Dose-Dependent Regulation of Alternative Splicing by MBNL Proteins Reveals Biomarkers for Myotonic Dystrophy

Stacey D Wagner, Adam J Struck, Riti Gupta, Dylan R Farnsworth, Amy E Mahady, Katy Eichinger, Charles A Thornton, Eric T Wang and J Andrew Berglund

PLOS Genetics, 2016, vol. 12, issue 9, 1-24

Abstract: Alternative splicing is a regulated process that results in expression of specific mRNA and protein isoforms. Alternative splicing factors determine the relative abundance of each isoform. Here we focus on MBNL1, a splicing factor misregulated in the disease myotonic dystrophy. By altering the concentration of MBNL1 in cells across a broad dynamic range, we show that different splicing events require different amounts of MBNL1 for half-maximal response, and respond more or less steeply to MBNL1. Motifs around MBNL1 exon 5 were studied to assess how cis-elements mediate the MBNL1 dose-dependent splicing response. A framework was developed to estimate MBNL concentration using splicing responses alone, validated in the cell-based model, and applied to myotonic dystrophy patient muscle. Using this framework, we evaluated the ability of individual and combinations of splicing events to predict functional MBNL concentration in human biopsies, as well as their performance as biomarkers to assay mild, moderate, and severe cases of DM.Author Summary: Our studies provide insight into the mechanisms of myotonic dystrophy, the most common adult form of muscular dystrophy. In this disease, a family of RNA binding proteins is sequestered by toxic RNA, which leads to mis-regulation and disease symptoms. We have created a cellular model with one of these family members to study how these RNA binding proteins function in the absence of the toxic RNA. In parallel, we analyzed transcriptomic data from over 50 individuals (44 affected by myotonic dystrophy) with a range of disease severity. The results from the transcriptomic data provide a rational approach to select biomarkers for clinical research and therapeutic trials.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgen00:1006316

DOI: 10.1371/journal.pgen.1006316

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