Gene expression analysis of a single or few cells

Heterogeneity of astrocytes: from development to injury - single cell gene expression

Astrocytes perform control and regulatory functions in the central nervous system; heterogeneity among them is still a matter of debate due to limited knowledge of their gene expression profiles and functional diversity. To unravel astrocyte heterogeneity during postnatal development and after focal cerebral ischemia, we employed single-cell gene expression profiling in acutely isolated cortical GFAP/EGFP-positive cells. Using a microfluidic qPCR platform, we profiled 47 genes encoding glial markers and ion channels/transporters/receptors participating in maintaining K⁺ and glutamate homeostasis per cell. Self-organizing maps and principal component analyses revealed three subpopulations within 10–50 days of postnatal development (P10–P50). The first subpopulation, mainly immature glia from P10, was characterized by high transcriptional activity of all studied genes, including polydendrocytic markers. The second subpopulation (mostly from P20) was characterized by low gene transcript levels, while the third subpopulation encompassed mature astrocytes (mainly from P30, P50). Within 14 days after ischemia (D3, D7, D14), additional astrocytic subpopulations were identified: resting glia (mostly from P50 and D3), transcriptionally active early reactive glia (mainly from D7) and permanent reactive glia (solely from D14). Following focal cerebral ischemia, reactive astrocytes underwent pronounced changes in the expression of aquaporins, nonspecific cationic and potassium channels, glutamate receptors and reactive astrocyte markers.

Stochastic profiling of transcriptional regulatory heterogeneities in tissues, tumors and cultured cells

Single-cell variations in gene and protein expression are important during development and disease. Such cell-to-cell heterogeneities can be directly inspected one cell at a time, but global methods are usually not sensitive enough to work with the starting material of a single cell. Here we provide a detailed protocol for stochastic profiling, a method that infers single-cell regulatory heterogeneities by repeatedly sampling small collections of cells selected at random. Repeated stochastic sampling is performed by laser-capture microdissection or limiting dilution, followed by careful exponential cDNA amplification, hybridization to microarrays and statistical analysis. Stochastic profiling surveys the transcriptome for programs that are heterogeneously regulated among cellular subpopulations in their native tissue context. The protocol is readily optimized for specific biological applications and takes about 1 week to complete.