Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

1] Department of Chemistry and Chemical Biology and Department of Physics, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA [2].
Nature (Impact Factor: 41.46). 05/2013; 498(7453). DOI: 10.1038/nature12172
Source: PubMed


Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output, with important functional consequences. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs or proteins simultaneously, because genomic profiling methods could not be applied to single cells until very recently. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.

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Available from: Alex K Shalek, May 19, 2014
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    • "Previous studies of cell-to-cell variability in the mRNA isoform ratios for two endogenous genes have indeed shown that this variability can be considerably large and originated by fluctuations in the regulatory splicing machinery (Waks et al. 2011). High heterogeneity in single-cell alternative splicing has also been observed in immune cells in response to lipopolysaccharide stimulation (Shalek et al. 2013). Heterogeneity in mitochondrial content will likely have an impact on AS through different processes, either directly as a modulator of energy supply (required for the majority of steps, from the molecular assembly of the spliceosomal complex to intron removal ) or indirectly through its influence on other gene expression or regulatory processes that are coupled to AS (Braunschweig et al. 2013): For instance, RNA Pol II elongation is known to play a role in AS regulation (Kornblihtt 2007). "
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    • "Some recent work has investigated cell–cell variability in RNA splicing. While a study using single-molecule FISH on two genes found that variability in splice isoform ratio exceeds the variability expected from random partitioning to a relatively modest level, quantitatively similar to the level we observed for polyadenylation isoforms (Waks et al, 2011), a single-cell transcriptomic study reported much more widespread bimodality in splice isoform usage (Shalek et al, 2013). BATBayes could help to reconcile these findings by accounting for both technical noise of single-cell transcriptomics and the probabilistic distribution of RNA molecules to isoforms. "
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