Abstract
BackgroundIntrons have been shown to be spliced in a defined order, and this order influences both alternative splicing regulation and splicing fidelity, but previous studies have only considered neighbouring introns. The detailed intron splicing order remains unknown.ResultsIn this work, a method was developed that can calculate the intron splicing orders of all introns in each transcript. A simulation study showed that this method can accurately calculate intron splicing orders. I further applied this method to real S. pombe, fruit fly, Arabidopsis thaliana, and human sequencing datasets and found that intron splicing orders change from gene to gene and that humans contain more not in-order spliced transcripts than S. pombe, fruit fly and Arabidopsis thaliana. In addition, I reconfirmed that the first introns in humans are spliced slower than those in S. pombe, fruit fly, and Arabidopsis thaliana genome-widely. Both the calculated most likely orders and the method developed here are available on the web.ConclusionsA novel computational method was developed to calculate the intron splicing orders and applied the method to real sequencing datasets. I obtained intron splicing orders for hundreds or thousands of genes in four organisms. I found humans contain more number of not in-order spliced transcripts.
Highlights
Introns have been shown to be spliced in a defined order, and this order influences both alternative splicing regulation and splicing fidelity, but previous studies have only considered neighbouring introns
The results of this work are available in [12]. Both short-read and long-read sequencing were used to obtain information on intron splicing orders as previously stated, and the methods are outlined in Fig. 1a, which shows how the short-read pair and long-read sequencing data indicate that intron 3 is spliced before intron 1
A simulation study showed that this method worked correctly To evaluate the framework developed here, the nascent RNA sequencing reads were simulated from S. pombe given random intron splicing orders for each transcript, and the most likely orders were calculated from the simulation data using the method developed here
Summary
Introns have been shown to be spliced in a defined order, and this order influences both alternative splicing regulation and splicing fidelity, but previous studies have only considered neighbouring introns. Splicing has been shown to be an integrated process coupled with transcription [1], and the co-transcriptional nature of splicing has been shown in various ways, such as via the sawtooth pattern of RNA-seq [2], real-time imaging [3], nuclear fraction RNA-seq [4], and electron imaging for direct visualization of co-transcription [5] These results showed that most introns in higher organisms are co-transcriptionally spliced. While using published long-read sequencing and short-read sequencing datasets, I calculated intron splicing orders for hundreds or thousands of genes in S. pombe, fruit fly, Arabidopsis thaliana, and humans. The results of this work are available in [12]
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