Fezf2 expression identifies a multipotent progenitor for neocortical projection neurons, astrocytes, and oligodendrocytes.
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ABSTRACT:
SUBMITTER: Guo C
PROVIDER: S-EPMC3857588 | biostudies-other | 2013 Dec
REPOSITORIES: biostudies-other
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This database provides a comparison of the genome-wide transcriptional profiles of the main CNS cell types and is a resource to the neuroscience community for better understanding the development, physiology, and pathology of the CNS. Keywords: Developmental CNS Cell type comparision FACS purification of astrocytes: Dissociated forebrains from S100β-EGFP mice were resuspended in panning buffer (DBPS containing 0.02% BSA and 12.5 U/ml DNase) and sequentially incubated on the following panning plates: secondary antibody only plate to deplete microglia, O4 plate to deplete OLs, PDGFRα plate to deplete OPCs, and a second O4 plate to deplete any remaining OLs. This procedure was sufficient to deplete all OL-lineage cells from animals P8 and younger, however, in older animals that had begun to myelinate, additional depletion of OLs and myelin debris was accomplished as follows. The nonadherent cells from the last O4 dish were harvested by centrifugation, and the cells were resuspended in panning buffer containing GalC, MOG, and O1 supernatant and incubated for 15 minutes at room temperature. The cell suspension was washed and then resuspended in panning buffer containing 20 μg donkey anti-mouse APC for 15 minutes. The cells were washed and resuspended in panning buffer containing propidium iodide (PI). EGFP+ astrocytes were then purified by fluorescence activated cell sorting (FACS). Dead cells were gated out using high PI staining and forward light scatter. Astrocytes were identified based on high EGFP fluorescence and negative APC fluorescence from indirect immunostaining for OL markers GalC, MOG, and O1. Cells were sorted twice and routinely yielded >99.5% purity based on reanalysis of double sorted cells.; FACS purification of neurons: EGFP- cells were the remaining forebrain cells after microglia, OLs, and astrocytes had been removed, and were primarily composed of neurons, and to a lesser extent, endothelial cells (we estimate < 4% endothelial cells at P7 and < 20% endothelial cells at P17). EGFP- cells from S100β-EGFP dissociated forebrain were FACS purified in parallel with astrocyte purification and were sorted based on their negative EGFP fluorescence immunofluorescence. Cells were sorted twice and routinely yielded >99.9% purity. In independent preparations, the EGFP- cell population was additionally depleted of endothelial cells and pericytes by sequentially labeling with biotin-BSL1 lectin and streptavidin-APC while also labeling for OL markers as described above. Cells were sorted twice and routinely yielded >99.9% purity.; Panning purification of oligodendrocyte lineage cells: Dissociated mouse forebrains were resuspended in panning buffer. In order to deplete microglia, the single-cell suspension was sequentially panned on four BSL1 panning plates. The cell suspension was then sequentially incubated on two PDGFRα plates (to purify and deplete OPCs), one A2B5 plate (to deplete any remaining OPCs), two MOG plates (to purify and deplete myelinating OLs), and one GalC plate (to purify the remaining PDGFRα-, MOG-, OLs). The adherent cells on the first PDGFRα, MOG, and GalC plates were washed to remove all antigen-negative nonadherent cells. The cells were then lysed while still attached to the panning plate with Qiagen RLT lysis buffer, and total RNA was purified. Purified OPCs were >95% NG2 positive and 0% MOG positive. Purified Myelin OLs were 100% MOG positive, >95% MBP positive, and 0% NG2 positive. Purified GalC OLs depleted of OPCs and Myelin OLs were <10% MOG positive and ~50% weakly NG2 positive, a reflection of their recent development as early OLs.; Data normalization and analysis: Raw image files were processed using Affymetrix GCOS and the MAS 5.0 algorithm. Intensity data was normalized per chip to a target intensity TGT value of 500, and expression data and absent/present calls for individual probe sets were determined. Gene expression values were normalized and modeled across arrays using the dChip software package with invariant-set normalization and a PM model. (www.dchip.org, Li and Wong, 2001). The 29 samples were grouped into 9 sample types: Astros P7-P8, Astros P17, Astros P17-gray matter (P17g), Neurons P7, Neurons P17, Neurons-endothelial cell depleted (P7n, P17n), OPCs, GalC-OLs, and MOG-OLs. Gene filtering was performed to select probe sets that were consistently expressed in at least one cell type, where consistently expressed was defined as being called present and having a MAS 5.0 intensity level greater than 200 in at least two-thirds of the samples in the cell type. We identified 20,932 of the 45,037 probe sets that were consistently expressed in at least one of the nine cell types. The Significance Analysis of Microarrays (SAM) method (Tusher et al., 2001) was used to determine genes that were significantly differentially expressed between different cell types (see Supplemental Table S2 for SAM cell type groupings). Clustering was performed using the hclust method with complete linkage in R. Expression values were transformed for clustering by computing a mean expression value for the gene using those samples in the corresponding SAM statistical analysis, and then subtracting the mean from expression intensities. In order to preserve the log2 scale of the data, unless otherwise indicated, no normalization by variance was performed. Plots were created using the gplots package in R. The Bioconductor software package (Gentleman et al., 2004) was used throughout the expression analyses. Functional analyses were performed through the use of Ingenuity Pathways Analysis (Ingenuity® Systems, www.ingenuity.com).
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