Examining Genetic Drivers of Myelodysplastic Syndromes Within Whole Exome Sequences
Mentor 1
Peter Tonellato
Location
Union Wisconsin Room
Start Date
27-4-2018 1:00 PM
Description
Myelodysplastic syndromes (MDS) are a group of biologically and clinically heterogeneous malignancies characterized by abnormal division of hematopoietic stem cells. Recurrently mutated genes drive pathogenesis in MDS and are closely associated with clinical phenotype. Research has demonstrated a high frequency and prognostic significance of mutations within 20 targeted genes in patients with MDS. The purpose of this study is to identify mutations within an expanded gene panel in a sample of patients with MDS and to predict the deleterious impact of mutations within the most frequently mutated genes. We will perform analysis on whole exome sequence samples from 48 MDS patients from the Center for International Blood and Marrow Transplant Research using the Genome Analysis Toolkit version 3.6 best practices model. We will write a script to run the samples, calling variants from 192 genes previously indicated to potentially have a role in MDS pathogenesis. We will analyze single nucleotide variants, insertions, deletions, and structural variants within these coding regions and use SnpEff to annotate the genes and perform preliminary predictions of variant effects. We will perform biochemical pathway analysis on the most frequently mutated genes, using Condel, Provean and Ingenuity Pathway Analysis to refine predictions of the deleterious impact of mutations and structural variants within target genes. Results from this study could deepen understanding of genetic drivers behind the development of MDS and potentially identify novel opportunities for therapeutic interventions by revealing clinically deleterious disrupted biochemical pathways.
Examining Genetic Drivers of Myelodysplastic Syndromes Within Whole Exome Sequences
Union Wisconsin Room
Myelodysplastic syndromes (MDS) are a group of biologically and clinically heterogeneous malignancies characterized by abnormal division of hematopoietic stem cells. Recurrently mutated genes drive pathogenesis in MDS and are closely associated with clinical phenotype. Research has demonstrated a high frequency and prognostic significance of mutations within 20 targeted genes in patients with MDS. The purpose of this study is to identify mutations within an expanded gene panel in a sample of patients with MDS and to predict the deleterious impact of mutations within the most frequently mutated genes. We will perform analysis on whole exome sequence samples from 48 MDS patients from the Center for International Blood and Marrow Transplant Research using the Genome Analysis Toolkit version 3.6 best practices model. We will write a script to run the samples, calling variants from 192 genes previously indicated to potentially have a role in MDS pathogenesis. We will analyze single nucleotide variants, insertions, deletions, and structural variants within these coding regions and use SnpEff to annotate the genes and perform preliminary predictions of variant effects. We will perform biochemical pathway analysis on the most frequently mutated genes, using Condel, Provean and Ingenuity Pathway Analysis to refine predictions of the deleterious impact of mutations and structural variants within target genes. Results from this study could deepen understanding of genetic drivers behind the development of MDS and potentially identify novel opportunities for therapeutic interventions by revealing clinically deleterious disrupted biochemical pathways.
