Journal
NATURE METHODS
Volume 7, Issue 4, Pages 311-317Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.1442
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Funding
- NCI NIH HHS [5-R01-CA105134-07, R01 CA105134-07, R01 CA105134] Funding Source: Medline
- NIH HHS [DP2 OD006464, 1-DP2-OD006464-01, DP2 OD006464-01] Funding Source: Medline
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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-kappa B 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.
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