Project description:Rod and cone photoreceptors in mammalian retina are generated from common pool(s) of neuroepithelial progenitors. NRL, CRX and NR2E3 are key transcriptional regulators that control photoreceptor differentiation. Mutations in NR2E3, a rod-specific orphan nuclear receptor, lead to loss of rods, increased density of S-cones, and supernormal S-cone-mediated vision in humans. To better understand its in vivo function, NR2E3 was expressed ectopically in the Nrl-/- retina, where post-mitotic precursors fated to be rods develop into functional S-cones similar to the human NR2E3 disease. Expression of NR2E3 in the Nrl-/- retina completely suppressed cone differentiation and resulted in morphologically rod-like photoreceptors, which were not functional. Gene profiling of FACS-purified photoreceptors confirmed the role of NR2E3 as a strong suppressor of cone genes and an activator of a subset of rod genes (including rhodopsin) in vivo. Ectopic expression of NR2E3 in cone precursors and differentiating S-cones of wild type retina also generates rod-like cells. The dual regulatory function of NR2E3 is not dependent upon the presence of NRL and/or CRX, but on the timing and level of its expression. Our studies reveal a critical role of NR2E3 in establishing functional specificity of post-mitotic photoreceptor precursors during retinal neurogenesis. Experiment Overall Design: We mated the Crx::Nr2e3/Nrlko mice with the Nrl::GFP transgenic mice, in which the expression of GFP is driven by an Nrl promoter. Mouse retinas were dissected at 4 wk. GFP+ photoreceptors were enriched by FACS (FACSAria, BD Biosciences, Franklin Lakes, NJ). RNA was extracted from 1~5x105 flow-sorted cells using Trizol (Invitrogen). Total RNA (40-60 ng) was used for linear amplification with Ovation Biotin labeling system (Nugen), and 2.75 ug of biotin-labeled fragmented cDNA was hybridized to mouse GeneChips MOE430.2.0 (Affymetrix) having 45,101 probesets (corresponding to over 39,000 transcripts, and 34,000 annotated mouse genes). Experiment Overall Design: Four independent samples were used at 4 weeks. We normalized Experiment Overall Design: Crx::Nr2e3/Nrl-ko-Gfp data along with Nrl-ko-Gfp 4 weeks samples ( 4 replicates, refer to Series submission GSE4051). The normalized data was then subjected to two stage analysis based on False Discovery Rate Confidence Interval (FDR-CI) for screening differentially expressed genes (24, 27) with a minimum fold change of 4.

Project description:Cone photoreceptors are specialised sensory retinal neurons responsible for photopic vision, colour perception and visual acuity. Retinal degenerative diseases are a heterogeneous group of eye diseases in which the most severe vision loss typically arises from cone photoreceptor dysfunction or degeneration. Establishing a method to purify cone photoreceptors from retinal tissue can accelerate the identification of key molecular determinants that underlie cone photoreceptor development, survival and function. The work herein describes a new method to purify enhanced green fluorescent protein (EGFP)-labelled cone photoreceptors from adult retina of Tg(3.2TαCP:EGFP) zebrafish. Electropherograms confirmed downstream isolation of high-quality RNA with RNA integrity number (RIN) >7.6 and RNA concentration >5.7 ng/µl obtained from both populations. Reverse Transcriptase-PCR (RT-PCR) confirmed that the EGFP-positive cell populations express known genetic markers of cone photoreceptors that were not expressed in the EGFP-negative cell population. This work is an important step towards the identification of cone photoreceptor-enriched genes, protein and signalling networks responsible for their development, survival and function. In addition, this advancement facilitates the identification of novel candidate genes for inherited human blindness. In order to analyse and sort samples by flow cytometry, values for FSC and SSC were displayed in a logarithmic scale, as this is normally the default starting display. This allowed for the identification of different sub-populations of cells present in the retina, which were mixed with unwanted cell debris and cell fragments. Since there were multiple cell populations, different levels of auto-fluorescence were thus successfully detected. It was therefore important to change the strategy and display side scatter and fluorescence characteristics of control and EGFP samples, which ultimately allowed the identification of the extremely well-defined population of EGFP-cone photoreceptors. This improved sorting process minimised RNA degradation. The purified EGFP+ cone photoreceptors represent ~5% of the original dissociated population, which is consistent with humans, wherein the total number of cones (6 million) in the retina is approximately 20 times the one of rods (120 million) (Williamson and Cummins 1983). This work allows high-quality RNA to be obtained from sorted-adult cone photoreceptors. RNA integrity is assessed via 28S and 18S rRNA (Imbeaud et al 2005), and our electropherogram results demonstrate production of high-quality RNA with two clearly visible ribosomal peaks (28S and 18S) from EGFP-sorted cones. In addition, the RNA Integrity Number (RIN), an algorithm for assigning integrity values to RNA based on 28S to 18S rRNA ratios (Sambrook et al 1989; Imbeaud et al 2005; Schroeder et al 2006), had a value of 7.6, higher than the minimum-required 7.0. RNA yields of 5.7 ng/µl were relatively high and sufficient for downstream profiling. RT-PCR confirmed expression of the cone specific gene gnat2, and promoter fragment TαC, but not the retinal pigment epithelium specific gene rpe65 in flow cytometry-sorted GFP-positive photoreceptors (GFP+ cells). rpe65 was neither present in flow cytometry-sorted GFP-negative cones (GFP- cells) as this gene is only expressed in the retinal pigment epithelium (RPE). This study therefore permits the identification of cone photoreceptor-enriched genes, protein and signalling networks responsible for their development, survival and function. In addition, this advancement facilitates the identification of novel candidate genes for inherited human blindness.

Project description:Brain circuits are assembled from a large variety of morphologically and functionally diverse cell types. It is not known how the intermingled cell types of individual brain regions differ in their expressed genomes. Here we describe an atlas of cell type transcriptomes of the adult retina. We found that each adult cell type expresses a specific set of genes, including a unique set of transcription factors, forming a “barcode” for cell identity. Cell type transcriptomes carry enough information to categorize cells into corresponding morphological classes and types. Surprisingly, several barcode genes are eye disease-associated genes that we demonstrate to be specifically expressed not only in photoreceptors but also in particular retinal circuit elements such as inhibitory neurons as well as in retinal microglia. Our data suggest that distinct cell types of individual brain regions are characterized by marked differences in their expressed genomes. To test whether amplifications were linear, we examined the relationship between gene expression values and the amounts of RNA in a cell group. We pooled together two retinas from the Chrnb4-GFP (cone) and six retinas from the ChAT-Cre × Rosa26-LSL-RFP (starburst amacrine cell) mouse lines. Five mixtures of GFP:RFP cells (“titration mixtures”) were then FACS-sorted with the following cone-starburst compositions: 0:200, 50:150, 100:100, 150:50 and 200:0. The total number of cells in each mixture was 200. Five mixtures from different mice were sorted 3 times to give biological triplicates. Next 20 genes with the highest specificity ratio for cones and another 20 for starburst cells were chosen and linear curves were fitted to the data pairs of expression value:cone number or expression value:starburst cell number. For both cone- and starburst-enriched genes, gene expression values increased linearly with an increase in the number of cones or starburst cells in the mixtures. The linear correlation coefficients were independent of the extent to which genes were expressed in the pure cone and starburst cell groups. This suggests that A practical use of the finding that amplification is linear is to separate the transcriptome of a cell group that contains cells from different types into its cell-type components. Assuming, for example, a cell group (Group A) containing a mixture of two cell types, Type 1 and Type 2, as well as a futher cell group (Group B) containing only Type 1 (Supplementary Figure 10). We wish to determine the transcriptome of Type 2 but we have no cell group (Group C) that contains Type 2 only. Or more generally, assume a cell group (Group A) containing a mixture of cell types, Type 1, Type 2…Type N, as well as a further cell group (Group B) containing only Type 1. We wish to determine the mixed transcriptome of Group C that contains Type 2….Type N, without Type 1. This separation of cell-type transcriptomes is useful for two reasons. First, ~80% of mouse retinal cells are rods30 and it is expected that transcripts from rods will be present in the solution after retina dissociation, leading to rod contamination of the transcriptome of each cell group. We wished to eliminate rod contamination. Second, we found that cones in some mouse lines are labeled together with a type of amacrine cell and we needed to determine the amacrine cell transcriptome alone. Due to linearity, the following procedure can be used to separate Type 1 from the rest of the cell types in a mixture (Group A). A set of cell type-specific genes for Type 1 is determined. This may be known a priori or from the dataset itself. The ratio of the expression value in Group A to the expression value in Group B is calculated for each Type 1-specific gene. The mean ratio is the estimate of the number of Type 1 cells in Group A. Next, the transcriptome (the expression values of all genes, which we treat as a vector) of Group B is multiplied by the mean ratio and the result is subtracted from the transcriptome of Group A. All negative numbers are then removed from this “unmixed” transcriptome by setting them to zero followed by normalization with the Group B (Type 1) transcriptome using quantile normalization. The quantile normalized “unmixed” transcriptome forms the prediction of the transcriptome of Group C. Note that if Group A contains only two cell types, Type 1 and Type 2, then the transcriptome of Group C is the transcriptome of Type 2 cells. We have demonstrated and quantitatively evaluated this procedure for the cone:starburst mixtures described above. In addition to the titration mixtures, we also made three “test mixtures” consisting the following cone:starburst cell numbers: 157:43, 75:125 and 183:17. Cones served as the Type 1 cells and starburst cells as Type 2. In our experiment, we had one pure cone group (200:0) and one pure starburst cell group (0:200) as well as six mixtures (50:150, 100:100, 150:50, 157:43, 75:125 and 183:17. First, we predicted the mixture composition using different numbers of cone-specific genes. Since we chose 20 cone-specific genes, the use of single genes presents 20 possible ways of predicting the number of cones in the mixture. Using two genes for the prediction provides 190 possible ways of predicting the number of cones in the mixture. The number of possible predictions when using k genes is: 20!/((20-k)! k!). When more than one gene is used for the prediction, the prediction is the mean of the individual gene-based predictions. Error was calculated as the mean of the absolute values of the deviation from the cone cell numbers in the mixtures. The mean and standard deviation of the prediction error decrease with the use of increasing number of genes. With 10 genes used for the prediction, for example, the prediction error will be approximately 12±3% (s.d.), regardless of which 10 genes are chosen, as long as they are cell type-specific. We pooled together two adult retinas from the Chrnb4-GFP (cone) and six adult retinas from the ChAT-Cre × Rosa26-LSL-RFP (starburst amacrine cell) mouse lines. Five mixtures of GFP:RFP cells (“titration mixtures”) were then FACS-sorted with the following cone-starburst compositions: ChAT.200: cone 0, ChAT.150: cone 50, ChAT.100: cone 100, ChAT.50 : cone 150, ChAT.0: cone 200. The total number of cells in each mixture was 200. Five mixtures from different mice were sorted 3 times to give biological triplicates (indicated by _1, _2, _3). X1, X2 and X3 stand for the following ratios: X1: ChAT.43 : cone 157, ChAT.125 : cone 75, ChAT.17 : cone 183. Arc represents as internal batch control to compare with other gene arrays within our dataset.

Project description:The loss of cone photoreceptor cells, which are critical for optimal daylight vision, have the great impact on vision during retinal degenerations. Retinal differentiation of human induced pluripotent stem cell (hiPSC) sources could provide a renewable source of cone photoreceptors towards developing a cone cell replacement therapy to treat blindness. Demonstration of comparable gene expression profiles between human foetal and stem cell-derived cones at equivalent stages is required to progress the cell transplantation approach into the patient, as it is hypothesised stem cell-derived cones are required to show high levels of developmental recapitulation of the in vivo generated cones. In this study, the AAV2/9.pR2.1.GFP reporter was used to specifically label L/M-opsin cone photoreceptors in human foetal retinal samples, obtained from the MRC-Wellcome Trust Human Developmental Biology Resource, at a range of developmental stages. The L/M-opsin cone population represent the majority cone cell types in the adult human retina and are the only photoreceptors present within the fovea. Using fluorescence activated cell sorting, L/M-opsin GFP+ cones and GFP- retinal populations, alongside total foetal retinal samples containing all retinal cell tytpes, were isolated and processed for bulk RNA sequencing and downstream comparative analysis. Using DESeq2 differential gene expression analyses, statistically significant genes enriched within the GFP+ human foetal LM-opsin cone populations were determined which led to the identification of a cone enriched gene signature of human L/M-opsin cone photoreceptors. The AAV2/9.pR2.1.GFP reporter was applied to hiPSC-derived retinal cultures to isolate and process cone-like cell populations for RNA sequencing using the same strategy developed within the human foetal retina. Applying the cone enriched gene signature to the transcriptome of hiPSC-derived GFP+ samples at equivalent developmental stages revealed some expression similarities in genes found to be enriched within the late foetal L/M-opsin cone photoreceptors. This analysis overall revealed an intermediate stage of cone differentiation was achieved within the hiPSC-derived samples and the comparison to human foetal L/M-opsin gene express profiles suggesting further differentiation of hiPSC-derived sample is required.

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