Total mRNA Quantification in Single Cells: Sarcoma Cell Heterogeneity
Open Access
- 19 March 2020
- Vol. 9 (3), 759
- https://doi.org/10.3390/cells9030759
Abstract
Single-cell analysis enables detailed molecular characterization of cells in relation to cell type, genotype, cell state, temporal variations, and microenvironment. These studies often include the analysis of individual genes and networks of genes. The total amount of RNA also varies between cells due to important factors, such as cell type, cell size, and cell cycle state. However, there is a lack of simple and sensitive methods to quantify the total amount of RNA, especially mRNA. Here, we developed a method to quantify total mRNA levels in single cells based on global reverse transcription followed by quantitative PCR. Standard curve analyses of diluted RNA and sorted cells showed a wide dynamic range, high reproducibility, and excellent sensitivity. Single-cell analysis of three sarcoma cell lines and human fibroblasts revealed cell type variations, a lognormal distribution of total mRNA levels, and up to an eight-fold difference in total mRNA levels among the cells. The approach can easily be combined with targeted or global gene expression profiling, providing new means to study cell heterogeneity at an individual gene level and at a global level. This method can be used to investigate the biological importance of variations in the total amount of mRNA in healthy as well as pathological conditions.Funding Information
- Stiftelsen Assar Gabrielssons Fond (-)
- Knut och Alice Wallenbergs Stiftelse (-)
- Cancerfonden (2016-438, 19-0306, 2018- 830)
- Barncancerfonden (2017-0043, MTI2019-0008)
- Stiftelserna Wilhelm och Martina Lundgrens (-)
- VINNOVA (-)
This publication has 47 references indexed in Scilit:
- The secrets of the cellMolecular Aspects of Medicine, 2018
- Mapping the Mouse Cell Atlas by Microwell-SeqCell, 2018
- Transcriptomic Characterization of the Human Cell Cycle in Individual Unsynchronized CellsJournal of Molecular Biology, 2017
- Effective detection of variation in single-cell transcriptomes using MATQ-seqNature Methods, 2017
- Pathogen Cell-to-Cell Variability Drives Heterogeneity in Host Immune ResponsesCell, 2015
- Coordinating genome expression with cell sizeTrends in Genetics, 2012
- c-Myc Is a Universal Amplifier of Expressed Genes in Lymphocytes and Embryonic Stem CellsCell, 2012
- Synthetic spike-in standards for RNA-seq experimentsGenome Research, 2011
- Genomewide characterization of non-polyadenylated RNAsGenome Biology, 2011
- Characterization of a newly derived human sarcoma cell line (HT-1080)Cancer, 1974