SINC-seq: correlation of transient gene expressions between nucleus and cytoplasm reflects single-cell physiology

Kyoto University researchers report a microfluidic system that physically separates nuclear RNA (nucRNA) and cytoplasmic RNA (cytRNA) from a single cell and enables single-cell integrated nucRNA and cytRNA-sequencing (SINC-seq). SINC-seq constructs two individual RNA-seq libraries, nucRNA and cytRNA, per cell, quantifies gene expression in the subcellular compartments, and combines them to create novel single-cell RNA-seq data. Leveraging SINC-seq, the researchers discover distinct natures of correlation among cytRNA and nucRNA that reflect the transient physiological state of single cells. These data provide unique insights into the regulatory network of messenger RNA from the nucleus toward the cytoplasm at the single-cell level.

Single-cell integrated nuclear and cytoplasmic RNA-seq (SINC-seq)

a SINC-seq and conventional scRNA-seq. b Workflow of SINC-seq. Single-cell isolation at a hydrodynamic trap via pressure-driven flow (t = 0 s); lysis of cell membrane and cytRNA extraction with isotachophoresis (ITP)-aided nucleic acid extraction (t > 0 s); ITP acceleration by changing voltages (t = 40 s); voltage deactivation and sample collection from the wells of the microchannel (t > 200 s). c Fluorescence microscopy images of the trapped single cell and nucleus after cytRNA extraction (stained with Hoechst) and extracted cytRNA stained with SYBR Green II. Scale bars are 20 μm. d Venn diagram of mean numbers of detected genes in cytRNA-seq and nucRNA-seq. e Percent proportion of abundance of transcripts in the cytoplasm. f Differential expression analysis between cytRNA and nucRNA. Genes enriched in cytRNA are on the right-hand side. Blue, genes with p values less than 0.001 and absolute log2 fold changes greater than unity. g Correlation coefficients of gene expression pattern computed with respect to the conventional scRNA-seq; our novel in silico single-cell normalization showed the best correlation with the scRNA-seq. We also include correlation of nucRNA vs. its in silico single cell