ABSTRACT
Efficient isolation of specific, intact, living neurons from the adult brain is problematic due to the complex nature of the extracellular matrix consolidating the neuronal network. Here, we present significant improvements to the protocol for isolation of pure populations of neurons from mature postnatal mouse brain using fluorescence activated cell sorting (FACS). The 10-fold increase in cell yield enables cell-specific transcriptome analysis by protocols such as nanoCAGE and RNA seq.
Subject(s)
Brain/cytology , Cell Survival/drug effects , Flow Cytometry/methods , Neurons/cytology , Trehalose/chemistry , Animals , Mice , Mice, Transgenic , RNA, Messenger/isolation & purification , Transcriptome , Trehalose/pharmacologyABSTRACT
BACKGROUND: The transcriptome of the cerebral cortex is remarkably homogeneous, with variations being stronger between individuals than between areas. It is thought that due to the presence of many distinct cell types, differences within one cell population will be averaged with the noise from others. Studies of sorted cells expressing the same transgene have shown that cell populations can be distinguished according to their transcriptional profile. METHODOLOGY: We have prepared a low-redundancy set of 16,209 full-length cDNA clones which represents the transcriptome of the mouse visual cortex in its coding and non-coding aspects. Using an independent tag-based approach, CAGE, we confirmed the cortical expression of 72% of the clones. Clones were amplified by PCR and spotted on glass slides, and we interrogated the microarrays with RNA from flow-sorted fluorescent cells from the cerebral cortex of parvalbumin-egfp transgenic mice. CONCLUSIONS: We provide an annotated cDNA clone collection which is particularly suitable for transcriptomic analysis in the mouse brain. Spotting it on microarrays, we compared the transcriptome of EGFP positive and negative cells in a parvalbumin-egfp transgenic background and showed that more than 30% of clones are differentially expressed. Our clone collection will be a useful resource for the study of the transcriptome of single cell types in the cerebral cortex.
