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Microexons: discovery, regulation, and function

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The importance of RNA splicing in numerous cellular processes is well established. However, an underappreciated aspect is the ability of the spliceosome to recognize a set of very small (3–30 nucleotide, 1–10 amino acid) exons named microexons. Despite their small size, microexons and their regulation through alternative splicing have now been shown to play critical roles in protein and system function. Here we review the discovery of microexons over time and the mechanisms by which their splicing is regulated, including recent progress made through deep RNA sequencing. We also discuss the functional role of microexons in biology and disease. WIREs RNA 2017, 8:e1418. doi: 10.1002/wrna.1418 This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease
Intron‐ and exon‐definition models. Schematic representation of the two primary models that drive assembly of splicing factors complexes and define the use of the splice sites in different mRNA architectures. The intron definition model is applicable to lower eukaryotes such as yeasts where the length of the intronic regions is rather small. The exon definition model proposes an explanation for more complex splicing regulation in higher eukaryotes due to the complexity of the genome organization and the presence of large intronic areas that are on average ten times longer than coding exons.
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Function of microexons. Inclusion of microexons can: (a) cause a frame‐shift leading to premature stop codons and degradation of the mRNA via nonsense‐mediated decay, (b) change protein structure which may in turn modulate protein–protein interactions, and (c) create sites for post‐translational modification of proteins.
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Identification of microexons. Currently available bioinformatics tools for identifying microexons. (a) Salzberg/GMAP and OLego algorithms: (1) When comparing cDNA sequences (Salzberg/GMAP) or RNA‐Seq reads (OLego) to the reference genome, there will be unmappable insertions in the cDNA/RNA‐Seq reads corresponding to unannotated microexons. (2) These algorithms search for potential matches to these segments at high resolution and evaluate candidate splice sites in the reference genome to identify novel exons. (3) After identification of the microexon, the reads map correctly. (b) VAST‐TOOLS: (1) cDNA libraries are used to build an exon junction database. (2) All possible microexon candidates are enumerated in silico by searching pairs of splice site separated by 3–15 nt within known introns. (3) Read mapping for an RNA‐Seq library of interest is performed against this exon‐microexon‐exon junction database to detect microexons. (c) ATMap: (1) Mapping of RNA‐Seq reads to a reference cDNA database lacking a microexon results in unmappable insertions in the read. (2) ATMap returns to the reference genome to identify splice sites surrounding a region that matches the read. (3) After identification of the microexon, the reads map correctly.
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RNA Evolution and Genomics > Computational Analyses of RNA
RNA Processing > Splicing Regulation/Alternative Splicing
RNA in Disease and Development > RNA in Disease

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