Gene Expression Nebulas
A data portal of transcriptomic profiles analyzed by a unified pipeline across multiple species

Gene Expression Nebulas

A data portal of transcriptome profiles across multiple species

PRJNA546254: Single-cell RNA sequencing reveals the impact of chromosomal instability on glioblastoma cancer stem cells

Source: NCBI / GSE132172
Submission Date: Jun 04 2019
Release Date: Jun 05 2019
Update Date: Jun 13 2019

Summary: Intra-tumor genetic heterogeneity comes from whole chromosome and/or focal copy number variations (CNVs). We investigated the impact of whole chromosome CNVs on gene expression by performing single-cell RNA sequencing on a chromosomally unstable glioblastoma cancer stem cell (CSC) line and a control normal, diploid neural stem cell (NSC) line. From the gene expression data, we computationally inferred large-scale CNVs in single cells. We find that gene expression across large genomic regions scales proportionally to whole chromosome copy number in chromosomally unstable CSCs. Also, we find that the differential expression of most genes between normal NSCs and glioblastoma CSCs is largely accounted for by copy number alterations. However, we identify 269 genes whose differential expression in glioblastoma CSCs relative to normal NSCs is independent of copy number. Moreover, a gene signature derived from the subset of genes that are differential expressed independent of copy number in glioblastoma CSCs correlates with tumor grade and is prognostic for patient survival. In conclusion, this study demonstrates the utility of single-cell RNA sequencing when analyzing chromosomally unstable cells.

Overall Design: Single-cell RNA sequencing of normal neural stem cells and glioblastoma cancer stem cells using C1 Single Cell Auto Prep system from Fluidigm and Illumina Nextera XT library sequencing as C1- protocol.

GEN Datasets:
GEND000052
Strategy:
Species:
Healthy Condition:
Cell Type:
Cell Line:
Protocol
Growth Protocol: Cells were grown in serum-free culture conditions as described in Pollard et al, Cell Stem Cell, 568-580, 2009.
Treatment Protocol: The cells were dissociated, filter strain with 40m, resuspended in the serum free culture medium.
Extract Protocol: Single cells were caputured, lysed, and cDNA prepared using the C1 Single Cell Auto Prep system from Fluidigm.
Library Construction Protocol: -
Sequencing
Molecule Type: poly(A)+ RNA
Library Source:
Library Layout: PAIRED
Library Strand: -
Platform: ILLUMINA
Instrument Model: Illumina HiSeq 2000
Strand-Specific: Unspecific
Samples
Basic Information:
Sample Characteristic:
Biological Condition:
Experimental Variables:
Protocol:
Sequencing:
Assessing Quality:
Analysis:
Data Resource GEN Sample ID GEN Dataset ID Project ID BioProject ID Sample ID Sample Name BioSample ID Sample Accession Experiment Accession Release Date Submission Date Update Date Species Race Ethnicity Age Age Unit Gender Source Name Tissue Cell Type Cell Subtype Cell Line Disease Disease State Development Stage Mutation Phenotype Case Detail Control Detail Growth Protocol Treatment Protocol Extract Protocol Library Construction Protocol Molecule Type Library Layout Strand-Specific Library Strand Spike-In Strategy Platform Instrument Model Cell Number Reads Number Gbases AvgSpotLen1 AvgSpotLen2 Uniq Mapping Rate Multiple Mapping Rate Coverage Rate
Publications
Single-cell RNA sequencing reveals the impact of chromosomal instability on glioblastoma cancer stem cells.
BMC medical genomics . 2019-05-31 [PMID: 31151460]