Integrating Transcriptome Sequencing From Mendelian Disease Patients and Healthy Controls to Improve Genetic Variant Interpretation

Abstract

Whole exome and whole genome sequencing have become increasingly routine approaches in understanding the genetic basis of Mendelian diseases. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25-50%, and a genetic diagnosis does not yield a full understanding of disease pathology. A key challenge of genome-based diagnostics is that the capacity DNA sequencing technologies to discover genetic variants substantially exceeds our ability to interpret their functional and clinical impact. One approach to improve the interpretation of genetic variation is to integrate functional genomic information such as transcriptome sequencing, which provides direct insight into transcriptional perturbations caused by genetic changes. Such approaches have already proven useful for elucidating mechanisms of cancer and common disease but have yet to be systematically applied to rare disease. Here, we present complementary approaches to integrate transcriptome sequencing into our understanding of the genetic etiology of Mendelian disease. We first present our work establishing the utility of transcriptome sequencing as a complementary diagnostic tool in Mendelian disease diagnosis. We then focus on developing and validating a transcript expression aware annotation metric which allows for the integration of publicly available population transcriptome datasets into clinical variant interpretation.