Detecting differential transcript usage in complex diseases with SPIT

Abstract

Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and different developmental stages, thereby contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function, potentially leading to pathogenesis of diseases. Detecting such events for single-gene genetic traits is relatively uncomplicated; however, the heterogeneity of populations with complex diseases presents an intricate challenge due to the presence of diverse causal events and undetermined subtypes. SPIT is the first statistical tool that quantifies the heterogeneity in transcript usage within a population and identifies predominant subgroups along with their distinctive sets of DTU events. We provide comprehensive assessments of SPITs methodology in both single-gene and complex traits and report the results of applying SPIT to analyze brain samples from individuals with schizophrenia. Our analysis reveals previously unreported DTU events in six candidate genes.