Open Access Research article

Transcriptome analysis in primary neural stem cells using a tag cDNA amplification method

Maria Sievertzon1, Valtteri Wirta1, Alex Mercer2, Konstantinos Meletis3, Rikard Erlandsson2, Lilian Wikström2, Jonas Frisén3 and Joakim Lundeberg1*

Author Affiliations

1 Royal Institute of Technology, AlbaNova University Center, KTH Genome Center, Department of Biotechnology, S-106 91 Stockholm, Sweden

2 NeuroNova AB, S-114 33 Stockholm, Sweden

3 Department of cell- and molecular biology, Medical Nobel Institute, Karolinska Institute, S-171 77 Stockholm, Sweden

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BMC Neuroscience 2005, 6:28  doi:10.1186/1471-2202-6-28

Published: 15 April 2005



Neural stem cells (NSCs) can be isolated from the adult mammalian brain and expanded in culture, in the form of cellular aggregates called neurospheres. Neurospheres provide an in vitro model for studying NSC behaviour and give information on the factors and mechanisms that govern their proliferation and differentiation. They are also a promising source for cell replacement therapies of the central nervous system. Neurospheres are complex structures consisting of several cell types of varying degrees of differentiation. One way of characterising neurospheres is to analyse their gene expression profiles. The value of such studies is however uncertain since they are heterogeneous structures and different populations of neurospheres may vary significantly in their gene expression.


To address this issue, we have used cDNA microarrays and a recently reported tag cDNA amplification method to analyse the gene expression profiles of neurospheres originating from separate isolations of the lateral ventricle wall of adult mice and passaged to varying degrees. Separate isolations as well as consecutive passages yield a high variability in gene expression while parallel cultures yield the lowest variability.


We demonstrate a low technical amplification variability using the employed amplification strategy and conclude that neurospheres from the same isolation and passage are sufficiently similar to be used for comparative gene expression analysis.