Transcriptionally Profiling Cells Sorted by Transcript Abundance

These authors contributed equally to this work. We have developed a quantitative technique for sorting cells based on endogenous RNA abundance with a molecular resolution of 10-20 transcripts. We demonstrate efficient and unbiased RNA extraction from transcriptionally sorted cells and report a high fidelity transcriptome measurement of (mouse) induced pluripotent stem cells (iPSCs) isolated from a heterogeneous reprogramming culture. This method is broadly applicable to profiling transcriptionally distinct cellular states without requiring antibodies or transgenic fluorescent proteins. A common challenge in biology is to identify and isolate transcriptionally distinct subpopulations within a single tissue or cell type. While a variety of techniques have been developed to discriminate among these alternative expression modes, the most widely used methods require either transgenic integration of fluorescent protein reporters or the availability of specific antibodies1–3. These approaches, however, are precluded for biological systems that are refractory to genetic manipulation (e.g., primary human tissue) Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#term