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The workflow of single-cell expression profiling using quantitative real-time PCR
Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819576/ https://www.ncbi.nlm.nih.gov/pubmed/24649819 http://dx.doi.org/10.1586/14737159.2014.901154 |
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author | Ståhlberg, Anders Kubista, Mikael |
author_facet | Ståhlberg, Anders Kubista, Mikael |
author_sort | Ståhlberg, Anders |
collection | PubMed |
description | Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are studied. New cell types and cell subtypes may be found and relevant pathways and expression networks can be identified. The most powerful technique for single-cell expression profiling is currently quantitative reverse transcription real-time PCR (RT-qPCR). A robust RT-qPCR workflow for highly sensitive and specific measurements in high-throughput and a reasonable degree of multiplexing has been developed for targeting mRNAs, but also microRNAs, non-coding RNAs and most recently also proteins. We review the current state of the art of single-cell expression profiling and present also the improvements and developments expected in the next 5 years. |
format | Online Article Text |
id | pubmed-4819576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-48195762016-04-22 The workflow of single-cell expression profiling using quantitative real-time PCR Ståhlberg, Anders Kubista, Mikael Expert Rev Mol Diagn Reviews Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are studied. New cell types and cell subtypes may be found and relevant pathways and expression networks can be identified. The most powerful technique for single-cell expression profiling is currently quantitative reverse transcription real-time PCR (RT-qPCR). A robust RT-qPCR workflow for highly sensitive and specific measurements in high-throughput and a reasonable degree of multiplexing has been developed for targeting mRNAs, but also microRNAs, non-coding RNAs and most recently also proteins. We review the current state of the art of single-cell expression profiling and present also the improvements and developments expected in the next 5 years. Taylor & Francis 2014-04-01 2014-03-21 /pmc/articles/PMC4819576/ /pubmed/24649819 http://dx.doi.org/10.1586/14737159.2014.901154 Text en © 2014 The Author(s). Published by Taylor & Francis. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. |
spellingShingle | Reviews Ståhlberg, Anders Kubista, Mikael The workflow of single-cell expression profiling using quantitative real-time PCR |
title | The workflow of single-cell expression profiling using quantitative real-time PCR |
title_full | The workflow of single-cell expression profiling using quantitative real-time PCR |
title_fullStr | The workflow of single-cell expression profiling using quantitative real-time PCR |
title_full_unstemmed | The workflow of single-cell expression profiling using quantitative real-time PCR |
title_short | The workflow of single-cell expression profiling using quantitative real-time PCR |
title_sort | workflow of single-cell expression profiling using quantitative real-time pcr |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819576/ https://www.ncbi.nlm.nih.gov/pubmed/24649819 http://dx.doi.org/10.1586/14737159.2014.901154 |
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