SERpredict: Detection of tissue- or tumor-specific isoforms generated through exonization of transposable elements
Britta Mersch, Noa Sela, Gil Ast, Sandor Suhai, Agnes Hotz- Wagenblatt

TL;DR
SERpredict is an automated pipeline that detects tissue- or tumor-specific isoforms generated by exonization of transposable elements in human and mouse genomes, highlighting the significant impact of TEs on transcriptome diversity.
Contribution
The paper introduces SERpredict, a novel Bayesian-based analysis pipeline for identifying transposable element exonizations that produce tissue- or tumor-specific isoforms.
Findings
SERpredict successfully identified several tissue- or tumor-specific isoforms.
Transposed elements have a greater impact on the human transcriptome than on mouse.
Alu elements significantly contribute to primate-specific transcriptome diversity.
Abstract
Background: Transposed elements (TEs) are known to affect transcriptomes, because either new exons are generated from intronic transposed elements (this is called exonization), or the element inserts into the exon, leading to a new transcript. Several examples in the literature show that isoforms generated by an exonization are specific to a certain tissue (for example the heart muscle) or inflict a disease. Thus, exonizations can have negative effects for the transcriptome of an organism. Results: As we aimed at detecting other tissue- or tumor-specific isoforms in human and mouse genomes which were generated through exonization of a transposed element, we designed the automated analysis pipeline SERpredict (SER = Specific Exonized Retroelement) making use of Bayesian Statistics. With this pipeline, we found several genes in which a transposed element formed a tissue- or tumor-specific…
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