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Nucleic Acids Res. 2018 Oct 1. doi: 10.1093/nar/gky870. [Epub ahead of print]

Mathematical modeling identifies potential gene structure determinants of co-transcriptional control of alternative pre-mRNA splicing.

Author information

1
San Diego Center for Systems Biology (SDCSB), University of California, San Diego, La Jolla, CA 92093, USA.
2
Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA 90095, USA.
3
Molecular Biology Institute (MBI), University of California, Los Angeles, Los Angeles, CA 90095, USA.
4
Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California, Los Angeles, CA 90095, USA.
5
Institute for Quantitative and Computational Biosciences (QCB) University of California, Los Angeles, Los Angeles, CA 90095, USA.

Abstract

The spliceosome catalyzes the removal of introns from pre-messenger RNA (mRNA) and subsequent pairing of exons with remarkable fidelity. Some exons are known to be skipped or included in the mature mRNA in a cell type- or context-dependent manner (cassette exons), thereby contributing to the diversification of the human proteome. Interestingly, splicing is initiated (and sometimes completed) co-transcriptionally. Here, we develop a kinetic mathematical modeling framework to investigate alternative co-transcriptional splicing (CTS) and, specifically, the control of cassette exons' inclusion. We show that when splicing is co-transcriptional, default splice patterns of exon inclusion are more likely than when splicing is post-transcriptional, and that certain exons are more likely to be regulatable (i.e. cassette exons) than others, based on the exon-intron structure context. For such regulatable exons, transcriptional elongation rates may affect splicing outcomes. Within the CTS paradigm, we examine previously described hypotheses of co-operativity between splice sites of short introns (i.e. 'intron definition') or across short exons (i.e. 'exon definition'), and find that models encoding these faithfully recapitulate observations in the fly and human genomes, respectively.

PMID:
30272246
DOI:
10.1093/nar/gky870

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