EventsThe 7th International Multidisciplinary Conference on Optofluidics 2017
Published
This submission belongs to the session 01. Micro-/nano-fluidics of the event The 7th International Multidisciplinary Conference on Optofluidics 2017
Published date
21 Jul, 2017
Citation
David A. Weitz, Single Cell Analysis Using Drop Based Microfluidics , in Proceedings of The 7th International Multidisciplinary Conference on Optofluidics 2017, Singapore, 25 July–28 July 2017, MDPI: Basel, Switzerland, doi: 10.3390/optofluidics2017-04168
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Single Cell Analysis Using Drop Based Microfluidics

1. Harvard University
Abstract

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships.

Keywords
Plant growth estimation combined with robust field monitors and micro-fluidic model simulating plant vascular system
Size-dependent Dielectrophoretic crossover frequency of shperical microparticles varies with different medium conductivity