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

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

2013 June 13 | Alex K. Shalek, Rahul Satija, Xian Adiconis, Rona S. Gertner, Jellert T. Gaublomme, Raktima Raychowdhury, Schragi Schwartz, Nir Yosef, Christine Malboeuf, Diana Lu, John T. Trombetta, Dave Gennert, Andreas Gnirke, Alon Goren, Nir Hacohen, Joshua Z. Levin, Hongkun Park, Aviv Regev
This study investigates the heterogeneity in the response of bone marrow-derived dendritic cells (BMDCs) to lipopolysaccharide (LPS) using single-cell RNA-Seq. The researchers found extensive and previously unobserved bimodal variation in mRNA abundance and splicing patterns, validated by RNA-FISH for select transcripts. Hundreds of key immune genes showed bimodal expression across cells, even for genes highly expressed at the population average. Splicing patterns also demonstrated significant heterogeneity between cells. Some bimodality was attributed to distinct maturity states of BMDCs, while other portions reflected differences in the usage of key regulatory circuits. The study highlights the power of single-cell genomics in uncovering functional diversity between cells and deciphering cell states and circuits.This study investigates the heterogeneity in the response of bone marrow-derived dendritic cells (BMDCs) to lipopolysaccharide (LPS) using single-cell RNA-Seq. The researchers found extensive and previously unobserved bimodal variation in mRNA abundance and splicing patterns, validated by RNA-FISH for select transcripts. Hundreds of key immune genes showed bimodal expression across cells, even for genes highly expressed at the population average. Splicing patterns also demonstrated significant heterogeneity between cells. Some bimodality was attributed to distinct maturity states of BMDCs, while other portions reflected differences in the usage of key regulatory circuits. The study highlights the power of single-cell genomics in uncovering functional diversity between cells and deciphering cell states and circuits.
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