A new view of transcriptome complexity and regulation through the lens of local splicing variations
Jorge Vaquero-Garcia,
Alejandro Barrera,
Matthew R Gazzara,
Juan González-Vallinas,
Nicholas F Lahens,
John B Hogenesch,
Kristen W Lynch,
Yoseph Barash
Affiliations
Jorge Vaquero-Garcia
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, United States
Alejandro Barrera
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, United States
Matthew R Gazzara
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
Juan González-Vallinas
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, United States
Nicholas F Lahens
Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
John B Hogenesch
Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
Kristen W Lynch
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, United States
Alternative splicing (AS) can critically affect gene function and disease, yet mapping splicing variations remains a challenge. Here, we propose a new approach to define and quantify mRNA splicing in units of local splicing variations (LSVs). LSVs capture previously defined types of alternative splicing as well as more complex transcript variations. Building the first genome wide map of LSVs from twelve mouse tissues, we find complex LSVs constitute over 30% of tissue dependent transcript variations and affect specific protein families. We show the prevalence of complex LSVs is conserved in humans and identify hundreds of LSVs that are specific to brain subregions or altered in Alzheimer's patients. Amongst those are novel isoforms in the Camk2 family and a novel poison exon in Ptbp1, a key splice factor in neurogenesis. We anticipate the approach presented here will advance the ability to relate tissue-specific splice variation to genetic variation, phenotype, and disease.