Quantification of translation uncovers the functions of the alternative transcriptome.

Translation has a fundamental function in defining the fate of the transcribed genome. RNA-sequencing (RNA-seq) data enable the quantification of complex transcript mixtures, often detecting several transcript isoforms of unknown functions for one gene. Here, we describe ORFquant, a method to annotate and quantify translation at the level of single open reading frames (ORFs), using information from Ribo-seq data. By developing an approach for transcript filtering, we quantify translation transcriptome-wide, revealing translated ORFs on multiple isoforms per gene. For most genes, one ORF represents the dominant translation product, but we also detect genes with translated ORFs on multiple transcript isoforms, including targets of RNA surveillance mechanisms. Measuring translation across human cell lines reveals the extent of gene-specific differences in protein production, supported by steady-state protein abundance estimates. Computational analysis of Ribo-seq data with ORFquant (https://github.com/lcalviell/ORFquant) provides insights into the heterogeneous functions of complex transcriptomes.