Roozbeh Dehghannasiri1, Linda Szabo2, Julia Salzman1,2. 1. Department of Biochemistry, Stanford University, Stanford, CA, USA. 2. Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Abstract
MOTIVATION: Identification of splice sites is critical to gene annotation and to determine which sequences control circRNA biogenesis. Full-length RNA transcripts could in principle complete annotations of introns and exons in genomes without external ontologies, i.e., ab initio. However, whether it is possible to reconstruct genomic positions where splicing occurs from full-length transcripts, even if sampled in the absence of noise, depends on the genome sequence composition. If it is not, there exist provable limits on the use of RNA-Seq to define splice locations (linear or circular) in the genome. RESULTS: We provide a formal definition of splice site ambiguity due to the genomic sequence by introducing equivalent junction, which is the set of local genomic positions resulting in the same RNA sequence when joined through RNA splicing. We show that equivalent junctions are prevalent in diverse eukaryotic genomes and occur in 88.64% and 78.64% of annotated human splice sites in linear and circRNA junctions, respectively. The observed fractions of equivalent junctions and the frequency of many individual motifs are statistically significant when compared against the null distribution computed via simulation or closed-form. The frequency of equivalent junctions establishes a fundamental limit on the possibility of ab initio reconstruction of RNA transcripts without appealing to the ontology of "GT-AG" boundaries defining introns. Said differently, completely ab initio is impossible in the vast majority of splice sites in annotated circRNAs and linear transcripts. AVAILABILITY AND IMPLEMENTATION: Two python scripts generating an equivalent junction sequence per junction are available at: https://github.com/salzmanlab/Equivalent-Junctions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Identification of splice sites is critical to gene annotation and to determine which sequences control circRNA biogenesis. Full-length RNA transcripts could in principle complete annotations of introns and exons in genomes without external ontologies, i.e., ab initio. However, whether it is possible to reconstruct genomic positions where splicing occurs from full-length transcripts, even if sampled in the absence of noise, depends on the genome sequence composition. If it is not, there exist provable limits on the use of RNA-Seq to define splice locations (linear or circular) in the genome. RESULTS: We provide a formal definition of splice site ambiguity due to the genomic sequence by introducing equivalent junction, which is the set of local genomic positions resulting in the same RNA sequence when joined through RNA splicing. We show that equivalent junctions are prevalent in diverse eukaryotic genomes and occur in 88.64% and 78.64% of annotated human splice sites in linear and circRNA junctions, respectively. The observed fractions of equivalent junctions and the frequency of many individual motifs are statistically significant when compared against the null distribution computed via simulation or closed-form. The frequency of equivalent junctions establishes a fundamental limit on the possibility of ab initio reconstruction of RNA transcripts without appealing to the ontology of "GT-AG" boundaries defining introns. Said differently, completely ab initio is impossible in the vast majority of splice sites in annotated circRNAs and linear transcripts. AVAILABILITY AND IMPLEMENTATION: Two python scripts generating an equivalent junction sequence per junction are available at: https://github.com/salzmanlab/Equivalent-Junctions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Manfred G Grabherr; Brian J Haas; Moran Yassour; Joshua Z Levin; Dawn A Thompson; Ido Amit; Xian Adiconis; Lin Fan; Raktima Raychowdhury; Qiandong Zeng; Zehua Chen; Evan Mauceli; Nir Hacohen; Andreas Gnirke; Nicholas Rhind; Federica di Palma; Bruce W Birren; Chad Nusbaum; Kerstin Lindblad-Toh; Nir Friedman; Aviv Regev Journal: Nat Biotechnol Date: 2011-05-15 Impact factor: 54.908
Authors: Matthew T Parker; Katarzyna Knop; Anna V Sherwood; Nicholas J Schurch; Katarzyna Mackinnon; Peter D Gould; Anthony Jw Hall; Geoffrey J Barton; Gordon G Simpson Journal: Elife Date: 2020-01-14 Impact factor: 8.140