Abstract
Discriminating cellular heterogeneity is important for understanding cellular physiology. However, it is limited by the technical difficulties of single-cell measurements. Here we develop a two-stage system to determine cellular heterogeneity. In the first stage, we perform multiplex single-cell RNA cytometry in a microwell array containing over 60,000 reaction chambers. In the second stage, we use the RNA cytometry data to determine cellular heterogeneity by providing a heterogeneity likelihood score (HLS). Moreover, we use Monte-Carlo simulation and RNA cytometry data to calculate the minimum number of cells required for detecting heterogeneity. We apply this system to characterize the RNA distributions of ageing-related genes in a highly purified mouse haematopoietic stem cell population. We identify genes that reveal novel heterogeneity of these cells. We also show that changes in expression of genes such as Birc6 during ageing can be attributed to the shift of relative portions of cells in the high-expressing subgroup versus low-expressing subgroup.
| Original language | English |
|---|---|
| Article number | 3451 |
| Journal | Nature Communications |
| Volume | 5 |
| DOIs | |
| State | Published - 25 Mar 2014 |
Bibliographical note
Funding Information:We thank L. Jerabek and T. Storm for laboratory management; T. Naik for antibody production, A. Mosley, J. Dollaga and D. Escoto for animal care; S. Karten for help with reviewing the manuscript text; Yuling Luo, Nan Su and Li-chong Wang form Advanced Cell Diagnostics for help with mRNA in-situ hybridization, and the Stanford Neuroscience Microscopy Service supported by NIH NS069375. This investigation was supported by the Center for Nanostructured Materials Technology (CNMT, Korea), and a grant from the Siebel Stem Cell Institute and the Thomas and Stacey Siebel Foundation, by a fellowship from the California Institute for Regenerative Medicine (TG2-01159) and by NIH grants R01AI047457, R01AI047458, R01CA86065, U54CA151459 and U01HL099999 (to I.L.W.). I.L.W. is the Virginia and Daniel K. Ludwig Professor of Clinical Cancer Research.