Unknown

Dataset Information

0

Highly multiplexed quantitation of gene expression on single cells.


ABSTRACT: Highly multiplexed, single-cell technologies reveal important heterogeneity within cell populations. Recently, technologies to simultaneously measure expression of 96 (or more) genes from a single cell have been developed for immunologic monitoring. Here, we report a rigorous, optimized, quantitative methodology for using this technology. Specifically: we describe a unique primer/probe qualification method necessary for quantitative results; we show that primers do not compete in highly multiplexed amplifications; we define the limit of detection for this assay as a single mRNA transcript; and, we show that the technical reproducibility of the system is very high. We illustrate two disparate applications of the platform: a "bulk" approach that measures expression patterns from 100 cells at a time in high throughput to define gene signatures, and a single-cell approach to define the coordinate expression patterns of multiple genes and reveal unique subsets of cells.

SUBMITTER: Dominguez MH 

PROVIDER: S-EPMC3814038 | biostudies-other | 2013 May

REPOSITORIES: biostudies-other

altmetric image

Publications

Highly multiplexed quantitation of gene expression on single cells.

Dominguez Maria H MH   Chattopadhyay Pratip K PK   Ma Steven S   Lamoreaux Laurie L   McDavid Andrew A   Finak Greg G   Gottardo Raphael R   Koup Richard A RA   Roederer Mario M  

Journal of immunological methods 20130313 1-2


Highly multiplexed, single-cell technologies reveal important heterogeneity within cell populations. Recently, technologies to simultaneously measure expression of 96 (or more) genes from a single cell have been developed for immunologic monitoring. Here, we report a rigorous, optimized, quantitative methodology for using this technology. Specifically: we describe a unique primer/probe qualification method necessary for quantitative results; we show that primers do not compete in highly multiple  ...[more]

Similar Datasets

2015-04-09 | E-GEOD-67685 | biostudies-arrayexpress
| S-EPMC4662681 | biostudies-literature
| S-EPMC4767631 | biostudies-literature
| S-EPMC5788347 | biostudies-literature
| S-EPMC10337260 | biostudies-literature
| S-EPMC4587398 | biostudies-literature
2018-01-31 | GSE102734 | GEO
| S-EPMC4807405 | biostudies-literature
2015-04-09 | GSE67685 | GEO
| S-EPMC3500620 | biostudies-literature