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Single-cell sequencing

The analysis of genomic and transcriptomic heterogeneity at the single cell level has provided new insights into many research areas, including cancer research, cell development and function, and immunology. However, the use of traditional short-read sequencing technology can introduce limitations in single-cell assays; for example, in transcriptome studies, it is not possible to identify transcript abundance at the isoform level. Long nanopore sequencing reads resolve these challenges, enabling end-to-end sequencing of full-length transcripts and large genomic regions in single reads, and spanning repetitive regions and structural variants.

Sequence full-length RNA transcripts for isoform-level single cell transcriptomics

Sequence full-length RNA transcripts for isoform-level single cell transcriptomics

Characterise splicing, chimeric transcripts, and sequence diversity across entire molecules

Characterise splicing, chimeric transcripts, and sequence diversity across entire molecules

Scale to your requirements with a range of nanopore sequencing platforms

Scale to your requirements with a range of nanopore sequencing platforms



Single-cell, isoform-level characterisation of RNA transcripts

Short-read based single-cell RNA sequencing (scRNA-Seq) methodologies only yield information from a small region close to one end of the transcript, precluding the facility to analyse splicing, chimeric transcripts, and sequence diversity across the molecule. In contrast, nanopore technology, which has no requirement for fragmentation, nor read length limitations, sequences the entire RNA (cDNA) molecule. As a result, full-length transcripts can be sequenced in single reads, allowing accurate, isoform-level characterisation and quantification (Figure 1).

How barcoding UMI's work

Figure 1: The power of single-cell sequencing comes from the facility to pool, sequence, and subsequently identify transcripts from hundreds of individual cells. All transcripts derived from the same cell can be identified using a unique cell barcode (cellBC). A unique molecular identifier (UMI), added to the original transcripts prior to amplification, further enables the identification of PCR duplicates that could impact transcript quantification, and can be used to generate more accurate consensus sequences. Short-read sequencing technologies only read approximately 50 bp of transcript sequence, precluding the identification of transcript isoforms. In contrast, long nanopore sequencing reads can span complete transcripts enabling in-depth, isoform-level gene expression analysis from single cells.

Introduction 2
tSNE plot of single-cell clusters

Figure 2: With the ability to obtain full-length transcripts using nanopore sequencing, Lebrigand et al. demonstrated the Clathrin light chain A gene ('Clta') isoform expression switch occurring during neuronal maturation in the mouse brain, displayed here in t-SNE plots a-c. Isoform Clta-204 was highly expressed in mature neurons (a), whereas isoform Clta-206 showed a higher expression level in precursor cells (b). Figure 2c provides an overlay of Clta-204/Clta-206 isoform expression in the isolated neuronal cells. Figure adapted from Lebrigand et al. 2020.

Full-length single-cell cDNA data reveals gene expression heterogeneity

Single-cell transcriptomics reveals intercellular gene expression heterogeneity at a level that cannot be achieved from bulk-cell analyses alone. Isoform-level expression data obtained from nanopore sequencing of single-cell libraries can reveal cell-type-specific differences in transcript splicing that are undetectable in short-read single-cell transcriptomic data. This is particularly useful for identifying phenomena such as isoform switching during cell development. For example, Lebrigand et al. demonstrated that, in the mouse brain, the Clathrin light chain A gene (‘Clta’) undergoes isoform switching during neuronal maturation, which they suggested may fine-tune the role this protein plays in different developmental stages (Figure 2). In this study, the team identified a total of 76 genes with cell-type specific isoform usage.

Case study


High throughput, error-corrected nanopore single-cell transcriptome sequencing

‘…combining the high throughput of nanopore sequencing with UMI guided error correction allows both high confidence definition of transcript isoforms and identification of sequence heterogeneity in single cells.’

Lebrigand et al.

Lebrigand et al. demonstrated how the addition of long nanopore sequencing reads to traditional short-read single-cell sequencing approaches enabled the accurate analysis of full-length transcripts. Following cell isolation using 10x Genomics technology, 1,141 cells from an E19 mouse brain library, across two batches, were subject to both long-read nanopore sequencing on the PromethION device and short-read sequencing. The short-read data was used to identify the cell barcode (cellBC) for each transcript and the associated unique molecular identifiers (UMIs). These data were then used to support the assignment of cellBC and UMIs to the genome-aligned nanopore sequencing reads.

In total, the team identified 18,439 previously-annotated transcripts and 15,317 novel transcripts, demonstrating the enhanced power of incorporating long sequencing reads to single-cell transcriptome studies. The data enabled the segregation of different cell types and the identification of differential isoform expression between cell types. Furthermore, the full-length reads provided more detailed insight into the association of individual SNVs in the glutamate receptor Gria2, and the identification of sequence heterogeneity within and between cell types.

Sequencing workflow
PromethION with kits and flow cells
Interested in both single-cell and spatial transcriptomics?

Discover how the subtleties of cellular diversity can be revealed with a combination of single-cell and spatial transcriptomics approaches.

Sequencing workflow

How do I prepare single-cell cDNA for sequencing using nanopore technology?

The most common single-cell sample preparation methods use emulsions to isolate single cells and generate full-length cDNA; however, the cDNA is often subsequently fragmented prior to sequencing. Methods have been developed within the nanopore user community which skip the cDNA fragmentation step and allow preparation of full-length cDNA libraries for nanopore sequencing, using the Ligation Sequencing Kit for library preparation. With this approach, Lebrigand et al. have demonstrated that sequencing a full-length cDNA single-cell library on a single PromethION Flow Cell typically generates ~50 million cell and UMI-assigned reads. For more information, including analysis options, we recommend referring to the publication by Lebrigand et al., and others listed in the ‘Related resources’ section below.

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Single-cell transcriptomics of human and animal cells

To obtain high yields of human or animal single-cell transcriptome data, we recommend the following:

portable MinION
Looking to QC your library first?

Find out about the versatile Flongle platform.


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