TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance
Samuel Valentini,
Caterina Marchioretti,
Alessandra Bisio,
Annalisa Rossi,
Sara Zaccara,
Alessandro Romanel,
Alberto Inga
Affiliations
Samuel Valentini
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
Caterina Marchioretti
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy; Department of Biomedical Sciences (DBS), University of Padova, 35131 Padova, Italy
Alessandra Bisio
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
Annalisa Rossi
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
Sara Zaccara
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy; Weill Medical College, Cornell University, New York 10065, NY, USA
Alessandro Romanel
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy; Corresponding author
Alberto Inga
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy; Corresponding author
Summary: Few studies have explored the association between SNPs and alterations in mRNA translation potential. We developed an approach to identify SNPs that can mark allele-specific protein expression levels and could represent sources of inter-individual variation in disease risk. Using MCF7 cells under different treatments, we performed polysomal profiling followed by RNA sequencing of total or polysome-associated mRNA fractions and designed a computational approach to identify SNPs showing a significant change in the allelic balance between total and polysomal mRNA fractions. We identified 147 SNPs, 39 of which located in UTRs. Allele-specific differences at the translation level were confirmed in transfected MCF7 cells by reporter assays. Exploiting breast cancer data from TCGA we identified UTR SNPs demonstrating distinct prognosis features and altering binding sites of RNA-binding proteins. Our approach produced a catalog of tranSNPs, a class of functional SNPs associated with allele-specific translation and potentially endowed with prognostic value for disease risk.