Abstract
The advent of second-generation sequencing and its application to RNA sequencing have revolutionized the field of genomics by allowing quantification of gene expression, as well as the definition of transcription start/end sites, exons, splice sites and RNA editing sites. However, due to the sequencing of fragments of cDNAs, these methods have not given a reliable picture of complete RNA isoforms. Third-generation sequencing has filled this gap and allows end-to-end sequencing of entire RNA/cDNA molecules. This approach to transcriptomics has been a “niche” technology for a couple of years but now is becoming mainstream with many different applications. Here, we review the background and progress made to date in this rapidly growing field. We start by reviewing the progressive realization that alternative splicing is omnipresent. We then focus on long-noncoding RNA isoforms and the distinct combination patterns of exons in noncoding and coding genes. We consider the implications of the recent technologies of direct RNA sequencing and single-cell isoform RNA sequencing. Finally, we discuss the parameters that define the success of long-read RNA sequencing experiments and strategies commonly used to make the most of such data.
Highlights
LIMITATIONSHigh-throughput transcriptional profiling (“RNA-seq”) was pioneered in 2008, which enabled a transcriptome-wide survey of gene expression and alternative splicing in a quantitative fashion (Mortazavi et al, 2008; Nagalakshmi et al, 2008; Pan et al, 2008; Sultan et al, 2008; Wang et al, 2008; Wilhelm et al, 2008)
Specialty section: This article was submitted to Genomic Assay Technology, a section of the journal Frontiers in Genetics
1) Which combinations of the previously mentioned variable sites are being generated as RNA isoforms? In theory, all these alternative sites can specify an exponential number of distinct RNA molecules by exploiting distinct combinations of the previously discussed sites; recent data suggest that for many genes, this is not the case
Summary
High-throughput transcriptional profiling (“RNA-seq”) was pioneered in 2008, which enabled a transcriptome-wide survey of gene expression and alternative splicing in a quantitative fashion (Mortazavi et al, 2008; Nagalakshmi et al, 2008; Pan et al, 2008; Sultan et al, 2008; Wang et al, 2008; Wilhelm et al, 2008). Despite the success of RNA-seq in greatly expanding our knowledge of the mammalian transcriptome, it relies on short sequencing reads (~100–150 bp), which must be computationally assembled into longer transcript models. This can be a notoriously difficult and error-prone task, when alternative splicing generates multiple partially redundant isoforms at a given locus (Steijger et al, 2013; Tilgner et al, 2013). Short-read RNA-seq can accurately measure percent spliced-in (PSI) scores for individual exons but cannot unambiguously resolve the connectivity between distant exons because they are never represented on the same sequenced fragment (Tilgner et al, 2015; Tilgner et al, 2018). With the emergence of third-generation sequencing, it is possible to sequence full-length transcripts “in one go,” thereby obviating the challenges posed by computational assembly and delivering reliable isoform structures
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