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'Our results show that current gene transcript annotations are incomplete and supports the use of long-read sequencing to identify novel RNA isoforms'

Ricardo De Paoli-Iseppi, The University of Melbourne, Australia

Accurately characterise and quantify full-length transcripts with nanopore reads of unrestricted length
Generate high sequencing yields from low input amounts
Eliminate PCR bias and explore epigenetic modifications with direct RNA sequencing

Full-length transcripts in single reads

Analysis of gene expression is important in many applications, from clinical research to developmental biology. However, the use of legacy short-read technologies can cause multi-mapping when aligning data and limit quantification accuracy; this can be further limited by PCR bias. In contrast, nanopore reads of unrestricted length allow transcripts to be sequenced end-to-end, enabling accurate quantification and complete characterisation of isoforms in a single dataset. Furthermore, direct RNA sequencing enables the simultaneous detection of epigenetic modifications and eliminates PCR bias.

Technology comparison

Oxford Nanopore sequencing

Legacy short-read sequencing

    • Generate complete, high-quality genomes with fewer contigs and simplify de novo assembly
    • Resolve genomic regions inaccessible to short reads, including complex structural variants (SVs) and repeats
    • Analyse long-range haplotypes, accurately phase single nucleotide variants (SNVs) and base modifications, and identify parent-of-origin effects
    • Sequence short DNA fragments, such as amplicons and cell-free DNA (cfDNA)
    • Sequence and quantify full-length transcripts to annotate genomes, fully characterise isoforms, and analyse gene expression — including at single-cell resolution
    • Resolve mobile genetic elements — including plasmids and transposons — to generate critical genomic insights
    • Enhance taxonomic resolution using full-length reads of informative loci, such as the entire 16S gene
    • Assembly contiguity is reduced and complex computational analyses are required to infer results
    • Complex genomic regions such as SVs and repeat elements typically cannot be sequenced in single reads (e.g. transposons, gene duplications, and prophage sequences)
    • Transcript analysis is limited to gene-level expression data
    • Important genetic information is missed
    • Eliminate amplification- and GC-bias, along with read length limitations, and access genomic regions that are difficult to amplify
    • Detect epigenetic modifications, such as methylation, as standard — no additional, time-consuming sample prep required
    • Create cost-effective, amplification-free, targeted panels with adaptive sampling to detect SVs, repeats, SNVs, and methylation in a single assay
    • Amplification is often required and can introduce bias
    • Base modifications are removed, necessitating additional sample prep, sequencing runs, and expense
    • Uniformity of coverage is reduced, resulting in assembly gaps
    • Analyse data as it is generated for immediate access to actionable results
    • Stop sequencing when sufficient data is obtained — wash and reuse flow cell
    • Combine real-time data streaming with intuitive, real-time EPI2ME data analysis workflows for deeper insights
    • Time to result is increased
    • Workflow errors cannot be identified until it is too late
    • Additional complexities of handling large volumes of bulk data
    • Sequence on demand with flexible end-to-end workflows that suit your throughput needs
    • Sequence at sample source, even in the most extreme or remote environments, with the portable MinION device — minimise potential sample degradation caused by storage and shipping
    • Scale up with modular GridION and PromethION devices — suitable for high-output, high-throughput sequencing to generate ultra-rich data
    • Sequence as and when needed using low-cost, independently addressable flow cells — no sample batching needed
    • Use sample barcodes to multiplex samples on a single flow cell
    • Bulky, expensive devices that require substantial site infrastructure — use is restricted to well-resourced, centralised locations, limiting global accessibility
    • High sample batching is required for optimal efficiency, delaying time to results
    • Lengthy sample prep is required
    • Long sequencing run times
    • Workflow efficiency is reduced, and time to result is increased

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