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Analysis of differential splicing suggests different modes of short-term splicing regulation.


ABSTRACT: Alternative splicing is an important mechanism in which the regions of pre-mRNAs are differentially joined in order to form different transcript isoforms. Alternative splicing is involved in the regulation of normal physiological functions but also linked to the development of diseases such as cancer. We analyse differential expression and splicing using RNA-sequencing time series in three different settings: overall gene expression levels, absolute transcript expression levels and relative transcript expression levels.Using estrogen receptor ? signaling response as a model system, our Gaussian process-based test identifies genes with differential splicing and/or differentially expressed transcripts. We discover genes with consistent changes in alternative splicing independent of changes in absolute expression and genes where some transcripts change whereas others stay constant in absolute level. The results suggest classes of genes with different modes of alternative splicing regulation during the experiment.R and Matlab codes implementing the method are available at https://github.com/PROBIC/diffsplicing An interactive browser for viewing all model fits is available at http://users.ics.aalto.fi/hande/splicingGP/ CONTACT: hande.topa@helsinki.fi or antti.honkela@helsinki.fiSupplementary data are available at Bioinformatics online.

SUBMITTER: Topa H 

PROVIDER: S-EPMC4908367 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Analysis of differential splicing suggests different modes of short-term splicing regulation.

Topa Hande H   Honkela Antti A  

Bioinformatics (Oxford, England) 20160601 12


<h4>Motivation</h4>Alternative splicing is an important mechanism in which the regions of pre-mRNAs are differentially joined in order to form different transcript isoforms. Alternative splicing is involved in the regulation of normal physiological functions but also linked to the development of diseases such as cancer. We analyse differential expression and splicing using RNA-sequencing time series in three different settings: overall gene expression levels, absolute transcript expression level  ...[more]

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