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Je něco špatně v tomto záznamu ?
The correlation between expression profiles measured in single cells and in traditional bulk samples
D. Dzamba, L. Valihrach, M. Kubista, M. Anderova,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
Directory of Open Access Journals
od 2011
Free Medical Journals
od 2011
Nature Open Access
od 2011-12-01
PubMed Central
od 2011
Europe PubMed Central
od 2011
ProQuest Central
od 2011-01-01
Open Access Digital Library
od 2011-01-01
Open Access Digital Library
od 2011-01-01
Health & Medicine (ProQuest)
od 2011-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2011
Springer Nature OA/Free Journals
od 2011-12-01
PubMed
27848982
DOI
10.1038/srep37022
Knihovny.cz E-zdroje
- MeSH
- analýza jednotlivých buněk * MeSH
- gliový fibrilární kyselý protein genetika MeSH
- messenger RNA genetika MeSH
- myši transgenní MeSH
- myši MeSH
- polymerázová řetězová reakce s reverzní transkripcí MeSH
- stanovení celkové genové exprese * MeSH
- zelené fluorescenční proteiny genetika MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Reverse transcription quantitative PCR (RT-qPCR) is already an established tool for mRNA detection and quantification. Since recently, this technique has been successfully employed for gene expression analyses, and also in individual cells (single cell RT-qPCR). Although the advantages of single cell measurements have been proven several times, a study correlating the expression measured on single cells, and in bulk samples consisting of a large number of cells, has been missing. Here, we collected a large data set to explore the relation between gene expression measured in single cells and in bulk samples, reflected by qPCR Cq values. We measured the expression of 95 genes in 12 bulk samples, each containing thousands of astrocytes, and also in 693 individual astrocytes. Combining the data, we described the relation between Cq values measured in bulk samples with either the percentage of the single cells that express the given genes, or the average expression of the genes across the single cells. We show that data obtained with single cell RT-qPCR are fully consistent with measurements in bulk samples. Our results further provide a base for quality control in single cell expression profiling, and bring new insights into the biological process of cellular expression.
Citace poskytuje Crossref.org
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