Research ArticleGENETICS

NanoSINC-seq dissects the isoform diversity in subcellular compartments of single cells

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Science Advances  07 Apr 2021:
Vol. 7, no. 15, eabe0317
DOI: 10.1126/sciadv.abe0317
  • Fig. 1 NanoSINC-seq.

    Workflow of NanoSINC-seq. (A) Single-cell isolation at a hydrodynamic trap via pressure-driven flow (t < 0 s). (B) Lysis of cell membrane and cytoplasmic RNA extraction via electrophoretic nucleic acid extraction (t = 0 s). (C) Sample extraction and library preparation for sequencing with long (ONT) and short (Illumina) read sequencers. Leading electrolyte (LE) and trailing electrolyte (TE) are aqueous buffers for the electrophoretic extraction with isotachophoresis (ITP) (12, 13, 32). P and E represent the pressure and electric field, respectively.

  • Fig. 2 Benchmark of NanoSINC-seq assessing detection of transcripts and comparing to SINC-seq.

    (A) Numbers of transcripts detected via ONT. (B) Number of genes detected via ONT. Cyt and Nuc indicate cytoplasmic and nuclear fractions, respectively. “_all” indicates all of the detected transcripts/genes in individual fractions. “_only” indicates transcripts/genes detected only in one of the fractions. “Common” indicates detected transcripts/genes both in nuclear and cytoplasmic fractions. (C) Differences in the coefficients of correlation at transcript level and gene level, obtained via ONT sequencing. Each coefficient of correlation was calculated for a pair of nuclear fractions, a pair of cytoplasmic fractions, and a pair of single cells, respectively. A similar analysis was performed for Illumina sequencing.

  • Fig. 3 NanoSINC-seq depicts the difference in transcripts between cytoplasmic and nuclear fractions.

    (A) Mean length of aligned reads of the three sample types: nuclei, cytoplasm, and single cells. The statistical test was performed with two-sided Wilcoxon signed-rank test for Nuc (n = 16) versus Cyt (n = 16) and two-sided single Wilcoxon rank sum test for Nuc (n = 16) versus single (n = 8). (B) Proportion of transcript biotypes of the three sample types: nuclei, cytoplasm, and single cells. The statistical analyses are provided in fig. S5. lincRNA, long intervening noncoding RNA. (C) Gene ontology (GO) analysis of DETs in the nuclei and cytoplasm by Metascape (31) . ATP, adenosine 5′-triphosphate. TPM, transcripts per million; TP53, tumor protein p53; TRBP, transactivation response RNA binding protein.

  • Fig. 4 Genes showing high diversity in the isoform usage in either cytoplasmic or nuclear fraction.

    Transcript coverage in the cytoplasmic (A) and nuclear DETs (B). Genes expressing multiple isoforms that were enriched in cytoplasm and nuclei (fig. S6C). Statistical analyses on the detection of multiple isoforms and enrichment are described in fig. S7. The isoforms were identified using a computational workflow that identifies transcripts with high confidence (FLAIR) (30).

  • Fig. 5 Comparison of cell-to-cell variability between cytoplasmic transcripts and nuclear transcripts.

    (A) Fano factors corresponding to cytoplasmic transcripts are plotted against corresponding nuclear transcripts. The identity line separates attenuated (top) and amplified (bottom) transcripts. (B) Statistical comparison of variability at gene resolution level. Fano factors at the gene level are calculated by averaging Fano factors at the transcript level. Genes showing amplified variation in the cytoplasm are on the right-hand side. Amplified genes (red) were identified as those exhibiting P values less than 0.05 and log2(FC) greater than unity, and the attenuated genes (blue) were identified as those exhibiting P values less than 0.05 and log2(FC) less than −1. [t test adjusted with a Benjamini-Hochberg correction; false discovery rate (FDR) < 0.1; n = 16 each]. (C) Proportion of transcriptional biotypes of amplified genes and attenuated genes. (D and E) Gene ontology analysis of amplified genes and attenuated genes. The statistical test was performed using Metascape (31).

Supplementary Materials

  • Supplementary Materials

    NanoSINC-seq dissects the isoform diversity in subcellular compartments of single cells

    Yusuke Oguchi, Yuka Ozaki, Mahmoud N. Abdelmoez, Hirofumi Shintaku

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