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Table 1 Comparison of published single-cell RNAseq isoform studies

From: Single-cell RNAseq for the study of isoforms—how is that possible?

 

Reference

Main focus of the study

Full-length isoforms?

Computatio-nal method

Aim

Organism, cell type

Library prep

Feature or event targeted

Illumina sequencing

Ramskold et al. [39]

Single-cell RNAseq, genes

MISO

Developed for bulk RNAseq

Experimental protocol development

Library preparation

Human, cancer cells

Smart-seq

Exon inclusion quantification

Shalek et al. [36]

Single-cell RNAseq, genes and isoforms

MISO

Developed for bulk RNAseq

Single-cell heterogeneity in immune response

Mouse, BMDCs

Smart-seq

Exon inclusion quantification

Zhang et al. [40]

Data from Shalek et al. [36]

Bulk RNA-seq, isoforms

WemIQ

Developed for bulk RNAseq + single-cell validation

Computational method development

Isoform identification

Mouse, BMCDs

Smart-seq

Single-cell bias in differential isoform detection

Marinov et al. [35]

Single-cell RNAseq, genes and isoforms

Pervouchine et al. [48]

Developed for bulk RNAseq

Single-cell isoform and gene expression heterogeneity

Mouse, lymphobl-astoid cells

Smart-seq

Novel splice junctions, exon inclusion quantification

Velten et al. [44]

Single-cell RNAseq, isoforms

BATBayes

3′ UTR variability among genes and cells

Mouse, ESCs

BATSeq

Alternative poly(A) sites

Welch et al. [42]

Data from Buettner et al. [17]

Single-cell RNAseq, isoforms

SingleSplice

Computational method development

Differential isoform usage

Mouse, ESCs

Smart-seq/C1

Differential isoform usage

Karlsson et al. [45]

Data from Zeisel et al. [18]

Single-cell RNAseq, isoforms

Alignment to FANTOM 5 database

Developed for CAGE

Single-cell isoform expression heterogeneity

Mouse, brain cells

STRT-seq/C1

Alternative TSS

Song et al. [38]

Single-cell RNAseq, isoforms

Expedition

Computational method development

Differential exon inclusion/exclusion

Human, iPSCs, NPCs and MNs

Smart-seq/C1

Exon inclusion quantification

Huang et al. [43]

Data from Wu et al. [49] and Scialdone et al. [50]

Single-cell RNAseq, isoforms

BRIE

Computational method development

Differential exon inclusion/exclusion

Human HCT116 cells + mESCs

Smart-seq + Smart-seq2

Exon inclusion quantification

Single-molecule sequencing

Oxford Nanopore

Byrne et al. [46]

Single-cell RNAseq, isoforms

Mandalorion

Computational method development

Isoform structure and quantification

Mouse, B1 cells

Smart-seq2

TSS, TTS, exon inclusion, intron retention, alt. 3′ and 5′ splice sites

PacBio

Karlsson and Linnarsson [47]

Single-cell RNAseq, isoforms

Self-designed pipeline

Single-cell isoform expression heterogeneity

Mouse, oligoden-drocytes and VLMCs

STRT-seq/C1

TSS, TTS, exon inclusion, alt. 3′ and 5′ splice sites

  1. Illumina involves short-read sequencing, and single-molecule sequencing involves long-read technologies. Studies are classified per ‘focus’, either bulk-RNAseq, single-cell RNAseq for gene expression or isoform single-cell RNAseq (or both). Only ‘computational methods’ used for isoform identification/quantification are specified. ‘Full-length’ is only considered as such when isoforms were reconstructed end-to-end, regardless of whether library preparation was full-length or not. Text in italics adds complementary information on the aim of the computational method/library protocol developed. When specified, the study was performed on data generated by other authors. ‘Feature/event targets’ refer to the approach taken to study isoform diversity, or to a specific aspect of it that is tackled. For more information, readers should refer to this review’s analysis or to the referenced papers
  2. BMDC bone-marrow-derived dendritic cell, ESC embryonic stem cell, iPSC induced pluripotent stem cell, mESC murine embryonic stem cell, MN motor neuron, NPC neural progenitor cell, TSS transcription start site, TTS transcription termination site, UTR untranslated region, VLMC vascular and leptomeningeal cell