2,336 research outputs found

    arrEYE : a customized platform for high-resolution copy number analysis of coding and noncoding regions of known and candidate retinal dystrophy genes and retinal noncoding RNAs

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    Purpose: Our goal was to design a customized microarray, arrEYE, for high-resolution copy number variant (CNV) analysis of known and candidate genes for inherited retinal dystrophy (iRD) and retina expressed noncoding RNAs (ncRNAs). Methods: arrEYE contains probes for the full genomic region of 106 known iRD genes, including those implicated in retinitis pigmentosa (RP) (the most frequent iRD), cone rod dystrophies, macular dystrophies, and an additional 60 candidate iRD genes and 196 ncRNAs. Eight CNVs in iRD genes identified by other techniques were used as positive controls. The test cohort consisted of 57 patients with autosomal dominant, X-linked, or simplex RP. Results: In an RP patient, a novel heterozygous deletion of exons 7 and 8 of the HGSNAT gene was identified: c.634-408_820+338delins AGAATATG, p.(G1u2 I 2Glyfs*2). A known variant was found on the second allele: c.1843G>A, p.(A1a615Thr). Furthermore, we expanded the allelic spectrum of USH2A and RCBTB1 with novel CNVs. Conclusion: The arrEYE platform revealed subtle single-exon to larger CNVs in iRD genes that could be characterized at the nucleotide level, facilitated by the high resolution of the platform. We report the first CNV in HGSNAT that, combined with another mutation, leads to RP, further supporting its recently identified role in nonsyndromic iRD

    Cellular Expression of Smarca4 (Brg1)-regulated Genes in Zebrafish Retinas

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    <p>Abstract</p> <p>Background</p> <p>In a recent genomic study, Leung et al. used a factorial microarray analysis to identify Smarca4 (Brg1)-regulated genes in micro-dissected zebrafish retinas. Two hundred and fifty nine genes were grouped in three-way ANOVA models which carried the most specific retinal change. To validate the microarray results and to elucidate cellular expression patterns of the significant genes for further characterization, 32 known genes were randomly selected from this group. <it>In situ </it>hybridization of these genes was performed on the same types of samples (wild-type (WT) and <it>smarca4<sup>a50/a50 </sup></it>(<it>yng</it>) mutant) at the same stages (36 and 52 hours post-fertilization (hpf)) as in the microarray study.</p> <p>Results</p> <p>Thirty out of 32 riboprobes showed a positive <it>in situ </it>staining signal. Twenty seven out of these 30 genes were originally further classified as Smarca4-regulated retinal genes, while the remaining three as retinal-specific expression independent of Smarca4 regulation. It was found that 90.32% of the significant microarray comparisons that were used to identify Smarca4-regulated retinal genes had a corresponding qualitative expression change in the <it>in situ </it>hybridization comparisons. This is highly concordant with the theoretical true discovery rate of 95%. Hierarchical clustering was used to investigate the similarity of the cellular expression patterns of 25 out of the 27 Smarca4-regulated retinal genes that had a sufficiently high expression signal for an unambiguous identification of retinal expression domains. Three broad groups of expression pattern were identified; including 1) photoreceptor layer/outer nuclear layer specific expression at 52 hpf, 2) ganglion cell layer (GCL) and/or inner nuclear layer (INL) specific expression at both 36 & 52 hpf, and 3) GCL and/or INL specific expression at 52 hpf only. Some of these genes have recently been demonstrated to play key roles in retinal cell-type specification, differentiation and lamination. For the remaining three retinal-specific genes that are independent of Smarca4 regulation, they all had a subtle expression difference between WT and <it>smarca4<sup>a50/a50 </sup></it>retinas as detected by <it>in situ </it>hybridization. This subtle expression difference was also detected by the original microarray analysis. However, the difference was lower than the fold change cut-off used in that study and hence these genes were not inferred as Smarca4-regulated retinal genes.</p> <p>Conclusions</p> <p>This study has successfully investigated the expression pattern of 32 genes identified from the original factorial microarray analysis. The results have demonstrated that the true discovery rate for identifying Smarca4-regulated retinal genes is 90.3%. Hence, the significant genes from the microarray study are good candidates for cell-type specific markers and will aid further investigation of retinal differentiation.</p

    Genome-Wide Analysis of Müller Glial Differentiation Reveals a Requirement for Notch Signaling in Postmitotic Cells to Maintain the Glial Fate

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    Previous studies have shown that Müller glia are closely related to retinal progenitors; these two cell types express many of the same genes and after damage to the retina, Müller glia can serve as a source for new neurons, particularly in non-mammalian vertebrates. We investigated the period of postnatal retinal development when progenitors are differentiating into Müller glia to better understand this transition. FACS purified retinal progenitors and Müller glia from various ages of Hes5-GFP mice were analyzed by Affymetrix cDNA microarrays. We found that genes known to be enriched/expressed by Müller glia steadily increase over the first three postnatal weeks, while genes associated with the mitotic cell cycle are rapidly downregulated from P0 to P7. Interestingly, progenitor genes not directly associated with the mitotic cell cycle, like the proneural genes Ascl1 and Neurog2, decline more slowly over the first 10–14 days of postnatal development, and there is a peak in Notch signaling several days after the presumptive Müller glia have been generated. To confirm that Notch signaling continues in the postmitotic Müller glia, we performed in situ hybridization, immunolocalization for the active form of Notch, and immunofluorescence for BrdU. Using genetic and pharmacological approaches, we found that sustained Notch signaling in the postmitotic Müller glia is necessary for their maturation and the stabilization of the glial identity for almost a week after the cells have exited the mitotic cell cycle

    Effects of Aging and Anatomic Location on Gene Expression in Human Retina

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    Objective: To determine the effects of age and topographic location on gene expression in human neural retina. Methods: Macular and peripheral neural retina RNA was isolated from human donor eyes for DNA microarray and quantitative RT-PCR analyses. Results: Total RNA integrity from human donors was preserved. Hierarchical clustering analysis demonstrates that the gene expression profiles of young, old, macula, and peripheral retina cluster into four distinct groups. Genes which are highly expressed in macular, peripheral, young, or old retina were identified, including inhibitors of Wnt Signaling Pathway (DKK1, FZD10, and SFRP2) which are preferably expressed in the periphery. Conclusion: The transcriptome of the human retina is affected by age and topographic location. Wnt pathway inhibitors in the periphery may maintain peripheral retinal cells in an undifferentiated state. Understanding the effects of age and topographic location on gene expression may lead to the development of new therapeutic interventions for age-related eye diseases

    Genetic Variations Strongly Influence Phenotypic Outcome in the Mouse Retina

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    Variation in genetic background can significantly influence the phenotypic outcome of both disease and non-disease associated traits. Additionally, differences in temporal and strain specific gene expression can also contribute to phenotypes in the mammalian retina. This is the first report of microarray based cross-strain analysis of gene expression in the retina investigating genetic background effects. Microarray analyses were performed on retinas from the following mouse strains: C57BL6/J, AKR/J, CAST/EiJ, and NOD.NON-H2-nb1 at embryonic day 18.5 (E18.5) and postnatal day 30.5 (P30.5). Over 3000 differentially expressed genes were identified between strains and developmental stages. Differential gene expression was confirmed by qRT-PCR, Western blot, and immunohistochemistry. Three major gene networks were identified that function to regulate retinal or photoreceptor development, visual perception, cellular transport, and signal transduction. Many of the genes in these networks are implicated in retinal diseases such as bradyopsia, night-blindness, and cone-rod dystrophy. Our analysis revealed strain specific variations in cone photoreceptor cell patterning and retinal function. This study highlights the substantial impact of genetic background on both development and function of the retina and the level of gene expression differences tolerated for normal retinal function. These strain specific genetic variations may also be present in other tissues. In addition, this study will provide valuable insight for the development of more accurate models for human retinal diseases

    The transcriptome of retinal Müller glial cells

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    Müller glial cells are the major type of glia in the mammalian retina. To identify the molecular machinery that defines Müller glial cell identity and function, single cell gene expression profiling was performed on Affymetrix microarrays. Identification of a cluster of genes expressed at high levels suggests a Müller glia core transcriptome, which likely underlies many of the functions of Müller glia. Expression of components of the cell cycle machinery and the Notch pathway, as well as of growth factors, chemokines, and lipoproteins might allow communication between Müller glial cells and the neurons that they support, including modulation of neuronal activity. This approach revealed a set of transcripts that were not previously characterized in (Müller) glia; validation of the expression of some of these genes was performed by in situ hybridization. Genes expressed exclusively by Müller glia were identified as novel markers. In addition, a novel BAC transgenic mouse that expresses Cre in Müller glia cells was generated. The molecular fingerprint of Müller glia provides a foundation for further studies of Müller glia development and function in normal and diseased states
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