Gene expression profiling and regulatory networks in single cells

Fumio Arai, Kentaro Hosokawa, Yoshiko Matsumoto, Hirofumi Toyama, Toshio Suda

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Tissues and organs are composed of various kinds of cells including stem cells, progenitors, and terminally differentiated cells that have large variations of gene expression. Within a seemingly homogeneous cell population, gene expression levels may differ dramatically on a cell-to-cell level. However, differences or variations of individual cells are masked by the averaging effect of pooled samples in population analysis. Therefore, analyzing transcript levels for multiple genes across multiple individual cells could be key for understanding the unique characteristics of individual cells and for clarifying the complicated mechanisms controlling the function of individual cells. Recent advances in cDNA amplification techniques from single cell samples allow for analyzing gene expression patterns in individual cells. Amplified cDNAs are applicable to measurements of gene expression systems such as microarrays, DNA sequencing, and TaqMan assay-based high throughput nanofluidic real time PCR array analysis. Gene expression profiling at the single cell level allows us to identify specific sub-populations in heterogeneous cell populations in tissues and clarify the complex networks controlling the function of individual cells.

Original languageEnglish
Title of host publicationNew Frontiers of Network Analysis in Systems Biology
PublisherSpringer Netherlands
Pages1-13
Number of pages13
ISBN (Electronic)9789400743304
ISBN (Print)9400743297, 9789400743298
DOIs
Publication statusPublished - 2012 Feb 1

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Keywords

  • Nanofluidic real time PCR array
  • Single cell
  • cDNA amplification

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Arai, F., Hosokawa, K., Matsumoto, Y., Toyama, H., & Suda, T. (2012). Gene expression profiling and regulatory networks in single cells. In New Frontiers of Network Analysis in Systems Biology (pp. 1-13). Springer Netherlands. https://doi.org/10.1007/978-94-007-4330-4_1