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- Title
Identifying single-cell molecular programs by stochastic profiling.
- Authors
Janes, Kevin A.; Chun-Chao Wang; Holmberg, Karin J.; Cabral, Kristin; Brugge, Joan S.
- Abstract
Cells in tissues can be morphologically indistinguishable yet show molecular expression patterns that are remarkably heterogeneous. Here we describe an approach to comprehensively identify co-regulated, heterogeneously expressed genes among cells that otherwise appear identical. The technique, called stochastic profiling, involves repeated, random selection of very small cell populations via laser-capture microdissection followed by a customized single-cell amplification procedure and transcriptional profiling. Fluctuations in the resulting gene-expression measurements are then analyzed statistically to identify transcripts that are heterogeneously coexpressed. We stochastically profiled matrix-attached human epithelial cells in a three-dimensional culture model of mammary-acinar morphogenesis. Of 4,557 transcripts, we identified 547 genes with strong cell-to-cell expression differences. Clustering of this heterogeneous subset revealed several molecular 'programs' implicated in protein biosynthesis, oxidative-stress responses and NF-κB signaling, which we independently confirmed by RNA fluorescence in situ hybridization. Thus, stochastic profiling can reveal single-cell heterogeneities without the need to measure expression in individual cells.
- Subjects
CELLS; TISSUES; INHOMOGENEOUS materials; MICRODISSECTION; EPITHELIAL cells
- Publication
Nature Methods, 2010, Vol 7, Issue 4, p311
- ISSN
1548-7091
- Publication type
Article
- DOI
10.1038/nmeth.1442