SaTAnn quantifies translation on the functionally heterogeneous transcriptome

Abstract

Abstract Deep sequencing methods have matured to comprehensively detect the full set of transcribed loci, but there is a gap to determine the function of the resulting highly complex transcriptomes. At the center of the gene expression cascade, translation is fundamental in defining the fate of much of the transcribed genome. We have developed a new approach (SaTAnn, Splice-aware Translatome Annotation) to annotate and quantify translation at the single open reading frame (ORF) level, that uses information from ribosome profiling to determine the translational state of each isoform in a comprehensive annotation. For most genes, one ORF represents the dominant translation product, but our approach also detects translation from ORFs belonging to multiple transcripts per gene, including targets of RNA surveillance mechanisms such as nonsense-mediated decay. Diversity in the translation output across human cell lines reveals the extent of gene-specific differences in protein production, which are supported by steady-state protein abundance estimates. Computational analysis of Ribo-seq data with SaTAnn (available at https://github.com/lcalviell/SaTAnn) provides a window into the functions of the heterogeneous transcriptome.