and show for the first time that it is possible to manipulate this environment using viral vectors to influence photoreceptor transplantation efficiency.
Photoreceptor; Retina; Transplantation; Neurotrophic factors; Gene therapy; Stem cell
The mammalian retina is a valuable model system to study neuronal biology in health and disease. To obtain insight into intrinsic processes of the retina, great efforts are directed towards the identification and characterization of transcripts with functional relevance to this tissue.
With the goal to assemble a first genome-wide reference transcriptome of the adult mammalian retina, referred to as the retinome, we have extracted 13,037 non-redundant annotated genes from nearly 500,000 published datasets on redundant retina/retinal pigment epithelium (RPE) transcripts. The data were generated from 27 independent studies employing a wide range of molecular and biocomputational approaches. Comparison to known retina-/RPE-specific pathways and established retinal gene networks suggest that the reference retinome may represent up to 90% of the retinal transcripts. We show that the distribution of retinal genes along the chromosomes is not random but exhibits a higher order organization closely following the previously observed clustering of genes with increased expression.
The genome wide retinome map offers a rational basis for selecting suggestive candidate genes for hereditary as well as complex retinal diseases facilitating elaborate studies into normal and pathological pathways. To make this unique resource freely available we have built a database providing a query interface to the reference retinome .
Purpose. Transplantation of stem, progenitor, or precursor cells has resulted in photoreceptor replacement and evidence of functional efficacy in rodent models of retinal degeneration. Ongoing work has been directed toward the replication of these results in a large animal model, namely, the pig. Methods. Retinal progenitor cells were derived from the neural retina of GFP-transgenic pigs and transplanted to the subretinal space of rhodopsin Pro347Leu-transgenic allorecipients, in the early stage of the degeneration and the absence of immune suppression. Results. Results confirm the survival of allogeneic porcine RPCs without immune suppression in the setting of photoreceptor dystrophy. The expression of multiple photoreceptor markers by grafted cells included the rod outer segment-specific marker ROM-1. Further evidence of photoreceptor differentiation included the presence of numerous photoreceptor rosettes within GFP-positive grafts, indicative of the development of cellular polarity and self-assembly into rudiments of outer retinal tissue. Conclusion. Together, these data support the tolerance of RPCs as allografts and demonstrate the high level of rod photoreceptor development that can be obtained from cultured RPCs following transplantation. Strategies for further progress in this area, together with possible functional implications, are discussed.
Midkine is a small heparin binding growth factor expressed in numerous tissues during development. The unique midkine gene in mammals has two paralogs in zebrafish: midkine-a (mdka) and midkine-b (mdkb). In the zebrafish retina, during both larval development and adult photoreceptor regeneration, mdka is expressed in retinal stem and progenitor cells and functions as a molecular component of the retina’s stem cell niche. In this study, loss-of-function and conditional overexpression were used to investigate the function of Mdka in the retina of the embryonic zebrafish.
The results show that during early retinal development Mdka functions to regulate cell cycle kinetics. Following targeted knockdown of Mdka synthesis, retinal progenitors cycle more slowly, and this results in microphthalmia, a diminished rate of cell cycle exit and a temporal delay of cell cycle exit and neuronal differentiation. In contrast, Mdka overexpression results in acceleration of the cell cycle and retinal overgrowth. Mdka gain-of-function, however, does not temporally advance cell cycle exit. Experiments to identify a potential Mdka signaling pathway show that Mdka functions upstream of the HLH regulatory protein, Id2a. Gene expression analysis shows Mdka regulates id2a expression, and co-injection of Mdka morpholinos and id2a mRNA rescues the Mdka loss-of-function phenotype.
These data show that in zebrafish, Mdka resides in a shared Id2a pathway to regulate cell cycle kinetics in retinal progenitors. This is the first study to demonstrate the function of Midkine during retinal development and adds Midkine to the list of growth factors that transcriptionally regulate Id proteins.
Proliferation; Growth factors; Signaling pathways
We collected a massive and heterogeneous dataset of 20 255 gene expression profiles (GEPs) from a variety of human samples and experimental conditions, as well as 8895 GEPs from mouse samples. We developed a mutual information (MI) reverse-engineering approach to quantify the extent to which the mRNA levels of two genes are related to each other across the dataset. The resulting networks consist of 4 817 629 connections among 20 255 transcripts in human and 14 461 095 connections among 45 101 transcripts in mouse, with a inter-species conservation of 12%. The inferred connections were compared against known interactions to assess their biological significance. We experimentally validated a subset of not previously described protein–protein interactions. We discovered co-expressed modules within the networks, consisting of genes strongly connected to each other, which carry out specific biological functions, and tend to be in physical proximity at the chromatin level in the nucleus. We show that the network can be used to predict the biological function and subcellular localization of a protein, and to elucidate the function of a disease gene. We experimentally verified that granulin precursor (GRN) gene, whose mutations cause frontotemporal lobar degeneration, is involved in lysosome function. We have developed an online tool to explore the human and mouse gene networks.
Transgenic labels that allow the visualization of specific populations of neurons have proven to be powerful tools for research. Further developing such resources to label additional cell types and specific organelles within these cell will provide additional experimental opportunities.
The retinal expression profile of a mitochondria-localized yellow fluorescent protein (YFP) in each of three transgenic mouse lines was determined. Each line, Mito-R, Mito-Y and Mito-Z, expresses YFP in distinct and reproducible populations of retinal neurons. In the Mito-R line, YFP is expressed in most or all retinal ganglion cells (RGCs) and photoreceptors making this line useful for studying axonal transport in diseases such as glaucoma and photoreceptor degeneration related to transport of mitochondria into the inner segments. In the Mito-Y line, YFP is expressed in many cell types in the dorsal retina and in a rough mosaic population of RGCs in the rest of the retina, making this line useful for study of how retinal mosaics are organized. In the Mito-Z line, YFP is expressed in a subset of RGCs, amacrine cells, bipolar cells and photoreceptors. The Mito-Z line is inserted on the X-Chromosome, resulting in X-inactivation mosaicism in female mice carrying a single copy of the transgene. In the female hemizygous retina, expression is present in distinct clonal columns, making this transgenic line useful for analysis of clonal proliferation and lateral migration of retinal neurons.
The retinal expression profiles of three transgenic mouse lines that express a mitochondrially localized YFP were characterized in this study. These lines will allow researchers to isolate and identify cell types within the retina and to study retinal mitochondrial trafficking and disease.
Innate immunity plays a role in many diseases, including glaucoma and AMD. We have used transcriptome profiling in the mouse to identify a network of genes involved in innate immunity that is present in the normal retina and that is activated by optic nerve crush (ONC).
Using a recombinant inbred (RI) mouse strain set (BXD, C57BL/6 crossed with DBA/2J mice), we generate expression datasets (Illumina WG 6.2 arrays) in the normal mouse retina and 2 days after ONC. The normal dataset is constructed from retinas from 80 mouse strains and the ONC dataset is constructed from 62 strains. These large datasets are hosted by GeneNetwork.org, along with a series of powerful bioinformatic tools.
In the retina datasets, one intriguing network involves transcripts associated with the innate immunity. Using C4b to interrogate the normal dataset, we can identify a group of genes that are coregulated across the BXD RI strains. Many of the genes in this network are associated with the innate immune system, including Serping1, Casp1, C3, Icam1, Tgfbr2, Cfi, Clu, C1qg, Aif1, and Cd74. Following ONC, the expression of these genes is upregulated, along with an increase in coordinated expression across the BXD strains. Many of the genes in this network are risk factors for AMD, including C3, EFEMP1, MCDR2, CFB, TLR4, HTA1, and C1QTNF5.
We found a retina-intrinsic innate immunity network that is activated by injury including ONC. Many of the genes in this network are risk factors for retinal disease.
An intrinsic innate immune network was identified in the mouse retina. This network is activated by injury and mutations in members of this network result in disease, including AMD.
innate immunity; genetic networks; retinal injury
Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.
To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.
We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (Simple Expression Ranking). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the Heat Kernel Diffusion Ranking leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.
In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.