Quantification of translation uncovers the functions of the alternative transcriptome.

Abstract:

: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.

journal_name

Nat Struct Mol Biol

authors

Calviello L,Hirsekorn A,Ohler U

doi

10.1038/s41594-020-0450-4

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

717-725

issue

8

eissn

1545-9993

issn

1545-9985

pii

10.1038/s41594-020-0450-4

journal_volume

27

pub_type

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