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Methods. 2014 May 1;67(1):3-12. doi: 10.1016/j.ymeth.2013.11.006. Epub 2013 Dec 7.

In silico to in vivo splicing analysis using splicing code models.

Author information

1
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
2
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
3
Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
4
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address: yosephb@mail.med.upenn.edu.

Abstract

With the growing appreciation of RNA splicing's role in gene regulation, development, and disease, researchers from diverse fields find themselves investigating exons of interest. Commonly, researchers are interested in knowing if an exon is alternatively spliced, if it is differentially included in specific tissues or in developmental stages, and what regulatory elements control its inclusion. An important step towards the ability to perform such analysis in silico was made with the development of computational splicing code models. Aimed as a practical how-to guide, we demonstrate how researchers can now use these code models to analyze a gene of interest, focusing on Bin1 as a case study. Bridging integrator 1 (BIN1) is a nucleocytoplasmic adaptor protein known to be functionally regulated through alternative splicing in a tissue-specific manner. Specific Bin1 isoforms have been associated with muscular diseases and cancers, making the study of its splicing regulation of wide interest. Using AVISPA, a recently released web tool based on splicing code models, we show that many Bin1 tissue-dependent isoforms are correctly predicted, along with many of its known regulators. We review the best practices and constraints of using the tool, demonstrate how AVISPA is used to generate high confidence novel regulatory hypotheses, and experimentally validate predicted regulators of Bin1 alternative splicing.

KEYWORDS:

AVISPA; Alternative splicing; BIN1; Centronuclear myopathy (CNM); Myotonic dystrophy (DM); Splicing code

PMID:
24321485
PMCID:
PMC4321995
DOI:
10.1016/j.ymeth.2013.11.006
[Indexed for MEDLINE]
Free PMC Article
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