Recent advances in genome sequencing technologies provided unexpected opportunities to characterize individual genomic landscape and identify mutations relevant for diagnosis and therapy in clinics. Specifically, whole-exome sequencing for complex disease (such as tumor/normal matched sample) and target resequencing for Mendelian disease, using next-generation sequencing (NGS) technologies, are gaining popularity in the human genetics community due to the moderate costs and the huge quantity of information provided by each experiment. However, NGS data analysis still remains the crucial bottleneck in this approach because of the great amount of data containing millions of potential disease-causing variants and difficulties involving the integration of different sources. Here, we describe the application of a bioinformatics analysis pipeline for NGS data in two case studies about rare cardiac diseases. The case 1 is focused on the target sequencing of 158 candidate genes in 91 patients affected by Brugada Syndrome (BrS). To date the clinical phenotype is associated with mutations in the SCN5A gene but explain only the 30% of the BrS cases. Therefore we selected a panel of genes previously associated to cases of arrhythmogenic disorders in literature and we analysed them in a cohort of BrS patients, which were negative for known SCN5A mutations. We found 98 novel genetic variations and 60 clinical rs belonging to 70 genes. In particular we found 13 genes significantly mutated in our cohort compared to healthy controls in 1000 Genomes data that were not previously associated to BrS phenotype. In case study 2 we performed a whole-exome sequencing experiment of trio family where the child is affected by a severe cardiac disease with unclear diagnosis. We developed a specific bioinformatics pipeline to filter out the germline mutations. We found six genes with novel deleterious mutations that were homozygous in the affected child, and heterozygous in both parents. Among the six mutated genes the TRDN and UNC45A genes were already associated to cardiac dysfunctions in literature. Functional studies will be performed to evaluate the involvement of the mutated genes in the disease onset. In conclusion, we developed an automatic and versatile pipeline to analyse NGS data coming from whole-exome sequencing and target sequencing strategies. In addition, we integrated in the pipeline several public variation databases to evaluate and interpret the candidate mutations. The mutations found were validated by Sanger sequencing to evaluate the strength of the pipeline filters.
NEXT-GENERATION SEQUENCING APPROACH FOR IDENTIFICATION OF CANDIDATE GENES IN ARRHYTHMOGENIC DISEASES / A. Pietrelli ; tutore: C. Battaglia ; co-tutor: G. De Bellis ; direttore del dottorato: M. Clerici. - Milano : Università degli studi di Milano. DIPARTIMENTO DI BIOTECNOLOGIE MEDICHE E MEDICINA TRASLAZIONALE, 2014 Feb 04. ((26. ciclo, Anno Accademico 2013.
|Titolo:||NEXT-GENERATION SEQUENCING APPROACH FOR IDENTIFICATION OF CANDIDATE GENES IN ARRHYTHMOGENIC DISEASES|
|Supervisori e coordinatori interni:||CLERICI, MARIO SALVATORE|
|Data di pubblicazione:||4-feb-2014|
|Parole Chiave:||bioinformatics; genomics ; Brugada syndrome ; NGS ; target sequencing|
|Settore Scientifico Disciplinare:||Settore BIO/10 - Biochimica|
|Citazione:||NEXT-GENERATION SEQUENCING APPROACH FOR IDENTIFICATION OF CANDIDATE GENES IN ARRHYTHMOGENIC DISEASES / A. Pietrelli ; tutore: C. Battaglia ; co-tutor: G. De Bellis ; direttore del dottorato: M. Clerici. - Milano : Università degli studi di Milano. DIPARTIMENTO DI BIOTECNOLOGIE MEDICHE E MEDICINA TRASLAZIONALE, 2014 Feb 04. ((26. ciclo, Anno Accademico 2013.|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.13130/pietrelli-alessandro_phd2014-02-04|
|Appare nelle tipologie:||Tesi di dottorato|