Abstract
Despite decades of research, the question of how the mRNA splicing machinery precisely identifies short exonic islands within the vast intronic oceans remains to a large extent obscure. In this study, we analyzed Alu exonization events, aiming to understand the requirements for correct selection of exons. Comparison of exonizing Alus to their non-exonizing counterparts is informative because Alus in these two groups have retained high sequence similarity but are perceived differently by the splicing machinery. We identified and characterized numerous features used by the splicing machinery to discriminate between Alu exons and their non-exonizing counterparts. Of these, the most novel is secondary structure: Alu exons in general and their 5′ splice sites (5′ss) in particular are characterized by decreased stability of local secondary structures with respect to their non-exonizing counterparts. We detected numerous further differences between Alu exons and their non-exonizing counterparts, among others in terms of exon–intron architecture and strength of splicing signals, enhancers, and silencers. Support vector machine analysis revealed that these features allow a high level of discrimination (AUC = 0.91) between exonizing and non-exonizing Alus. Moreover, the computationally derived probabilities of exonization significantly correlated with the biological inclusion level of the Alu exons, and the model could also be extended to general datasets of constitutive and alternative exons. This indicates that the features detected and explored in this study provide the basis not only for precise exon selection but also for the fine-tuned regulation thereof, manifested in cases of alternative splicing.
Highlights
How are short exons, embedded within vast intronic sequences, precisely recognized and processed by the splicing machinery? Despite decades of molecular and bioinformatic research, the features that allow recognition of exons remain poorly understood
Our findings reveal insights regarding the role of local RNA secondary structures, exon–intron architecture constraints, and splicing regulatory signals
We integrated these features in a computational model, which was able to successfully mimic the function of the splicing machinery and discriminate between true Alu exons and their intronic counterparts, highlighting the functional importance of these features
Summary
How are short exons, embedded within vast intronic sequences, precisely recognized and processed by the splicing machinery? Despite decades of molecular and bioinformatic research, the features that allow recognition of exons remain poorly understood. Various factors are thought to be of importance. These include the splicing signals flanking the exon at both ends, known as the 59 and 39 splice sites (59ss and 39ss, respectively), auxiliary cis-elements known as exonic and intronic splicing enhancers and silencers (ESE/Ss and ISE/S) that promote or repress splice-site selection, respectively [1,2], and exon [3] and intron length [4]. Secondary structure is thought to present binding sites for auxiliary splicing factors, correctly juxtapose widely separated cis-elements, and directly affect the accessibility of the splice sites. Only very few studies have used bioinformatic approaches to broadly study the effects of secondary structure on splicing [13,14,15]
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