The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Nov. 19, 2013
Filed:
Dec. 16, 2010
Geoffrey Gurtner, Stanford, CA (US);
Michael Januszyk, Menlo Park, CA (US);
Ivan Vial, Stanford, CA (US);
Jason Glotzbach, Palo Alto, CA (US);
Geoffrey Gurtner, Stanford, CA (US);
Michael Januszyk, Menlo Park, CA (US);
Ivan Vial, Stanford, CA (US);
Jason Glotzbach, Palo Alto, CA (US);
The Board of Trustees of the Leland Stanford Junior University, Palo Alto, CA (US);
Abstract
Understanding the heterogeneity within a stem cell population remains a major impediment to the development of clinically effective cell-based therapies. Gene expression patterns exhibited by individual cells are a crucial component of this heterogeneity, yet transcriptional events within a single cell are inherently stochastic and can produce tremendous variability, even among genetically identical cells. It remains unclear how mammalian cellular systems overcome this intrinsic noisiness of gene expression to produce consequential variations in function. To address these questions, we utilized a novel single cell analysis method to characterize transcriptional programs across hundreds of individual murine long-term hematopoietic stem cells (LT-SCs). We demonstrate that multiple subpopulations exist within this putatively homogeneous stem cell population, defined by nonrandom patterns that are distinguishable from noise and can predict functional properties of these cells. This represents a powerful new tool to elucidate the relationship between transcriptional and phenotypic variation within a cell population.