Chabane, K. | Search bioRxiv

bioRxiv2025

Detecting aberrant splicing events in short-read RNA-seq with SAMI, an UMI-aware Nextflow pipeline

SummaryDespite RNA-sequencing solutions have existed for 15 years, successfully replacing micro-arrays for gene expression profiling, their potential to analyse splicing is still to be achieved in clinical settings. Powerful tools were developed to quantify known iso-forms, to compare sample groups or to identify outliers in large datasets, but most fail to address the most common situation in routine diagnostics: identifying non-recurring events in low-dimension data. To fill this gap, we developed SAMI (Splicing Analysis with Molecular Indexes), an UMI-aware pipeline focusing on splicing events which differ from provided annotation. The ability of SAMI and concurrent software to detect intragenic splicing aberrations and gene fusions was assessed, both on real data from a commercial control sample and simulated data generated with ASimulatoR. Availability and ImplementationNextflow pipeline and Singularity container recipe freely available under GPL 3 licence at https://github.com/HCL-HUBL/SAMI Contactsylvain.mareschal@chu-lyon.fr

bioinformatics↗

bioRxiv2020

Performances of targeted RNA-sequencing for the analysis of fusion transcripts, gene mutation and expression in haematological malignancies.

RNA sequencing holds great promise to improve the diagnostic of haematological malignancies, because this technique enables to detect fusion transcripts, to look for somatic mutations in oncogenes, and to capture transcriptomic signatures nosological entities. However, the analytical performances of targeted RNA sequencing have not been extensively described in diagnostic samples. Using a targeted panel of 1385 cancer-related genes in a series of 100 diagnosis samples and 8 controls, we detected all the already known fusion transcripts, and also discovered unknown and/or unsuspected fusion transcripts in 12 samples. Regarding the analysis of transcriptomic profiles, we show that targeted RNA sequencing is performant to discriminate acute lymphoblastic leukemia entities driven by different oncogenic translocations. Additionally, we show that 86% of the mutations identified at the DNA level are also detectable at the mRNA level, except for nonsense mutations which are subjected to mRNA decay. We conclude that targeted RNA sequencing might improve the diagnosis of haematological malignancies. Standardization of the preanalytical steps and further refinements of the panel design and of the bioinformatical pipelines will be an important step towards its use in standard diagnostic procedures.

genomics↗