Dataset Information

Analysis of gene expression in wild-type and Notch1 mutant retinal cells by single cell profiling.

ABSTRACT: The vertebrate retina comprises sensory neurons, the photoreceptors, as well as many other types of neurons and one type of glial cell. These cells are generated by multipotent and restricted retinal progenitor cells (RPCs), which express Notch1. Loss of Notch1 in RPCs late during retinal development results in the overproduction of rod photoreceptors at the expense of interneurons and glia.To examine the molecular underpinnings of this observation, microarray analysis of single retinal cells from wild-type or Notch1 conditional knockout retinas was performed. In situ hybridization was carried out to validate some of the findings.The majority of Notch1-mutant cells lost expression of known Notch target genes. These cells also had low levels of RPC and cell cycle genes, and robustly up-regulated rod precursor genes. In addition, single wild-type cells, in which cell cycle marker genes were down-regulated, expressed markers of both rod photoreceptors and interneurons.

SUBMITTER: Mizeracka K

PROVIDER: S-EPMC3882027 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analysis of gene expression in wild-type and Notch1 mutant retinal cells by single cell profiling.

Mizeracka Karolina K Trimarchi Jeffrey M JM Stadler Michael B MB Cepko Constance L CL

Developmental dynamics : an official publication of the American Association of Anatomists 20130902 10

<h4>Background</h4>The vertebrate retina comprises sensory neurons, the photoreceptors, as well as many other types of neurons and one type of glial cell. These cells are generated by multipotent and restricted retinal progenitor cells (RPCs), which express Notch1. Loss of Notch1 in RPCs late during retinal development results in the overproduction of rod photoreceptors at the expense of interneurons and glia.<h4>Results</h4>To examine the molecular underpinnings of this observation, microarray ...[more]

PMID: 23813500

Similar Datasets

Project description:The effect of sampling time in the context of growth conditions on a dynamic metabolic system was investigated in order to assess to what extent a single sampling time may be sufficient for general application, as well as to determine if useful kinetic information could be obtained. A wild type yeast strain (W) was compared to a snf1Delta mutant yeast strain (S) grown in high-glucose medium (R) and in low-glucose medium containing ethanol (DR). Under these growth conditions, different metabolic pathways for utilizing the different carbon sources are expected to be active. Thus, changes in metabolite levels relating to the carbon source in the growth medium were anticipated. Furthermore, the Snf1 protein kinase complex is required to adapt cellular metabolism from fermentative R conditions to oxidative DR conditions. So, differences in intracellular metabolite levels between the W and S yeast strains were also anticipated. Cell extracts were collected at four time points (0.5, 2, 4, 6 h) after shifting half of the cells from R to DR conditions, resulting in 16 sample classes (WR, WDR, SR, SDR) x (0.5, 2, 4, 6 h). The experimental design provided time course data, so temporal dependencies could be monitored in addition to carbon source and strain dependencies. Comprehensive two-dimensional (2D) gas chromatography coupled to time-of-flight mass spectrometry (GC x GC-TOFMS) was used with discovery-based data mining algorithms ( Anal. Chem. 2006, 78, 5068-5075 (ref 1); J. Chromatogr., A 2008, 1186, 401-411 (ref 2)) to locate regions within the 2D chromatograms (i.e., metabolites) that provided chemical selectivity between the 16 sample classes. These regions were mathematically resolved using parallel factor analysis to positively identify the metabolites and to acquire quantitative results. With these tools, 51 unique metabolites were identified and quantified. Various time course patterns emerged from these data, and principal component analysis (PCA) was utilized as a comparison tool to determine the sources of variance between these 51 metabolites. The effect of sampling time was investigated with separate PCA analyses using various subsets of the data. PCA utilizing all of the time course data, averaged time course data, and each individual time point data set independently were performed to discern the differences. For the yeast strains examined in the current study, data collection at either 4 or 6 h provided information comparable to averaged time course data, albeit with a few metabolites missing using a single sampling time point.

Dataset Information

Analysis of gene expression in wild-type and Notch1 mutant retinal cells by single cell profiling.

Publications

Analysis of gene expression in wild-type and Notch1 mutant retinal cells by single cell profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets