Rakshya U. Sharma, a junior Computer Science major and Bioinformatics minor at University of California, Santa Cruz, developed a computational tool to detect Survival Motor Neuron mutations in Whole Exome Sequencing data.
Spinal Muscular Atrophy (SMA) is a genetic disease that affects nerve cells in the spinal cord and causes muscle weakness. BSRP 2022 has been one of the most influential experiences in my academic career. It has provided me to grow as a scientist and thrive as an individual. This experience has allowed me to work with brilliant minds at the Broad and conduct cutting edge research. In addition, I appreciate the guidance of the BSRP faculty members who have taught me useful networking techniques, scientific communication, and graduate school application strategies. From this experience, my passion for science and research has grown stronger.Pathogenic variants that cause the loss of the SMN1 gene are responsible for SMA. Currently, published tools exist for detecting the most common causal mutations in whole genome sequencing (WGS) data. The goal of this project is to develop a computational tool that can accurately detect these mutations in whole exome sequencing (WES) data aligned to GRCh38. For this project we used the WES data from rare disease cases from the Broad Center for Mendelian Genomics (CMG), the Rare Genomics Project (RGP) and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) consortium and created a pipeline to detect the pathogenic SMN mutations. Using this method we were able to identify candidate diagnoses for SMA. Future directions for this work will be following up in the affected samples, validating the results and extending the algorithm to detect carrier status and category of disease severity.
Project: Spinal Muscular Atrophy diagnosis using whole exome sequencing data