Splicing Kinetics and Coordination Revealed by Direct Nascent RNA Sequencing through Nanopores.

Understanding how splicing events are coordinated across numerous introns in metazoan RNA transcripts requires quantitative analyses of transient RNA processing events in living cells. We developed nanopore analysis of co-transcriptional processing (nano-COP), in which nascent RNAs are directly sequenced through nanopores, exposing the dynamics and patterns of RNA splicing without biases introduced by amplification. Long nano-COP reads reveal that, in human and Drosophila cells, splicing occurs after RNA polymerase II transcribes several kilobases of pre-mRNA, suggesting that metazoan splicing transpires distally from the transcription machinery. Inhibition of the branch-site recognition complex SF3B rapidly diminished global co-transcriptional splicing. We found that splicing order does not strictly follow the order of transcription and is associated with cis-acting elements, alternative splicing, and RNA-binding factors. Further, neighboring introns in human cells tend to be spliced concurrently, implying that splicing of these introns occurs cooperatively. Thus, nano-COP unveils the organizational complexity of RNA processing.

Calculating the most likely intron splicing orders in S. pombe, fruit fly, Arabidopsis thaliana, and humans.

BACKGROUND: 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 detailed intron splicing order remains unknown. RESULTS: In 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. CONCLUSIONS: A 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.