Kiera Berger, Bioinformatics Thesis Defense

In partial fulfillment of the requirements for the degree of 
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

Kiera Berger

Defends her thesis:
Clinical Utility of Targeted RNA-seq in Neuromuscular and Immune Disorders

Tuesday, April 19
11AM EDT
In-person: IBB 1128
Via Zoom: https://gatech.zoom.us/j/93978888179?pwd=aUtFeEJXdWNUSDVrWTcvZTRscWt0QT09

Thesis advisor: 
Dr. Gregory Gibson, Regents Professor, School of Biological Sciences, Georgia Institute of Technology 

Committee Members: 
Dr. Madhuri Hegde, Chief Scientific Officer, Global Lab Services, PerkinElmer Inc.
Dr. I. King Jordan, Professor, School of Biological Sciences, Georgia Institute of Technology
Dr. Patrick McGrath, Associate Professor, School of Biological Sciences, Georgia Institute of Technology
Dr. Subra Kugathasan, Professor, Departments of Pediatrics and Human Genetics, Emory University School of Medicine

Abstract:
A specific genetic diagnosis leads to lower health care costs and improvement in clinical outcomes for rare congenital diseases. Despite significant advancements in sequencing technology and bioinformatic analysis, only about 35% of patients suspected of having a rare congenital disease receive a genetic diagnosis. Some of the main challenges facing WES and WGS are the interpretation of variants of uncertain significance (VUS) and accurately identifying and predicting the effect of potential splice variants. Recent research indicates RNA-seq can improve diagnostic yield for these disorders, but lack of standards for efficient analysis of RNA-seq data is a significant impediment to clinical implementation of functional assays for diagnosing rare disease. Through analysis of cohorts with neuromuscular disorders, primary immunodeficiencies, and inflammatory bowel disease, I show the clinical utility of RNA-seq and argue that my method of multi-faceted analysis in targeted RNA-seq outperforms whole transcriptome sequencing and any single tool developed for the identification of aberrant splicing.