Archive / INF Seminars / INF_2019_04_02_Luciano_Cascione
USI - Email

Unleash the power within RNA-Seq


Host: Prof. Ernst-Jan Camiel Wit




USI Lugano Campus, room SI-004, Informatics building

Luciano Cascione
Institute of Oncology Research (IOR) and Swiss Institute of Bioinformatics (SIB)


Luciano Cascione studied Computer Science at the University of Catania (Italy) and was visiting scholar at Ohio State University (US) at Carlo Croce's Lab. He has joined the Institute of Oncology Research (IOR) in 2013 as post-doc in the Lymphoma Genomics group. From 2018 he runs the Bioinformatics Core Unit at IOR and he is group leader of Swiss Institute of Bioinformatics (SIB).
RNA-sequencing (RNA-Seq) is an essential technique to characterize the transcriptome of cells and opened a new era in transcriptome analysis. Sequencing reads are used as the basis for abundance quantification of genes. Many studies aim at comparing abundance levels of genes between given conditions (e.g. Normal vs Tumor, Untreated vs Treated). However, through alternative splicing a large majority of human genes produce different transcripts called gene isoforms. On average each gene has 3.4 isoforms and if we look at protein coding genes this number goes to 7:1. Isoform switches could have a substantial biological impact, and they are implicated in many diseases and are especially prominent in cancer. Actually, differential usage of isoforms (isoform switches) alter the function, cellular localization, and stability of the corresponding RNA or protein. Analyses of RNA-Seq data utilizing isoform-level information remain rare making RNA-Seq data clearly underutilized. Advanced bioinformatics tool for the analysis of RNA-Seq data have enabled the quantification of transcriptomes with isoform resolution. This has allowed the genome-wide analysis of isoform usage and thereby the identification of isoform switchings. In this presentation we present a pipeline for the identification of isoform switches and the subsequent integration of multiple predictors of isoform function, to identify isoform switches with predicted functional consequences. We applied the pipeline to lymphoma RNA-Seq datasets and we found that isoform switches with predicted functional consequences were common, affecting a good number of multi-isoform genes. Among these, switches leading to the loss of sequence-encoding protein domains were frequent, particularly after pharmacological perturbation.