|Oleh I. Petriv1, Florian Kuchenbauer2, Allen Delaney3, Veronique Lecault1, Adam White1, David G. Kent2, Lindsay Laycock2, Michael Heuser2, Tobias Berg2, Michael R. Copley2, Jens Ruschmann2, Sanja Sekulovic2, Frann Antignano2, Etsushi Kuroda2, Victor Ho2, Claudia Benz2, Timotheus Y. F. Halim2, Vincenzo Giambra2, Gerald Krystal2, Connie J. Eaves2, Fumio Takei2, Andrew P. Weng2, James M. Piret4, Marco A. Marra3, R. Keith Humphries2, Carl L. Hansen1
1 University of British Columbia, Canada; 2 Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC; 3 Genome Sciences Centre, BC Cancer Agency, Vancouver, BC; 4 Michael Smith Laboratories,University of British Columbia, Vancouver, BC
The hematopoietic system is comprised of a large number of highly specialized cell types that occupy distinct niches and which perform a diversity of functions ranging from innate immune response to oxygen transport. All these cell types are thought to be derived from a common stem cell and represent a hierarchal tree of differentiation. miRNA expression is a critical player in orchestrating this differentiation. Due primarily to technical limitations in the analysis of limited cell populations the program of miRNA expression across the hematopoietic tree is largely unknown. Here we report the development of a microfluidic RT-qPCR approach for global miRNA profiling in limited populations and apply this to expression analysis of 27 distinct cell populations from the murine hematopoietic system. Expression of 288 miRNAs in each population was measured in multiple replicates for a total of over 80,000 RT-qPCR assays using microfluidic qPCR arrays (Fluidigm Biomark™ Dynamic Array). Using synthetic miRNA standards the sensitivity and efficiency of each assay was calibrated to allow for accurate comparison of expression across species and populations. In addition we show this technique is capable of measuring up to 12 miRNA species at single-cell resolution. We demonstrate that global miRNA profiling of the murine hematopoietic tree allows for direct and independent reconstruction of the known hierarchal relationships. We further find that the number of miRNA species expressed in a cell population is not correlated with differentiation state and that miRNA expression patterns in stem cell and progenitor populations are closely related with major reprogramming upon commitment to a single lineage. Single cell measurements further show that miRNA expression levels are tightly regulated within highly purified populations, suggesting that miRNA may be suitable biomarkers for assessing heterogeneity in a given population.
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