Abstract
Intron retention (IR) is an alternative splicing mode whereby introns, rather than being spliced out as usual, are retained in mature mRNAs. It was previously considered a consequence of mis-splicing and received very limited attention. Only recently has IR become of interest for transcriptomic data analysis owing to its recognized roles in gene expression regulation and associations with complex diseases. In this article, we first review the function of IR in regulating gene expression in a number of biological processes, such as neuron differentiation and activation of CD4+ T cells. Next, we briefly review its association with diseases, such as Alzheimer's disease and cancers. Then, we describe state-of-the-art methods for IR detection, including RNA-seq analysis tools IRFinder and iREAD, highlighting their underlying principles and discussing their advantages and limitations. Finally, we discuss the challenges for IR detection and potential ways in which IR detection methods could be improved.
Highlights
Different mRNA splicing isoforms can be produced from pre-mRNA by skipping or joining coding/non-coding gene fragments, referred to as alternative splicing (AS) (Ner-Gaon et al, 2004)
Because introns often contain premature termination codons (PTCs), intron-retaining isoforms (IRIs) are often rapidly degraded by the nonsense-mediated decay (NMD) pathway that is triggered by PTCs (Ge and Porse, 2014)
IRIs may escape from the NMD pathway (Lykke-Andersen and Jensen, 2015) and be translated into protein isoforms that are often truncated (Lindeboom et al, 2016; Ottens and Gehring, 2016) and harmful to cells (Brady et al, 2017; Kanagasabai et al, 2017; Uzor et al, 2018; Mukherjee et al, 2019; Wang et al, 2019)
Summary
Different mRNA splicing isoforms can be produced from pre-mRNA by skipping or joining coding/non-coding gene fragments, referred to as alternative splicing (AS) (Ner-Gaon et al, 2004). IRIs may escape from the NMD pathway (Lykke-Andersen and Jensen, 2015) and be translated into protein isoforms that are often truncated (Lindeboom et al, 2016; Ottens and Gehring, 2016) and harmful to cells (Brady et al, 2017; Kanagasabai et al, 2017; Uzor et al, 2018; Mukherjee et al, 2019; Wang et al, 2019). Regarding the proportion of IRIs escaping from the NMD pathway, it has been shown that ∼10% of human alternatively spliced nonsense-mediated decay (AS-NMD) transcripts are translated into truncated proteins (de Lima Morais and Harrison, 2010). Deep learning-based AS detection methods have been developed, such as deep learning augmented RNA-seq analysis of transcript splicing (DARTS) (Zhang et al, 2019) and SpliceAI (Jaganathan et al, 2019). We will describe current computational approaches to IR detection and discuss their advantages and limitations
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