Comprehensive qPCR profiling of gene expression in single neuronal cells

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, California, USA.
Nature Protocol (Impact Factor: 8.36). 01/2012; 7(1):118-27. DOI: 10.1038/nprot.2011.430
Source: PubMed

ABSTRACT A major challenge in neuronal stem cell biology lies in characterization of lineage-specific reprogrammed human neuronal cells, a process that necessitates the use of an assay sensitive to the single-cell level. Single-cell gene profiling can provide definitive evidence regarding the conversion of one cell type into another at a high level of resolution. The protocol we describe uses Fluidigm Biomark dynamic arrays for high-throughput expression profiling from single neuronal cells, assaying up to 96 independent samples with up to 96 quantitative PCR (qPCR) probes (equivalent to 9,216 reactions) in a single experiment, which can be completed within 2-3 d. The protocol enables simple and cost-effective profiling of several hundred transcripts from a single cell, and it could have numerous utilities.

Download full-text


Available from: Ami Citri, Jul 07, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The development of cancer is a dynamic evolutionary process in which intra-clonal, genetic diversity provides a substrate for clonal selection and a source of therapeutic escape. The complexity and topography of intra-clonal genetic architecture has major implications for biopsy-based prognosis and for targeted therapy. High depth, next generation sequencing (NGS) efficiently captures the mutational load of individual tumours or biopsies. But, being a snapshot portrait of total DNA, it disguises the fundamental features of sub-clonal variegation of genetic lesions and of clonal phylogeny. Single cell genetic profiling provides a potential resolution to this problem but methods developed to date all have limitations. We present a novel solution to this challenge using leukaemic cells with known mutational spectra as a tractable model. DNA from flow sorted single cells is screened using multiplex targeted Q-PCR within a micro-fluidic platform allowing unbiased single cell selection, high throughput and comprehensive analysis for all main varieties of genetic abnormalities: chimaeric gene fusions, copy number alterations and single nucleotide variants. We show, in this proof of principle study, that the method has a low error rate and can provide detailed sub-clonal genetic architectures and phylogenies.
    Genome Research 09/2013; DOI:10.1101/gr.159913.113 · 13.85 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a highly sensitive bioanalytical microarray assay that enables the analysis of small genomic sample material. By combining an optimized cDNA purification step with single molecule cDNA detection on the microarray, the platform has improved sensitivity compared to conventional systems, allowing amplification-free determination of expression profiles with as little as 600ng total RNA. Total RNA from cells was reverse transcribed into fluorescently labeled cDNA and purified employing a precipitation method that minimizes loss of cDNA material. The microarray was scanned on a fluorescence chip-reader with single molecule sensitivity. Using the newly developed platform we were able to analyze the RNA expression profile of a subpopulation of rare multiple myeloma CD138 negative progenitor (MM CD138(neg)) cells. The high-sensitivity microarray approach led to the identification of a set of 20 genes differentially expressed in MM CD138(neg) cells. Our work demonstrates the applicability of a straight-forward single-molecule DNA array technology to current topics of molecular and cellular cancer research, which are otherwise difficult to address due to the limited amount of sample material.
    Journal of Biotechnology 02/2013; 164(4). DOI:10.1016/j.jbiotec.2013.01.027 · 2.88 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we have developed a method to perform single-neuron RNA-Seq. Following electrophysiology recording from an individual neuron, total RNA was extracted by aspirating the cellular contents into a fine glass electrode tip. The mRNAs were reverse transcribed and amplified to construct a single-neuron cDNA library, and subsequently subjected to high-throughput sequencing. This approach was applied to both individual neurons cultured from embryonic mouse hippocampus, as well as neocortical neurons from live brain slices. We found that the average pairwise Spearman's rank correlation coefficient of gene expression level expressed as RPKM (reads per kilobase of transcript per million mapped reads) was 0.51 between five cultured neuronal cells, whereas the same measure between three cortical layer 5 neurons in situ was 0.25. The data suggest that there may be greater heterogeneity of the cortical neurons, as compared to neurons in vitro. The results demonstrate the technical feasibility and reproducibility of RNA-Seq in capturing a part of the transcriptome landscape of single neurons, and confirmed that morphologically identical neurons, even from the same region, have distinct gene expression patterns.
    Frontiers in Genetics 07/2012; 3:124. DOI:10.3389/fgene.2012.00124